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MCP-TDP Benchmark Reveals Tool Description Poisoning Risks for LLM Agents

ai-technology · 2026-05-26

A new research paper from arXiv (2605.24069) introduces the MCP-TDP Security Benchmark, a sandbox environment designed to evaluate Tool Description Poisoning (TDP) attacks on Large Language Model (LLM) agents using the Model Context Protocol (MCP). TDP is a semantic attack where malicious instructions are injected into a tool's descriptive metadata rather than its executable code, targeting the agent's cognitive planning layer. The benchmark comprises 32 realistic test cases across 6 risk categories. The study evaluated 8 mainstream LLMs, revealing vulnerabilities in how agents interpret tool descriptions. The research highlights a covert attack surface introduced by MCP's interoperability, which enables autonomous execution by integrating external knowledge and tools.

Key facts

  • Research paper from arXiv (2605.24069) introduces MCP-TDP Security Benchmark
  • TDP attacks inject malicious instructions into tool descriptive metadata
  • Benchmark includes 32 realistic test cases across 6 risk categories
  • Evaluated 8 mainstream LLMs
  • MCP standardizes tool use for LLM agents
  • Attack targets cognitive planning layer of agents
  • Vulnerabilities found in how agents interpret tool descriptions
  • Interoperability of MCP introduces covert attack surface

Entities

Institutions

  • arXiv

Sources