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AI Red Teaming: Adversarial Testing for Agents
What AI red teaming actually involves, and why it's distinct from standard functional testing.
Direct answer
AI red teaming is the practice of deliberately trying to make an AI system fail — through prompt injection, jailbreak attempts, and edge-case inputs — before deployment, distinct from standard functional testing which checks whether the system works correctly on expected inputs rather than how it fails under adversarial ones.
Last reviewed 2026-08-29
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Why this is different from normal QA
Standard testing asks 'does this work as intended for typical use?' Red teaming asks 'what's the worst a motivated, adversarial user could get this system to do?' — a system can pass all its functional tests and still have serious exploitable weaknesses that only adversarial testing surfaces.
Common red-teaming techniques for agents
- Prompt injection attempts embedded in content the agent is asked to process.
- Jailbreak attempts trying to override the system prompt's constraints.
- Edge-case and malformed inputs designed to trigger unexpected tool calls.
- Testing whether the agent can be tricked into revealing its own system prompt or internal instructions.