Security Analysis Project 🛡️

A sophisticated real-time security analysis tool that leverages Twitter data to detect potential security threats, analyze sentiment, and identify fake news using advanced machine learning techniques.

🌟 Features

Real-time Analysis

• Live Twitter data streaming and analysis
• Instant threat detection and alerts
• Real-time sentiment tracking
• Dynamic data visualization

Security Features

• 🔍 Fake news detection using ML models
• 🎯 Sentiment analysis with NLTK and TextBlob
• 🚨 Threat level assessment
• 📊 Comprehensive analytics dashboard

Data Visualization

• Interactive charts and graphs
• Sentiment distribution analysis
• Threat level indicators
• Historical data tracking

🛠️ Tech Stack

Frontend

• React.js - UI framework
• Material-UI - Component library
• Chart.js - Data visualization
• Axios - HTTP client

Backend

• Python Flask - Web framework
• NLTK - Natural Language Processing
• Hugging Face Transformers - ML models
• SQLite/SQLAlchemy - Database

External APIs

• Twitter API v2
• NewsAPI
• VirusTotal API

📦 Installation

Prerequisites

• Python 3.8+
• Node.js 14+
• Docker & Docker Compose

Setup Steps

1. Clone the Repository bash git clone https://github.com/Stavin13/security-analysis.git cd security-analysis

2. Install Dependencies bash npm install pip install -r requirements.txt

Setup Instructions

1. Create .env file in backend directory with:

   • TWITTER_BEARER_TOKEN
   • NEWS_API_KEY
   • VT_API_KEY
   • hf_token

2. Create .env file in frontend directory with:

   • REACT_APP_API_URL

3. Get API keys from:

   • Twitter: https://developer.twitter.com
   • NewsAPI: https://newsapi.org
   • VirusTotal: https://www.virustotal.com
   • HuggingFace: https://huggingface.co

4. Run the Application bash npm start python app.py

5. Access the Dashboard Open your browser and navigate to http://localhost:3000

🚀 Usage

1. Access the application at http://localhost:3000
2. Enter keywords for analysis
3. View real-time results in the dashboard
4. Monitor security threats and sentiment analysis

📊 API Endpoints

Analysis Endpoints

• POST /analyze - Analyze tweets
• GET /history - Get analysis history
• GET /news - Get news analysis

Health Check

• GET /health - API health status

🔒 Security

• Rate limiting implemented
• API key validation
• CORS protection
• Input sanitization

🤝 Contributing

We welcome contributions to improve the Security Analysis Project!

Contribution Guidelines

1. Fork the repository

2. Create your feature branch:

   git checkout -b feature/YourFeatureName

3. Follow coding standards:

   • Use meaningful variable names
   • Add comments for complex logic
   • Follow PEP 8 for Python code
   • Use ESLint rules for JavaScript

4. Commit your changes:

   git commit -m 'feat: Add YourFeatureName'

   Commit message format:

   • feat: for new features
   • fix: for bug fixes
   • docs: for documentation
   • style: for formatting
   • refactor: for code refactoring

5. Push to your branch:

   git push origin feature/YourFeatureName

6. Open a Pull Request with:

   • Clear description of changes
   • Screenshots (if UI changes)
   • Any relevant issue numbers

Development Setup

1. Set up development environment
2. Install dependencies
3. Create necessary .env files
4. Run tests before submitting PR

📝 License

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

👤 Author

Stavin

• GitHub: @Stavin13

🙏 Acknowledgments

• Twitter API Documentation
• Hugging Face Transformers
• NLTK Community
• React.js Documentation

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📧 Contact

For any inquiries or support, please contact us at stavinfernandes2098@gmail.com

Thank you for your interest in the Security Analysis Project!