Overview
DeepTeam is an open-source framework for red-teaming large language models and LLM systems, focused on security and robustness evaluation. It helps researchers and engineering teams systematically discover adversarial weaknesses and assess model risks before and after deployment.
Key Features
- Attack strategies and templates for generating adversarial inputs across diverse threat scenarios.
- Evaluation tooling for measuring model safety, robustness, and reproducibility with quantifiable metrics.
- Extensible testing pipelines that integrate red-team workflows into CI/CD and evaluation processes.
Use Cases
- Pre-deployment security evaluations to identify abuse vectors and sensitive data leakage risks.
- Continuous robustness regression testing in enterprise or research settings to monitor model quality over time.
- Comparative assessments of defense strategies under realistic and adversarial attack conditions.
Technical Details
- Modular architecture supports adding new attack strategies or plugging in custom model endpoints.
- Integrates with retrieval, logging, and monitoring systems to collect rich signals during red-team tests.
- Open-source design emphasizes auditability, reproducibility, and community-driven contribution of emerging attack vectors.