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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-1.0.1.tar.gz (8.1 kB view details)

Uploaded Source

Built Distribution

favihunter-1.0.1-py3-none-any.whl (10.0 kB view details)

Uploaded Python 3

File details

Details for the file favihunter-1.0.1.tar.gz.

File metadata

  • Download URL: favihunter-1.0.1.tar.gz
  • Upload date:
  • Size: 8.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.12.3 Linux/6.8.0-45-generic

File hashes

Hashes for favihunter-1.0.1.tar.gz
Algorithm Hash digest
SHA256 1a178eca365336085f7f5ae53305a3c349c6e1a229acaa29eb146654d882422d
MD5 04edd0fe1642efc50325ce12f6a11bc8
BLAKE2b-256 399fa55674334a88f2be5fc8ec7c2c8e557c77796554d6199570d500b7dec7f0

See more details on using hashes here.

File details

Details for the file favihunter-1.0.1-py3-none-any.whl.

File metadata

  • Download URL: favihunter-1.0.1-py3-none-any.whl
  • Upload date:
  • Size: 10.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.12.3 Linux/6.8.0-45-generic

File hashes

Hashes for favihunter-1.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 7bd58253a46e607ad3c2681a096c7d42622cb280851bd0160b6a1e5dcbe1a99c
MD5 32335eb97f69f61edd207b5be67c7ca3
BLAKE2b-256 5b4a31e56172acc2871867dc4a478b36cb76f876506d3a95561ad01feaac0212

See more details on using hashes here.

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