An AI-powered binary analysis and optimization system that enhances disassembled code analysis through machine learning techniques.
Neurassembly is designed to analyze and optimize disassembled binary code. By leveraging machine learning, it aims to improve the efficiency of reverse-engineered code while maintaining its original functionality, particularly useful in malware analysis and security research.
- Machine learning-based disassembled code optimization
- Integration with popular disassemblers
- Pattern recognition for common code obfuscation techniques
- Performance optimization of disassembled code
- Automated binary analysis and optimization
/src: Core source code/api: Disassembler integration interfaces/data: Binary analysis and processing/evaluation: Performance metrics and validation/model: ML models and optimization logic
- Develop an AI system for analyzing disassembled code patterns
- Improve efficiency of reverse-engineered code
- Identify and optimize obfuscated code patterns
- Provide automated optimization of disassembled binaries
Project is under active development.