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AI red teaming

Also called: red teaming · adversarial testing

AI red teaming is attacking your own AI system before others do: probing models, applications and agents for jailbreaks, prompt injection, data leaks, unsafe actions and harmful outputs. It ranges from manual expert testing to automated attack tools and scored campaigns.

How it works

Red teams define what must not happen, then try to make it happen through crafted prompts, poisoned content, malicious tools and multi-step agent scenarios. Findings feed fixes, guardrails and regression tests.

How to defend

Red-team before launch and after major changes, include indirect injection and tool abuse rather than only chat prompts, and turn findings into automated tests.

Real cases 2 stories

  1. MED

    Research · arXiv

    BRANCH: a tree search bypassed six AI guardrail systems

    BRANCH is an attack from Mindgard that rewrites a blocked prompt step by step until every detector in a multi-scanner guardrail passes it. The authors report a 100% attack success rate against six guardrail systems across 120 scenarios.

  2. INFO

    Lab safety · Anthropic

    Anthropic Cyber Verification Program: tiered access for defenders

    Anthropic is expanding its Cyber Verification Program into Defense, Red Team and Specialized tiers that relax Claude's cyber safeguards for verified security teams. Anthropic says its public models block most cyber work.