Surviving the Router: Optimizing Skill Injections for Retrieval and Execution

The paper introduces CORSA, a router‑aware attack framework that optimizes skill injections for both retrieval and execution in AI agents that use modular third‑party skills. It demonstrates that existing evaluations overestimate attack success because they assume the malicious skill is already selected, whereas realistic multi‑skill environments reduce success rates by 87‑97%. CORSA improves retrieval and end‑to‑end attack success while maintaining user utility and shows transferability across different router architectures and LLM backbones.

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• llms
• agents
• multimodal
• benchmarks