AI and MCP for Reverse Engineering

Unlock the power of **AI in reverse engineering and binary analysis with Model Context Protocol (MCP)**. In this course, you’ll learn how to integrate Large Language Models (LLMs) into your reverse engineering workflow using the Model Context Protocol (MCP) — a cutting-edge framework designed to connect AI hosts with your debugging, disassembly, and decompiling tools. Inspired by the rise of Vibe Coding—a modern trend focused on fluid, creative, AI-enhanced development—this course brings the same philosophy to the world of reverse engineering. Welcome to AI and MCP for Reverse Engineering: a smarter, more intuitive way to analyze, automate, and understand complex binaries with the help of Generative AI. Whether you're working in malware analysis, vulnerability research, ethical hacking, or software protection, this course will show you how to leverage AI to automate repetitive tasks, gain intelligent insights, and streamline both static and dynamic analysis. AI-Driven Debugging and Analysis: Enhancing reverse engineering skills with Generative-AI You’ll explore how Generative AI can support reverse engineering, static and dynamic analysis for Windows and Linux. What You’ll Learn - What Model Context Protocol (MCP) is and how it enables AI integration in reverse engineering and debugging - How to connect LLM-based AI hosts to your debugging, disassembly, and decompiling tools and workflows - Prompt engineering and context structuring techniques for reverse engineering tasks - AI-assisted reverse engineering for windows x86, x64 and Linux binaries - Use cloud-based AI Agents as well as run LLM locally for reverse engineering - Vibe-coding your own MCP tools Who This Course Is For - Reverse engineers and malware analysts looking to increase productivity with AI - Ethical hackers and penetration testers exploring automation with LLMs - Cybersecurity professionals interested in practical AI integration - Developers, researchers, and learners curious about applying AI to binary analysis Prerequisites - A basic understanding of reverse engineering or low-level programming - Familiarity with tools like debuggers, disassemblers, or decompilers (helpful but not mandatory) - Curiosity and openness to experiment with AI in technical workflows Why Take This Course? AI and LLMs are rapidly transforming the field of reverse engineering and debugging. With the Model Context Protocol as your bridge, you can plug powerful AI hosts into your environment and achieve deeper insights with less manual effort. Whether you're analyzing malware, reversing binaries, debugging protected applications, or decompiling complex binaries, this course equips you with the hands-on skills to make AI your trusted assistant in technical analysis. And now, with **AI and MCP for Reverse Engineering**, you're not just learning to reverse — you're learning to reverse with clarity, creativity, and intelligent flow. Enroll now and I will see you inside!

What you'll learn:

• What Model Context Protocol (MCP) is
• How to enable AI integration in reverse engineering and debugging
• How to connect LLM-based AI hosts to your debugging, disassembly, and decompiling tools and workflows
• Prompt engineering and context structuring techniques for reverse engineering tasks
• Real-world use cases where AI significantly enhances reverse engineering, debugging, and static analysis
• Vibe coding your MCP tools
• Create your own MCP server
• Use cloud-based LLM and also run LLM locally for reverse engineering
• Run Windows-based LLM and also Linux-based LLM
• MCP servers for x64dbg, dnSpy, ghidra, Cutter, IDA Pro and more
• Run MCP server in virtual machine and access from the host machine
• Create your own Crackmes for testing
• Use Claude Desktop, 5ire and LM Studio for MCP integration
• Run your own LLM models using LM Studio for Inferencing
• Using OpenAI API for LLM
• AI-assisted reverse engineering of x86 and x64 windows and Linux binaries
• and more. . .