IMCP
Explore AI security vulnerabilities within a deliberately insecure framework designed for educational purposes.
About
IMCP is a deliberately vulnerable framework designed to expose critical security weaknesses in AI/ML systems. It serves as a safe, controlled environment for security researchers, developers, and educators to learn about and mitigate emerging AI threats, offering hands-on experience with real-world AI vulnerabilities. IMCP is structured as a 'vulnerable by design' platform that includes model poisoning, prompt injection, embedding vector exploits and more, and is designed to act as a 'DVWA for AI'.
Key Features
- Realistic AI service implementation
- 2 GitHub stars
- Provides detailed documentation for in-depth learning
- Includes a comprehensive test suite for demonstrations
- Demonstrates 16 unique AI-specific security vulnerabilities
- Compatible with modern LLM APIs (e.g., OpenAI)
Use Cases
- Learn about model poisoning techniques
- Understand and mitigate prompt injection attacks
- Explore vulnerabilities in RAG systems
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