A comprehensive Python-based tool that analyzes Linux iptables firewall rules, detects redundant or conflicting rules, suggests optimization strategies, and provides interactive visualizations with beautiful CLI graphics for better security management.

• Redundant Rule Detection: Identifies duplicate rules that can be removed
• Conflict Resolution: Finds rules that contradict each other
• Performance Optimization: Suggests rule reordering for better efficiency
• Security Analysis: Detects potential security vulnerabilities
• Unreachable Rule Detection: Finds rules that will never be executed

• Priority-based Suggestions: Categorizes recommendations by importance (🔥Critical, 🚨High, ⚠️Medium, 💡Low)
• Risk Assessment: Evaluates the risk level of each recommendation
• Impact Analysis: Estimates performance and security improvements
• Implementation Guidance: Provides step-by-step instructions

• Colorful Progress Bars: Visual score representation for security and efficiency
• ASCII Bar Charts: Issue distribution visualization
• Severity Pie Charts: Visual breakdown of issue severity levels
• Priority Charts: Recommendation priorities with icons and colors
• Impact Gauges: Visual optimization benefits display
• Professional Styling: VS Code-like syntax highlighting with emojis

• Interactive Rule Flow Diagrams: Visualize packet flow through rules
• Dependency Graphs: Show relationships between chains and rules
• Security Dashboards: Real-time security and efficiency scores
• Rule Coverage Heatmaps: Analyze protocol and port coverage
• Optimization Impact Charts: Visualize potential improvements

• Enhanced CLI: Beautiful terminal interface with charts and colors
• Web Interface: User-friendly Streamlit-based GUI with interactive features
• Python API: Integrate into your own applications

• Python 3.8 or higher
• Linux system with iptables (for live analysis)
• Administrator privileges (for applying changes)

1. Clone the repository:

git clone https://github.com/your-username/firewall-optimizer.git cd firewall-optimizer

2. Install dependencies:

pip install -r requirements.txt

python main.py analyze

python main.py optimize

python main.py visualize

python main.py webapp

That's it! The tool includes sample data, so you can start exploring immediately!

Our enhanced CLI provides a beautiful terminal experience with:

• 🔥 Colorful Startup Banner with ASCII art
• 📊 Progress Bars for security and efficiency scores
• 📈 Bar Charts showing issue distribution
• 🥧 Pie Charts for severity level breakdown
• 🎯 Priority Visualization for recommendations
• ⚡ Impact Gauges showing optimization benefits
• 🌈 Color-coded Output for easy reading

 ╔══════════════════════════════════════════════════════════╗ ║ ║ ║ 🔥 AI-Powered Firewall Rule Optimizer 🔥 ║ ║ ║ ║ Analyze • Optimize • Visualize • Secure ║ ║ ║ ╚══════════════════════════════════════════════════════════╝ ──────────────────────────────────────── 📊 Score Overview ──────────────────────────────────────── Security Score.......... ████████████████████░░░░░░░░░░ 54.0% Efficiency Score........ ██░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 5.0% ──────────────────────────────────────── 📊 Issues Distribution ──────────────────────────────────────── Conflicting............. ████████████████████████████████ 15 Unreachable............. ██████████████████████████████ 13 Inefficient Order....... ████████████████████████ 11 Security Risk........... ████ 2 

🧠 Console Output

📊 Run in your browser: python main.py webapp

🧠 AI-Powered Analysis Dashboard

📈 Real-time Visualizations of Issues and Priorities

🌐 Rule Flow Diagrams & Dependency Mapping

🌐 Visualization

python main.py analyze

python main.py analyze --input /path/to/iptables-rules.txt

python main.py analyze --input system

python main.py analyze --output report.json --format json

# Generate recommendations with visual priority charts python main.py optimize # Optimize specific configuration python main.py optimize --input /path/to/rules.txt # Save optimized rules python main.py optimize --input rules.txt --output optimized.txt # Apply to system with backup (requires root) sudo python main.py optimize --input system --apply --backup

# Create all interactive visualizations python main.py visualize # Specific visualization types python main.py visualize --type flow # Rule flow diagram python main.py visualize --type issues # Issues dashboard  python main.py visualize --type graph # Network topology

# Launch web app (default: localhost:8501) python main.py webapp # Custom port and host python main.py webapp --port 8080 --host 0.0.0.0

python main.py backup --input system --description "Before optimization"

python main.py restore --backup /path/to/backup.json

Launch the interactive web interface:

python main.py webapp

Then open your browser to http://localhost:8501

Features:

• 📁 Upload firewall configuration files or use sample data
• 🔍 Real-time analysis with colorful charts and metrics
• 📊 Interactive visualizations and dashboards
• 💾 Backup and restore functionality
• ⚙️ Configurable analysis settings
• 📤 Export reports in multiple formats

Our CLI features beautiful terminal graphics with:

• 🎨 VS Code-like syntax highlighting with colors
• 📊 ASCII progress bars and charts
• 🔥 Emoji-rich output for better readability
• 📈 Visual data representation right in your terminal

For complete command documentation, see COMMANDS.md - a comprehensive guide with:

• 📋 All available commands and options
• 💡 Usage examples and best practices
• 🎨 CLI features and visual elements
• 🔧 Advanced configuration options
• 🚨 Safety features and troubleshooting

# Analyze a configuration file python main.py analyze --input /etc/iptables/rules.v4 # Analyze current system rules python main.py analyze --input system # Save analysis to file python main.py analyze --input rules.txt --output analysis.json --format json

# Generate recommendations python main.py optimize --input rules.txt # Generate and save optimized rules python main.py optimize --input rules.txt --output optimized_rules.txt # Apply optimizations (with backup) python main.py optimize --input system --apply --backup

python main.py visualize --input rules.txt --output ./reports

python main.py visualize --input rules.txt --output ./reports --type flow

python main.py backup --input system --description "Before optimization"

python main.py restore --backup backup_20250126_143022.json --apply

fromoptimizerimport ( IptablesParser, FirewallAnalyzer, FirewallRecommender, FirewallVisualizer ) # Initialize componentsparser=IptablesParser() analyzer=FirewallAnalyzer() recommender=FirewallRecommender() visualizer=FirewallVisualizer() # Load and parse configurationwithopen('rules.txt', 'r') asf: rules_content=f.read() config=parser.parse_iptables_save(rules_content) # Analyze configurationanalysis=analyzer.analyze_configuration(config) print(f"Security Score: {analysis.security_score:.1f}/100") print(f"Issues Found: {len(analysis.issues)}") # Generate recommendationsplan=recommender.generate_recommendations(config, analysis) print(f"Recommendations: {len(plan.recommendations)}") # Create visualizationsflow_chart=visualizer.create_rule_flow_diagram(config) dashboard=visualizer.create_issue_dashboard(analysis) # Show interactive plotsflow_chart.show() dashboard.show()

• COMMANDS.md - Comprehensive command documentation with examples
• Use python main.py --help for general help
• Use python main.py <command> --help for command-specific help

1. Beautiful Visual Output: ASCII progress bars, charts, and colored text
2. Instant Feedback: No configuration needed - works with sample data
3. Professional Styling: VS Code-like syntax highlighting with emojis
4. Smart Graphics: Charts adjust to terminal width automatically
5. Cross-Platform: Works on Windows, macOS, and Linux
6. Comprehensive: Analysis, optimization, visualization, and web interface

• Detects 47+ different types of firewall issues
• Provides actionable recommendations for each issue
• Calculates security and efficiency scores
• Identifies unreachable and redundant rules

• Beautiful terminal graphics without external dependencies
• Real-time progress indicators during analysis
• Color-coded severity levels (🔴Critical, 🟡Medium, 🟢Low)
• Interactive web charts with Plotly integration

• Automatic backup creation before any changes
• Dry-run mode by default (no accidental modifications)
• Comprehensive logging and audit trails
• Linux system integration with iptables

firewall-optimizer/ │ ├── data/ # Sample data and test files │ └── sample_rules.txt # Sample iptables rules │ ├── optimizer/ # Core optimizer package │ ├── __init__.py # Package initialization │ ├── parser.py # Iptables rule parser │ ├── analyzer.py # Rule analysis engine │ ├── recommender.py # Optimization recommender │ ├── visualizer.py # Visualization components │ └── utils.py # Utility functions │ ├── web_ui/ # Streamlit web interface │ └── app.py # Main web application │ ├── main.py # Command line interface ├── requirements.txt # Python dependencies ├── README.md # This file └── .github/ └── copilot-instructions.md # Copilot customization 

The optimizer can be configured through YAML configuration files:

# optimizer_config.yamlbackup: enabled: truedirectory: './backups'max_backups: 10auto_backup_before_changes: trueanalysis: check_redundant_rules: truecheck_conflicting_rules: truecheck_rule_ordering: truecheck_unreachable_rules: truecheck_security_issues: trueconfidence_threshold: 0.8security: allow_system_modifications: falserequire_sudo_confirmation: truevalidate_rules_before_apply: truevisualization: default_theme: 'plotly_white'save_format: 'html'include_interactive: true

FIREWALL ANALYSIS RESULTS ============================================================ Overall Scores: Security Score: 78.5/100 Efficiency Score: 85.2/100 Statistics: Total Rules: 23 Total Chains: 6 Total Tables: 3 Accept Rules: 8 Drop Rules: 12 Reject Rules: 1 Issues Found (4): Redundant (2 issues): • Redundant rule found: duplicate of rule at line 15 → Remove the duplicate rule to improve performance • Redundant rule found: duplicate of rule at line 22 → Remove the duplicate rule to improve performance Security Risk (1 issues): • Administrative port 22 open to all sources → Restrict access to administrative ports to specific source IPs Inefficient Order (1 issues): • Specific rule at line 18 comes after general rule at line 12 → Move more specific rules before general ones for better performance 

• Dry Run Mode: All operations default to dry run mode
• Automatic Backups: Creates backups before any modifications
• Rule Validation: Validates rules before applying changes
• Confirmation Prompts: Requires explicit confirmation for system changes
• Rollback Capability: Can restore from backups if needed

1. Always test in dry run mode first
2. Create backups before making changes
3. Validate optimized rules in a test environment
4. Review all recommendations before applying
5. Keep the original configuration as a backup

Run the example analysis with sample data:

# Test with sample rules python main.py analyze --input data/sample_rules.txt # Test web interface python main.py webapp # Test visualization generation python main.py visualize --input data/sample_rules.txt --output ./test_reports

• streamlit - Web interface framework
• pandas - Data manipulation and analysis
• numpy - Numerical computing
• matplotlib - Static plotting
• plotly - Interactive plotting
• networkx - Graph analysis
• seaborn - Statistical visualization
• pyparsing - Text parsing
• pyyaml - YAML configuration
• click - Command line interface

• scikit-learn - Machine learning (for advanced analysis)
• xgboost - Gradient boosting (for ML features)
• dash - Alternative web framework
• flask - Lightweight web framework

We welcome contributions! Please see our contributing guidelines:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

# Clone the repository git clone https://github.com/your-username/firewall-optimizer.git cd firewall-optimizer # Create virtual environment python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate# Install development dependencies pip install -r requirements.txt pip install -e .# Run tests python -m pytest tests/ # Run linting black optimizer/ flake8 optimizer/ mypy optimizer/

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

• iptables - The Linux firewall utility that makes this project possible
• Streamlit - For providing an excellent web framework for data applications
• Plotly - For interactive visualization capabilities
• NetworkX - For graph analysis and visualization
• The Python Community - For the amazing ecosystem of tools and libraries

• 📧 Email: [email protected]
• 🐛 Issues: GitHub Issues
• 💬 Discussions: GitHub Discussions

⭐ Star this repository if you find it useful!

Made with ❤️ by the Akshay Kale