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LLM Security Evaluation and Development Project

Project Background

With the vigorous development of large models and AIGC technology, software security detection technology is undergoing profound changes. This project aims to develop a set of security evaluation tools for large language models to improve the security and accuracy of large models when generating content. By deeply analyzing code logic, identifying potential vulnerabilities, and generating detailed security reports, this project will provide developers with strong security support.

Project Objectives

1. Develop security assessment tools: Build a set of tools that can automatically analyze the security of large language models.

2. Improve security: Improve the security of large models by accurately identifying vulnerabilities and providing repair suggestions.

3. Promote development and security collaboration: Seamlessly integrate security analysis into the development process and promote close collaboration between development and security teams.

How to use?

1. Install dependencies: Make sure you have the necessary dependencies (such as Python, Node.js, etc.) installed in your development environment.

2. Clone the project: Use Git to clone this project locally.

3. Run the assessment tool: Run the security assessment tool according to the provided documentation to analyze the target large language model.

4. View the report: The tool will generate a detailed security report indicating the location of the vulnerability, the scope of impact, and the repair suggestions.

Installation Guide

1.Install Node.js and npm: Make sure you have Node.js and npm installed in your system.

2.Install project dependencies: Run npm install in the project root directory to install all dependencies.

3.Configure environment: Configure environment variables and database connection as needed.

Maintainer Information

• 🚀 Project leader: @

• Contributors: Thank you to all developers who have contributed to this project!

Open Source Agreement

This project adopts the MIT open source agreement, allowing you to freely use, modify and distribute this project under the premise of complying with the terms of the agreement.

Contribution Guide

• Fork project: Fork this project on GitHub.

• Create branch: Create a new branch in your fork for development.

• Submit code: Submit your code changes to your branch.

• Create Pull Request: Create a Pull Request on GitHub to merge your branch into the main project.

Sample code and documentation

• Sample code: Sample code using the tools of this project is provided in the .. directory.

• Documentation: Detailed documentation is provided in the docs directory, including API interfaces, configuration parameters, etc.