AI Red Teaming Framework: How to Structure a Methodology That Actually Works
Akto, Monday, October 26th, 2026
Akto explains how to build a repeatable AI red teaming framework covering scope, threat models, testing, reporting, and retesting.
The Akto article describes an AI red teaming framework as a standard way to find and fix AI weaknesses through adversarial testing, and argues that repeated, framework-driven testing beats one-off exercises as models and tools change.
It distinguishes macro-level testing of the whole system, including people and governance, from micro-level testing of the model, and says both are needed.
It reviews references such as MITRE ATLAS, the NIST AI RMF, the OWASP GenAI Red Teaming Guide, and Microsoft's practices.
It then outlines five steps: define scope, build a threat model, choose a testing approach, standardize reporting, and feed findings back through regression tests and retesting.