MCP Tool Descriptions Can Be Silently Altered After Approval, Exposing AI Agents

A security vulnerability in the Model Context Protocol (MCP) ecosystem allows tool descriptions fetched by AI agents to be modified after a user has reviewed and approved them, with no diff, lockfile, or signature to flag the change. Because tool descriptions are loaded directly into an agent's context window on every connection, a malicious or compromised npm package maintainer can inject prompt-injection instructions — such as silently exfiltrating SSH private keys — without touching the user's config file. Existing security scanners like Dependabot, Snyk, and CodeQL do not inspect MCP tool descriptions, leaving the attack surface entirely unmonitored. A tool called Bulwark has been developed to address this gap by generating a content-hash lockfile of all tool description strings, enabling verification of any material changes between sessions. The broader issue stems from four compounding ecosystem properties: tool descriptions acting as prompt content, no pinning mechanism, widespread use of auto-resolving unpinned package fetches, and a lack of organizational inventory of deployed MCP servers.