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Credits

Original Scraper by Danny Chrastil (@DisK0nn3cT): https://github.com/DisK0nn3cT/linkedin-gatherer

Modified by @vysecurity

Updated to Python3 by @joshuaplatz

Installation

sudo apt install python3-pip
pip install -r requirements.txt

Change Log

[v0.1 BETA 12-07-2017] Additions:

  • UI Updates
  • Constrain to company filters
  • Addition of Hunter for e-mail prediction

To-Do List

  • Allow for horizontal scraping and mass automated company domain, and format prediction per company
  • Add Natural Language Processing techniques on titles to discover groups of similar titles to be stuck into same "department". This should then be visualised in a graph.

Usage

Put in LinkedIn credentials in LinkedInt.cfg Put Hunter.io API key in LinkedInt.cfg Run LinkedInt.py and follow instructions

Example

██╗ ██╗███╗ ██╗██╗ ██╗███████╗██████╗ ██╗███╗ ██╗████████╗
██║ ██║████╗ ██║██║ ██╔╝██╔════╝██╔══██╗██║████╗ ██║╚══██╔══╝
██║ ██║██╔██╗ ██║█████╔╝ █████╗ ██║ ██║██║██╔██╗ ██║ ██║
██║ ██║██║╚██╗██║██╔═██╗ ██╔══╝ ██║ ██║██║██║╚██╗██║ ██║
███████╗██║██║ ╚████║██║ ██╗███████╗██████╔╝██║██║ ╚████║ ██║
╚══════╝╚═╝╚═╝ ╚═══╝╚═╝ ╚═╝╚══════╝╚═════╝ ╚═╝╚═╝ ╚═══╝ ╚═╝
Providing you with Linkedin Intelligence
Author: Vincent Yiu (@vysec, @vysecurity)
Original version by @DisK0nn3cT
[*] Enter search Keywords (use quotes for more percise results)
"General Motors"
[*] Enter filename for output (exclude file extension)
generalmotors
[*] Filter by Company? (Y/N):
Y
[*] Specify a Company ID (Provide ID or leave blank to automate):
[*] Enter e-mail domain suffix (eg. contoso.com):
gm.com
[*] Select a prefix for e-mail generation (auto,full,firstlast,firstmlast,flast,first.last,fmlast):
auto
[*] Automaticly using Hunter IO to determine best Prefix
[!] {first}.{last}
[+] Found first.last prefix

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LinkedIn Recon Tool

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