Fausto-404/js-reverse-automation--skill

What it solves

It automates the tedious process of frontend JavaScript reverse engineering. Instead of manually analyzing obfuscated code or struggling to recreate complex browser environments (environment patching), it uses AI and remote procedure calls (JSRPC) to treat the actual browser as a decryption engine, significantly speeding up the process of uncovering encryption logic for login parameters, request signatures, and encrypted responses.

How it works

The project integrates AI agents (via MCP - Model Context Protocol) with a real browser to automate the reverse engineering pipeline across several phases (Phase 0-9):

1. Discovery: Uses chrome-devtools-mcp to connect to a live browser, hooking into network requests (fetch, XHR) and common crypto libraries to find where encryption happens.
2. Analysis: Employs runtime probes, Webpack module parsing, and a scoring system to pinpoint the exact encryption functions.
3. Execution: Instead of rewriting the JS in Python, it generates JSRPC injection code to call the original functions directly in the browser.
4. Delivery: Automatically sets up a Python Flask proxy and provides configuration for Burp Suite's autoDecoder to integrate the decryption/encryption process into a professional penetration testing workflow.
5. Evolution: Stores experience in an evolution matrix to improve handling of new obfuscation and anti-debugging techniques over time.

Who it’s for

• Security researchers and penetration testers performing web security audits.
• Data scrapers needing to bypass complex JavaScript encryption/signing.
• Developers analyzing frontend security implementations.

Highlights

• JSRPC Integration: Bypasses the need for manual environment patching by calling functions in a real browser.
• Full-Chain Automation: Moves from discovery to a working Flask proxy and Burp Suite configuration automatically.
• Anti-Debugging Support: Includes capabilities to detect and bypass anti-hooking and anti-debugging mechanisms.
• Evidence-Based Validation: Uses SHA-256 fingerprinting and differential analysis to ensure the identified encryption functions are correct before delivery.