arXiv AI By Lin-Fa Lee, YI-YU Chang, Kuo-Hui Yeh

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

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WebMCP-Phalanx introduces a dual‑layer runtime for browser‑integrated LLM agents that enforces trust boundaries on web‑exposed tools. The first layer uses cryptographic capability credentials to bind tools to their registering principals and propagate provenance labels, while the second layer separates semantic inspection from privileged tool use via a Quarantine Agent that validates tool metadata before a Privileged Agent can execute it. Empirical results show the approach eliminates revocation and overwrite attacks, blocks most prompt‑injection attempts, and maintains task utility comparable to a no‑attack baseline.

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