This repository host a small proof-of-concept that deanonymizes emails.
Instructions on how to extract a token required to use the tool can be found here: https://www.gosecure.net/blog/2021/05/27/step-by-step-how-to-deanonymize-emails-on-linkedin/
The script can be launched this way. The output was masked on purpose for demonstration.
>python outlook_http_client.py samples_demo.txt > profiles_demo.json
[+] *******@yahoo.com: Not Found
[!] Nb failures: 1
[+] *******@gmail.com: Found
[+] Summary: Paul *******, "Attorney and Counsel" at "*******", "Waltham, Massachusetts, United States"
[+] *******@hotmail.com: Found
[+] Summary: David *******, "Engineering Specialist*******" at "*******", "Greater McAllen Area"
[+] *******@libero.it: Found
[+] Summary: antonio *******, "******* Professional" at "*******", "Naples, Campania, Italy"
[+] *******@hotmail.com: Not Found
[!] Nb failures: 1
[+] *******@soton.ac.uk: Found
[+] Summary: Tom *******, "Student *******" at "", "Southampton, England, United Kingdom"
[+] *******@yahoo.com: Found
[+] Summary: Madhukar *******, "Financial Crimes*******" at "*******", "New York City Metropolitan Area"
[+] *******@inmovement.org: Not Found
[!] Nb failures: 1
[+] *******@hotmail.com: Found
[+] Summary: Shaun *******, "Strategic *******" at "*******", "Bismarck, North Dakota, United States"
The stdout will include the complete LinkedIn profile in a JSON format.
The output json include the following fields:
- companyName
- displayName
- headline
- id
- linkedInUrl
- location
- photoUrl
- positions
- schools
- summary
Their are few other less interesting fields:
- locale
- connectionCount
- connectionDegree
- connectionStatus
- newsMentions
- reportProfileUrl
- skillEndorsements
- skills
