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Discover and track internet assets using favicon hashes through search engines.

Project description

Favihunter

Favicons are small icons in modern web applications that could be very useful for us in our day-to-day hunting activities, especially when we combine these icons with modern search engines to find assets on the internet.

This project helps security professionals find assets online using favicon hashes through search engines such as:

🛠️ Installation

Optional - Creating a virtualenv before installing the dependencies

Note: The use of virtual environments is optional, but recommended. In this way, we avoid possible conflicts in different versions of the project's dependencies. Learn how to install and use virtualenv according to your OS here

Via PyPI (Recommended)

You can install FaviHunter directly from PyPI:

pip install favihunter

Via Source (Using Poetry)

Cloning the project:

git clone https://github.com/eremit4/favihunter.git

Installing the dependencies:

poetry install

🕵️‍♂️ Using

Discovering the project capabilities:

favihunter --help

Analyzing a specific URL:

favihunter --url <url address>

Analyzing a file with URLs:

favihunter --urls <file path>

Analyzing a local favicon image:

favihunter --favicon <file path>

Cleaning the favicon local directory:

favihunter --remove-favicons

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

favihunter-1.1.1.tar.gz (8.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

favihunter-1.1.1-py3-none-any.whl (10.5 kB view details)

Uploaded Python 3

File details

Details for the file favihunter-1.1.1.tar.gz.

File metadata

  • Download URL: favihunter-1.1.1.tar.gz
  • Upload date:
  • Size: 8.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.12.3 Linux/6.8.0-49-generic

File hashes

Hashes for favihunter-1.1.1.tar.gz
Algorithm Hash digest
SHA256 1910ad31a04e554dd6a49334f7f407ae6ed4c8faff516677a17efb1421c4ca16
MD5 84d407773ae277590804d5c8909ae6e5
BLAKE2b-256 e1ef2c33f65a9d1c0d92199225c1e4b173b15c8ed32c3a934939572c006ece13

See more details on using hashes here.

File details

Details for the file favihunter-1.1.1-py3-none-any.whl.

File metadata

  • Download URL: favihunter-1.1.1-py3-none-any.whl
  • Upload date:
  • Size: 10.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.12.3 Linux/6.8.0-49-generic

File hashes

Hashes for favihunter-1.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 9f1ae449c4b944bb56e93010051db466bf65738c77230f4584e6db5d5a8c42f6
MD5 55a9e125e95b9b667e9ab43b2b3d3f51
BLAKE2b-256 5586baf0c9983f7759f8c84bb126a88142ca17ba9e98a524f97298fdf1ccfec9

See more details on using hashes here.

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