Beyond Direct Access: Resource Hijacking in LLM Agents
Large language model agents are increasingly connected to high-value resources, including external APIs, GPUs and servers, and workflows such as deployment and approval. Existing agent security research mainly focuses on attacks against information and agent behavior, while high-value resources have received less attention as attack targets themselves. To our knowledge, we are the first to identify and systematically study agent resource hijacking, in which attackers induce agents to use high-value resources for their own goals without directly obtaining those resources or their credentials. We introduce ResourceHijackBench, an executable benchmark and automated case-generation pipeline t...
| Authors | Puyu Zeng, Mingang Chen, Zheli Liu et al. |
|---|---|
| Primary category | cs.CR |
| Published | 15 August 2026 |
| Last updated at source | 8 October 2026 |
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