Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Static application security testing (SAST) tools help developers quickly catch potential vulnerabilities as they code. However, these tools rely on inflexible rules that often generate a high number of false positives, reducing trust in their accuracy and slowing adoption. To help developers access context-aware vulnerability detection, we’ve released an open source AI-native SAST solution. This tool scans code changes incrementally and surfaces security issues in real time.

It’s no surprise that AI is being integrated into identity governance and administration (IGA) platforms. Automation promises productivity boosts, risk detection can be in real-time and cloud environments allow greater scalability. What’s more, the pace of AI means IGA is quickly moving beyond slower, more rigid, rule-based approaches.

The recent supply chain attack involving Mercor and the LiteLLM vulnerability serves as a massive wake-up call for enterprise security teams. While the security industry has spent the last year fixating on prompt injections and model jailbreaks, this breach highlights a far more systemic vulnerability. The weakest link in enterprise AI is not necessarily the model itself. It is the middleware connecting the models to your data.

The data from this year's State of Secrets Sprawl report shows that AI is not creating a new secrets problem; it is accelerating every condition that already made secrets dangerous.

This week Anthropic announced Project Glasswing, a cybersecurity initiative built around Claude Mythos Preview, an unreleased frontier AI model capable of autonomously discovering and developing exploits for zero-day vulnerabilities across major operating systems and web browsers. According to early details, the model has already identified thousands of critical vulnerabilities that traditional tools have missed for years.

Following our article on the challenges posed by agentic AI, we gave OpenClaw access to one of our legacy networks In my previous article on OpenClaw I wrote: “Even the most ‘risk-on’ organizations with deep AI and security experience, will likely find it challenging to configure OpenClaw in a way that effectively mitigates the risk of compromise or data loss, while still retaining any productivity value.” The Red Team here at Sophos took that as ‘challenge accepted’, s

Everyone is calling Claude Mythos a watershed moment. I’d like to offer a slightly different take. Not because the capability isn’t real, it is. But if Mythos is the moment that finally convinced your organization that rapid vulnerability discovery is an existential threat, you’ve been watching the wrong thing. We saw this coming. Vulnerability Management has been moving in this direction for years, and we built Nucleus with this trajectory in mind. What surprises me is the surprise.