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arXiv · 2606.21338

"What Happens Locally, Leaks Globally": Detecting Privacy Leakage Risks in MCP Servers

Biwei Yan·Minghui Xu·Yijun Yang·Boyang Ma·Xuelong Dai·Jingku Li·Yue Zhang
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Abstract

The Model Context Protocol (MCP) has rapidly become the de facto standard for connecting large language models (LLMs) to external resources, but it also introduces a class of privacy risks that existing tools are ill-equipped to detect. Unlike conventional exfiltration bugs, leakage in MCP servers is largely protocol-induced: credentials, API keys, and Personally Identifiable Information (PII) cross the local/LLM boundary simply by being returned, logged, or raised inside a tool handler, with no explicit outbound request in the source code. We present MCPPrivacyDetector, a context-aware cross-language static analysis framework that detects such leakage in multilingual MCP servers. MCPPrivacyDetector lifts heterogeneous code implemented across different programming language (e.g., Python) into a unified program representation, applies context-aware semantic filtering to isolate genuinely sensitive values and protocol-specific implicit sinks (e.g., @mcp.tool handlers), and performs taint analysis to enumerate feasible flows. Applied to 10,655 real-world MCP servers, MCPPrivacyDetector finds leakage rates above 10%. Case studies confirm concrete exposures including leaked Bearer tokens, propagated API keys, and plaintext authentication credentials, arguing for systematic, protocol-aware safeguards in the emerging LLM agent toolchain.

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Biwei Yan, Minghui Xu, Yijun Yang, Boyang Ma, Xuelong Dai, Jingku Li, Yue Zhang. 2026-06-19. "What Happens Locally, Leaks Globally": Detecting Privacy Leakage Risks in MCP Servers. https://arxiv.org/abs/2606.21338

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