Intent-Governed Tool Authorization for AI Agents
- URL: http://arxiv.org/abs/2606.22916v1
- Date: Mon, 22 Jun 2026 06:55:57 GMT
- Title: Intent-Governed Tool Authorization for AI Agents
- Abstract summary: Intent-Governed Access Control (IGAC) treats the user's expressed intent as a monotone, auditable policy attribute for AI-agent tool use.<n>IGAC introduces intent certificates, session-scoped policy narrowing, intent-aware manifest filtering, and intent-tool-payload checks.<n>We map IGAC onto OpenPort, an existing governance substrate that already implements authorization-dependent discovery, scope and ABAC-style policy checks.
- Score: 4.805352087824778
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: 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.
Related papers
- Authority Is Not a String: A Capability-Scoped Harness for Prompt-Injection-Resistant Coding Agents [1.8587887164315786]
Coding agents use system-level tools to read files, execute commands, and modify source code.<n>Indirect prompt injection exploits this authority by placing instructions in repository files or tool output that cause the agent to perform actions the user did not request.<n>We propose CapScope, a harness-level authorization mechanism that restricts tool use without requiring the model to identify malicious text.
arXiv Detail & Related papers (2026-09-08T07:37:00Z) - ROPE: Routed Origin Policy Enforcement against Indirect Prompt Injection [61.4148196085256]
We present ROPE (Routed Origin Policy Enforcement), which is anchored in a structural notion of trust.<n>Our approach admits two provable guarantees: 1) at every step of a trajectory, no value whose only origin is attacker-writable content reaches an origin-guarded parameter, and 2) no rewording of an injection changes an admission decision.
arXiv Detail & Related papers (2026-08-27T01:22:14Z) - IACM-RL: Intent-Aware Context Management and Reinforcement Learning for Complex Tool Invocation under Dynamic Intent Fluctuations [86.93902234336393]
IACM-RL is a comprehensive framework for robust tool invocation.<n>We introduce the DynamicIntent pipeline, synthesizing trajectories across 13 fine-grained fluctuation scenarios.<n>Second, IACM-RL deploys a BeliefState-based Self-Generated Context Manager.
arXiv Detail & Related papers (2026-08-03T12:09:50Z) - Capability Gates Are Not Authorization: Confused-Deputy Failures in LLM Agent Frameworks [0.0]
We audit whether LangChain/LangGraph, LlamaIndex, and the Stripe Agent Toolkit re-authorize each model-emitted call, with concrete argument values, before execution.<n>Across pinned public-source commits, all three provide capability gating by default, but none provides a deterministic fail-closed per-call value authorization gate by default.<n>We introduce ScopeGate, a five-stage PDP/PEP for agent tool calls: scope, authorization, money ceiling, idempotency, and default deny.
arXiv Detail & Related papers (2026-06-27T01:33:19Z) - Capable but Careless: Do Computer-Use Agents Follow Contextual Integrity? [54.701199583505144]
Cross-application access creates a privacy risk that has been largely overlooked.<n>We introduce AgentCIBench, an evaluation harness that turns this risk into executable, deterministically scored scenarios.<n>We evaluate 15 frontier agents and find a surprisingly high failure rate.
arXiv Detail & Related papers (2026-06-22T11:36:58Z) - Sovereign Assurance Boundary: Certificate-Bound Admission for Agentic Infrastructure [2.124730017640531]
Sovereign Assurance Boundary is a certificate-bound runtime admission layer for autonomous execution authority.<n>We detail the airlock-broker architecture, formalize its admission and revocation invariants, and report preliminary feasibility measurements from a Go prototype.
arXiv Detail & Related papers (2026-06-10T03:49:57Z) - Proof-Carrying Agent Actions: Model-Agnostic Runtime Governance for Heterogeneous Agent Systems [0.6526824510982799]
This paper presents Proof-Carrying Agent Actions (PCAA), a runtime-neutral governance model centered on an action certificate.<n>PCAA organizes control around five checkpoints: pre-action admissibility, action open, assumption capture, approval, and outcome closure.<n>We study the model through a reference implementation in a heterogeneous agent control plane and a disclosure-bounded evaluation protocol.
arXiv Detail & Related papers (2026-06-02T18:10:35Z) - Securing LLM Agents Need Intent-to-Execution Integrity [49.490963596514185]
We argue that securing LLM agents requires defining an end-to-end correctness property that specifies when an agent's execution faithfully reflects the user's intent.<n>We observe that LLM agents are structurally analogous to compilers, where security violations correspond to mis-executions that do not preserve user intent.<n>We derive four integrity properties that must hold simultaneously: emphTool Integrity, emphInstruction Integrity, emphJudgment Integrity, and emphData Flow Integrity.
arXiv Detail & Related papers (2026-05-16T12:53:31Z) - Execution Envelopes: A Shared Admission Contract for Backend AI Execution Requests [0.0]
This paper introduces the execution envelope, a normalized internal admission object.<n>It records what kind of execution, what resources were requested, what policy-relevant scope accompanied the request, and what the backend ultimately granted.<n>The central claim is that a shared execution-admission contract is a useful missing primitive for modern AI backends.
arXiv Detail & Related papers (2026-05-08T03:02:38Z) - KnowU-Bench: Towards Interactive, Proactive, and Personalized Mobile Agent Evaluation [72.01173512175531]
KnowU-Bench is an online benchmark for personalized mobile agents.<n>It covers 42 general GUI tasks, 86 personalized tasks, and 64 proactive tasks.<n>Our experiments reveal a striking degradation: agents that excel at explicit task execution fall below 50% under vague instructions.
arXiv Detail & Related papers (2026-04-09T16:50:50Z) - Before the Tool Call: Deterministic Pre-Action Authorization for Autonomous AI Agents [0.0]
Open Agent Passport (OAP) is an open specification and reference implementation that intercepts tool calls synchronously before execution.<n>OAP enforces authorization decisions in a measured median of 53 ms (N=1,000)<n>The same infrastructure that enforces security constraints also enforces quality gates, operational contracts, and compliance controls.
arXiv Detail & Related papers (2026-03-21T21:34:09Z) - IMMACULATE: A Practical LLM Auditing Framework via Verifiable Computation [49.796717294455796]
We present IMMACULATE, a practical auditing framework that detects economically motivated deviations.<n>IMMACULATE selectively audits a small fraction of requests using verifiable computation, achieving strong detection guarantees while amortizing cryptographic overhead.
arXiv Detail & Related papers (2026-02-26T07:21:02Z) - OpenPort Protocol: A Security Governance Specification for AI Agent Tool Access [11.289770127178882]
This paper introduces OpenPort Protocol, a governance-first specification for exposing application tools through a secure server-side gateway.<n>OpenPort defines authorization-dependent discovery, stable response envelopes with machine-actionable texttagent.* reason codes, and an authorization model combining integration credentials, scoped permissions, and ABAC-style policy constraints.<n>For write operations, OpenPort specifies a risk-gated lifecycle that defaults to draft creation and human review, supports time-bounded auto-execution under explicit policy, and enforces high-risk safeguards including preflight impact binding and idempotency
arXiv Detail & Related papers (2026-02-22T05:16:40Z) - Sponge Tool Attack: Stealthy Denial-of-Efficiency against Tool-Augmented Agentic Reasoning [58.432996881401415]
Recent work augments large language models (LLMs) with external tools to enable agentic reasoning.<n>We propose Sponge Tool Attack (STA), which disrupts agentic reasoning solely by rewriting the input prompt.<n>STA generates benign-looking prompt rewrites from the original one with high semantic fidelity.
arXiv Detail & Related papers (2026-01-24T19:36:51Z) - DeepAgent: A General Reasoning Agent with Scalable Toolsets [111.6384541877723]
DeepAgent is an end-to-end deep reasoning agent that performs autonomous thinking, tool discovery, and action execution.<n>To address the challenges of long-horizon interactions, we introduce an autonomous memory folding mechanism that compresses past interactions into structured episodic, working, and tool memories.<n>We develop an end-to-end reinforcement learning strategy, namely ToolPO, that leverages LLM-simulated APIs and applies tool-call advantage attribution to assign fine-grained credit to the tool invocation tokens.
arXiv Detail & Related papers (2025-10-24T16:24:01Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.