Searching for a goal by username using Mayoret.

Goal search by username: Discover a world of information with Mayoret

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Command line options

Usernames

You can specify multiple usernames separated by a space. Usernames are optional as there are other modes of operation (see below).

Parsing account pages and online documents

Megre will attempt to obtain information about the owner of the document/account (including username and other identifiers) and will search the extracted username and identifiers.

Basic parameters

reports

Output options

Other modes of operation

Extracting information from pages

Maigret may parse URLs and web page content from URLs to obtain information about the account holder and other meta-information. You must specify a URL with the –parse option, which can be a link to an account or an online document. Once the parsing phase is complete, Magret will begin the search phase for the supported identifiers found (usernames, IDs, etc.).

Examples

Collection of personal information

Maigret analyzes account web pages and extracts personal information, links to other profiles, and more. The resulting information is displayed as additional output in the CLI output and as tables in HTML and PDF reports. Additionally, Maigret uses the found IDs and usernames from the links to start a recursive search.

СEnabled by default, can be disabled with

Recursive search

Megre can get some common IDs and usernames from the links on the account page (often people link to their other accounts) and immediately start a new search. All information collected will be displayed in CLI output and reports.

Enabled by default, can be disabled with

reports

Maigret currently supports HTML, PDF, TXT, XMind 8 mindmap and JSON reports.

HTML/PDF reports include:

• Profile photo

• All personal information collected

• Additional information about alleged personal data (name, gender, location), obtained from the statistics of all found accounts

Additionally, there is a short text report in the CLI output after the search phase is complete.

Warning: XMind 8 Mind Maps are not compatible with XMind 2022!

Tags

The database of Megre sites is very large (and will be even larger), and it may be overhead to search all sites. Also, it is often difficult to understand which sites are more interesting for us in the case of a certain person. Tagging allows you to select a subset of sites by interest (photos, messaging, finance, etc.) or by country. The tags of found accounts are grouped and displayed in reports.

Censorship and captcha detection

Megre can detect common errors such as censorship stub pages, CloudFlare encoded pages, and more. If you receive more than 3% of errors of a certain type during a session, you will receive a warning message in the CLI output with recommendations for improving performance and avoiding problems.

Retries

Megre will retry requests with temporary errors (connection failures, proxy errors, etc.).

One attempt by default, can be changed with an option.

Checking archives and mirrors

Megre’s database contains not only original websites, but also mirrors, archives and aggregators.

Example:

• Reddit BigData Search

• Picuki, a mirror of Instagram

• Checking the Twitter shadow ban

Allows you to get additional information about an individual and verify the presence of an account, even if the main site is not available (bot protection, captcha, etc.)

Simple API

Maigret can be easily integrated using the maigret Python package . Example: Official Telegram bot 

Philosophy

TL;DR: Username => Dossier

Maigret is designed to collect all available information about a person by their login. What kind of information is this? First, links to personal accounts. Second, all pieces of information that can be retrieved by a machine, such as: other usernames, full name, URLs of people’s images, date of birth, location (country, city, etc.), gender.

All this information forms a certain dossier, but it is also useful for other tools and analytical purposes. Each piece of data collected has a label in a specific format (eg follower_count number of followers or created_at time of account creation) so that it can be analyzed by different systems and stored in databases.

Road map

Current state

• Database statistics of sites – good

• Statistics of scanning sessions – good

• Automatic detection of the site engine is good

• Engines for all sites – WIP

• A unified reporting flow is fine

• Retries are good

Supported identifier types

Megre can search not only by common usernames, but also by certain common identifiers. There is a list of all currently supported identifiers.

• gaia_id – Google’s internal numeric user ID, formerly located in the Google Plus account URL.

• steam_id – Steam’s internal numeric user ID.

• wikimapia_uid is Wikimapia.org’s internal numeric user ID.

• uidme_uguid – internal numeric user ID of uID.me.

• yandex_public_id – internal letter ID of the user of Yandex sites. See also: YaSeeker.

• vk_id – VK.com’s internal numeric user ID.

• ok_id – internal numerical ID of the OK.ru user.

• yelp_userid – Yelp’s internal user ID.

Tags

The use of tags allows you to select a subset of sites from the large Megre database for searching.

Warning: Tagging is currently unstable.

There are several types of tags:

1. Country codes: us, jp, br… (ISO 3166-1 alpha-2). These tags reflect the language of the site and the regional origin of its users, and are then used to identify the location of the username owner. If the regional origin is difficult to establish or the site is positioned as global, the country code is not specified. There can be multiple country code tags for one site.

2. Site Engines. Most of them are now forum engines: uCoz, vBulletin, XenForota, etc. A complete list of engines stored in the Magret database.

3. Subject/type of sites and user interests. The full list of “standard” tags is present in the source code for just a moment.

Using

Examples of use

Start searching for accounts with the username machine42 on the top 500 sites from the Magret database.

Start searching for accounts with the username machine42 on all sites from the Megre database.

Start searching […] and generate HTML and PDF reports.

Start searching for accounts with the username machine42 on Facebook only.

Get the information from the Steam page at the URL and start searching for accounts with the found username machine42.

Start looking for accounts with the username machine42 on US and Japanese sites only.

Start searching for accounts with the username machine42 only on sites related to software development.

Start searching for accounts with machine42 login only on uCoz sites (mainly CIS countries).

Settings

Settings can also be configured using settings files. See the JSON settings file for a list of supported options.

Once started, Megre attempts to load the configuration from the following sources in the same order:

Missing any of these files is not an error. If the following settings file contains an already known parameter, this parameter will be overwritten. Thus, it is possible to create an individual configuration for different users and directories.

Testing

Recommended to use Python 3.7/3.8 for testing due to some conflicts in 3.9.

Installation test requirements:

To check Megre, use the following commands:

How to publish a new version of Maigret

Collaborative rights required, email Soxoj to obtain them.

To publish a new version, you must create a new branch in the repository with the changed version number and the actual changelog. After that you have to create a release and the GitHub action will automatically create a new PyPi package.

• An example of a new branch: https://github.com/soxoj/maigret/commit/e520418f6a25d7edacde2d73b41a8ae7c80ddf39

• Example release: https://github.com/soxoj/maigret/releases/tag/v0.4.1

1. Create a new branch locally with a new version name:

Check the current version number here: https://pypi.org/project/maigret/ . Only increase the patch version (the third number) if there are no critical changes.

2. Update the version of Maigret with three files manually:

• setup.py

• maigret/__version__.py

• docs/source/conf.py

3. Create a new empty text section at the beginning of the CHANGELOG.md file with the current date:

4. Get automatically generated release notes:

• Open https://github.com/soxoj/maigret/releases/new

• Click Select Tag, enter v0.4.0 (your version)

• Click Create New Tag

• Click + Automatically create release notes

• Copy all the text from the description text box below

• Paste it into an empty text section in CHANGELOG.txt

• Remove the extra lines ## What’s Changed and ## New Members section if it exists

• Close the new release page

5. Record all changes, click, make a request to receive:

6. Merger request

7. Create a new issue

• Open https://github.com/soxoj/maigret/releases/new again

• Click Select Tag

• Please enter the current version as v0.4.0

• Also, enter the current version in the Release Name field

• Click Create New Tag

• Click + Automatically create release notes

• Click the “Publish Release” button.

8. That’s it, now you can just wait for PyPi to click.

You can follow it on the action page: https://github.com/soxoj/maigret/actions/workflows/python-publish.yml