cs.AI updates on arXiv.org 10月21日 12:25
MCP生态系统安全分析
index_new5.html
../../../zaker_core/zaker_tpl_static/wap/tpl_guoji1.html

 

本文对MCP生态系统进行首次全面安全分析,揭示其架构与安全风险,并提出防御策略。

arXiv:2510.16558v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) is an emerging open standard that enables AI-powered applications to interact with external tools through structured metadata. A rapidly growing ecosystem has formed around MCP, including a wide range of MCP hosts (i.e., Cursor, Windsurf, Claude Desktop, and Cline), MCP registries (i.e., mcp.so, MCP Market, MCP Store, Pulse MCP, Smithery, and npm), and thousands of community-contributed MCP servers. Although the MCP ecosystem is gaining traction, there has been little systematic study of its architecture and associated security risks. In this paper, we present the first comprehensive security analysis of the MCP ecosystem. We decompose MCP ecosystem into three core components: hosts, registries, and servers, and study the interactions and trust relationships among them. Users search for servers on registries and configure them in the host, which translates LLM-generated output into external tool invocations provided by the servers and executes them. Our qualitative analysis reveals that hosts lack output verification mechanisms for LLM-generated outputs, enabling malicious servers to manipulate model behavior and induce a variety of security threats, including but not limited to sensitive data exfiltration. We uncover a wide range of vulnerabilities that enable attackers to hijack servers, due to the lack of a vetted server submission process in registries. To support our analysis, we collect and analyze a dataset of 67,057 servers from six public registries. Our quantitative analysis demonstrates that a substantial number of servers can be hijacked by attackers. Finally, we propose practical defense strategies for MCP hosts, registries, and users. We responsibly disclosed our findings to affected hosts and registries.

Fish AI Reader

Fish AI Reader

AI辅助创作,多种专业模板,深度分析,高质量内容生成。从观点提取到深度思考,FishAI为您提供全方位的创作支持。新版本引入自定义参数,让您的创作更加个性化和精准。

FishAI

FishAI

鱼阅,AI 时代的下一个智能信息助手,助你摆脱信息焦虑

联系邮箱 441953276@qq.com

相关标签

MCP生态系统 安全分析 防御策略
相关文章