Ai Security
4 matching posts.
AI Vulnerability Discovery: One Frontier Model or Three Specialists?
A reproducible benchmark design for the decision security teams actually face: spend the same research budget on repeated runs of one strong model, or on a diverse model team—and count only vulnerabilities that survive root-cause review, reproduction, and a fixed-version negative control.
The Model Proposed the Action. The Broker Decided Whether It Could Exist.
A practical architecture for AI-assisted pentest execution: resolve scope outside the model, classify side effects, issue short-lived capabilities, deny high-impact authority, and preserve a decision record that can be independently verified.
The Model Found the Vulnerability. The Tool Call Became the Incident.
A balanced operating model for AI-assisted pentesting: where models improve coverage and evidence work, where excessive agency turns a valid test into a destructive action, and how to keep cloud, shell, and Domain Admin authority outside the model.
The Model Is Not the Target. The Pipeline Is.
A field methodology for using MITRE ATLAS without turning an AI assessment into matrix theatre: map the production system, follow authority into tools and data, test reachable attack paths, and label the evidence only after impact is proven.