X Bot Blocker

A powerful and accurate bot detection and blocking system for X (Twitter) that protects users from automated accounts, spam, and malicious bots while maintaining high accuracy and minimal false positives.

Features

Core Features

• 🔍 Advanced Bot Detection

  • Profile analysis
  • Content analysis
  • Image analysis
  • Pattern recognition
  • Language detection
  • Behavior analysis

• 🛡️ Protection

  • Automated blocking
  • Rate limit management
  • Whitelist/blacklist support
  • Block history tracking

• ⚙️ Configuration

  • YAML-based settings
  • Hot-reload support
  • Environment variables
  • Customizable thresholds

Current Status

• ✅ Phase 1: Foundation (Completed)
  • Configuration Management
  • Blocked Accounts Tracking
  • Rate Limit Optimization
• 🔄 Phase 2: Core Enhancement (In Progress)
  • Enhanced Bot Detection
  • Monitoring & Alerts

Installation

1. Clone the repository:

git clone https://github.com/yourusername/x-bot-blocker.git
cd x-bot-blocker

2. Install dependencies:

pip install -r requirements.txt

3. Configure environment variables:

cp .env.example .env
# Edit .env with your X API credentials

4. Configure settings:

cp config.yaml.example config.yaml
# Edit config.yaml with your preferences

Usage

1. Start the bot:

python x_bot_blocker.py

2. Monitor the logs:

tail -f bot_blocker.log

3. Export blocked accounts:

python export_blocked.py

Configuration

The bot uses a YAML configuration file (config.yaml) for settings:

api:
  rate_limit:
    max_blocks_per_day: 1000
    cooldown_period: 60

bot_detection:
  min_account_age_days: 30
  min_followers: 10
  max_following_ratio: 10
  min_tweets: 5
  bot_probability_threshold: 0.7

scanning:
  mentions_count: 200
  followers_count: 200
  likes_count: 200
  scan_interval: 60

Development

Project Structure

x-bot-blocker/
├── config.yaml           # Configuration settings
├── requirements.txt      # Python dependencies
├── x_bot_blocker.py      # Main bot script
├── config_manager.py     # Configuration management
├── bot_detection.py      # Bot detection logic
├── image_analysis.py     # Image analysis module
└── blocked_accounts.csv  # Blocked accounts database

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

Testing

python -m pytest tests/

Documentation

• Core Focus - Project goals and scope
• Implementation Plan - Development roadmap
• API Documentation - API reference
• User Guide - Usage instructions

License

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

Support

For support, please:

1. Check the documentation
2. Search existing issues
3. Create a new issue if needed

Acknowledgments

• X API for providing the platform
• OpenCV for image analysis
• LangDetect for language detection
• All contributors and users