Evaluation of AI model resilience to adversarial inputs, perturbations, edge cases, and anomalous operating conditions. Covers adversarial testing, stress testing on out-of-distribution inputs, prediction stability analysis, robustness to noise and distortions, and verification of model behavior under targeted attacks like adversarial examples, data poisoning, or model evasion.