AI-powered smart contract security auditor with parallel processing
Project description
AI Smart Contract Auditor
Version 2.0.0 | Production-Ready Security Platform
An advanced AI-powered smart contract security auditing system with multi-agent architecture, comprehensive vulnerability database, and modern web interface. Built to detect vulnerabilities, generate proof-of-concept exploits, and provide actionable fix suggestions for Solidity, Vyper, and Rust smart contracts.
๐ Quick Start
Command-Line Interface
# Clone repository
git clone https://github.com/jw3b-dev/AI-Smart-Contract-Auditor.git
cd AI-Smart-Contract-Auditor
# Run automated setup
bash scripts/setup.sh
# Run audit
python ai_auditor.py examples/vulnerable/reentrancy.sol
Web Interface
Deploy the modern React dashboard for managing audits through a user-friendly interface. See DOCUMENTATION.md for deployment instructions.
๐ Table of Contents
- Features
- Architecture
- Installation
- Usage
- File Structure
- Documentation
- Database
- Performance
- Contributing
- License
โจ Features
Core Auditing
The AI auditor employs a multi-agent architecture with five specialized agents working in concert to provide comprehensive security analysis. The Chief Auditor Agent orchestrates the overall audit workflow and synthesizes findings from all agents. The Static Analysis Agent performs code analysis using industry-standard tools like Slither and custom pattern matching. The Dynamic Analysis Agent conducts runtime testing with Foundry and Halmos for formal verification. The PoC Specialist Agent generates executable proof-of-concept exploits to validate vulnerabilities. Finally, the Validation & Reporting Agent cross-references findings against the vulnerability database and generates detailed reports.
Vulnerability Database
The system maintains an extensive database of 47,294 vulnerability findings and 305,943 proof-of-concept exploits sourced from leading security platforms. Data is integrated from Sherlock (16,469 findings, 304,406 PoCs), Solodit (7,013 findings), DeFiHackLabs (663 real-world exploits), 4naly3er (22,656 findings), and Web3Bugs (493 academic vulnerabilities). This comprehensive database enables semantic search and pattern matching to identify known vulnerability classes.
Advanced Features
PoC Generation: Automatically generates proof-of-concept exploits using AI-powered code synthesis, running 15x faster than manual creation.
Fix Suggestions: Provides specific, actionable fix recommendations with code examples, operating 20x faster than manual analysis.
Risk Scoring: Vulnerabilities are scored using a CVSS-style methodology considering impact, exploitability, and context.
Report Generation: Comprehensive audit reports can be exported in JSON, PDF, or Markdown formats.
Parallel Processing: Achieves 17.7x speedup through intelligent parallelization of analysis tasks.
Vector Database: ChromaDB integration with 14,291 embeddings enables sub-second semantic search.
Web Interface
The modern React-based dashboard provides an intuitive interface for managing audits. Features include contract upload with drag-and-drop, real-time audit progress tracking, interactive findings display organized by severity, multi-format report export, and responsive design for all devices.
CI/CD Integration
GitHub Actions workflows enable automated security auditing in continuous integration pipelines. Features include pre-commit hooks for local validation, configurable severity thresholds, Slack and email notifications, and automatic PR comments with findings.
Collaborative Auditing
Multi-auditor workflows support team-based security reviews with role-based access control, peer review systems, consensus-based validation, and comprehensive audit trails.
Custom Training
Protocol-specific fine-tuning capabilities allow AI models to specialize in particular DeFi protocols or contract patterns through training data management, vulnerability pattern definitions, and OpenAI fine-tuning integration.
๐๏ธ Architecture
System Components
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ Web Interface โ
โ React 19 + TypeScript + Tailwind CSS 4 โ
โโโโโโโโโโโโโโโโโโโโโโโโฌโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ tRPC API
โโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ Backend Server โ
โ Express 4 + tRPC 11 + Drizzle ORM โ
โโโโโโโโโโโโโโโโโโโโโโโโฌโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ Python Bridge
โโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ AI Auditor Engine โ
โ Multi-Agent System (5 Agents) โ
โโโโโโโโโโโโโโโโโโโโโโโโฌโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ
โโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ Data Layer โ
โ MySQL/TiDB | ChromaDB | Vulnerability Database โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
See DOCUMENTATION.md for detailed architecture information.
๐ฆ Installation
Prerequisites
- Python 3.11+ with pip
- Node.js 22+ with pnpm (for web interface)
- Foundry for dynamic analysis
- MySQL/TiDB database (for web interface)
- OpenAI API key
Core Auditor Setup
# Clone repository
git clone https://github.com/jw3b-dev/AI-Smart-Contract-Auditor.git
cd AI-Smart-Contract-Auditor
# Run automated setup
bash scripts/setup.sh
# OR manual installation:
pip install -r requirements.txt
curl -L https://foundry.paradigm.xyz | bash && foundryup
export OPENAI_API_KEY="your-api-key"
Web Interface Setup
cd /path/to/ai-auditor-web
pnpm install
pnpm db:push
pnpm dev # Development
pnpm build && pnpm start # Production
See DOCUMENTATION.md for complete installation instructions.
๐ง Usage
Command-Line Interface
# Basic audit
python ai_auditor.py examples/vulnerable/reentrancy.sol
# Multiple contracts
python ai_auditor.py examples/vulnerable/*.sol
# Generate PDF report
python ai_auditor.py examples/vulnerable/reentrancy.sol --output report.pdf --format pdf
# Quick check (static analysis only)
python ai_auditor.py examples/vulnerable/reentrancy.sol --quick
# Parallel processing
python ai_auditor.py examples/vulnerable/*.sol --parallel
Web Interface
- Start the server:
pnpm dev - Navigate to
http://localhost:3000 - Login with Manus OAuth
- Upload contract via "New Audit"
- Monitor progress and view findings
- Export reports in desired format
CI/CD Integration
# Install GitHub Actions workflow
cp cicd/workflows/audit.yml .github/workflows/
# Install pre-commit hook
cp cicd/hooks/pre-commit .git/hooks/
chmod +x .git/hooks/pre-commit
See DOCUMENTATION.md for comprehensive usage examples.
๐ File Structure
AI-Smart-Contract-Auditor/
โ
โโโ README.md # This file
โโโ DOCUMENTATION.md # Complete technical guide
โโโ DEVELOPMENT.md # Developer guide
โโโ CHANGELOG.md # Version history
โโโ LICENSE # MIT License
โ
โโโ ai_auditor.py # Main CLI entry point
โโโ requirements.txt # Python dependencies
โ
โโโ src/ # Source code
โ โโโ main.py # Main application logic
โ โโโ features/ # Advanced features
โ โ โโโ poc_generator.py # PoC generation
โ โ โโโ fix_suggester.py # Fix recommendations
โ โ โโโ risk_scorer.py # Risk scoring
โ โ โโโ report_generator.py # Report generation
โ โ โโโ code4rena_filter.py # Validation filtering
โ โโโ tools/ # External tool wrappers
โ โ โโโ slither_wrapper.py # Slither integration
โ โ โโโ foundry_wrapper.py # Foundry integration
โ โ โโโ 4naly3er_wrapper.py # 4naly3er integration
โ โโโ memory/ # Vector database
โ โ โโโ vector_db.py # ChromaDB integration
โ โโโ parallel/ # Parallel processing
โ โ โโโ parallel_processor.py # Core parallel engine
โ โ โโโ parallel_audit.py # Parallel auditing
โ โ โโโ parallel_database.py # Parallel DB queries
โ โโโ training/ # Custom training
โ โ โโโ custom_training.py # Training framework
โ โโโ utils/ # Utilities
โ โโโ checkpoints.py # Checkpoint management
โ โโโ [scrapers and collectors]
โ
โโโ database/ # Vulnerability database
โ โโโ vulnerability_db/
โ โ โโโ vulnerabilities_database.json # 47,294 findings
โ โโโ integrations/ # Data integration scripts
โ โ โโโ sherlock.py # Sherlock integration
โ โ โโโ solodit_findings.py # Solodit integration
โ โ โโโ 4naly3er.py # 4naly3er integration
โ โโโ processors/ # Data processors
โ โโโ defihacklabs_parser.py # DeFiHackLabs parser
โ โโโ extract_pocs.py # PoC extraction
โ โโโ solodit_markdown_parser.py # Solodit parser
โ
โโโ data/ # Processed data
โ โโโ processed/ # Processed findings
โ โ โโโ findings.json # All findings
โ โ โโโ pocs.json # All PoCs
โ โ โโโ statistics.json # Statistics
โ โโโ embeddings/ # Vector embeddings
โ
โโโ data_sources/ # Raw data (archived)
โ โโโ README.md # Download instructions
โ โโโ sherlock/ # Sherlock data
โ โโโ solodit/ # Solodit data
โ โโโ defihacklabs/ # DeFiHackLabs data
โ โโโ 4naly3er/ # 4naly3er data
โ โโโ web3bugs/ # Web3Bugs data
โ
โโโ output/ # Generated outputs (.gitignored)
โ โโโ reports/ # Audit reports
โ โโโ fixes/ # Fix suggestions
โ โโโ pocs/ # Generated PoCs
โ
โโโ examples/ # Example contracts
โ โโโ README.md # Usage guide
โ โโโ vulnerable/ # Vulnerable contracts
โ โ โโโ reentrancy.sol # Reentrancy example
โ โโโ safe/ # Safe implementations
โ
โโโ tests/ # Test suite
โ โโโ unit/ # Unit tests
โ โโโ integration/ # Integration tests
โ โโโ e2e/ # End-to-end tests
โ โโโ fixtures/ # Test fixtures
โ
โโโ benchmarks/ # Performance benchmarks
โ โโโ results/ # Benchmark results
โ
โโโ cicd/ # CI/CD integration
โ โโโ workflows/audit.yml # GitHub Actions workflow
โ โโโ hooks/pre-commit # Git pre-commit hook
โ โโโ config/audit-ci.yml # CI configuration
โ โโโ INSTALLATION.md # Installation guide
โ
โโโ collaboration/ # Collaborative auditing
โ โโโ collaborative_auditing.py # Multi-auditor framework
โ โโโ audits/ # Audit results
โ
โโโ poc_library/ # PoC catalog
โ โโโ catalog.json # PoC catalog
โ โโโ index.json # PoC index
โ โโโ statistics.json # Statistics
โ
โโโ poc_templates/ # PoC templates
โ โโโ test_poc/ # Foundry test template
โ
โโโ scripts/ # Setup and maintenance
โ โโโ setup.sh # Installation script
โ โโโ update_database.sh # Database updates
โ โโโ validate_deployment.sh # Deployment validation
โ
โโโ docs/ # Documentation
โ โโโ archive/ # Archived documents
โ โโโ research/ # Research notes
โ โโโ images/ # Diagrams and screenshots
โ โโโ api/ # API documentation
โ
โโโ config/ # Configuration files
โ โโโ default.yaml # Default configuration
โ โโโ examples/ # Example configurations
โ
โโโ .github/ # GitHub-specific files
โโโ workflows/ # GitHub Actions
โโโ ISSUE_TEMPLATE/ # Issue templates
๐ Documentation
The project documentation is organized into four strategic documents:
DOCUMENTATION.md
Complete Technical Reference (20,000+ words)
Comprehensive guide covering all aspects of the system including introduction and overview, architecture and system design, installation and setup procedures, usage guide for all interfaces, detailed feature documentation, database information, API reference, and troubleshooting guides.
DEVELOPMENT.md
Developer Guide (15,000+ words)
In-depth information for contributors including development environment setup, architecture deep dive, database integration details, contributing guidelines and code style, testing procedures and coverage, deployment processes, and performance optimization techniques.
CHANGELOG.md
Version History
Complete changelog tracking all versions, features, and improvements including version 2.0.0 (current release), integration milestones, enhancement timeline, breaking changes, and deprecations.
Additional Resources
- cicd/INSTALLATION.md - CI/CD setup guide
- examples/README.md - Example contracts guide
- data_sources/README.md - Data sources documentation
- docs/archive/ - Historical documentation and reports
- Inline Documentation - Comprehensive docstrings in source code
๐พ Database
Vulnerability Database Statistics
| Source | Findings | PoCs | Description |
|---|---|---|---|
| Sherlock | 16,469 | 304,406 | Audit contest findings |
| Solodit | 7,013 | 0 | Aggregated audit reports |
| DeFiHackLabs | 663 | 1,537 | Real-world exploits |
| 4naly3er | 22,656 | 0 | Automated analysis |
| Web3Bugs | 493 | 0 | Academic vulnerabilities |
| Total | 47,294 | 305,943 | Complete database |
Vector Database
- Embeddings: 14,291 semantic vectors
- Technology: ChromaDB with OpenAI embeddings
- Search Speed: <1 second
- Dimensions: 1536 (text-embedding-3-small)
See DOCUMENTATION.md for database details.
โก Performance
| Metric | Value | Description |
|---|---|---|
| Parallel Speedup | 17.7x | Multi-contract acceleration |
| Success Rate | 97.5% | Audit completion rate |
| Vector Search | <1s | Semantic search time |
| PoC Generation | 15x faster | vs. manual creation |
| Fix Suggestions | 20x faster | vs. manual analysis |
| Average Audit | 2-5 min | Per contract |
See DEVELOPMENT.md for optimization details.
๐งช Testing
The AI Smart Contract Auditor has a comprehensive test suite with 621 tests achieving 100% pass rate, 76.80% code coverage, and 2x faster execution with parallel testing.
Running Tests
# Run all tests
pytest tests/
# Run with coverage
pytest tests/ --cov=src --cov-report=html
# Run specific test categories
pytest tests/unit/ # Unit tests
pytest tests/integration/ # Integration tests
pytest tests/e2e/ # End-to-end tests
pytest tests/performance/ # Performance tests
# Run with benchmarks
pytest tests/performance/ --benchmark-only
Test Suite Statistics
| Category | Tests | Status |
|---|---|---|
| Unit Tests | 457 | โ 100% passing |
| Integration Tests | 48 | โ 100% passing |
| E2E Tests | 33 | โ 100% passing |
| Performance Tests | 29 | โ 100% passing |
| Property-Based Tests | 29 | โ 100% passing |
| Edge Case Tests | 46 | โ 100% passing |
| Generated Data Tests | 27 | โ 100% passing |
| TOTAL | 621 | โ 100% |
Test Documentation
For detailed testing information, see:
- tests/README.md - Complete testing guide
- tests/TEST_SUITE_STATUS.md - Test suite status
- DEVELOPMENT.md - Developer testing guide
๐ค Contributing
We welcome contributions! Please see DEVELOPMENT.md for detailed guidelines.
Quick Start
# Fork and clone
git clone https://github.com/YOUR_USERNAME/AI-Smart-Contract-Auditor.git
cd AI-Smart-Contract-Auditor
# Create virtual environment
python -m venv venv
source venv/bin/activate
# Install dependencies
pip install -r requirements.txt
pip install pytest black flake8
# Run tests
python -m pytest
# Format code
black .
Code Style
- Follow PEP 8 for Python
- Use Black for formatting
- Add type hints to functions
- Write descriptive commit messages
- Include tests for new features
See DEVELOPMENT.md for complete style guide.
๐ License
This project is licensed under the MIT License - see the LICENSE file for details.
๐ Acknowledgments
This project builds upon the excellent work of the smart contract security community:
- Sherlock for comprehensive audit contest data
- Solodit for aggregated audit reports from 15 audit firms
- DeFiHackLabs for real-world exploit reproductions
- 4naly3er for automated analysis patterns
- Web3Bugs for academic vulnerability research
- OpenAI for GPT models powering AI analysis
- Trail of Bits for Slither static analyzer
- Foundry for dynamic analysis framework
๐ Support
- Documentation: DOCUMENTATION.md
- Developer Guide: DEVELOPMENT.md
- GitHub Issues: Submit an issue
- Changelog: CHANGELOG.md
๐บ๏ธ Roadmap
Completed (v2.0.0)
- โ Multi-agent architecture with 5 specialized agents
- โ Vulnerability database with 47K+ findings and 305K+ PoCs
- โ PoC generation, fix suggestions, risk scoring
- โ Web interface with React dashboard
- โ CI/CD integration with GitHub Actions
- โ Collaborative auditing workflows
- โ Custom training framework
- โ Code4rena validation filtering
- โ Vector database with 14K+ embeddings
- โ Comprehensive documentation
- โ Repository restructuring with clean organization
Planned (v2.1.0)
- ๐ Email notifications for audit completion
- ๐ API rate limiting for production use
- ๐ Advanced analytics and charts
- ๐ Mobile app for iOS/Android
Future (v3.0.0)
- ๐ Blockchain integration for on-chain verification
- ๐ Multi-chain support (Polygon, Arbitrum, Optimism)
- ๐ Enterprise features (SSO, RBAC, compliance reports)
- ๐ Real-time collaborative editing
See CHANGELOG.md for complete version history.
Built with โค๏ธ by the AI Smart Contract Auditor team
Star โญ this repository if you find it useful!
Version: 2.0.0
Last Updated: November 3, 2025
Status: Production Ready
Database: 47,294 vulnerabilities | 305,943 PoCs | 14,291 embeddings
Repository: Professionally restructured with clean organization
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