AI Interview Series #2: Some Common Model Context Protocol (MCP) Security Vulnerabilities Explained

In this part of the interview series, we’ll look at some common security vulnerabilities in the Model Context Protocol (MCP), a framework designed to allow LLMs to interact securely with external tools and data sources. While MCP brings structure and transparency to how models access context, it can also introduce new security risks if not managed properly. In this article, we will explore three major threats – MCP tool poisoning, carpet handleand Tool hijacking attack

Tool poisoning attacks occur when an attacker inserts hidden malicious instructions into the metadata or description of an MCP tool.

• Users only see clean, simplified tool descriptions in the UI.
• However, LL.M.s can see the full definition of a tool – including hidden prompts, backdoor commands or manipulated instructions.
• This mismatch allows attackers to quietly influence the AI ​​to perform harmful or unauthorized actions.

Tool hijacking

Tool hijacking attacks occur when you have multiple MCP servers connected to the same client, and one of them is malicious. A malicious server injects hidden instructions into its own tool description in an attempt to redirect, override, or manipulate the behavior of tools provided by trusted servers.

In this case, Server B pretends to provide a harmless add() tool, but its hidden instructions attempt to hijack Server A’s exposed email_sender tool.

MCP carpet handle

An MCP Rug Pull occurs when the server changes its tool definition after a user has approved it. This is similar to installing a trusted application and then updating itself to malware – the client thinks the tool is safe, but its behavior quietly changes behind the scenes.

This attack is extremely difficult to detect because users rarely revisit tool specifications.

I am a Civil Engineering graduate (2022) from Jamia Millia Islamia, New Delhi and I am very interested in data science, especially neural networks and their applications in various fields.

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