Convergent Detour Hijacking: Task-Preserving Resource Amplification in Skill-Based LLM Agents
LLM agents increasingly rely on third-party skills, using natural-language descriptions for selection and instruction bodies for planning. This progressive-disclosure design exposes two sequential control points to untrusted publishers: a static skill may steer an otherwise correct task onto an unnecessarily costly trajectory. Prior work studies selection manipulation, malicious skill instructions, and tool-chain resource amplification largely separately, leaving their end-to-end composition unclear. We introduce Convergent Detour Hijacking (CDH), a text-only, runtime-independent attack that couples these stages. Under shared semantic cover, a description establishes relevance during sele...
| Authors | Junliang Liu, Ruoyu Li, Wenxin Tang et al. |
|---|---|
| Primary category | cs.CR |
| Published | 12 August 2026 |
| Last updated at source | 12 August 2026 |
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