| title | AI Pentest API |
|---|---|
| emoji | 🛡️ |
| colorFrom | purple |
| colorTo | blue |
| sdk | docker |
| app_port | 7860 |
| pinned | false |
An autonomous, AI-powered penetration testing tool that automates vulnerability discovery and reporting
This folder contains the clean, standalone version of the AI Pentest Scanner. It is separated from legacy bot components for easier management.
The AI Pentest Scanner leverages multi-agent AI systems to perform comprehensive security scanning, including reconnaissance, vulnerability detection, and automated report generation.
- 🤖 Multi-Agent AI System - Specialized agents for different pentesting tasks
- 🎯 Automated Reconnaissance - Intelligent target enumeration and information gathering
- 🔍 Vulnerability Scanning - Automated detection of security weaknesses
- 📊 Auto-Report Generation - Professional reports in Markdown, HTML, JSON, and PDF
- 🖥️ Web UI - User-friendly interface for managing scans
- 💻 CLI Support - Run scans directly from terminal
Frontend:
- React (Vite)
- Tailwind CSS
Backend:
- Python Flask API
- Groq API (LLM)
- Gemini API (LLM)
Tools:
- Conda (Environment Management)
- npm (Package Manager)
- Python 3.8+
- Node.js 16+
- Conda
- Clone the repository:
git clone https://github.com/samarth70/AI-Pentest-Scanner.git
cd AI-Pentest-Scanner- Install backend dependencies:
conda create -n agenticAi python=3.10
conda activate agenticAi
pip install -r requirements.txt- Install frontend dependencies:
cd frontend
npm install- Configure environment variables:
Create a
.envfile in the root directory:
GROQ_API_KEY=your_groq_api_key
GEMINI_API_KEY=your_gemini_api_key
- Start the Backend API:
conda activate agenticAi
python api_server.pyThe API will start at http://localhost:5000.
- Start the Frontend: Open another terminal:
cd frontend
npm run devThe UI will start at http://localhost:5173.
- Access the Application:
Open your browser and navigate to
http://localhost:5173
Run scans directly from the terminal:
python main.py --target example.comAdditional CLI options:
python main.py --target example.com --scan-type full --output-format pdfFor detailed architecture, design decisions, and technical specifications, see:
- Architectural Documentation - Complete system architecture, agent design, and implementation details
AI-Pentest-Scanner/
├── api_server.py # Flask backend for the web UI
├── main.py # CLI entry point
├── agents/ # AI agents for different pentesting tasks
│ ├── recon_agent.py # Reconnaissance agent
│ ├── vuln_agent.py # Vulnerability scanning agent
│ └── report_agent.py # Report generation agent
├── core/ # Core configurations and utilities
│ ├── config.py # Configuration settings
│ └── security.py # Security utilities
├── frontend/ # Vite + React + Tailwind frontend
│ ├── src/ # React source code
│ ├── public/ # Static assets
│ └── package.json # Frontend dependencies
├── reports/ # Generated scan results
│ ├── markdown/ # Markdown reports
│ ├── html/ # HTML reports
│ ├── json/ # JSON reports
│ └── pdf/ # PDF reports
├── .env # Environment variables (API keys)
└── requirements.txt # Python dependencies
This tool is intended for educational purposes and authorized security testing only. Always obtain proper authorization before scanning targets.
This project is licensed under the MIT License - see the LICENSE file for details.
Samarth Agarwal
- GitHub: @samarth70
- Groq for providing fast LLM inference
- Google Gemini for AI capabilities
- The open-source security community