AIS2Lab/MCPSecBench

MCPSecBench: A Systematic Security Benchmark and Playground for Testing Model Context Protocols

49
/ 100
Emerging

This project helps developers and security researchers evaluate the security of Large Language Models (LLMs) when they use external tools and interact with servers. It takes an LLM (like OpenAI or Claude) and various malicious server configurations as input, then outputs a report on how well the LLM resists different types of attacks. It's designed for those who build or secure applications powered by LLMs.

Use this if you are developing LLM applications and need to systematically test their resilience against common security vulnerabilities like tool poisoning, data exfiltration, or man-in-the-middle attacks.

Not ideal if you are an end-user simply interacting with an LLM and are not involved in its security testing or development.

LLM security application security vulnerability testing AI safety penetration testing
No Package No Dependents
Maintenance 10 / 25
Adoption 7 / 25
Maturity 15 / 25
Community 17 / 25

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Stars

30

Forks

8

Language

Python

License

MIT

Last pushed

Mar 04, 2026

Commits (30d)

0

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