Maigret: Investigating usernames online
Link to tool: https://github.com/soxoj/maigret
In one our previous OSINT Tool Reviews, we took a close look at a Command Line Interface and Graphical User Interface-based tool that has the capability to search across over 800 online sources (including social media). In this OSINT Tool Review, we will look at Maigret, another tool that can be used to investigate usernames.
Many readers will no doubt be curious with regards to the origin of the name Mairgret. As indicated by the tool’s developers, the name is based on Commissioner Jules Maigret is a fictional French police detective, created by Georges Simenon. His investigation method is based on understanding the personality of different people and their interactions.
Maigret is quite a powerful Python-based script that enables Digital Investigators and OSINT Analysts to conduct searches against usernames and detailing all available metadata obtained from webpages where a match is confirmed. The tool itself is based on the popular Python-based script Sherlock but is considerably far easier to deploy. According to Maigret’s Github repository, the tool currently supports more than 2000 websites, the full list of which can be found here. The most significant sites of which include various Tor and IS2P sites in addition to other domains associated with adult, dating, hacking and gaming forums. One point to note is that Maigret can also verify whether the username is associated with a Kik instant messaging application account. This is quite important since Kik is often associated with highly nefarious activity which includes the distribution of child sexual abuse material (of all categories).
In addition to being capable of extracting available metadata from profile matches, Maigret can also allow Digital Investigators to narrow searches by site categories and country codes. The tool also has an in-built captcha detection tool that can be used to bypass verification requests and can also retry searches in the event where search requests are timed out. Maigret is very flexible and can be installed and deployed via the popular Command-Line Interfaces Python or Docker. Additionally, the tool can be run through cloud shells and Jupyter notebooks such as Colab or Binder.
COMMAND-LINE INTERFACE OUTPUT
Search results are immediately indicated through the Command Line Interface. During this review, we used Python to conduct simultaneous searches against multiple target usernames. The search results which can be observed through the Command Line Interface vary depending on the website itself. For example, DeviantArt can provide a substantial amount of user information concerning account creation date and date/time of last activity. On the other hand, more privacy-conscious websites will offer little further information other than confirming the existence of an account that matches the username.
What is undeniably impressive about Maigret is its capability to output a report in PDF or HTML. The report will input a time / date stamp concerning when the search was undertaken in addition to high-confidence information concerning the target such as likely gender and location. The report goes further to provide you with details concerning each match that Maigret has discovered in addition to available metadata that it has managed to extract. What we consider to be most interesting is that Maigret also outputs a Mindmap file that can be opened with MindManager, enabling us to visualise the result of each search and its matches.
Maigret is a very powerful, yet easy-to-deploy and easy-to-use tool that has far-ranging capabilities. What impresses us the most is the large number of sources that it searches against in addition to its capability to output HTML, PDF and Mindmap reports for each search. Based on this, we thoroughly recommend the use of Maigret for Digital Investigators and Analysts that require the capability to conduct fast and efficient searches against a considerably large volume of web sources.