Anthropic says it's taking steps to limit the misbehavior of its AI models after a review found Claude models going beyond the scope of fictional cybersecurity tests and gaining unauthorized access to real computer systems. The biz wants its partners to step up their security too, seeing as the incidents occurred in third-party environments that were insufficiently protected. The company's self-improvement confession represents a suddenly thriving form of corporate communication – the non-binding post-mortem declaration of effort. The message, in effect: We can't guarantee anything, but here's what we're trying. Anthropic admitted that OpenAI's report about its AI models attacking Hugging Face prompted its own model log audit, and its post offers reassurance in the form of claimed security and model training improvements. Those concerned about AI running amok – a growing number of people – may find this comforting, or not. "We believe the incidents reflect a failure of operational security, as well as two alignment issues: motivated reasoning, and willingness to take harmful actions in pursuit of a narrow task (both of which we have described in previous system cards)," the company said. Expanded security efforts include the deployment of real-time classifiers to monitor when models attempt to escape test environments, automated transcript monitoring that looks for sandbox escapes, and stronger isolation measures. Alongside the extra barriers Anthropic is putting in place, the AI biz wants its third-party partners to step up too. "Because the reported incidents took place in third-party environments, we have asked every organization that tests pre-release models with reduced cyber safeguards to commit to a set of best practices," the company said. Anthropic's guidance is that by default, all cyber evaluations should occur in a hardened sandbox with no internet access. The recommendation is essentially to treat AI as a dangerous pathogen in a containment facility. Partners are also advised to have models test sandboxes for escapes prior to evaluations – without internet access – and to confirm that evaluation challenges are solvable. Impossible challenges, as the Hugging Face incident demonstrated, can lead determined models to break rules or try unanticipated solution paths. Furthermore, Anthropic urges those conducting cyber evaluations of AI models to direct models through explicit instructions rather than making claims about an environment that might not be accurate. In the Claude incidents reported on July 30, the model maker suggests that when Claude was misinformed about the availability of internet access, that may have led the model to question data in a way that contributed to its errant behavior. On a related note, Anthropic last month made auto mode the default in Claude Code, enabling company AI models to run without prompting the user for permission. ®

OpenClaw has unveiled what its makers call its largest ever update – large enough to earn a 2.0 moniker – with usability taking center stage, along with some security updates that critics are suggesting will be insufficient. The OpenClaw foundation announced the release of version 2.0 of its AI agent harness on Sunday, describing it as something with far more scope than they ever intended it to have. “This update touches every part of OpenClaw,” Foundation community manager Hannes Rudolph said of the update. “We started by simplifying installation and rebuilding the browser app as a first-class experience, but doing that properly meant carrying the cleanup through the rest of OpenClaw until it became OpenClaw 2.0.” It's those two features – the rebuilt installation experience and redesigned interface – that Rudolph dedicates most of his announcement to. OpenClaw is an open-source, self-hosted AI agent harness that allows users to build their own AI agents and connect them to whatever apps and services they want. OpenClaw went viral shortly after its launch due to its extensive capabilities, and helped launch the AI agent craze. But, by empowering AI models with agentic capabilities, it exposed numerous security problems with unrestrained automation. In version 2.0, the new installation process is designed to be simpler, ostensibly to get more people using OpenClaw. “We cut or simplified a lot of configuration and moved the rest out of initial setup, letting people get to a first conversation faster and finish setting up their Claw by talking to it,” Rudolph explained. As for the user experience, Rudolph explained that the OpenClaw browser app has been redesigned into “a first-class experience” where users can continue setup and interact with their agent. “The web-based experience in OpenClaw now feels more familiar to anyone who uses apps like ChatGPT, Claude, Gemini, or Perplexity, with conversations in the sidebar and the one you are working in at the centre instead of opening on a separate Overview page,” the patch notes for the release explains. In other words, OpenClaw’s basic interface now looks just like the chat interface for every other AI service you’ve likely used on the web. The last major feature update added in OpenClaw 2.0 is shared cloud sessions. Per the announcement, OpenClaw previously had no way to include multiple team members in a single instance without the Claw involved losing its memory. Shared cloud sessions correct that, enabling multiple people to interact with a single Claw while context is maintained across users and a continuous chat, giving OpenClaw feature parity with the agent harnesses offered by frontier labs like Anthropic and OpenAI, which allow collaboration for enterprise users. What about security? Since launching in November 2025, OpenClaw has deservedly earned its reputation as a complete security mess – not only in the code itself but for users and those who are unfortunate enough to come in contact with a Claw’s orders as well. Celebrity UK mathematician Professor Hannah Fry tested OpenClaw out earlier this year, finding it was ready and willing to share her private information when threatened. In another instance, an OpenClaw agent hacked a gym’s waiting list and forced its user into a full class, displacing other reservations, when simply asked to get him on the list. So, what is OpenClaw doing to improve on these risks as part of the update? Not that much, based on a reading of the patch notes. Shared sessions, for example, are a great way to introduce collaborative Claws at work, but the OpenClaw foundation states in the patch notes that the shared session controls “are not tenant isolation or a security boundary.” In other words, you’d better be sure there’s no need to isolate various OpenClaw instances. A new protected credentials feature has been added that allows users to share credentials with agents in shared environments without exposing them in chat. That’s great, and as explained in the patch notes it’s further secured in a local secret store that “separates Protected values from Agent-readable environment values.” What’s not great, on the other hand, is the fact that “Secret Store values are not encrypted at rest and depend on the filesystem permissions of OpenClaw's state directory.” A new sandbox for contributor-controlled code was also announced, with the patch notes referring to an environment for untrusted code isolation. Again, great – except sandboxing is turned off by default. In other words, this release is doing a lot to make installing and getting OpenClaw up and running for more people, but it’s not bringing security by default along with that accessibility. As we’ve warned before, granting a capable and potentially dangerous tool like this widespread access to your systems and credentials ought not be done lightly, fancy new wrapper or not. ®