Connecting Large Language Models (LLMs) to local tools via the Model Context Protocol (MCP) unlocks immense productivity, but it introduces a critical attack surface: Zero-Click Remote Code Execution (RCE) . The scenario is stark. An attacker sends a Google Calendar invite containing a malicious payload in the description. Your Claude Desktop, configured with a standard Calendar MCP server and a terminal tool, reads the schedule. The LLM interprets the payload as a command, invokes your local terminal tool, and executes code on your machine—all without you clicking a link or approving a specific prompt. This article details the root cause of this "Confused Deputy" vulnerability in MCP integrations and provides a production-grade, TypeScript-based solution to sandbox and sanitize tool execution. The Anatomy of an MCP RCE To mitigate the risk, we must understand how benign data transforms into malicious code. The vulnerability chain relies on Indirect Prompt Injection ...
Practical programming blog with step-by-step tutorials, production-ready code, performance and security tips, and API/AI integration guides. Coverage: Next.js, React, Angular, Node.js, Python, Java, .NET, SQL/NoSQL, GraphQL, Docker, Kubernetes, CI/CD, cloud (Amazon AWS, Microsoft Azure, Google Cloud) and AI APIs (OpenAI, ChatGPT, Anthropic, Claude, DeepSeek, Google Gemini, Qwen AI, Perplexity AI. Grok AI, Meta AI). Fast, high-value solutions for developers.