Source URL: https://embracethered.com/blog/posts/2025/anthropic-filesystem-mcp-server-bypass/
Source: Embrace The Red
Title: Anthropic Filesystem MCP Server: Directory Access Bypass via Improper Path Validation
Feedly Summary: A few months ago I was looking at the filesystem MCP server from Anthropic.
The server allows to give an AI, like Claude Desktop, access to the local filesystem to read files or edit them and so forth.
I was curious about access control and in the documentation there is a configuration setting to set allowedDirectories, which the AI should be allowed access to:
As you can see the example shows two folders being allowlisted for access.
AI Summary and Description: Yes
Summary: The text discusses the configuration of access control settings for an AI system (Claude Desktop) that interacts with the local filesystem. This has implications for AI Security and Information Security as it highlights the importance of controlled access in AI applications.
Detailed Description: The provided text touches on several significant aspects of AI Security and governance related to file access permissions and configuration settings:
– **AI File Access Control**: The mention of the filesystem server MCP from Anthropic indicates a practical implementation of AI that interacts with local data. This raises questions about how access control can be effectively managed.
– **Configuration Settings**: The existence of a configuration setting for `allowedDirectories` suggests a mechanism for specifying which directories the AI has permission to access. This is crucial for reducing security risks associated with unauthorized data access.
– **Allowlisting**: The example demonstrates the practice of allowlisting (or whitelisting), which is a security measure aimed at specifying certain directories as safe for use by the AI, thereby limiting its access to only those locations.
– **Implications for Security Practitioners**: Security professionals must consider how such settings can be applied effectively in deployments of AI systems to mitigate risks related to data exposure and maintain compliance with data governance policies.
In summary, the text provides insights into the configurations vital for ensuring secure interaction between AI systems and the local file systems, emphasizing the need for sound security practices in the development and deployment of AI technologies. This is essential for professionals working in AI Security and Information Security domains, who must implement frameworks to govern access controls and protect sensitive data.