Open-source tool automates opt-outs from 500 data brokers
Stephen Thorn’s new GitHub project targets major data aggregators including Acxiom and LexisNexis, offering a transparent alternative to paid privacy services.
Developer Stephen Thorn has released an open-source automated runner designed to remove personal information from more than 500 people-search sites and data broker databases. The macOS-based tool, available on GitHub under the repository name stephenlthorn/auto-identity-remove, operates on a monthly schedule to manage the growing demand for digital privacy control.
The script utilises a generic-runner.js file to handle approximately 470 brokers derived from two public datasets. For each site, the software employs four distinct strategies in sequence. Where sites require manual intervention, the tool automatically opens the relevant forms in the user’s browser, ensuring that users retain agency over the final submission step.
To navigate common anti-bot protections, the tool includes automated CAPTCHA solving capabilities. Without a third-party service like CapSolver, sites protected by reCAPTCHA are added to a manual list for user action. The software also tracks persistent state via a state.json file, ensuring that completed opt-outs are not resubmitted on every run, thereby conserving resources and reducing noise.
The tool is positioned as a free alternative to commercial privacy services such as Incogni and Optery, which charge annual subscription fees. Thorn notes that while paid services offer professionally maintained flows for a broader range of brokers, this open-source option targets specific gaps left by those providers, including major entities such as Acxiom, LexisNexis, ZoomInfo, and Clearbit.
Configuration files and state tracking data are gitignored to ensure personal information remains on the user’s machine. The default re-check window is set to 90 days, based on observations that brokers typically re-add user data within this period. Upon completion of a run, the tool sends an iMessage notification to the user.
Thorn suggests that using both a paid service and this open-source script represents the strongest approach for comprehensive data removal. The project welcomes pull requests, particularly from contributors who can provide verified working selectors for additional brokers, further expanding the tool’s coverage of the data broker landscape.
