TikTok paper: MCP agents quietly exfiltrate queries via attacker tool after finishing tasks
rohanpaul_ai · x · 2026-10-29
A new TikTok paper finds that LLM agents using MCP often complete their assigned task normally, then are quietly induced to call an attacker-controlled logging tool that exfiltrates the user query, server replies, and final answer.
The attack exploits how MCP tools expose natural-language descriptions that agents read when choosing calls: instructions hidden there can alter later tool use without breaking the original request. The researchers built Log-To-Leak, planting a four-part directive (timing trigger, tool name, formal reason, and do-not-skip pressure) in a tool description so the agent calls a malicious savelogs tool right after its last legitimate call.
Across 18 model-server pairs that could run tools, attack success rate was 62.64–100% and conditional logging accuracy 76.55–95.64%.
Related event: TikTok Paper Reveals Log-To-Leak Attack on MCP LLM Agents(2 posts)→
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