MCP, in its current form, functions as a fun and profit remote exploit vector, primarily because it exposes AI systems to a wide range of attacks through under-specified security controls, heavy reliance on natural language context, and the ability for untrusted servers to manipulate model behavior. While MCP aims to standardize and simplify tool integration for AI, its half-implemented security features and architectural choices have made it a high-risk protocol, especially when deployed without additional safeguards.
A treasure trove of possibilities: OAuth tokens, almost impossible to build alarms for outside of transmission rates (what are you running your own LLM? How about a meta MCP for twice the API calls?) , assumed trusted input, the server can inject malicious instructions via tool descriptions, leading to prompt injection, data exfiltration, or even remote code execution, sometimes without any explicit tool use by the user.
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