maigret

What it is and what it does

Maigret is a command-line and Python library tool for open-source intelligence (OSINT) that discovers accounts and gathers information about a person using only their username. It checks across a database of thousands of websites, extracting profile data, linked accounts, and other available information from public pages and APIs. The tool supports multiple output formats (HTML, PDF, JSON, CSV, interactive graphs), can filter searches by site category or country tags, and includes optional AI-assisted analysis to summarize findings.

The package is designed for both CLI usage and programmatic embedding in Python projects. It handles common obstacles like blocks and censorship, fetches an auto-updated site database from GitHub, and works with Tor and I2P sites. A built-in web interface allows browsing results as an interactive graph. Installation is straightforward via pip, and the tool requires no external API keys or authentication to operate.

Use it for:

• Verify whether a username exists across major social platforms and dating sites in a single scan
• Conduct background research on individuals for security, HR, or investigative purposes by gathering linked accounts
• Generate formatted reports (HTML, PDF, graph) of discovered accounts and profile information for documentation
• Recursively search for related usernames and IDs discovered during initial searches to map account networks
• Filter searches by geographic region or site category (e.g., photo sites, dating platforms) to narrow results

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Maigret searches for a person across thousands of websites by username alone, gathering account information and linked identities without requiring API keys.

Yes, with conditions. Maigret is actively maintained, has no known vulnerabilities, and offers genuine value for OSINT workflows and username verification at scale. Install it if you need batch account discovery or recursive username mapping. Be aware: the heavy dependency tree (25 packages) adds complexity; PDF reports require system libraries; and the tool's effectiveness depends on site database freshness and tolerance for blocks/CAPTCHAs. Not suitable for high-frequency automated queries without proxy rotation.

Install

maigret on PyPI

pip install maigret

uv add maigret

poetry add maigret

Installing maigret

Before you install

Low friction: pure Python wheel with no compiled dependencies. Active maintenance—last commit 2026-08-14, 3 days since latest release. Supports Python 3.10 through 3.14. Heavy dependency tree (25 runtime packages including aiohttp, lxml, requests) is standard for web-scraping tools.

License in practice

MIT license (permissive). You may use, modify, and distribute freely for any purpose, including commercial, with minimal restrictions—only attribution and license inclusion required.

Quickstart

pip install maigret
maigret username

# For HTML report:
maigret username --html

# For programmatic use:
from maigret import search
results = await search('username')

Requires Python 3.10 or higher. Optional PDF reports need system-level graphics libraries on Linux/macOS (install with pip install 'maigret[pdf]').

Verify before relying

• Whether the 3,000+ sites database is actively maintained and how often it updates beyond the stated 24-hour auto-fetch
• Performance characteristics and typical runtime for searches across all 3,000+ sites versus the default 500 highest-ranked sites
• Reliability of CAPTCHA bypass and block detection against modern anti-scraping measures
• Data retention and privacy implications of collected dossiers, especially for commercial use

Package facts

Evidence: maigret-0.6.4-py3-none-any.whl

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