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LinkedIn enumeration tool to extract valid employee names from an organization through search engine scraping. Names can be formatted in a defined naming convention for further security testing.
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Latest commit 4a362c7 May 23, 2019
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LICENSE Initial commit May 16, 2019 v0.0.3 May 16, 2019 Fix typo May 23, 2019 Update May 16, 2019
requirements.txt Initial commit May 16, 2019
user_agents.txt Initial commit May 16, 2019 Update May 16, 2019


CrossLinked simplifies the processes of searching LinkedIn to collect valid employee names when performing password spraying or other security testing against an organization. Using similar search engine scraping capabilities found in tools like subscraper and pymeta, CrossLinked will find valid employee names and help format the data according to the organization's account naming convention. Results will be written to a 'names.txt' file in the current directory for further testing.


git clone
cd crosslinked
pip3 install -r requirements.txt


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


  -h, --help    show this help message and exit
  -t TIMEOUT    Timeout [seconds] for search threads (Default: 25)
  -j JITTER     Jitter for scraping evasion (Default: 0)
  -o OUTFILE    Change name of output file (default: names.txt
  -f NFORMAT    Format names, ex: 'domain\{f}{last}', '{first}.{last}'
  -s, --safe    Only parse names with company in title (Reduces false positives)
  -v            Show names and titles recovered after enumeration


Two additional scripts are included in this repo to aid in generating potential username and password files:

  • - Generates custom password lists using words and variables defined at the top of the script. Perform number/letter substitutions, append special characters, and more. Once configured, run the script with no arguments to generate a 'passwords.txt' output file.

  • - Generates custom usernames using inputs from firstname.txt and lastname.txt files, provided at the command line. Format is defined similiar to and will be written to 'users.txt'.

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