OpenPort Protocol: A Security Governance Specification for AI Agent Tool Access
OpenPort Protocol:面向 AI 智能体工具访问的安全治理规范
为 AI 智能体提供结构化工具访问,同时将授权、写入控制与审计牢牢保留在服务端。
研究概览
AI 智能体需要的不只是一份可以调用的工具清单。系统还需要一条由服务端执行的治理边界,用来决定某个凭证当前可以发现哪些能力、读取哪些数据,以及写入请求应当如何被审查和执行。
OpenPort 通过感知授权的工具发现、作用域与属性策略检查、草稿优先写入、高风险操作的 preflight 与重放保护、机器可处理的稳定失败语义、速率限制和结构化审计事件来定义这条边界。参考运行时与一致性验证工具,则使这些治理要求能够跨模型和智能体运行时被实际执行和检验。
核心贡献
- 01
协议契约
定义与模型和运行时无关的工具发现及调用接口,包括端点、响应封装、工具元数据与稳定的 agent.* 原因码。
- 02
受治理的执行路径
将集成凭证、作用域与 ABAC 风格策略约束,同草稿优先写入、preflight 影响绑定、幂等性、可选 State Witness、速率限制和结构化审计结合起来。
- 03
可执行验证
将规范与参考运行时、分层一致性配置、负向安全测试、模糊及滥用回归测试和发布门禁配套交付。
证据与适用范围
本文目前是 arXiv 预印本,其验证对象是一个固定发布点的最小参考运行时所呈现的协议不变量。论文并未宣称该最小运行时已具备生产就绪性;当时仍有部分增强控制处于部分覆盖或后续工作阶段,生产部署还需要持久化治理状态、分布式准入控制和经过强化的领域适配器。
英文摘要
AI agents increasingly require direct, structured access to application data and actions, but production deployments still struggle to express and verify the governance properties that matter in practice: least-privilege authorization, controlled write execution, predictable failure handling, abuse resistance, and auditability. This paper introduces OpenPort Protocol (OPP), a governance-first specification for exposing application tools through a secure server-side gateway that is model- and runtime-neutral and can bind to existing tool ecosystems. OpenPort defines authorization-dependent discovery, stable response envelopes with machine-actionable agent.* reason codes, and an authorization model combining integration credentials, scoped permissions, and ABAC-style policy constraints. 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. To address time-of-check/time-of-use drift in delayed approval flows, OpenPort also specifies an optional State Witness profile that revalidates execution-time preconditions and fails closed on state mismatch. Operationally, the protocol requires admission control (rate limits/quotas) with stable 429 semantics and structured audit events across allow/deny/fail paths so that client recovery and incident analysis are deterministic. We present a reference runtime and an executable governance toolchain (layered conformance profiles, negative security tests, fuzz/abuse regression, and release-gate scans) and evaluate the core profile at a pinned release tag using artifact-based, externally reproducible validation.
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