Darkweb Downloader | Securely And AnonymouslyDownload Files From The Dark Web Using Tor

Darkweb Downloader Ultimate Edition

Securely and anonymously download files from the dark web using Tor, with real-time download progress tracking and activity logging.

This Python script facilitates the anonymous downloading of files from URLs listed in a urls.txt file through the Tor network. The script ensures privacy by routing requests through Tor and provides real-time progress updates on the downloads, including download speed and percentage completion. This form handles multi-threaded downloads, zero byte file handling, and randomly timed retry queue to avoid givin up to quickly. Retries are set at 25, with a random number up to 300 seconds as a diff to avoid pattern blocking by the thread actors.

Features

  • Anonymity: Uses Tor to anonymize your internet traffic.
  • Progress Tracking: Real-time download speed with download time, size, and speed.
  • Logging: Detailed logs of all successful and failed download activities.
  • User-Agent Customization: Sends requests with a generic Mozilla user-agent to mimic typical user traffic.

Prerequisites

Before running this script, make sure you have the following installed:

  • Python 3.x
  • Tor Browser or a standalone Tor service

Dependencies

This script requires several Python libraries:

  • requests
  • PySocks (or socks depending on your environment)
  • tqdm

Installation

  1. Clone the Repository:
git clone https://github.com/alenperic/Darkweb-Downloader-Ultimate.git cd DarkWeb-Downloader-Ultimate
  1. Install Required Libraries:
pip install -r requirements.txt
  1. Configure Tor: Ensure that Tor is running and configured to accept connections through a SOCKS proxy (default is localhost:9150 for Tor Browser).
  2. Set Up Configuration Files: Edit the urls.txt file to include the URLs you wish to download files from.

Usage

Add links to be downloaded to the urls.txt file. Run the script using:

python download.py

The files will be downloaded to the downloaded_files directory, and progress will be shown in the command line interface.

Contributing

Contributions to this project are welcome. Please fork the repository and submit a pull request.

CREDITS: alenperic/Darkweb-Downloader for the orginal code and inspiration!

GitHub:

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