Credits
Original Scraper by Danny Chrastil (@DisK0nn3cT): https://github.com/DisK0nn3cT/linkedin-gatherer
Modified by @vysecurity
Requirements
pip install beautifulsoup4
pip install thready
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.py Put Hunter.io API key in LinkedInt.py Run LinkedInt.py and follow instructions
Example
βββ βββββββ ββββββ ββββββββββββββββββ βββββββ ββββββββββββ
βββ ββββββββ ββββββ ββββββββββββββββββββββββββββ ββββββββββββ
βββ βββββββββ ββββββββββ ββββββ βββ ββββββββββββ βββ βββ
βββ ββββββββββββββββββββ ββββββ βββ ββββββββββββββββ βββ
ββββββββββββββ βββββββββ βββββββββββββββββββββββββ ββββββ βββ
ββββββββββββββ ββββββββ ββββββββββββββββββ ββββββ βββββ βββ
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