AI and MCP for Reverse Engineering — 90% Off Coupon

AI assisted reversing by integrating LLMs with tools via Model Context Protocol (MCP) to automate & accelerate analysis

4.7 165 students enrolledCreated by Paul Chin, PhDLast updated: 🌐 English

Course Overview — Key Details

A quick-reference summary of the most important course details: provider, instructor, difficulty, duration, and what the coupon covers.

•Course Title: AI and MCP for Reverse Engineering
•Provider: Udemy (listed via CourseSpeak)
•Instructor: Paul Chin, PhD
•Coupon Verified On: November 11, 2025
•Difficulty Level: All Levels
•Category: IT & Software
•Subcategory: Reverse Engineering
•Duration: 12h 30m of on-demand video
•Language: English
•Access: Lifetime Access · Mobile & TV compatible
•Certificate: Certificate of completion included
•Top Learning Outcomes: 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
•Prerequisites: A basic understanding of reverse engineering or low-level programming · Familiarity with tools like debuggers, disassemblers, or decompilers
•Coupon: Click REDEEM COUPON below to apply discount
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What You'll Learn

Skills and competencies you'll gain from this Udemy course:

✓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. . .

Course Requirements & Prerequisites

Background knowledge or tools recommended before starting this course:

•A basic understanding of reverse engineering or low-level programming
•Familiarity with tools like debuggers, disassemblers, or decompilers
•Curiosity and openness to experiment with AI in technical workflows

About This Udemy Course

Full course description including curriculum, tools covered, and learning methodology:

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About the Instructor

This course is taught by Paul Chin, PhD. For full instructor bio, credentials, and other courses they teach, visit the instructor profile on Udemy.

•Instructor: Paul Chin, PhD
•Field: IT & Software
•Teaching Style: Practical, project-based learning (as described in course curriculum)

Is the AI and MCP for Reverse Engineering Coupon Worth It?

AI and MCP for Reverse Engineering is a it & software course offered on Udemy by instructor Paul Chin, PhD, spanning 12h 30m of on-demand content. It holds a 4.7/5 rating from over 165 enrolled students.

Through CourseSpeak, you can access this course with a 90% discount coupon. The coupon was last verified on November 11, 2025. Udemy coupons are time-limited and claimed on a first-come basis — we recommend redeeming as soon as possible.

New to redeeming coupons? Visit our How to Redeem Udemy Coupon on CourseSpeak for detailed instructions on how to apply coupon codes.

✓ Our Take: Based on the rating (4.7/5) and enrollment numbers (165 students), this course appears well-regarded in its category. Use the coupon to access it at a significantly reduced price — and judge for yourself using Udemy's 30-day money-back guarantee.

Course Rating Summary

Aggregate rating data sourced from Udemy as of November 2025. For individual student reviews, visit the course page directly.

4.7
165 ratings
5 stars
75%
4 stars
15%
3 stars
6%
2 stars
2%
1 star
2%

* Rating distribution is estimated. For exact per-star counts, visit the Udemy course page.

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