Blockchain Security Audit Toolkit

A comprehensive Python-based toolkit for conducting thorough blockchain and DeFi smart contract security audits.

Features

• Signature Analysis: Advanced pattern matching for detecting high and medium risk function signatures in smart contracts
• Risk Assessment: Comprehensive risk level determination and detailed security recommendations
• DeFi Focus: Specialized analysis for DeFi protocols and common attack vectors

Installation

pip install web3 eth-utils eth-abi
git clone https://github.com/314-hash/securityaudits.github.io
cd securityaudits.github.io

Quick Start

from audit_tools.signature_analyzer import SignatureAnalyzer

# Initialize the analyzer
analyzer = SignatureAnalyzer()

# Analyze function signatures
results = analyzer.analyze_signatures([
    "transferOwnership(address)",
    "delegatecall(bytes)",
    "withdraw(uint256)"
])

# Print results
print(f"Overall Risk Level: {results['risk_level']}")
print("\nFindings:")
for finding in results['findings']:
    print(f"- {finding['signature']}: {finding['risk_level']} risk")
print("\nRecommendations:")
for rec in results['recommendations']:
    print(f"- {rec}")

Components

SignatureAnalyzer

The SignatureAnalyzer class provides functionality to analyze smart contract function signatures for potential security risks. It categorizes risks into three levels:

• HIGH: Critical security risks like delegatecall, selfdestruct, etc.
• MEDIUM: Potentially risky operations like transfers, administrative functions, etc.
• LOW: Standard functions with no immediate security concerns

Risk Patterns

The analyzer checks for various risk patterns including:

High Risk Patterns

• delegatecall operations
• selfdestruct capability
• raw operations
• assembly code usage
• signature recovery (ecrecover)
• ownership transfers

Medium Risk Patterns

• transfer functions
• administrative operations
• token approvals
• asset management functions
• external calls
• minting/burning capabilities

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.