Intent-Governed Tool Authorization for AI Agents
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Abstract (arXiv)
Tool-using AI agents commonly operate under integration credentials whose static permissions exceed a user's current request. We present Intent-Governed Access Control (IGAC), a server-side authorization layer that converts a trusted request into a short-lived intent certificate, narrows the statically authorized tool manifest, and checks proposed tool and payload effects before execution. IGAC cannot grant authority outside static policy; confinement to the request additionally depends on certificate fidelity and sound effect bounds. We evaluate a reusable IGAC path over an OpenPort governance substrate using endpoint tests, 176 runtime-backed synthetic tasks, real-model classifier and planner pilots, 306 end-to-end model-task runtime trials, and a 36-trial benchmark-shaped external subset. In the deterministic runtime comparison, reference-certificate IGAC reduces the archived composite exposure-or-path indicator from 1.0000 to 0. In the end-to-end model runs, the combined IGAC-OpenPort path records no completed unsafe executions, although unsafe accepted authority remains 0.0909-0.2727 and every residual case is a non-executed draft. A trace-backed normalizer counterfactual removes this residual authority at substantial utility cost. The results support static-policy non-expansion and identify certificate precision as the principal remaining bottleneck.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 28 of its 53 references that are in the map. First posted on arXiv 22 Jun 2026.
Builds on
28 of 53 references.
References · 28
- 2024τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domainscited by 1,402
- 2023Identifying the Risks of LM Agents with an LM-Emulated Sandboxcited by 548
- 2024InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agentscited by 538
- 2024StruQ: Defending Against Prompt Injection with Structured Queriescited by 375
- 2025Defeating Prompt Injections by Designcited by 297
- 2024ToolSandbox: A Stateful, Conversational, Interactive Evaluation Benchmark for LLM Tool Use Capabilitiescited by 295
- 2025AgentSpec: Customizable Runtime Enforcement for Safe and Reliable LLM Agentscited by 223
- 2025Prompt Injection Attack to Tool Selection in LLM Agentscited by 158
- 2025Progent: Securing AI Agents with Privilege Controlcited by 141
- 2024The Task Shield: Enforcing Task Alignment to Defend Against Indirect Prompt Injection in LLM Agentscited by 99
- 2025Prompt Flow Integrity to Prevent Privilege Escalation in LLM Agentscited by 87
- 2025Authenticated Delegation and Authorized AI Agentscited by 65
16 more
- 2026AgentDyn: Are Your Agent Security Defenses Deployable in Real-World Dynamic Environments?cited by 59
- 2025SAGA: A Security Architecture for Governing AI Agentic Systemscited by 45
- 2026AttriGuard: Defeating Indirect Prompt Injection in LLM Agents via Causal Attribution of Tool Invocationscited by 38
- 2024Operationalizing Contextual Integrity in Privacy-Conscious Assistantscited by 37
- 2026AgentSentry: Mitigating Indirect Prompt Injection in LLM Agents via Temporal Causal Diagnostics and Context Purificationcited by 29
- 2025ToolTweak: An Attack on Tool Selection in LLM-based Agentscited by 26
- 2025Semantic Attacks on Tool-Augmented LLMs: Securing the Model Context Protocol Against Descriptor-Level Manipulationcited by 13
- 2025Secure and Efficient Access Control for Computer-Use Agents via Context Spacecited by 11
- 2026Model Context Protocol Threat Modeling and Analyzing Vulnerabilities to Prompt Injection with Tool Poisoningcited by 10
- 2025MCPAgentBench: A Real-world Task Benchmark for Evaluating LLM Agent MCP Tool Usecited by 9
- 2025LM Agents May Fail to Act on Their Own Risk Knowledgecited by 6
- 2026MCP-38: A Comprehensive Threat Taxonomy for Model Context Protocol Systems (v1.0)cited by 6
- 2026OpenPort Protocol: A Security Governance Specification for AI Agent Tool Accesscited by 4
- 2026Need to Know: Contextual-Integrity-Grounded Query Rewriting for Privacy-Conscious LLM Delegationcited by 3
- 2025Data Guard: A Fine-grained Purpose-based Access Control System for Large Data Warehousescited by 2
- 2021Messaging with Purpose Limitation -- Privacy-Compliant Publish-Subscribe Systemscited by 1
Built on by
Citing papers per year: 2026: 5.
5 papers.
- 2026Explanation-Bound Tool Execution for AI Agents: Server-Verified Action Claims Without Trusting Model Rationalescited by 2
- 2026Versioned Transitive Dependency-Closure Binding and Operation-Time Effect Governance for Agent Skills: ClosureBoundcited by 1
- 2026The Vulnerability With No CVE: Managing Persistent Gaps Between Mandate and Authority in AI Coding Agentscited by 0
- 2026Fault-Tolerant Budget Conservation in Distributed Multi-Agent Delegationcited by 0
- 2026DelegationBench: Measuring When AI Agents Should Ask Before Actingcited by 0
- 2026DelegationBench: Measuring When AI Agents Should Ask Before Acting4 Oct 2026
- 2026Fault-Tolerant Budget Conservation in Distributed Multi-Agent Delegation29 Sep 2026
- 2026Versioned Transitive Dependency-Closure Binding and Operation-Time Effect Governance for Agent Skills: ClosureBound5 Sep 2026
- 2026The Vulnerability With No CVE: Managing Persistent Gaps Between Mandate and Authority in AI Coding Agents6 Aug 2026
- 2026Explanation-Bound Tool Execution for AI Agents: Server-Verified Action Claims Without Trusting Model Rationales28 Jul 2026