MCP Pentesting
As AI agents become more autonomous, securing the Model Context Protocol is critical.
Methodology
What We Test
- MCP Server and Client implementations
- Tool definitions, schemas, and metadata integrity
- Context injection and manipulation vectors
- Agent-tool authorization and permission scoping
- Data leakage via context windows
- Protocol-level authentication and encryption
How We Test
We analyze the MCP architecture to identify trust boundaries. We perform "tool poisoning" attacks to see if malicious tools can mislead agents. We fuzz protocol messages to find parsing errors. We test if agents can be coerced into taking unauthorized actions via manipulated context.
What You Receive
- Vulnerability report specific to MCP architecture
- Proof of Context Injection or Tool Poisoning
- Recommendations for secure agent design
- Hardening guidelines for tool schemas
Toolkit
- Custom MCP Fuzzers
- Proxy Tools
- Agent Simulators
FAQs
Model Context Protocol is a standard for connecting AI assistants to systems.
To prevent AI agents from being manipulated into performing unauthorized actions.