de-anonymizer

This tool assists with automating discovering the true identities of people by using publicly available data.

It uses partial (name,address) tuples and attempts to unmask them.

Requirements:

Beautiful Soup 4 and requests

pip install beautifulsoup4 requests

Set-up:

You need:

1. A CSV file with the people you wish to de-anonymize. This file should have the following columns: partialName,partialAddress,City,State

   
   josep,720 Gree,Wilmington,DE
   ron,700 Ad,Tallahassee,FL
   
   

2. A CSV file with the addresses you wish to search over. This file should have the following columns: streetName,City,State

    Alan-a-dale Trail,Tallahassee,FL
    Alanthus Ct,Tallahassee,FL
    Alban Ave,Tallahassee,FL
    Greenbriar Dr,Wilmington,DE
    Greendale Rd,Wilmington,DE
   

3. You can generate a list for a city using data from geographic.org with: deanon.py geographic.org --state FL --city Orlando.

4. You can also obtain a list of all the roads in a county from the Census Bureau at: https://www.census.gov/cgi-bin/geo/shapefiles/index.php. After downloading the roads shape-file, you can parse using deanon.py dbf -f file.dbf -code Orlando-FL

Usage:

1. de-anonymize: deanon.py deanon -t examples/targets -s examples/streets

   1. output:

      partialName,FullName,partialAddress,FullAddress,URL
      joseph,Joseph R Biden,720 gree,720 Greenhill Ave,Wilmington,DE,https://www.whitepages.com/address/720-Greenhill-Ave/Wilmington-DE
      ron,Ronald Desantis,700 ad,700 Adams St,Tallahassee,FL,https://www.whitepages.com/address/700-Adams-St/Tallahassee-FL
      

   2. If you have an account with scraperapi.com, you can pass your API key in with -scraper-api-key xxx. This will help mitigate 403s and 401s.

2. Help: deanon.py --help

3. Modules: most of the source files can be ran as stand-alone scripts. See the usage prompt after running as main for details.