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arXiv 2602.01129cs.CR
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SMCP: 安全模型上下文协议

SMCP: Secure Model Context Protocol

Huazhong University of Science and Technology(华中科技大学)

Xinyi Hou, Shenao Wang, Yifan Zhang, Ziluo Xue, Yanjie Zhao, Cai Fu, Haoyu Wang

AI总结:

SMCP通过统一身份管理、强认证和细粒度策略执行,提升智能体系统在工具调用中的安全性和可靠性。

摘要:

基于大型语言模型(LLMs)的智能体AI系统正从封闭的单一模型框架转向开放生态系统,该生态系统连接了各种智能体、外部工具和资源。模型上下文协议(MCP)已成为一种标准,用于统一工具访问,使智能体能够更灵活地发现、调用和协调工具。然而,随着MCP的广泛应用,也带来了一套新的安全和隐私挑战。这些挑战包括未经授权的访问、工具污染、提示注入、特权提升和供应链攻击等风险,这些风险可能影响协议工作流程的不同部分。尽管近期研究已探讨了可能的攻击面并提出了有针对性的对策,但MCP在协议层面仍缺乏系统性的安全改进。为此,我们引入了安全模型上下文协议(SMCP),该协议在MCP基础上增加了统一的身份管理、强大的相互认证、持续的安全上下文传播、细粒度的策略执行以及全面的审计日志记录。在本文中,我们介绍了SMCP的主要组成部分,解释了它如何帮助降低安全风险,并通过实际例子展示了其应用。我们希望这项工作能为开发强大且适应性强,同时安全且可靠的智能体系统做出贡献。

英文摘要:

Agentic AI systems built around large language models (LLMs) are moving away from closed, single-model frameworks and toward open ecosystems that connect a variety of agents, external tools, and resources. The Model Context Protocol (MCP) has emerged as a standard to unify tool access, allowing agents to discover, invoke, and coordinate with tools more flexibly. However, as MCP becomes more widely adopted, it also brings a new set of security and privacy challenges. These include risks such as unauthorized access, tool poisoning, prompt injection, privilege escalation, and supply chain attacks, any of which can impact different parts of the protocol workflow. While recent research has examined possible attack surfaces and suggested targeted countermeasures, there is still a lack of systematic, protocol-level security improvements for MCP. To address this, we introduce the Secure Model Context Protocol (SMCP), which builds on MCP by adding unified identity management, robust mutual authentication, ongoing security context propagation, fine-grained policy enforcement, and comprehensive audit logging. In this paper, we present the main components of SMCP, explain how it helps reduce security risks, and illustrate its application with practical examples. We hope that this work will contribute to the development of agentic systems that are not only powerful and adaptable, but also secure and dependable.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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