Understanding security risks in AI model context protocols

The Model Context Protocol (MCP) enables AI systems to coordinate tasks across tools and services, but this connectivity introduces security risks. As enterprises adopt MCP-based systems, security measures often lag behind.

This white paper explores MCP vulnerabilities and offers guidance for securing AI applications. Key insights include:

· How prompt injection, tool shadowing, and data exfiltration exploit MCP
· Demonstrations of hidden vulnerabilities in accessible MCP servers
· Security practices like runtime monitoring, allowlisting, and proxy layers

Learn to protect your AI systems from emerging threats in this essential guide.