AI Red Teaming — How to Break Models Safely

AI red teaming is the practice of intentionally attacking your own AI systems to uncover security and safety issues before real attackers do. It’s a structured way to discover prompt vulnerabilities, data leakage paths, and unsafe behaviors.

Typical red teaming activities:

• Designing prompt‑injection and jailbreak scenarios.
• Crafting adversarial inputs and edge‑case queries.
• Testing for bias, unfair treatment, and safety violations.
• Measuring how systems behave under stress and rate limits.

The AI Security pillar page shows how red teaming fits into an overall AI security and governance program.