PyRIT
ActiveDescription
The Python Risk Identification Tool for generative AI — an open-source framework by Microsoft for proactively identifying risks in generative AI systems through red teaming and automated probing.
Key Features
- Automated red teaming framework: automated attack probing tool designed specifically for generative AI systems, helping security professionals systematically identify security risks in LLM applications
- Multi-stage attack strategies: supports progressive attack paths from simple prompt injection to complex multi-turn dialogues, simulating adversarial behavior in real threat scenarios
- Risk quantification and scoring: built-in metrics like Attack Success Rate (ASR) for quantifying system security risks, supporting comparison of different protection strategy effectiveness
- Extensible attack modules: modular architecture supports custom attack scenarios and probes, enabling tailored red team test cases for specific business scenarios
- Microsoft official maintenance and ecosystem integration: part of Microsoft's AI security ecosystem, deeply integrated with Azure AI Foundry, AI Red Teaming Agent and other toolchains
Use Cases
💡 Pre-deployment security assessment of LLM applications: before releasing generative AI apps, automatically probe for prompt injection, jailbreak, data leakage and other vulnerabilities, quantifying risk levels
💡 Continuous security monitoring: regularly execute red team tests during AI system operation to detect security degradation introduced by model updates or new attack techniques
💡 Security compliance verification: provides auditable security testing evidence for AI systems in regulated industries (finance, healthcare, government) to meet compliance review requirements
💡 AI security research and benchmarking: supports systematic research on generative AI security in academia and industry, establishing security benchmarks and attack taxonomy systems
💡 Protection strategy effectiveness validation: compare actual protective effects of different security measures (system prompt hardening, output filtering, content moderation) under adversarial attacks
Tags
Categories
Quick Start
Install: pip install pyrit; initialize Orchestrator: from pyrit.orchestrator import PromptSendingOrchestrator; orchestrator = PromptSendingOrchestrator(); configure targets and attack probes; run red team tests and analyze risk metrics like ASR