The Model Context Protocol (MCP) is an emerging standard designed to enable
seamless interaction between Large Language Model (LLM) applications and
external tools or resources. Within a short period, thousands of MCP services
have already been developed and deployed. However, the client-server
integration architecture inherent in MCP may expand the attack surface against
LLM Agent systems, introducing new vulnerabilities that allow attackers to
exploit by designing malicious MCP servers. In this paper, we present the first
systematic study of attack vectors targeting the MCP ecosystem. Our analysis
identifies four categories of attacks, i.e., Tool Poisoning Attacks, Puppet
Attacks, Rug Pull Attacks, and Exploitation via Malicious External Resources.
To evaluate the feasibility of these attacks, we conduct experiments following
the typical steps of launching an attack through malicious MCP servers:
upload-download-attack. Specifically, we first construct malicious MCP servers
and successfully upload them to three widely used MCP aggregation platforms.
The results indicate that current audit mechanisms are insufficient to identify
and prevent the proposed attack methods. Next, through a user study and
interview with 20 participants, we demonstrate that users struggle to identify
malicious MCP servers and often unknowingly install them from aggregator
platforms. Finally, we demonstrate that these attacks can trigger harmful
behaviors within the user's local environment-such as accessing private files
or controlling devices to transfer digital assets-by deploying a
proof-of-concept (PoC) framework against five leading LLMs. Additionally, based
on interview results, we discuss four key challenges faced by the current
security ecosystem surrounding MCP servers. These findings underscore the
urgent need for robust security mechanisms to defend against malicious MCP
servers.