Vulnerable MCP Filesystem Server

Overview

The Vulnerable MCP FS‑Server is a deliberately insecure file system server built to demonstrate how Model Context Protocol (MCP) can expose filesystem resources, tools, and prompts to an AI assistant. It is part of a security curriculum that teaches students how to identify, exploit, and remediate common vulnerabilities in AI‑integrated systems. By running this server locally or on a cloud instance, developers can see firsthand how an AI assistant might be coerced into revealing sensitive data or executing unintended actions when interacting with a file‑based MCP endpoint.

The server implements the core MCP architecture: it advertises resources (files and directories), a set of tools for reading, writing, and deleting files, and a simple prompt that instructs the AI on how to use these tools. The file system is intentionally misconfigured—files are world‑readable, directories lack proper permissions, and the toolset exposes a command‐line interface that accepts arbitrary file paths. This design allows an attacker‑simulated AI to traverse the filesystem, read hidden configuration files, and even modify or delete critical data. The server’s output logs every request, providing a clear audit trail that can be analyzed to understand how the AI interacts with external resources.

Key capabilities include:

• Resource enumeration: The server lists all files and directories in the exposed path, making it easy for an AI to discover hidden or sensitive data.
• Tool execution: Read, write, and delete operations are exposed as callable tools, letting the AI perform file manipulations directly.
• Prompt integration: A pre‑defined prompt guides the AI to use the tools, demonstrating how context can be leveraged to direct assistant behavior.
• Logging and monitoring: Every interaction is logged with timestamps, request payloads, and tool outputs, enabling developers to trace the AI’s actions.

Real‑world use cases for this MCP server include:

• Security training: Educators can use it to teach students about the risks of exposing file systems to AI assistants and how to harden endpoints.
• Penetration testing: Red teams can simulate attacks where an AI assistant is tricked into revealing credentials or manipulating system files.
• AI workflow validation: Developers can test how their AI applications handle untrusted file operations, ensuring that proper safeguards are in place before deployment.

Because the server is intentionally vulnerable, it serves as a living laboratory for exploring the intersection of AI and system security. By integrating it into an MCP‑enabled workflow, developers can observe how a seemingly benign AI assistant can become a vector for privilege escalation or data exfiltration when interacting with poorly protected file resources. This makes the Vulnerable MCP FS‑Server an invaluable tool for anyone looking to understand, test, and mitigate security risks in AI‑augmented environments.