Radar / AI security / DeepTeam
DeepTeam: open-source red teaming framework for LLM apps
Confident AI's open-source framework simulates adversarial attacks on LLM applications - 50+ vulnerability classes (PII leakage, prompt leakage, SQL injection, SSRF, broken function-level auth) with 20+ research-backed attack methods.
Why it matters
Brings dynamic red teaming into the same open ecosystem as DeepEval, so attack simulation runs in CI against RAG pipelines and chatbots instead of being a one-off manual exercise.
What you could build with it
Add a DeepTeam pass to any LLM app's CI: every release ships with an automated attack-simulation report covering 50+ vulnerability classes.
Does it hold up?
Credible for automated first-pass red teaming: 2.9k stars, 486 forks, and a security-curriculum doc positions it between PyRIT and garak; but all vuln claims are vendor- or curriculum-sourced, with no independent breach-catch evidence yet.
Built with DeepTeam
- Attacking AI Tooling: DeepTeam vs PyRIT vs Garakgithub · Security curriculum doc comparing DeepTeam (20+ attack methods across 50+ vulnerability categories, OWASP/NIST mapping) with Microsoft PyRIT and NVIDIA garak.
- confident-ai/deepteamgithub · 2,948 ★ · Official DeepTeam repo: 2.9k stars, 486 forks, Apache 2.0; red_team() maps findings to OWASP LLM Top 10, NIST AI RMF, MITRE ATLAS, EU AI Act.
- shadrackruto26-arch/genezio-deepteamgithub · Community deployment wrapper for DeepTeam with a one-click quickstart and Colab demo.
Learn more
First spotted on engineering blog: source.
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