confident-ai/deepteam

DeepTeam is a red teaming framework for LLMs and AI agents that simulates attacks to uncover vulnerabilities in AI systems.

The tool addresses the need to identify security weaknesses in language models and AI applications before deployment. It works by simulating attacks such as jailbreaking, prompt injection, and multi-turn exploitation to detect vulnerabilities including bias, personally identifiable information leakage, and SQL injection. The framework runs locally on the user's machine and is built on DeepEval, an open-source LLM evaluation framework. It provides over fifty ready-to-use vulnerabilities, each powered by any LLM of the user's choice, and uses LLM-as-a-Judge metrics that execute locally to produce binary pass or fail scores with reasoning. The tool also offers guardrails to prevent identified issues in production environments.

Teams building AI agents, retrieval-augmented generation pipelines, and chatbots should consider DeepTeam if they need to systematically test for security vulnerabilities before release. The framework is designed for developers who want to run red teaming locally without external dependencies. Those seeking to centralize red teaming results, manage risk assessments, and monitor vulnerabilities across production systems can integrate with the Confident AI platform, though the core red teaming functionality operates independently.

The project maintains active development with regular updates to its vulnerability library and attack simulations. The codebase shows consistent refinement of its core red teaming capabilities and integration points with the broader evaluation ecosystem.