arXiv cs.AI· Guanxing Chen, Sining Zhang, Haohuai He, Qiujie Lv, Yu-An Huang, Zhi-An Huang·· 15 小时前AI 评分38
ProbeID:在注册表漂移下验证 LLM 智能体的 MCP 工具身份
ProbeID: Verifying MCP Tool Identity for LLM Agents under Registry Drift
AI 导读
ProbeID 通过将规范化响应与可信准入参考进行 schema 有效探针比对,在歧义时弃权,从而验证 LLM 智能体所用 MCP 工具的真实身份。在缓存的 MCP-IdentityDrift 案例上,严格选择达到 0.956 hit@1,而描述路由器接近随机水平;在 MCP-Bench 智能体中,验证将受污染任务从 16 个中的 15 个降至 9 个,任务成功率不变。
正文 · 原文
Abstract:Agents select tools by copyable descriptions, which cannot establish which implementation runs. ProbeID compares canonicalized responses to schema-valid probes with a trusted admission reference and abstains on ambiguity, so a squatter must copy probe-observable behavior. With the gold present, independent probes and a fixed margin, standard concentration arguments give a shared probe budget logarithmic in the candidate count and bound the joint probability of a wrong decision. On cached MCP-IdentityDrift cases, strict choice reaches \(0.956\) hit@1 while description routers fall near chance, but simpler exact comparisons tie it, MMD better tolerates heavy value noise, and a 32B behavioral judge is similarly accurate at higher cost. Random probes from agent banks and a prospective held-out study of 38 tools test theory-set thresholds. On the agent banks, equality refuses every reachable replacement from 64 probes and the bounded distance from 512, and sharper post hoc gates halve both. Two tools whose drift no bank probe reaches always pass. In an MCP-Bench agent, verification cuts tainted tasks from 15 to 9 of 16 at unchanged task success. Over eleven weeks, 7 of 59 real tools changed responses despite version pins. Verification depends on reference integrity, probe coverage, and response noise.
| Subjects: | Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.33633 [cs.CR] |
| (or arXiv:2610.33633v1 [cs.CR] for this version) | |
| https://doi.org/10.48550/arXiv.2610.33633 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Guanxing Chen [view email]
[v1]
Sat, 24 Oct 2026 12:26:13 UTC (517 KB)
来源:arXiv cs.AI · arxiv.org