Agentic AI Security · Part 2 of 3 Deterministic controls are essential when AI agents can act. They also have a precise limit: they can enforce what we have specified and can observe. The rest of the safety problem does not disappear. The FireCompass AI Safety and Governance series Your AI Agent Is Safe. Until… Read More »Guardrails Are Not a Safety Architecture
API Penetration Testing: What It Is, How It Works, and How to Do It Continuously APIs now carry the business logic and the sensitive data, which makes them the attack surface most likely to be under-tested. This guide covers what API penetration testing is, the risks it targets, how an agentic AI approach runs it… Read More »API Penetration Testing: What It Is, How It Works, and How to Do It Continuously
What adversarial exposure validation actually means, why point-in-time testing fails in 2026, and how to build a real AEV program. No hype, just numbers.
A technical breakdown of how agentic AI platforms discover, exploit, and chain findings into multi-stage attack paths across web, API, and network.
Insights from a closed-door roundtable on AI agent safety and governance, chaired by Bruce Schneier and hosted by FireCompass founder Bikash Barai. Participant comments are kept anonymous by agreement. The most useful thing about this roundtable was that nobody pretended to have the answer. A room of senior security leaders spent an hour on AI… Read More »AI Agents Are Doing Real Work. Governing Them Is the Unsolved Problem