ECDSA Security Analysis Suite
A comprehensive security analysis tool for ECDSA signatures, detecting various vulnerabilities and attack vectors.
Features
Vulnerability Detection
- Hidden Number Problem (HNP) Analysis
- Lattice Attack Vulnerability Assessment
- Side Channel Leakage Detection
- Bleichenbacher Attack Analysis
- Prefix Lattice Attack Detection
- Fault Injection Simulation
- Quantum Vulnerability Assessment
- Zero-Value Attack Analysis
- Timing Correlation Analysis
- Entropy Pattern Analysis
- Modular Arithmetic Pattern Detection
Advanced Analysis Capabilities
- Machine Learning-based Pattern Detection
- Statistical Analysis
- Power Analysis Simulation
- Cache Timing Analysis
- Comprehensive Risk Assessment
Usage
Clone the repository
Dependencies
- ecdsa
- numpy
- scipy
- rich
- matplotlib
- scikit-learn
Usage
python3 enhanced_analysis.py
Output
Features in Detail
Quantum Analysis
- Estimates required qubits for attacks
- Analyzes Shor's algorithm applicability
- Evaluates quantum safety score
- Provides timeline estimates
Modular Pattern Analysis
- Detects weak modular patterns
- Analyzes exploitation difficulty
- Provides statistical correlations
- Evaluates attack complexity
Side Channel Analysis
- Timing leakage detection
- Power analysis simulation
- Cache vulnerability assessment
- Exploitation probability calculation
Security Recommendations
The tool provides:
- Detailed vulnerability reports
- Risk assessments
- Actionable recommendations
- Mitigation strategies
Visualization
Includes visual analysis of:
- Signature distributions
- Risk assessments
- Timing patterns
- Cluster analysis
Contributing
Contributions are welcome! Please feel free to submit a Pull Request. Hoping to make this ECDSA Security Suite a complete vulnerability Detection program!
License
This project is licensed under the MIT License - see the LICENSE file for details.
Warning
This tool is for security research and educational purposes only. Do not use it to analyze production systems without proper authorization.
Authors
Acknowledgments
- ECDSA implementation based on Python ecdsa library
- Visualization using matplotlib and rich
- Statistical analysis using numpy and scipy