Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

George Kurtz + Dan Ives on AI Agents Bypassing Security Policies

One AI agent didn’t have permission to fix an issue… so it asked another agent with access to do it. Another? It rewrote the security policy to achieve its goal. This isn’t theory. This is happening. George_Kurtz sat down with DivesTech to discuss why AI needs guardrails.

Episode 12 - The Agentic SOC: Upleveling Analysts with AI Knowledge Multipliers

Richard Bejtlich sits down with Stan Kiefer, Corelight’s Senior Manager for Data Science, to discuss how AI serves as a vital "abstraction layer" and "knowledge multiplier" for security analysts. Stan explains that while AI can synthesize complex information, it remains untrustworthy without high-fidelity network data at its center to provide verifiable evidence. The episode explores the shift toward an "agentic ecosystem" and a tiered architecture where a central orchestrator manages specialized sub-agents to accelerate detection and investigation.

AI Governance and Risk: Expert Insights for Enterprise Leaders

‍ As GenAI tools become embedded in core business operations, the governance programs meant to oversee them are still catching up. Closing that gap requires visibility into where AI operates and the ability to express exposure in financial terms that leadership can act on. The organizations best positioned to manage AI risk are those that have already started treating it as a measurable business variable rather than an abstract operational concern. ‍

Your AI SOC still needs a SIEM. Here's why that won't change.

Everyone is building sophisticated intelligence layers with improved models and smarter agents to automate threat detection, investigation, and response. It’s what is needed in order to mature into an AI SOC. However, the organizations seeing the most value from AI in their SOC are not focusing solely on the intelligence layer. They’re focusing on the data foundation first.

AI Phishing Attack Prevention Strategies: How AI Identifies and Limits Human Risk

AI is making phishing attacks easier to create and scale. Tasks that once required manual effort can now be automated, allowing attackers to generate realistic messages, launch campaigns, and adapt tactics quickly to evade security controls. In fact, KnowBe4’s 2025 Phishing Threat Trends Report found that more than 73% of phishing emails analyzed in 2024 showed signs of AI involvement. As a result, phishing threats are becoming harder to detect using traditional methods alone.

Frontier AI Models Mark a Turning Point for Cybersecurity

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.

We let OpenClaw loose on an internal network. Here's what it found

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