Hybrid Analysis for Secure MCP Tool Use in LLM Agents
The rapid development of large language model (LLM) agents has enabled their broad adoption across diverse real-world tasks. To standardize interactions between LLM agents and external environments, Model Context Protocol (MCP) tools have emerged as a de facto standard and have been widely integrated into these systems. However, the use of MCP tools also introduces new safety risks, as LLM agents can be induced to perform malicious or unauthorized actions. Although prior work has proposed defenses for securing tool use in LLM agents, most methods rely on static analysis, i.e., inspecting prompts and generated outputs, which limits the defense effectiveness and robustness. To address these...
| Authors | Ping He, Yuexiang Xie, Yaliang Li et al. |
|---|---|
| Primary category | cs.CR |
| Published | 28 July 2026 |
| Last updated at source | 28 July 2026 |
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