Claude AI agent working alongside x64dbg in an AI-assisted reverse-engineering workflow

Connect AI to Reverse-Engineering Tools

Work with MCP integrations for x64dbg, dnSpy, Ghidra, GhidrAssist, Cutter, IDA Pro, Frida, and more.

ChatGPT guidance for implementing an MCP tool for reverse-engineering automation

Build Your Own MCP Tools and Servers

Create MCP servers and tools, structure prompts and context, and use vibe coding to automate debugging and analysis workflows.

LM Studio local language model configuration for reverse-engineering workflows

Use Cloud and Local LLMs

Integrate Claude Desktop, 5ire, OpenAI API, LM Studio, and locally hosted models across Windows and Linux environments.

AI-Driven Debugging and Binary Analysis

Unlock the power of AI in reverse engineering and binary analysis with Model Context Protocol (MCP). This hands-on course shows you how to connect LLM-based AI hosts to debugging, disassembly, and decompilation tools so you can automate repetitive work, gain intelligent insights, and streamline both static and dynamic analysis. You will learn how MCP links AI agents with practical reverse-engineering environments and how to structure prompts and context for reliable technical workflows. Through guided demonstrations and practical exercises, you will use AI-assisted techniques on Windows x86/x64 and Linux binaries; work with MCP servers for x64dbg, dnSpy, Ghidra, GhidrAssist, Cutter, IDA Pro, and Frida; create crackmes for testing; and access MCP servers running inside virtual machines from a host AI agent. You will also vibe-code your own MCP tools and servers for memory reading and writing, register operations, memory mapping, assembly, disassembly, and debugger session control. The course covers cloud-based and locally hosted LLM workflows using Claude Desktop, 5ire, the OpenAI API, LM Studio, and DeepSeek. You will learn how to load and configure local models, connect them through streamable HTTP or stdio, and apply AI to real reversing tasks such as identifying serial-key validation logic, generating keys, bypassing trial periods and anti-debugging protections, and analyzing client-server activation systems. This course is designed for reverse engineers, malware analysts, ethical hackers, penetration testers, cybersecurity professionals, developers, researchers, and technically curious learners who want to apply generative AI to binary analysis. A basic understanding of reverse engineering or low-level programming is recommended, along with familiarity with debuggers, disassemblers, or decompilers, a Windows PC, and a willingness to experiment.

Paul Chin, PhD, course instructor

Meet Your Instructor: Paul Chin, PhD

Paul Chin is a semi-retired college lecturer with a PhD in Computer Science and over 30 years of experience teaching computing and information technology. His interests span reverse engineering, coding, music, health, spirituality, and well-being. Whether teaching face-to-face or online, he finds fulfillment in helping students succeed through practical skills, clear explanations, and personal growth.

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What Udemy Learners Are Saying

Genuine feedback from learners enrolled in the Udemy edition of this course.

Good beginner level AI assisted cracking tutorials!!
Gurwinder

Udemy learner • 4.5/5

This is a very good course. It has really opened my understanding of reverse engineering. It makes my job easier. Great job Professor Paul and keep up the good work.
Chata

Udemy learner • 5/5

Bring AI into Your Reverse-Engineering Workflow

Learn to connect LLMs with reverse-engineering tools, automate repetitive analysis, build MCP integrations, and work with both cloud and local AI models.