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InSpy is a python based LinkedIn enumeration tool. Inspy has two functionalities: TechSpy and EmpSpy.
  • TechSpy - Crawls LinkedIn job listings for technlogoies used by the provided company. InSpy attempts to identify technologies by matching job descriptions to keywords from a new line delimited file.
  • EmpSpy - Crawls LinkedIn for employees working at the provided company. InSpy searches for employees by title and/or departments from a new line delimited file. InSpy may also create emails for the identified employees if the user specifies an email format.

Installation
Run 
pip install -r requirements.txt
within the cloned InSpy directory.

Help
InSpy - A LinkedIn enumeration tool by Jonathan Broche (@jonathanbroche)

positional arguments:
  company               Company name to use for tasks.

optional arguments:
  -h, --help            show this help message and exit
  -v, --version         show program's version number and exit

Technology Search:
  --techspy [file]      Crawl LinkedIn job listings for technologies used by
                        the company. Technologies imported from a new line
                        delimited file. [Default: tech-list-small.txt]
  --limit int           Limit the number of job listings to crawl. [Default:
                        50]

Employee Harvesting:
  --empspy [file]       Discover employees by title and/or department. Titles
                        and departments are imported from a new line delimited
                        file. [Default: title-list-small.txt]
  --emailformat string  Create email addresses for discovered employees using
                        a known format. [Accepted Formats: first.last@xyz.com,
                        last.first@xyz.com, first_last@xyz.com, last_first@xyz.com, 
                        firstl@xyz.com, lfirst@xyz.com,
                        flast@xyz.com, lastf@xyz.com, first@xyz.com,
                        last@xyz.com]

Output Options:
  --html file           Print results in HTML file.
  --csv file            Print results in CSV format.
  --json file           Print results in JSON.


InSpy - A Linkedin Enumeration Tool


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 colleagues (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" (we all work together on the same team in this case).

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.

Installation
The Endorser will work on pretty much any *nix (Linux, Mac, BSD) system with Python 3.0+.
  1. git clone https://github.com/eth0izzle/the-endorser.git
  2. sudo pip3 install -r requirements.txt
  3. Setup your LinkedIn credentials in config.yaml
  4. Download ChromeDriver for your platform (requires Chrome) and place in ./drivers. Alternatively you can use PhantomJS and launch with the --driver phantomjs flag (note phantomjs is 8x slower).
  5. python3 the-endorser.py <profile1> <profile2>

Usage
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)

Outputs
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: def run(profiles)
Currently there is only one output module (digraph). In the future the plan is add modules for Maltego and and Plot.ly - but feel free to get involved!

Digraph
It's best to read this from right-to-left to identify people that have arrows from multiple profiles. Square box = skill, ellipse = person.


The Endorser - An OSINT tool that allows you to draw out relationships between people on LinkedIn via endorsements/skills

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