An OSINT tool that allows you to draw out relationships between people on LinkedIn via endorsements/skills.
Check out the example (digraph), which is based on mine and my friends (David Prince) LinkedIn profile. By glancing at the visualisation you can easily see, by the number of "arrows", there is some sort of relationship between us and "Zoë Rose" (in this case we used to work together). If I was carrying out an investigation I would focus my efforts towards her next.
Due to the way LinkedIn's privacy settings work this tool works best when your target is within your 3rd degree network or higher. Using a LinkedIn Premium or Recruiter account will allow you to map targets outside of your network.
All you need it Python 3.4+ and do the following:
git clone https://github.com/eth0izzle/the-endorser.git
sudo pip3 install -r requirements.txt
apt-get install graphvizor
brew install graphvizor
choco install graphiz
--driver phantomjsflag (note phantomjs is 8x slower).
python3 the-endorser.py <profile1> <profile2> <profile3> <etc..> <etc..>
usage: python the-endorser.py https://www.linkedin.com/in/user1 https://www.linkedin.com/in/user2 Maps out relationships between peoples endorsements on LinkedIn. positional arguments: profiles Space separated list of LinkedIn profile URLs to map optional arguments: -h, --help show this help message and exit --config_file CONFIG_FILE Specify the path of the config.yaml file (default: ./the-endorser/config.yaml) --driver DRIVER Selenium WebDriver to use to parse the webpages: chromedriver, phantomjs (default: chromedriver) --output OUTPUT Output module to visualise the relationships: digraph, stdout (default: digraph) --log LOG Path of log file. None for stdout. (default: None) --log-level LOG_LEVEL Logging output level: DEBUG, INFO, WARNING, ERROR. (default: INFO)
The Endorser is "modular" in the sense that it can output and visualise the data in different ways. An output module just needs one method:
Currently there is only one output module (digraph). In the future I plan to add modules for Maltego and Plot.ly - but feel free to get involved!
It's best to read the graph from right-to-left, identifying people that have a large collection of "arrows" from multiple profiles (different colours). Square box = skill, ellipse = person.
Check out the issue tracker and see what tickles your fancy.
git checkout -b my-new-feature
git commit -am 'Add some feature'
git push origin my-new-feature
MIT. See LICENSE