Maigret: A 3000+ Site Username Reconnaissance Tool for OSINT

Why Maigret is notable

Traditional username search tools cover only dozens of platforms; Maigret can scan more than 3000 sites. By default it checks the top 500 sites by traffic; adding the -a flag scans the full list. It supports filtering by tag, country, or category (social, technical).

For each discovered account it extracts publicly available fields such as avatar, bio, location, registration date, and linked accounts. It can perform recursive searches by feeding newly discovered usernames back into the engine.

Technical architecture

Maigret is written in pure Python and requires Python 3.10 or newer. The site database is auto‑updating: each execution pulls the latest configuration from the project's GitHub repository (once every 24 hours); an embedded fallback database is used when offline.

The project provides a command‑line interface, an embeddable Python library ( import maigret), and a web UI that displays results graphically and can export reports as HTML or XMind files. The tool can route traffic through Tor or I2P to query dark‑web sites.

Quick start

pip install maigret
maigret YOUR_USERNAME

A Telegram bot ( @maigret_search_bot) accepts usernames via chat. Docker images are available for the web UI, and a one‑click Cloud Shell launch is provided.

Adoption

Commercial OSINT products Social Links and UserSearch are built on Maigret, indicating enterprise‑level validation. The GitHub repository has over 21 000 stars, with 535 stars added on the day of writing.

Typical use cases

Security research – measuring exposure of a digital footprint.

Social‑engineering defense – understanding information an attacker could collect.

Account recovery – confirming identity through linked accounts.

Content moderation – detecting cross‑platform abuse.

Users must comply with applicable laws and the terms of service of each site; Maigret only collects publicly available data.