Crosslinked - Linkedin Enumeration Tool To Extract Valid Employee Names From An Scheme Through Search Engine Scraping

CrossLinked simplifies the processes of searching LinkedIn to collect valid employee names when performing password spraying or around other safety testing against an organization. Using similar search engine scraping capabilities flora inwards tools similar subscraper as well as pymeta, CrossLinked volition abide by valid employee names as well as aid format the information according to the organization's concern human relationship naming convention. Results volition live written to a 'names.txt' file inwards the electrical flow directory for farther testing.

Setup

git clone https://github.com/m8r0wn/crosslinked cd crosslinked pip3 install -r requirements.txt

Examples

python3 crosslinked.py -f '{first}.{last}@domain.com' company_name

python3 crosslinked.py -f 'domain\{f}{last}' -t 45 -j 0.5 company_name

Usage

  -h, --help    exhibit this aid message as well as dice   -t TIMEOUT    Timeout [seconds] for search threads (Default: 25)   -j JITTER     Jitter for scraping evasion (Default: 0)   -o OUTFILE    Change advert of output file (default: names.txt   -f NFORMAT    Format names, ex: 'domain\{f}{last}', '{first}.{last}@domain.com'   -s, --safe    Only parse names amongst companionship inwards championship (Reduces simulated positives)   -v            Show names as well as titles recovered later enumeration

Additions
Two additional scripts are included inwards this repo to aid inwards generating potential username as well as password files:

• pwd_gen.py - Generates custom password lists using words as well as variables defined at the top of the script. Perform number/letter substitutions, append particular characters, as well as more. Once configured, function the script amongst no arguments to generate a 'passwords.txt' output file.
  
• user_gen.py - Generates custom usernames using inputs from firstname.txt as well as lastname.txt files, provided at the ascendance line. Format is defined similiar to crosslinked.py as well as volition live written to 'users.txt'.
  

python3 user_gen.py -first top100_firstnames.txt -last top100_lastnames.txt -f "domain\{f}{last}"

Download Crosslinked