DeepTeam is an open-source red teaming framework for LLM systems: penetration testing, but for AI. It simulates attacks such as jailbreaking, prompt injection, and multi-turn exploitation against your chatbots, agents, and RAG pipelines to surface vulnerabilities before your users, or your adversaries, find them.
DeepTeam is developed by Confident AI on GitHub, where it has earned more than 3,000 stars under the Apache-2.0 license, and it is actively maintained, with updates in October 2026. It is built on DeepEval, the widely used open-source LLM evaluation framework, and runs locally on your machine. The framework ships more than 50 ready-to-use vulnerability categories, each with explanations, including PII leakage, prompt leakage, and bias, and each is assessed with LLM-as-a-judge metrics that produce binary pass/fail scores with reasoning, powered by any LLM you choose. Attack simulations range from single-turn jailbreaks to multi-turn exploitation strategies that wear a model down over a conversation. DeepTeam also offers guardrails to block the same classes of issues in production, closing the loop between finding weaknesses and preventing them. Results can stay local, or flow into the optional Confident AI platform, where teams manage risk assessments, monitor vulnerabilities in production, and share reports. That combination, an open local framework plus an optional commercial platform, is why it is listed as freemium here.
The DeepTeam framework itself is free and open source under Apache-2.0. The optional Confident AI cloud platform, for managing results, monitoring, and team reporting, is a paid product, making the overall offer freemium.
DeepTeam is for AI security teams, LLM application developers, and enterprises deploying chatbots or agents who need systematic, repeatable red teaming as part of their release process, not one-off manual probing.