Chao Gu, Quanyan Zhu · 2026 · arXiv
DOI: 10.48550/arXiv.2610.31376 · open-access PDF
本论文研究了快速注入的大型语言模型(LLM)代理人的安全工具执行问题。使用Petri网,我们将LLM和其工具之间的执行工具作为监管控制问题正式化,其中标记代表能力,批准和预算。由于过渡只在需要标记的情况下出现,注射请求的先决条件未满足或已经消耗,无论其编写如何,都被拒绝。
Machine translation (Meta M2M100); the English original follows.
This paper studies the problem of safe tool execution for large language model (LLM) agents under prompt injection. Using Petri nets, we formalize the execution harness between the LLM and its tools as a supervisory control problem, in which marks represent capabilities, approvals and budgets. Since a transition fires only if the marks it needs are present, an injected request whose preconditions are unmet or already spent is refused regardless of its wording. Treating tool outcomes as uncontrollable, we enforce safety by the conventional maximally permissive supervisor, and this safety transf
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