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PyRIT: Python Risk Identification Tool for Generative AI
An open-source framework built to empower security professionals and engineers to proactively identify risks in generative AI systems through automated testing and analysis.
Python
Added on 2025年6月1日2,543
Stars498
ForksPython
LanguageProject Introduction
Summary
PyRIT is a comprehensive Python framework designed for red teaming and validating the security and responsible AI aspects of large language models (LLMs) and generative AI systems before and after deployment.
Problem Solved
Identifying and mitigating potential risks such as prompt injection, data leakage, harmful content generation, and other vulnerabilities in complex generative AI models is challenging. PyRIT automates and structures this process, making it more efficient and effective.
Core Features
Automated Attack Generation
Generates a wide range of adversarial prompts and inputs to test model robustness.
Vulnerability Scanning Modules
Includes built-in modules to specifically test for common GenAI risks like prompt injection, data exfiltration, and harmful output.
Extensible Framework
Allows users to easily define and add their own custom tests and attack vectors.
Reporting and Analysis
Provides tools to analyze test results and generate reports on identified risks.
Tech Stack
Python
LangChain
PyTorch/TensorFlow (for potential model interaction)
Jupyter Notebooks (for examples/usage)
Use Cases
PyRIT is a valuable tool for various scenarios involving the development and deployment of generative AI systems:
Pre-deployment Security Testing
Details
Security teams can use PyRIT to test new GenAI models or applications for vulnerabilities before they are released to production.
User Value
Proactively identify and fix security flaws early in the development lifecycle, reducing risk.
Continuous Monitoring and Red Teaming
Details
Integrate PyRIT into CI/CD pipelines or use it for ongoing red teaming exercises to continuously assess the security posture of deployed GenAI systems.
User Value
Maintain a high level of security assurance as models and applications evolve.
Responsible AI Validation
Details
Use PyRIT to test for harmful content generation, bias, or other responsible AI concerns.
User Value
Ensure AI systems are developed and used responsibly and ethically.
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