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Discover and monitor internet assets using favicon hashes across search engines.

Project description

Favihunter

Favicons are tiny icons used by modern web applications. When combined with search engines, they’re great pivots for discovering related internet assets.

This tool helps security practitioners find assets using favicon hashes across multiple search engines:

🛠️ Installation

Option A — PyPI (standard)

pip install favihunter

Option B — pipx (isolated CLI install) — recommended for command-line tools

# install pipx if you don’t have it
python3 -m pip install --user pipx
python3 -m pipx ensurepath  # then restart your shell

# install favihunter
pipx install favihunter

# upgrade later
pipx upgrade favihunter

# run without installing (one-shot)
pipx run favihunter --help

Option C — From source (Poetry)

git clone https://github.com/eremit4/favihunter.git
cd favihunter
poetry install

Using a virtual environment is recommended to avoid dependency conflicts.

⚡ Quickstart

favihunter --url https://python.org

Favihunter downloads the favicon, computes hashes (MMH3, MD5, SHA256, and optional perceptual hash), and prints ready-to-click search URLs.

🕵️‍♂️ Usage

favihunter --help

Analyze a single URL:

favihunter --url <url>

Analyze a file with URLs (one per line):

favihunter --urls <file>

Analyze a local favicon file:

favihunter --favicon <path/to/favicon.ico>

Clean the temp folder:

favihunter --remove

VirusTotal pivot:

favihunter --url <url> --virus-total

✅ Requirements

  • Python 3.8+
  • Linux/macOS (Windows is likely fine via PowerShell; please open an issue if you hit problems)

🧹 Uninstall / Upgrade

pip

pip install --upgrade favihunter
pip uninstall favihunter

pipx

pipx upgrade favihunter
pipx uninstall favihunter

Project details


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  • Download URL: favihunter-1.3.2.tar.gz
  • Upload date:
  • Size: 11.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.12.3 Linux/6.8.0-85-generic

File hashes

Hashes for favihunter-1.3.2.tar.gz
Algorithm Hash digest
SHA256 d59fd1b706520292be621a66745a67953cd35884256fbfdee7eedfb467c51daa
MD5 90288a61a4cf9a8ca87b21017a90d639
BLAKE2b-256 63e4fee4e207d82cc14e6c79ebb8b43bcd641b71c68e04fd0d4beb63f546307f

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Details for the file favihunter-1.3.2-py3-none-any.whl.

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  • Download URL: favihunter-1.3.2-py3-none-any.whl
  • Upload date:
  • Size: 14.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.12.3 Linux/6.8.0-85-generic

File hashes

Hashes for favihunter-1.3.2-py3-none-any.whl
Algorithm Hash digest
SHA256 38b3278a830d3ed520dfcb2c8bebabdd83c9cd81a0f97013ed1fd97b58f38e4e
MD5 fc576a31c7a7da728943ef718ca0bd31
BLAKE2b-256 584320fa1851cc7da474d1e0bd7359350d00957f8a154618c921bb8c122f33a6

See more details on using hashes here.

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