TorrentMonitor - Comprehensive BitTorrent Peer Tracking Tool

TorrentMonitor is an advanced Python-based tool designed to revolutionize the way you track and monitor peers in BitTorrent networks. With real-time notifications, detailed peer information, and seamless integration with Telegram, this tool offers unparalleled insight into the activities within torrent swarms.

Whether you're an internet researcher, a security analyst, or just interested in monitoring torrent activity, TorrentMonitor brings automation, accuracy, and convenience together in a single, powerful tool.

Why TorrentMonitor?

• Real-Time Peer Monitoring: Capture extensive data on every peer connected to your torrent. From IP addresses and geolocation to the client's software and download progress, you get a complete view of network activity.

• Geolocation Precision: TorrentMonitor leverages the GeoLite2 and DB-IP ASN databases to pinpoint the exact location of peers. This data can be essential for network research, security analysis, and gaining insights into user demographics.

• Telegram Alerts: Receive instant notifications via Telegram when specific peer criteria are met (e.g., peers from a particular country, ISP, or region). This makes TorrentMonitor a powerful tool for automated network tracking.

• Torrent Client Simulation: TorrentMonitor can simulate different torrent clients (e.g., uTorrent, BitTorrent, qBittorrent, Transmission, Deluge) by randomly selecting a new user-agent on each execution. This enhances anonymity and replicates the behavior of various clients in the torrent network, providing more flexibility in peer interactions.

• Scalability: Monitor any number of .torrent files at once. TorrentMonitor is built to scale efficiently, tracking peers across multiple torrents while maintaining performance.

• Customizable Filters: Focus your monitoring efforts by setting filters, such as specific countries or ISPs, to track only the peers you are most interested in.

• Extensive Reporting: TorrentMonitor logs all peer data into an SQLite database for long-term analysis and exports this data into CSV files, providing flexibility for further processing or integration with other systems.

Features

• Comprehensive Peer Data Collection: Collect data such as:

  • IP address
  • ISP (Internet Service Provider)
  • Client software (uTorrent, qBittorrent, etc.)
  • Geolocation (country, city, region)
  • Download and upload speeds
  • Number of seeds and peers connected
  • Torrent file info (name, size, progress, etc.)

• Torrent Client Simulation: Randomly simulate various BitTorrent clients with each session by automatically changing the user-agent. This feature can mimic popular clients like:

  • uTorrent 3.5.5
  • BitTorrent 7.10.5
  • qBittorrent 4.3.6
  • Transmission 3.00
  • Deluge 2.0.4
  • Vuze 5.7.7

• Intelligent Session Management: Fine-tune session parameters (download/upload speed, connection limits, scraping intervals) for optimized tracking and bandwidth usage.

• CSV Export & Database Storage: Automatically store detailed data in an SQLite database for easy querying and export to CSV for detailed analysis.

• IP Filtering: Filter out local IP addresses and private ranges to avoid logging irrelevant data.

Installation

Prerequisites

• Python 3.6+
• Telegram Account: Get your Telegram API credentials by following this guide.
• GeoLite2 Database: Download from MaxMind.
• DB-IP ASN Lite Database: Download from DB-IP.
• Transmission-cli: Ensure that transmission-cli is installed on your system for efficient torrent management:

  sudo apt install -y transmission-cli

Setup

1. Clone the repository:

   git clone https://github.com/N4rr34n6/TorrentMonitor.git

2. Navigate to the directory:

   cd Torrent-Monitor

3. Install dependencies:

   pip install -r requirements.txt

4. Configure Telegram:

   • Open TorrentMonitor.py and replace the placeholders for api_id, api_hash, phone, and recipient with your actual Telegram API credentials.

5. Download GeoIP Databases:

   • Download the GeoLite2-City.mmdb and dbip-asn-lite.mmdb files from their respective sources.
   • Important: Place both files in the same directory as the TorrentMonitor script to ensure proper geolocation functionality.

Usage

To start tracking torrents, provide a folder containing .torrent files. Use the following command to run TorrentMonitor:

python3 TorrentMonitor.py -d TorrentsDir -o Test -g -T 150 -c Spain -db Test.db

Command-line Arguments

Argument	Description	Default
-d, --torrent_folder	Specify the folder containing .torrent files (required).	None
-o, --output	Specify an output file (CSV) to store peer data.	None
-g, --geo	Enable geolocation for peers' IPs.	False
-T, --time	Time interval (seconds) between peer checks.	30
-v, --verbose	Enable verbose logging for detailed activity logs.	False
-c, --country	Filter peers by country or ISO code.	None
-db, --database	Specify the SQLite database to use.	Monitor.db

Example:

python3 TorrentMonitor.py -d torrents/ -o peers_log.csv -g -T 60 -v

This command tracks all .torrent files in the torrents/ directory, saves peer data into peers_log.csv, enables geolocation, and sets the check interval to 60 seconds.

Database Schema

TorrentMonitor logs peer information into an SQLite database (Monitor.db) with two key tables:

1. report_table: Logs detailed peer connection information.
2. info_torrent: Stores metadata for each monitored torrent file.

report_table Columns:

• ip: Peer IP address
• port: Connection port
• isp: ISP of the peer
• client: Torrent client (e.g., uTorrent, qBittorrent)
• country: Country of the peer
• city: City of the peer
• first_seen: First time the peer was seen
• last_seen: Last time the peer was seen
• torrent: Torrent file name
• name: Torrent name
• infohash: Torrent infohash
• download_speed: Peer’s download speed
• upload_speed: Peer’s upload speed

Telegram Integration

Once configured, TorrentMonitor sends real-time notifications via Telegram when specific conditions are met, such as detecting a peer from a target country or ISP. This feature enables remote monitoring and instant alerts.

Setting Up Telegram:

• Replace the api_id, api_hash, phone, and recipient in the script with your own credentials.
• Customize notification messages in the send_notification function to include peer-specific data points.

Scalability and Use Cases

TorrentMonitor is ideal for:

• Network Security: Identifying suspicious peer connections.
• Academic Research: Studying peer behavior in torrent swarms.
• DMCA Monitoring: Tracking infringing downloads from specific regions.
• Torrent Site Admins: Understanding user demographics and download patterns.

Future Features

• Improved Analytics: Enhanced data visualization and reporting tools.
• Cross-platform Support: Ensure compatibility with more OS environments.
• Custom Alerts: More granular conditions for triggering Telegram notifications.

Contributing

We welcome contributions from the community! Feel free to open an issue or submit a pull request if you'd like to improve TorrentMonitor.

License

This project is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0). See the LICENSE file for more details.