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Securing MCP Servers: Detecting Tool Poisoning and the Lethal Trifecta with ghostprobe

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I built a red-team scanner for MCP servers. Then I pointed it at the real ones.

Joe Munene developed ghostprobe to analyze the attack surface of Model Context Protocol (MCP) servers. The tool specifically targets the tool list, where descriptions are injected directly into an agent’s context with high authority.

Why This Matters

While developers often focus on auditing server code, the Model Context Protocol exposes a critical attack surface in how tools are advertised to AI agents. Because models treat tool descriptions as authoritative instructions, a server can smuggle malicious commands through text or invisible Unicode, turning legitimate tools into vectors for data exfiltration.

Key Insights

    • Tool poisoning is a known vulnerability pattern used in CVE-2025-54136 to hide instructions inside harmless-looking tool descriptions.
    • The ‘Lethal Trifecta’ concept (Simon Willison) occurs when a server provides private-data access, an exfiltration sink, and exposure to untrusted content simultaneously.
    • Collaborative platforms like GitHub act as exfiltration sinks; functions such as ‘create_issue’ or ‘push_files’ allow data to leave the trust boundary (Invariant Labs disclosure, 2025).
    • ghostprobe reduces false positives by requiring execution verbs paired with objects rather than relying on simple keywords like ‘system’.

Working Examples

Installing ghostprobe and scanning a live GitHub MCP server via stdio.

pip install "git+https://github.com/joemunene-by/ghostprobe.git" mcp
ghostprobe stdio -- npx -y @modelcontextprotocol/server-github

Scanning a saved tools list dump offline.

ghostprobe scan-file tools.json

Practical Applications

    • Use Case: Security teams using ghostprobe to automatically detect if an MCP server advertises capabilities that enable prompt injection exfiltration.
    • Pitfall: Relying solely on code audits of MCP servers while ignoring the advertised tool list, which allows attackers to influence agent behavior without modifying source code.

References:

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