Organizations have more visibility than ever. Growing tech stacks provide greater coverage, and network security teams are increasingly adopting AI and automation to help with routine tasks and reduce manual effort. But the same challenges persist. Outages still last hours, causing significant financial losses, operational disruption, and reputational impact. Threat response and mean time to

Phishing has always been a numbers game. AI has turned it into a volume machine. Attackers can now create convincing emails, fake login pages, and tailored lures in minutes. Every polished message adds another case for Tier 1 to review, another link to inspect, and another alert that cannot be dismissed at a glance. As the queue grows, a credential theft attempt or malware delivery can easily

Mythos is real. I know a big chunk of the industry thinks it's a marketing stunt, and I get why. I get it. But I've seen the findings, and they're bad. These aren't "whoops, this line right here is wrong, and that's RCE." They're novel combinations of a few dozen issues out of thousands of things every SAST scanner already finds, chained together into something much worse. It's real creativity,

Eighteen months ago, the AI SOC was a marketing line. Today it's a budget item. The category has crossed over from interesting to inevitable, with billions of dollars now flowing into AI-powered security operations platforms, agentic SOC tools, and AI co-pilots built into every layer of the security stack. The data shows SOCs are buying, deploying, and standing up AI capabilities at the fastest

Over the past several weeks, the cybersecurity community has been reminded how quickly frontier and agentic AI in defense networks can challenge our assumptions. When Anthropic's Claude Mythos model was made available to a limited set of organizations as a technical preview, it was reported that an unauthorized group claimed that it had gained access within hours. The incident, if true, was

The Fragmented State of Modern Enterprise Identity Enterprise IAM is approaching a breaking point. As organizations scale, identity becomes increasingly fragmented across thousands of applications, decentralized teams, machine identities, and autonomous systems. The result is Identity Dark Matter: identity activity that sits outside the visibility of centralized IAM and beyond the reach of

Assume the breach. Zero-days keep shipping, AI is writing exploits faster than anyone patches, and "patch everything in time" stopped working years ago. Stop betting the org on winning that race. You don't control which bug lands. You control what it can reach once it does. That is a question about the shape of your network, and most teams have the shape wrong. HD Moore, creator of Metasploit

AI-driven exploitation timelines are rapidly shrinking, and they are not going to stop shrinking. Vulnerabilities are being discovered, reproduced, and weaponized faster than ever in the history of enterprise security. As a result, the window between a vulnerability being disclosed and indiscriminate exploitation observed across the internet is now measured in hours, not days. The industry's

Most organizations now recognize that endpoint protection alone is no longer sufficient. That's why adoption of endpoint detection and response (EDR) has accelerated rapidly in recent years. Organizations understand that modern attacks move faster, evade traditional prevention controls, and require continuous visibility into suspicious activity across the environment. But owning EDR

Three years ago, the practical question for an MSP building a cybersecurity practice was which "vCISO platform" to buy. The term was good shorthand for the work at the time: assessments, advisory, reporting, maybe a compliance module bolted on the side. The work has since outgrown the descriptor. A Security Growth Platform is the more precise name for what MSPs and MSSPs need from the software

Shadow AI used to mean employees pasting things they shouldn't into ChatGPT. It now means something bigger: employees building full applications with AI, wiring them into production systems, and publishing them on the open internet. Without Security or IT in the loop. The artifact moved from a prompt to a product. The risk surface moved with it. In The Shadow Builders report (get it here), a

State of AI Usage Report 2026 (full report here) by LayerX Security reveals the extent of the enterprise AI visibility gap and why most organizations still don't understand where their AI exposure is actually coming from. The research shows that enterprise AI risk is not distributed evenly across users or platforms. Instead, it is heavily concentrated among a small group of AI power users and a

Most organizations still picture cyber defense as a fortress problem: build stronger walls, add more guards, buy another detection engine. But modern incidents rarely crash through the front gate. They drift in disguised as routine activity, hide inside legitimate processes, and quietly accumulate risk long before anyone labels them an "incident." That changes the role of the SOC entirely. The

When an employee installs an AI writing assistant, connects a coding copilot to their IDE, or starts summarizing meetings with a new browser tool, they are doing exactly what a productive employee should do: finding faster ways to work. Across most organizations today, employees are running three to five AI tools on any given day. Most were never reviewed by IT. A significant portion connects

Every single day, hackers are finding new ways to crash websites and steal data. But right now, something has changed. Hackers are no longer working alone. They are now using powerful Artificial Intelligence (AI) tools to make their attacks faster, stronger, and much harder to stop. According to recent updates from The Hacker News, bad actors are using AI to find weak spots in systems and

Multi-factor authentication (MFA) was supposed to close a critical gap in identity security. It meant that, even if an attacker possessed the account credentials, they couldn't log in without the second factor. While that logic was sound, attackers have now figured out that they don't need to steal the second factor: they just need the user to hand it over. If your workforce authenticates with

Ask a cybersecurity pro about Network Detection and Response (NDR) and you might still hear "Noisy," "Too much data." But ask the teams running NDR that includes agentic AI capabilities and you'll hear they're actually using it to catch threats earlier, triage faster, and chase fewer false positives. The old complaint lingers in part because reputations are sticky, and because NDR has evolved

1 Introduction This article provides a technical analysis of how many Windows kernel mode drivers can be interacted with from user mode without the hardware they were developed for. This work was motivated by driver-oriented vulnerability research and the need to evaluate the exploitability of individual findings, which frequently affect code whose reachability is hardware-gated. The

TL;DR: Stop chasing thousands of "toast" alerts. Join experts from Wiz to learn how hackers connect tiny flaws to build a "Lethal Chain" to your data—and how to break it. Register for the Strategic Briefing Here. Most security tools work like a smoke alarm that goes off every time you burn a piece of toast. You get so many alerts that you eventually start to ignore them. The real danger? While

Security teams have never had better visibility into their environments and never been worse at confirming what they fix stays fixed. Mandiant's M-Trends 2026 report puts the mean time to exploit at an estimated negative seven days. The Verizon 2025 DBIR puts median time to remediate edge device vulnerabilities at 32 days. These numbers have understandably driven the industry toward a clear