arXiv:2608.24017cs.CRcs.AI2026-08

为浏览器内LLM代理设计双层信任架构,解决工具调用中的安全漏洞。

WebMCP-Phalanx: Enforcing and Characterizing Trust Boundaries for Browser-Integrated LLM Agents

论文配图:WebMCP-Phalanx: Enforcing and Characterizing Trust Boundaries for Browser-Integrated LLM Agents
图 1 · 摘自论文原文
  • 通过加密凭证绑定工具与创建者,全程追踪工具归属
  • 双代理机制阻断80次注入攻击,仅2次成功逃逸
  • 适合关注浏览器安全的AI应用开发者

新兴的W3C WebMCP提案允许LLM代理调用网页暴露的工具。但在多方网页环境中,基于同源策略(SOP)的浏览器安全模型无法提供足够的工具溯源与生命周期保障,引发三类风险:主体归属伪造、工具生命周期失控、语义提示注入。我们提出WebMCP-Phalanx,一种双层代理运行时架构。第一层提供浏览器原生信任锚点,通过加密保护的能力凭证将每个工具与其注册主体绑定,并在工具全生命周期中传播溯源标签。第二层将语义检查与特权工具调用分离:无调用权限的隔离代理(Q-LLM)检查工具元数据、输出及页面内容是否存在提示注入;验证后的内容才传递给特权代理(P-LLM)执行,且Q-LLM内部状态对页面脚本不可见。实证评估显示,浏览器原生所有权机制将撤销与覆盖攻击成功率从100%降至0%。双代理运行时拦截全部80次嵌入工具描述中的提示注入攻击,仅2次工具返回攻击成功。所有实验中任务效用与无攻击基线无统计差异。然而,在白盒自适应攻击下,可通过恶意工具名在检查前调用绕过基于描述的过滤。此发现推动引入调用时机门控,延迟工具调用直至所有代理可见元数据均完成验证。

原文摘要 · Abstract (English)

The emerging W3C WebMCP proposal enables LLM agents to invoke tools exposed by web pages. In multi-party web environments, however, integrating agent execution into a browser security model centered on the Same-Origin Policy (SOP) leaves insufficient provenance and lifecycle guarantees for agent-accessible tools, creating three risks: subject-attribution spoofing, uncontrolled tool lifecycles, and semantic prompt injection. We propose WebMCP-Phalanx, a dual-layer agent runtime architecture. Its first layer provides a browser-native trust anchor that binds each tool to its registering principal through cryptographically protected capability credentials and propagates provenance labels throughout the tool lifecycle. Its second layer separates semantic inspection from privileged tool use. A Quarantine Agent (Q-LLM), without tool invocation authority, inspects tool metadata, outputs, and page-supplied content for prompt injection. Validated content is then forwarded to a Privileged Agent (P-LLM) for execution, while the Q-LLM's internal state remains hidden from page scripts. Empirical evaluation shows that the browser-native ownership mechanism reduces revocation and overwrite attack success from 100\% to 0\%. The dual-agent runtime blocks all 80 prompt-injection attempts embedded in tool descriptions and limits tool-return attacks to 2 successful cases out of 80. Across experiments, task utility remains statistically indistinguishable from the no-attack baseline. Under a white-box adaptive attacker, however, description-based filtering can be bypassed through malicious tool names invoked before inspection. This finding motivates a call-timing gate that delays tool invocation until all agent-visible tool metadata has been validated.

浏览器安全LLM代理信任边界

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