AI-Powered Cybersecurity Assistant for Security Professionals

CyberSec CLI is a comprehensive, production-ready cybersecurity platform that combines an intelligent command-line interface with a modern web application. It features advanced network scanning capabilities, AI-powered security analysis, and enterprise-grade deployment options with Redis caching, PostgreSQL database, and comprehensive monitoring.

• High-Performance Scanning: 76,260 packets/second with adaptive concurrency control
• Multiple Scan Types: TCP connect, SYN scan, UDP scanning, service detection
• Intelligent Service Detection: Enhanced active probing for accurate service identification
• CVE Enrichment: Automatic vulnerability intelligence integration
• Port Priority System: Smart port prioritization for efficient scanning

• Natural Language Interface: Ask security questions in plain English
• Intelligent Threat Analysis: AI-driven vulnerability assessment and recommendations
• Multi-Provider Support: OpenAI GPT, Anthropic Claude, and local LLM options
• Real-time Security Insights: Context-aware security recommendations

• Interactive CLI: Rich terminal UI with themes, progress bars, and live updates
• Modern Web Interface: Real-time dashboard with WebSocket support
• RESTful API: Comprehensive API with WebSocket streaming
• Mobile Responsive: Optimized for desktop and mobile devices

• Redis Integration: Intelligent caching and job queuing with automatic fallback
• PostgreSQL Database: Scalable data storage with migration support
• Rate Limiting: Advanced abuse protection with sliding window algorithms
• Monitoring & Metrics: Prometheus integration with Grafana dashboards
• Docker Deployment: Production-ready containerized deployment

• Python 3.10 or higher
• Docker & Docker Compose (for containerized deployment)
• Redis (optional, for enhanced performance)
• PostgreSQL (optional, for production deployments)

# Clone the repository
git clone https://github.com/Yash7256/cybersec-cli.git
cd cybersec-cli

# Run the quick start script
bash scripts/quickstart.sh

# Configure your environment
cp .env.example .env
# Edit .env and add your OPENAI_API_KEY

# Start the CLI
python -m cybersec_cli

# Clone and setup
git clone https://github.com/Yash7256/cybersec-cli.git
cd cybersec-cli
cp .env.example .env

# Configure environment variables
nano .env
# Add your OPENAI_API_KEY and other settings

# Start the full stack
docker-compose up -d

# Access the web interface
open http://localhost:8000

# Install from PyPI (when available)
pip install cybersec-cli

# Or install from source
pip install -e .

# Start the interactive shell
cybersec

# Show help
help

# Basic network scan
scan example.com

# Advanced scanning options
scan 192.168.1.1-254 --ports 1-1000 --service-detection --cve-enrichment

# AI-powered security analysis
ask "What are the security implications of an open SSH port?"

# Generate security report
report example.com --format pdf --export-path ./reports/

Access the modern web dashboard at http://localhost:8000:

• Real-time Scanning: Live scan progress with Server-Sent Events
• Historical Analysis: Scan history and trend analysis
• API Access: Comprehensive REST API with interactive documentation
• Export Capabilities: Multiple formats (JSON, CSV, PDF, XML)

# Start a scan via API
curl -X POST "http://localhost:8000/api/scan" \
  -H "Content-Type: application/json" \
  -d '{"target": "example.com", "ports": "1-1000"}'

# Stream scan results in real-time
curl "http://localhost:8000/api/scan/stream?target=example.com"

Create a .env file in the project root:

# Required for AI features
OPENAI_API_KEY=sk-your-openai-api-key

# Database Configuration
DATABASE_URL=postgresql://user:password@localhost:5432/cybersec
REDIS_URL=redis://localhost:6379

# Scanning Configuration
ADAPTIVE_SCANNING=true
MAX_CONCURRENCY=100
DEFAULT_TIMEOUT=3.0

# Security
SECRET_KEY=your-secret-key-here
WEBSOCKET_API_KEY=your-websocket-api-key

# Rate Limiting
RATE_LIMIT_ENABLED=true
CLIENT_RATE_LIMIT=10
TARGET_RATE_LIMIT=50

The application uses a hierarchical configuration system:

1. Environment Variables (highest priority)
2. Configuration File: ~/.cybersec/config.yaml
3. Default Values (lowest priority)

Example config.yaml:

ai:
  provider: "openai"
  model: "gpt-4"
  temperature: 0.7

scanning:
  default_timeout: 3
  max_threads: 50
  adaptive_scanning: true
  enhanced_service_detection: true

ui:
  theme: "matrix"
  show_banner: true
  color_output: true

output:
  default_format: "table"
  save_results: true
  export_path: "./reports/"

The docker-compose.yml includes:

• Redis: Caching and job queuing
• PostgreSQL: Primary database
• CyberSec Web: Main application
• Celery Worker: Background task processing
• Nginx: Reverse proxy and SSL termination
• Prometheus: Metrics collection
• Grafana: Visualization dashboard

# Scale the workers
docker-compose up -d --scale celery-worker=4

# View logs
docker-compose logs -f cybersec-web

# Monitor metrics
open http://localhost:3000  # Grafana
open http://localhost:9090  # Prometheus

• User Guide - Complete CLI and web interface usage
• API Documentation - RESTful API and WebSocket interface
• Deployment Guide - Docker, Kubernetes, and cloud deployment
• Configuration Guide - Advanced configuration options

• Redis Integration - Caching and performance optimization
• Security Best Practices - Security configuration and hardening
• Performance Tuning - Optimization and benchmarking
• Troubleshooting - Common issues and solutions

• CLI Examples - Practical command-line examples
• API Examples - Code samples and integration guides
• Deployment Scripts - Automation and deployment scripts

# Run all tests
pytest

# Run with coverage
pytest --cov=cybersec_cli --cov-report=html

# Run specific test categories
pytest -m unit          # Unit tests only
pytest -m integration   # Integration tests only
pytest -m slow          # Include slow tests

# Run performance benchmarks
python tests/benchmarking/run_all_benchmarks.py

# Generate comparison reports
python tests/benchmarking/tools/generate_report.py

We welcome contributions! Please see our Contributing Guidelines for details.

# Clone the repository
git clone https://github.com/Yash7256/cybersec-cli.git
cd cybersec-cli

# Create a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install in development mode
pip install -e ".[dev]"

# Install pre-commit hooks
pre-commit install

# Run the development server
python -m cybersec_cli --debug

• Linting: flake8 src/
• Formatting: black src/
• Type Checking: mypy src/
• Security: bandit -r src/

cybersec-cli/
├── src/cybersec_cli/          # Main application code
│   ├── commands/              # CLI command implementations
│   ├── tools/                # Security tools and scanners
│   ├── analysis/             # Security analysis modules
│   ├── ai/                   # AI integration
│   ├── core/                 # Core functionality
│   ├── utils/                # Utility functions
│   └── ui/                   # User interface components
├── web/                      # Web application
│   ├── routes/               # API endpoints
│   └── static/               # Static assets
├── api/                      # API-specific code
├── tasks/                    # Background tasks (Celery)
├── scripts/                  # Deployment and utility scripts
├── docs/                     # Documentation
├── tests/                    # Test suite
├── monitoring/               # Monitoring configuration
└── systemd/                  # Systemd service files

This tool is designed for authorized security testing and educational purposes only. Users are responsible for:

• Legal Compliance: Ensure you have proper authorization before scanning
• Responsible Usage: Use only on networks you own or have permission to test
• Data Privacy: Handle scan results according to applicable regulations

For security concerns, see our Security Policy.

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

• Built with ❤️ using Python, FastAPI, and modern web technologies
• Inspired by industry-standard tools like Nmap, Masscan, and security best practices
• Powered by OpenAI and other amazing AI providers
• Community contributions and feedback

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Documentation: Wiki