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MCP-Security-Checklist

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2025-04-14

Une liste de contrôle de sécurité complète pour les outils d'IA basés sur MCP. Construit par Slowmist pour sauvegarder les écosystèmes de plugin LLM.

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🛡️ MCP Security Checklist

MCP Security Checklist

Welcome to the MCP Security Checklist repository! This project offers a comprehensive security checklist designed specifically for MCP-based AI tools. Created by SlowMist, our goal is to help safeguard the LLM plugin ecosystems.

📦 Getting Started

To begin using the MCP Security Checklist, you can download the latest release here. Follow the instructions provided in the release notes to execute the checklist effectively.

🛠️ Prerequisites

Before you start, ensure you have the following tools installed:

  • Python 3.8 or later
  • Git
  • A code editor (like VSCode or PyCharm)

🔍 Overview

The MCP Security Checklist covers various aspects of security for AI tools built on the MCP framework. Here are some key areas we focus on:

  • Authentication: Ensuring that only authorized users can access the system.
  • Data Protection: Safeguarding sensitive information from unauthorized access.
  • API Security: Protecting APIs from common vulnerabilities.
  • Logging and Monitoring: Keeping track of system activities for auditing and troubleshooting.
  • Vulnerability Management: Regularly checking for and addressing potential security flaws.

📜 Checklist Structure

The checklist is divided into several sections, each focusing on a specific area of security. Here’s a brief overview of what you can expect:

1. Authentication

  • Use multi-factor authentication (MFA).
  • Implement strong password policies.
  • Regularly review user access levels.

2. Data Protection

  • Encrypt sensitive data at rest and in transit.
  • Regularly back up data and test restore procedures.
  • Limit data access based on user roles.

3. API Security

  • Use HTTPS for all API calls.
  • Validate input to prevent injection attacks.
  • Rate limit API requests to mitigate denial-of-service attacks.

4. Logging and Monitoring

  • Implement centralized logging.
  • Set up alerts for suspicious activities.
  • Regularly review logs for anomalies.

5. Vulnerability Management

  • Conduct regular security assessments.
  • Keep software dependencies up to date.
  • Have a plan for addressing discovered vulnerabilities.

🔗 Links and Resources

For additional information, check the Releases section of this repository. You can download the latest version of the checklist here.

📚 Further Reading

🛡️ Contributing

We welcome contributions to the MCP Security Checklist. If you have suggestions or improvements, please follow these steps:

  1. Fork the repository.
  2. Create a new branch for your feature or bug fix.
  3. Make your changes and commit them.
  4. Push your branch to your forked repository.
  5. Open a pull request.

🤝 Code of Conduct

We expect all contributors to adhere to our code of conduct. Please treat everyone with respect and kindness.

📄 License

This project is licensed under the MIT License. See the LICENSE file for details.

💬 Contact

For questions or feedback, please reach out via GitHub issues or directly through the repository.

Thank you for checking out the MCP Security Checklist! Your contribution helps improve the security of AI tools in the MCP ecosystem. Let's work together to create a safer environment for all.

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    Reviews

    3.4 (11)
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    2025-04-23

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