This article explains how to use AI agents and Model Context Protocol (MCP) servers for effective threat modeling in security operations. It outlines the five layers of context needed for thorough analysis and emphasizes the importance of integrating internal software data to enhance detection coverage.

The article provides an in-depth explanation of the Model Context Protocol (MCP), highlighting its role in enhancing the capabilities of large language models (LLMs) through improved context provision. It also conducts a detailed threat model analysis, identifying key security vulnerabilities and potential attack vectors associated with MCP's functionalities, such as sampling and composability.