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arXiv 提交日期: 2026-06-22
📄 Abstract - Intent-Governed Tool Authorization for AI Agents

AI agents increasingly act through external tools: they read private data, construct structured payloads, submit write requests, export records, and coordinate workflows across application boundaries. Existing authorization mechanisms usually ask whether an integration credential, app, or token can call a tool. That question is necessary but incomplete. A tool call can be authorized by static credentials and still be unjustified by the user's current request. For example, a credential that can read and export records should not expose export authority when the user only asked for a bounded summary, and a model-generated delete call should not execute merely because the integration has a delete scope. This paper proposes Intent-Governed Access Control (IGAC), a server-side authorization layer that treats the user's expressed intent as a monotone, auditable policy attribute for AI-agent tool use. IGAC introduces intent certificates, session-scoped policy narrowing, intent-aware manifest filtering, and intent-tool-payload consistency checks. The central invariant is that user intent may only reduce the authority granted by static integration policy; it never expands scopes, data policy, tenant boundaries, or review requirements. We map IGAC onto OpenPort, an existing governance substrate that already implements authorization-dependent discovery, scope and ABAC-style policy checks, draft-first writes, preflight impact binding, state-witness checks, idempotency, stable reason codes, and audit.

顶级标签: agents systems llm
详细标签: tool authorization intent governance access control policy narrowing ai agent security 或 搜索:

基于意图驱动的AI智能体工具授权机制 / Intent-Governed Tool Authorization for AI Agents


1️⃣ 一句话总结

本文提出了一种名为“意图驱动访问控制”(IGAC)的新方法,通过在服务器端验证用户实际请求的意图是否与AI智能体调用工具的操作一致,确保即使工具本身拥有权限,也不允许执行超出用户当前需求的操作,从而提升AI系统的安全性和可控性。

源自 arXiv: 2606.22916