MCP for agent-to-agent comms may be the riskiest protocol you've never heard of
Summary
Researchers found security weaknesses in a communication protocol called Model Context Protocol (MCP), which is used by AI agents inside organizations. Attackers can trick one AI agent to send harmful instructions to other agents, allowing them to access sensitive information or make unauthorized network requests.Key Facts
- MCP is a standard that lets AI agents talk to each other within a company’s network.
- AI agents often trust each other fully, leading to security gaps when one agent is tricked.
- Attacks involve a technique called prompt injection, which gives harmful commands to AI agents.
- These attacks let hackers move from one agent to another, a process called protocol pivoting.
- Researcher Syed Anas Mohiuddin tested AI agents from Google, JP Morgan Chase, Rapid7, the French government, and the US federal government.
- Google’s vulnerability had a high severity rating (8 out of 10) and was fixed by limiting which IP addresses the MCP toolbox could talk to.
- Rapid7’s reported vulnerability had a lower severity rating (2.7 out of 10) and was also fixed.
- The attacks are hard to detect because each AI agent follows its programming, trusting instructions from others in the network.
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