The analysis_claude_code project employs a systematic approach to reverse engineering analysis, and its key features include:
- Mixed analysis methodsCombine static code analysis (e.g., code preprocessing, LLM-assisted analysis) and dynamic behavioral verification (e.g., runtime analysis, integration testing) to ensure the accuracy of analysis results.
- Modular Processing FlowOver 50,000 lines of obfuscated code split into 102 logical modules (.mjs format) for chunked analysis and verification.
- Cross-validation mechanism: Through multiple rounds of iterative analysis and result comparison, the accuracy of core architecture design reaches 95%, and the accuracy of key mechanism implementation reaches 98%.
- Documented Workflow: Provide standard operating procedures (SOPs) for reverse engineering, including reusable analysis scripts such as beautify.js and split.js.
- Extensible Validation FrameworkSupports the addition of custom analysis rules and test cases for continuous updating and validation of analysis results.
This structured and repeatable reverse engineering methodology is not only applicable to Claude Code analysis, but can also be used as a reference framework for reverse engineering other complex systems.
This answer comes from the articleanalysis_claude_code: a library for reverse engineering Claude Code.The
May not be reproduced without permission:AI productivity tools " What are the unique aspects of the reverse engineering analysis methodology offered by the program?
English 
简体中文 
日本語 
Deutsch 
Português do Brasil