DeepTeam

What DeepTeam is

DeepTeam is an Apache 2.0 open-source Python framework from Confident AI Inc. for red-teaming large language model systems. It dynamically simulates adversarial behavior and checks vulnerabilities including bias, toxicity, personal-information leakage, prompt leakage and security risks. Documentation describes more than 50 ready-made vulnerability checks, with attack patterns such as jailbreaks, prompt injection, automated evasion, data extraction and response manipulation. DeepTeam scores model outputs with vulnerability-specific LLM-as-a-Judge metrics that return a binary result together with reasoning. Its supported references include OWASP, NIST AI RMF, MITRE ATLAS, the EU AI Act, BeaverTails and Aegis. Listed model providers include OpenAI, Claude, Gemini, Azure OpenAI, AWS Bedrock, Vertex AI, Mistral, LiteLLM and Portkey. CI/CD connections include GitHub Actions, GitLab CI, Jenkins, CircleCI, Buildkite and Azure Pipelines. Tests generate attacks dynamically, so a prepared dataset is not required. Results can remain local or be sent to Confident AI for centralized viewing and production red-teaming through a UI. Deployment is self-hosted, and installation uses a Python virtual environment with pip.

Who it suits

DeepTeam suits developers and AI teams that need repeatable red-team checks for language-model applications. It fits organizations wanting open-source, self-hosted testing with named safety standards, model-provider connections and CI/CD options.

Getting started

1. Create a Python virtual environment
2. Install DeepTeam with pip
3. Configure a supported model provider
4. Run vulnerability or custom test cases
5. Connect results to local storage or Confident AI
6. Add the checks to a supported CI/CD system

Verdict

Choose DeepTeam for open-source LLM red teaming with broad vulnerability coverage and integrations for development pipelines. Its dynamic attacks and standards support structured security checks. Look elsewhere if you require a managed hosted deployment instead of running the framework yourself.