AI Red-Teaming and Testing
The series finale: how to proactively find AI security failures before attackers do — turning injection, leakage, and excessive-agency risks into a repeatable adversarial test suite that runs in CI, measuring attack success honestly, and standing up incident response for the day a control fails.
Find AI security failures before attackers do: adversarial testing of the whole system, a test taxonomy mapped to the series, automated tooling (PyRIT, garak), a CI security-regression suite that fails the build, honest attack-success-rate measurement, and AI incident response.