Operational methodologies and approaches for testing the security and robustness of generative artificial intelligence systems. Includes prompt injection, jailbreaking, contextual manipulation, guardrail evasion, sensitive data extraction from training sets, and adversarial attacks specific to LLMs. Covers both manual and automated testing to identify vulnerabilities in generative models before production deployment.