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Thu 13 Aug 13:45 UTC
Automationevaluationupdated 13 Aug 2026

maigret

Maigret is a Python OSINT tool that checks a username across more than 3,000 sites, then collects profile details and links into readable or machine-friendly reports. It turns a slow, repetitive account hunt into one command, with no site API keys required for the standard search.

Verdict

Maigret is the strongest first pick when a username search needs to become an investigation artifact, not just a list of possible accounts. Its reports, recursive discovery, and programmable interface justify the extra complexity over simpler checkers. Use it as a lead generator, verify consequential matches by hand, and avoid exposing the stock web UI directly to the internet.

Setup4/5Simple pip start, with extra services for protected sites and Tor
Docs5/5Clear install, CLI, library, export, proxy, and troubleshooting guides
Community5/5Large audience with active site fixes, issues, and pull requests
Maturity4/5Established core, but live-site drift and release labeling need care

Who it’s for

Investigators and security teams tracing a reused username across public websites.
Journalists and researchers who need exportable evidence rather than a page of search links.
Python developers who want to embed username discovery in a larger OSINT workflow.
Analysts who need Tor, I2P, proxy, recursive-search, and graph-export options in one tool.

Who it’s NOT for

Anyone who needs every hit to be conclusive evidence of identity: an open issue documents one site reporting three random usernames as claimed, so results require manual verification.
Teams expecting a supported authenticated REST service: the project currently offers a CLI, Python library, and web UI, while REST API support remains an open feature request.
Operators who want a public web UI with built-in access control: the README warns that its one-click Render deployment has no login, so anyone with the URL can use it.
Windows users who cannot investigate security-software alerts: an open report says Microsoft Defender flagged the downloadable executable, making the pip or source route the safer evaluation path.
Commercial data products that expect the public site definitions to stay accurate without upkeep: the README says checks break over time and sells a separately maintained daily-updated database.

Setup reality

The first useful search is genuinely easy: install Python 3.10 or newer, run pip install maigret, then pass a username. Docker images and a Windows executable widen the choices, but advanced use adds real work. PDF output needs extra system graphics libraries, Tor and I2P require separately running gateways, Cloudflare handling requires FlareSolverr and is explicitly experimental, and a publicly reachable web UI needs your own authentication and rate controls. Large or recursive scans also need patient result checking because sites change, block automation, and sometimes produce false positives.

More than a username checker

Maigret starts with a familiar OSINT task: enter a username and see where it appears. The difference is what happens after a possible account is found. The tool can extract details from profile pages and APIs, follow discovered usernames and identifiers recursively, and turn the result into HTML, PDF, CSV, JSON, text, XMind, Neo4j, or an interactive graph.

The public database covers more than 3,000 sites. A normal run checks the 500 highest-ranked entries, while flags can scan everything or narrow the work by country and category tags. That default is sensible. Hitting every supported service creates more delay, more blocks, and more noise than most first passes need. Maigret also updates its database from GitHub once per day and falls back to the bundled copy offline.

No API keys are required for ordinary username checks. Investigators can route requests through a normal proxy, Tor, or I2P. A parser can start from a profile URL, extract identifiers, and launch a wider search. Username permutation support covers cases such as combining a first and last name into likely handles.

Setup is easy until the web fights back

The basic path is as clean as advertised: use Python 3.10 or newer, install the PyPI package, and run maigret USERNAME. There are official Docker variants for the command line and web interface, plus a downloadable Windows executable. Developers can call the asynchronous search function from Python instead of wrapping the command, which is the better route for a durable internal workflow.

The complexity arrives at the edges. PDF reports are an optional install and need operating-system graphics libraries. Tor and I2P modes assume their gateways are already running. Sites protected by JavaScript challenges can be routed through a separate FlareSolverr instance, but the README labels that Cloudflare bypass experimental and warns that its behavior may change without compatibility guarantees.

The bundled web UI is excellent for exploring the relationship graph and downloading reports. It is not a finished multi-user service. The README explicitly says the one-click Render deployment has no login and can be used by anyone who knows its URL. Put authentication, request limits, and an acceptable-use policy in front of it before making it reachable outside a trusted network. A request for a proper authenticated REST API is still open, so service integrations should currently use the Python library or build their own boundary.

Results are leads, not identity proof

Username reuse is useful evidence, but it is not proof that two profiles belong to the same person. Common handles collide, profile pages change, and websites sometimes return the same response for existing and nonexistent users. Maigret uses claimed and unclaimed response markers, status codes, redirects, and page data to make that decision, yet the database is only as accurate as the current behavior of thousands of independent sites.

A July 2026 issue gives the right warning: the Telegram bot's automated probe marked three random usernames as claimed on one forum. Current pull requests also repair integrations when an API times out or a profile route stops exposing structured data. This is healthy maintenance, but it demonstrates why consequential findings need to be opened and checked manually. The self-check command helps maintainers find broken definitions; it does not remove uncertainty from a finished report.

The optional AI mode sends a generated Markdown report to an OpenAI-compatible chat endpoint for a short investigation summary. It introduces an API key, a third-party or local model, privacy decisions, and another source of mistaken inference. Keep the underlying links and distinguish extracted facts from model-written conclusions.

Reporting is where Maigret earns its place

The export range is a genuine advantage. HTML and PDF suit a human handoff, CSV and newline-delimited JSON fit analysis pipelines, and the graph output makes connections easier to inspect. Neo4j export writes an idempotent Cypher script, so repeated imports do not have to duplicate the same entities. Keyword highlighting can also elevate profiles that mention terms relevant to the investigation.

Maigret is especially strong when the first match reveals another identifier. Recursive searching can turn scattered public clues into a connected dossier, and the library interface lets a team attach its own review and storage process. The responsible workflow is to start narrow, preserve source URLs, verify important matches, and expand only when the evidence justifies it. Running all sites and accepting every green result produces volume, not certainty.

Active project, confusing release pointer

The repository was pushed on August 12, 2026, one day after stable version 0.6.4 was published. Its 22 open items combine issues and pull requests, and the recently updated queue includes site repairs, report improvements, new site submissions, and maintenance work. That combination points to an active project rather than a large abandoned backlog.

Release discovery has one avoidable trap. GitHub's latest-release API currently returns a development Windows build tagged main from April, even though stable releases through 0.6.4 are newer. An open issue explains that the development workflow took the Latest marker and that branch-like tags can resolve ambiguously. Choose a numbered stable release or PyPI version instead of assuming GitHub's green Latest label identifies the safest build. Windows evaluators should also know that an open report says Defender flagged the standalone executable; installing through pip or inspecting and building the source avoids relying on that binary while the report is investigated.

Maigret is an unusually capable open tool for turning username reuse into structured research. Its breadth also guarantees ongoing breakage at individual sites. Pick it when reports, recursive clues, and integration matter, then pair it with human verification and careful access controls. If all you need is a quick presence list, Sherlock is easier to explain and operate.

Alternatives

ProjectWhat it isPick it when
SherlockA focused command-line username checker with a large, familiar community.pick this instead when you mainly need account-presence checks and prefer a narrower tool with fewer dossier and graph features.
WhatsMyNameA community-maintained username enumeration dataset used by several OSINT tools.pick this instead when you want site definitions to feed your own workflow rather than a full investigation application.
SpiderFootA broader OSINT automation platform that connects many target and data types.pick this instead when usernames are only one part of an investigation spanning domains, IP addresses, emails, and infrastructure.

What people are saying

  1. [github-trending] soxoj/maigret

Sources

  1. Maigret README
  2. Maigret release v0.6.4
  3. False-positive site probe issue
  4. Development release marked latest issue
  5. Windows Defender report
  6. REST API feature request