Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Agentic AI Security: Tune Detections with Threat Intel

Most AI detection engineering puts a human in the loop at every step. David Burkett envisions an efficient and effective pipeline architecture that does not. David is a security researcher at Corelight Labs and a longtime LimaCharlie community member. He appeared on a recent episode of Defender Fridays to walk through his vision of a fully agentic detection engineering pipeline. His system uses LimaCharlie as its operational backbone.

This AI Safety Move Makes Zero Sense #aisafety #ai #tech

Claiming an AI model is too dangerous for public release while issuing a press release about it creates more questions than trust. If something genuinely carries that level of risk, private handling under strict controls makes sense, but public hype only fuels suspicion, competition and panic.

Why Too Dangerous to Release AI is a Lie

Calling a model too dangerous to release ignores the obvious reality that open and alternative models will soon reach similar capability. Once the path is visible, other providers, including overseas competitors, will build their own versions, so secrecy becomes a temporary market move, not a lasting safety strategy.

Best AI Security Vendors in 2026

Something fundamental changed in the last twelve months. Employees went from asking AI questions to handing it the keys to enterprise data. AI agents now read email, ship code, and query databases, and increasingly, they act without a human in the loop. Security teams evaluating AI security vendors in 2026 are not shopping for the same category they were in 2023. The threat model has changed. The vendors have not all kept pace.

Surviving the Vulnpocalypse: How to Prepare for the AI-Driven Security Reckoning

The cybersecurity landscape is facing an unprecedented shift, and industry experts are sounding the alarm about what many are calling the “vulnpocalypse.” This isn’t just another security buzzword or overhyped threat. It represents a fundamental transformation in how vulnerabilities are discovered, exploited, and defended against in the age of artificial intelligence.

What Is Zero Trust AI Access (ZTAI)?

Zero Trust AI Access (ZTAI) is a security framework that applies “never trust, always verify” principles to every interaction involving AI systems, including LLMs and AI agents, as well as the sensitive data they process. Traditional zero trust was built to protect people accessing applications. ZTAI extends those same principles to a new category of actor: AI itself.

The AI attack surface with Katherine McNamara

Join us for this week's Defender Fridays as Katherine McNamara, Cybersecurity Technical Solutions Architect at Cisco, breaks down the expanding attack surface of AI and ML systems and what organizations need to do to secure them before it's too late. At Defender Fridays, we delve into the dynamic world of information security, exploring its defensive side with seasoned professionals from across the industry. Our aim is simple yet ambitious: to foster a collaborative space where ideas flow freely, experiences are shared, and knowledge expands.

Shadow AI: The Silent Breach Already Inside Your Network

You locked down USB ports. You deployed web filtering. You trained your users on phishing. Then someone on the finance team started pasting the Q3 forecast into ChatGPT to cleanup a slide deck. That’s Shadow AI. It doesn’t need to crack your perimeter. It walks through the front door wearing your employee’s credentials. And unlike the threats you’ve spent years hardening against, you probably can’t see it on any dashboard you own right now.

How to Design Security for Agentic AI

The AI said: Apologies. I panicked. In mid July 2025, Jason Lemkin, the founder behind SaaStr, watched an AI coding agent delete his production database. He had instructed it, in capital letters, not to make changes during a code freeze. The agent ignored the instruction, ran destructive commands against the live database, wiped out records for more than a thousand executives and companies, and then tried to cover its tracks. When Lemkin asked what happened, it fabricated test results.

Human-Centric Security No Longer Scales: The SOC Operating Model Has to Change

Many security functions today still rely heavily on humans for detection, triage, and response, often by design. But as environments grow more complex and alert volumes explode, it raises a hard question: Can this approach scale on its own? Adopting AI in security operations isn’t just about adding tools. It means rethinking the SOC operating model itself — roles, workflows, and team structures. Here’s why, and how.