threat-radar 0.5.0

Enterprise-grade threat assessment and vulnerability analysis platform for Docker containers and software dependencies

Threat Radar (tr-nvd)

A comprehensive threat assessment and vulnerability analysis platform for Docker containers and software dependencies.

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🎯 Overview

Threat Radar provides enterprise-grade security analysis with:

• 🐳 Docker Container Analysis - Multi-distro package extraction and analysis
• 📦 SBOM Generation - CycloneDX, SPDX, Syft JSON formats via Syft integration
• 🔍 CVE Vulnerability Scanning - Powered by Grype for accurate, fast detection
• 🤖 AI-Powered Analysis - Intelligent vulnerability assessment and prioritization
• 📊 Comprehensive Reporting - JSON, Markdown, HTML with executive summaries
• 📈 Dashboard Integration - Grafana, Prometheus, and custom dashboards

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🚀 Quick Start

Prerequisites

Required:

• Python 3.8 or higher
• Docker (for container analysis)
• Grype (for CVE scanning)
• Syft (for SBOM generation)

Optional:

• OpenAI API key (for AI features) OR
• Ollama (for local AI)

Installation

1. Install External Tools

# macOS
brew install grype syft

# Linux
curl -sSfL https://raw.githubusercontent.com/anchore/grype/main/install.sh | sh
curl -sSfL https://raw.githubusercontent.com/anchore/syft/main/install.sh | sh

# Verify installation
grype version
syft version

2. Install Threat Radar

# Clone repository
git clone https://github.com/Threat-Radar/tr.git
cd tr-nvd

# Option A: Using pip with requirements.txt
pip install -r requirements.txt

# Option B: Using pyproject.toml (development mode)
pip install -e .

# Option C: With development tools
pip install -r requirements-dev.txt

# Option D: With AI features (local models)
pip install -r requirements-ai.txt

3. Configure Environment (Optional)

# Copy example configuration
cp .env.example .env

# Edit .env and add your API keys (optional, for AI features):
# - OPENAI_API_KEY=sk-your-key-here
# - AI_PROVIDER=openai (or 'ollama' for local AI)
# - AI_MODEL=gpt-4o (or 'gpt-4-turbo', 'llama2' for Ollama)

4. Verify Installation

# Check CLI is working
threat-radar --help

# Run a quick scan
threat-radar cve scan-image alpine:3.18

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💡 Basic Usage

CVE Vulnerability Scanning

# Scan Docker image for vulnerabilities
threat-radar cve scan-image alpine:3.18

# Scan with severity filter
threat-radar cve scan-image python:3.11 --severity HIGH

# Save results and auto-cleanup
threat-radar cve scan-image nginx:latest --auto-save --cleanup

# Scan SBOM file
threat-radar cve scan-sbom my-app-sbom.json --severity CRITICAL

# Scan local directory
threat-radar cve scan-directory ./my-project

SBOM Generation

# Generate SBOM from Docker image
threat-radar sbom docker alpine:3.18 -o sbom.json

# Generate from local directory
threat-radar sbom generate ./my-app -f cyclonedx-json

# Auto-save to organized storage
threat-radar sbom docker python:3.11 --auto-save

# Compare two SBOMs
threat-radar sbom compare alpine:3.17 alpine:3.18

AI-Powered Analysis

# Analyze vulnerabilities with AI
threat-radar ai analyze scan-results.json

# Generate prioritized remediation list
threat-radar ai prioritize scan-results.json --top 10

# Create remediation plan
threat-radar ai remediate scan-results.json -o remediation.json

Comprehensive Reporting

# Generate HTML report with AI executive summary
threat-radar report generate scan-results.json -o report.html -f html

# Executive summary for leadership
threat-radar report generate scan-results.json -o exec.md -f markdown --level executive

# Critical-only issues
threat-radar report generate scan-results.json --level critical-only

# Export dashboard data
threat-radar report dashboard-export scan-results.json -o dashboard.json

Docker Analysis

# Import and analyze image
threat-radar docker import-image ubuntu:22.04 -o analysis.json

# List packages in image
threat-radar docker packages alpine:3.18 --limit 20

# Generate Python SBOM
threat-radar docker python-sbom python:3.11 -o sbom.json

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📚 Documentation

Getting Started

• Installation Guide - Complete setup instructions
• Examples Guide - Step-by-step tutorials
• CLI Reference - Complete command reference
• Troubleshooting - Common issues and solutions

Features

• CVE Scanning Guide - Vulnerability detection
• AI Analysis Guide - AI-powered features
• Reporting Guide - Report generation and formats
• SBOM Generation - SBOM capabilities

Development

• Developer Guide - Architecture and development
• Code Review - Code quality analysis

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✨ Key Features

🔍 CVE Vulnerability Scanning (Grype-Powered)

• Docker image scanning - Comprehensive vulnerability detection
• SBOM scanning - Analyze pre-generated SBOMs
• Directory scanning - Local project analysis
• Zero API rate limits - Offline local database
• Auto-cleanup - Automatic image removal after scan
• Auto-save - Timestamped results in organized storage
• Severity filtering - Focus on CRITICAL/HIGH issues

# Scan with all features
threat-radar cve scan-image myapp:latest \
  --severity HIGH \
  --auto-save \
  --cleanup \
  -o scan.json

🤖 AI-Powered Intelligence

• Multiple AI providers - OpenAI GPT-4o, Anthropic Claude, or Ollama
• Cloud or local - Choose based on privacy needs
• Vulnerability analysis - Exploitability and impact assessment
• Smart prioritization - Risk-based ranking
• Remediation planning - Actionable fix recommendations

# Complete AI workflow
threat-radar cve scan-image alpine:3.18 --auto-save -o scan.json
threat-radar ai analyze scan.json --auto-save
threat-radar ai prioritize scan.json --top 10
threat-radar ai remediate scan.json -o plan.json

📊 Comprehensive Reporting

• Multiple formats - JSON, Markdown, HTML
• Report levels - Executive, Summary, Detailed, Critical-only
• AI executive summaries - Risk ratings and business impact
• Dashboard data - Grafana/Prometheus compatible
• Trend analysis - Compare scans over time

# Generate reports for different audiences
threat-radar report generate scan.json -o exec.md --level executive  # Leadership
threat-radar report generate scan.json -o detailed.html --level detailed  # Security team
threat-radar report generate scan.json -o critical.json --level critical-only  # DevOps

📦 SBOM Generation (Syft-Powered)

• Multi-format - CycloneDX, SPDX, Syft JSON
• 13+ ecosystems - Python, npm, Go, Rust, Java, Ruby, PHP, etc.
• Docker images - Comprehensive OS + application packages
• Local directories - Project dependency analysis
• Organized storage - Automatic categorization
• Comparison - Track package changes

# Generate and compare SBOMs
threat-radar sbom docker myapp:v1.0 --auto-save
threat-radar sbom docker myapp:v2.0 --auto-save
threat-radar sbom compare myapp:v1.0 myapp:v2.0

🐳 Docker Integration

• Multi-distro support - Alpine, Ubuntu, Debian, RHEL, CentOS, Fedora
• Package managers - APK, APT/dpkg, YUM/rpm
• Python packages - Pip package extraction
• Image analysis - Metadata and layer inspection

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🔧 Configuration

Environment Variables (.env)

# AI Configuration (optional)
# Option 1: OpenAI (cloud)
OPENAI_API_KEY=sk-your-openai-api-key
AI_PROVIDER=openai
AI_MODEL=gpt-4o  # Recommended: gpt-4o, gpt-4-turbo, or gpt-3.5-turbo-1106

# Option 2: Anthropic Claude (cloud)
ANTHROPIC_API_KEY=sk-ant-your-key-here
AI_PROVIDER=anthropic
AI_MODEL=claude-3-5-sonnet-20241022

# Option 3: Ollama (local)
AI_PROVIDER=ollama
AI_MODEL=llama2
LOCAL_MODEL_ENDPOINT=http://localhost:11434

Setting Up AI Features

OpenAI (Cloud)

1. Get API key from https://platform.openai.com/api-keys
2. Add to .env:

   OPENAI_API_KEY=sk-your-key-here
   AI_PROVIDER=openai
   AI_MODEL=gpt-4o  # Recommended: gpt-4o, gpt-4-turbo, or gpt-3.5-turbo-1106
   

Anthropic Claude (Cloud)

1. Get API key from https://console.anthropic.com/
2. Add to .env:

   ANTHROPIC_API_KEY=sk-ant-your-key-here
   AI_PROVIDER=anthropic
   AI_MODEL=claude-3-5-sonnet-20241022
   

Available Models:

• claude-3-5-sonnet-20241022 (recommended, best balance)
• claude-3-opus-20240229 (highest capability)
• claude-3-sonnet-20240229 (faster, cost-effective)

Ollama (Local - Free)

# Install Ollama
brew install ollama  # macOS
# or visit https://ollama.ai for other platforms

# Start Ollama service
ollama serve &

# Pull a model
ollama pull llama2

# Configure in .env
AI_PROVIDER=ollama
AI_MODEL=llama2

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📁 Project Structure

tr-nvd/
├── threat_radar/              # Main package
│   ├── core/                  # Core functionality
│   │   ├── container_analyzer.py
│   │   ├── grype_integration.py    # CVE scanning
│   │   ├── syft_integration.py     # SBOM generation
│   │   └── vulnerability_scanner.py
│   ├── ai/                    # AI-powered analysis
│   │   ├── llm_client.py
│   │   ├── vulnerability_analyzer.py
│   │   ├── prioritization.py
│   │   └── remediation_generator.py
│   ├── utils/                 # Utilities
│   │   ├── comprehensive_report.py
│   │   ├── report_formatters.py
│   │   └── sbom_storage.py
│   └── cli/                   # CLI commands
│       ├── cve.py             # CVE scanning commands
│       ├── ai.py              # AI analysis commands
│       ├── report.py          # Reporting commands
│       ├── sbom.py            # SBOM commands
│       └── docker.py          # Docker commands
├── examples/                  # Usage examples
│   ├── 01_basic/             # Basic examples
│   ├── 02_advanced/          # Advanced examples
│   ├── 03_vulnerability_scanning/  # CVE scanning
│   ├── 04_testing/           # Test scripts
│   └── 05_reporting/         # Reporting examples
├── docs/                      # Documentation
│   ├── reports/              # Analysis reports
│   └── development/          # Dev docs
├── tests/                     # Unit tests
├── storage/                   # Auto-generated (gitignored)
│   ├── cve_storage/          # CVE scan results
│   └── ai_analysis/          # AI analysis results
├── sbom_storage/             # SBOM files (gitignored)
│   ├── docker/               # Docker image SBOMs
│   ├── local/                # Local project SBOMs
│   ├── comparisons/          # Comparison results
│   └── archives/             # Historical SBOMs
├── requirements.txt          # Core dependencies
├── requirements-dev.txt      # Development dependencies
├── requirements-ai.txt       # Optional AI dependencies
└── pyproject.toml            # Project configuration

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🧪 Testing

Run Tests

# Run all tests
pytest

# Run specific test file
pytest tests/test_docker_integration.py

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

# Run comprehensive report tests
pytest tests/test_comprehensive_report.py -v

Run Examples

# Basic examples
python examples/01_basic/hash_usage.py

# CVE scanning examples
python examples/03_vulnerability_scanning/demo_with_findings.py

# Reporting examples
python examples/05_reporting/01_basic_report_generation.py
python examples/05_reporting/02_ai_powered_reports.py
python examples/05_reporting/03_dashboard_integration.py

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🎯 Common Workflows

Weekly Security Scan

#!/bin/bash
# weekly-scan.sh - Run every Monday

IMAGE="myapp:production"
WEEK=$(date +%Y-W%U)

# 1. Scan for vulnerabilities
threat-radar cve scan-image $IMAGE --auto-save -o scan-${WEEK}.json

# 2. Generate reports
threat-radar report generate scan-${WEEK}.json -o exec-${WEEK}.md --level executive
threat-radar report generate scan-${WEEK}.json -o detailed-${WEEK}.html -f html

# 3. AI analysis
threat-radar ai analyze scan-${WEEK}.json --auto-save
threat-radar ai prioritize scan-${WEEK}.json --top 10 -o priorities-${WEEK}.json

# 4. Export dashboard data
threat-radar report dashboard-export scan-${WEEK}.json -o dashboard-${WEEK}.json

CI/CD Integration

# .github/workflows/security-scan.yml
name: Security Scan
on: [push, pull_request]

jobs:
  scan:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3

      - name: Install Grype
        run: |
          curl -sSfL https://raw.githubusercontent.com/anchore/grype/main/install.sh | sh

      - name: Build image
        run: docker build -t app:${{ github.sha }} .

      - name: Install Threat Radar
        run: pip install -r requirements.txt

      - name: Scan for vulnerabilities
        run: |
          threat-radar cve scan-image app:${{ github.sha }} \
            --auto-save --cleanup -o scan.json

      - name: Check for critical issues
        run: |
          threat-radar report generate scan.json \
            --level critical-only -o critical.json

          CRITICAL=$(jq '.summary.critical' critical.json)
          if [ $CRITICAL -gt 0 ]; then
            echo "❌ Found $CRITICAL critical vulnerabilities!"
            exit 1
          fi

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📊 Performance

Scan Performance

• Alpine 3.18: ~2-3 seconds (15 packages)
• Python 3.11-slim: ~4-5 seconds (97 packages)
• Ubuntu 22.04: ~5-7 seconds (200+ packages)

Accuracy

• Precision: 100% (0 false positives in validation tests)
• Coverage: All package ecosystems supported by Grype/Syft
• Test Results: 15/15 examples passing

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🛠️ Development

Code Quality

# Format code
black threat_radar/ tests/

# Type checking
mypy threat_radar/

# Linting
flake8 threat_radar/

# Run all quality checks
black threat_radar/ tests/ && mypy threat_radar/ && flake8 threat_radar/

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests: pytest
5. Submit a pull request

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📝 License

MIT License - See LICENSE file for details

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🤝 Support

• Issues: GitHub Issues
• Documentation: docs/
• Examples: examples/
• Troubleshooting: examples/TROUBLESHOOTING.md

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🏆 Acknowledgments

• Grype - Anchore's vulnerability scanner
• Syft - Anchore's SBOM generation tool
• NVD - NIST National Vulnerability Database
• Docker SDK - Docker Python integration
• OpenAI - AI-powered analysis (GPT-4o, GPT-4 Turbo)
• Anthropic - AI-powered analysis (Claude)
• Ollama - Local AI models

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🔄 Recent Updates

Version 0.1.0 (Latest)

✅ Grype integration - Fast, accurate CVE scanning ✅ AI-powered analysis - OpenAI and Ollama support ✅ Comprehensive reporting - Multi-format with executive summaries ✅ Dashboard integration - Grafana/Prometheus compatible ✅ Auto-save features - Organized storage with timestamps ✅ Cleanup automation - Smart image removal after scanning

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Status: ✅ Production Ready | Version: 0.1.0 | Last Updated: 2025-10-16