Analysis & Playbooks
AI Agents & Autonomous System Risk
Memory Poisoning: The Attack Vector Nobody's Modeling
Everyone focuses on prompt injection at the input layer. The real break is persistent memory that carries corrupted context across sessions, undetected by every control in the chain.
Trust Architecture Reality Checks
Your AI Agent Is a Privileged Interpreter: The Trust Boundary Security Teams Keep Missing
Everyone focuses on what agents can access. The actual control surface is what they are allowed to interpret as permission, and that boundary does not exist in most enterprise deployments.
Trust Architecture Reality Checks
Spotlighting: The Trust Boundary Enforcement That Actually Works
Most enforcement models assume clean context at every step. The pattern that survives audit: narrow execution windows with explicit boundary checks before every privileged action.
AI Agents & Autonomous System Risk
When AI Agents Sign Transactions: The Authentication Gap Nobody's Solving
Traditional auth models verify identity at session start. Agents execute over extended chains. That gap between initial auth and transaction signing is where institutional liability lives.
AI Agent Authentication Audit
15 questions that map where authentication and authorization models break when AI agents interpret context as commands. Answer on-page, get your gap score instantly. No signup required.
AI Agent Failure & Control Gap Report
CVE-driven incident index mapping identity failures, tool execution boundary breaks, and the gap between what security reviews validate and what production adversaries exploit.
Trust Models Work In Theory. Break At Scale. I Map Why.
For CISOs, CTOs, security architects, and policy-aware engineers building AI agents and blockchain systems who need reality, not hype. Subscribe to see what most architecture reviews miss.