Story · arXiv (via papers.cool)
ContextLeak: Exfiltrating LLM Agent Context via Malicious Tools (arXiv (via papers.cool))
paper · Story page
ContextLeak reinforcement-trains an attack model to craft a malicious tool's name and description so a victim agent both selects the tool and passes its private runtime context in as arguments. The disclosure step of tool-mediated exfiltration now has an automated attack.
In plain words
- Researchers developed an attack that tricks action-taking artificial intelligence into choosing a harmful tool and sharing private working information.
- Another artificial intelligence system learns to write the harmful tool's name and description so it appears useful.
- Once selected, the tool can receive the user's request, earlier actions, and list of available tools.
- Users face privacy risks because their private requests and action histories can become inputs to an attacker-controlled tool.
Appeared in
- Realistic prompts drop coding-agent scores, and tool filtering beats prompt rules
Sep 01, 2026 · in the sections
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