CAGE: Certified Authorization under Typed-Return Uncertainty for Tool-Using Agents

Computer Science > Artificial Intelligence [Submitted on 31 Jul 2026] CAGE: Certified Authorization under Typed-Return Uncertainty for Tool-Using Agents Blaise Delattre, Cong Wang, Yang Cao Tool-using LLM agents act on typed tool returns, records pairing provenance and categorical fields with numerical values. Runtime permission gates generally authorize the observed return and action, leaving the decision unprotected against small errors in how the return was bound to its source. We ask whether a candidate action stays authorized over a declared neighborhood of plausible correctly bound returns: one admissible binding fault plus bounded numerical drift. We prove that certifying the categorical and numerical channels separately does not compose: perturbations that are safe on each channel alone can jointly turn the same action unsafe. CAGE certifies this joint neighborhood directly, enumerating the discrete branches exactly and certifying the continuous perturbation within each branch. Across synthetic, policy-as-code, regulatory, and real-transaction settings, CAGE removes the in-budget false allows that accurate pointwise gates admit, while keeping a useful fraction of decisions autonomous. When the policy is executable, CAGE-Exact certifies the policy itself; otherwise CAGE-Lip and CAGE-RS certify a learned gate under an explicit, measured fidelity assumption. Comments: Code: this https URL Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2607.29190 [cs.AI]   (or arXiv:2607.29190v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2607.29190 Focus to learn more Submission history From: Blaise Delattre [view email] [v1] Fri, 31 Jul 2026 09:11:56 UTC (300 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-07 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)