A GitHub-hosted open source script lets users privately scan their LinkedIn contacts against millions of DOJ-released Epstein court records, turning public archives into searchable intelligence.
Open source developers are increasingly building public-interest investigative tools on top of newly released government data, and the latest example is EpsteIn (Epstein + LinkedIn), a free Python script now available on GitHub.
The tool allows users to check whether any of their LinkedIn contacts are mentioned across more than 3.5 million pages of Jeffrey Epstein-related court files recently released by the United States Department of Justice (DOJ). Instead of relying on centralised platforms, the script runs entirely on a user’s local machine, keeping searches private and under individual control.
The project’s GitHub description states: “Search the publicly released Epstein court documents for mentions of your LinkedIn connections.”
After comparing names from a LinkedIn data export with a public index created by Patrick Duggan (DugganUSA.com), the script generates an HTML report listing the person’s name, company and position, number of mentions, short excerpts, and direct links to the original DOJ-hosted documents.
The creator, identified as Finke, notes the tool began out of personal curiosity.
Documentation warns of false positives, especially for common names, and stresses that a mention does not imply wrongdoing. References may include victims, employees, witnesses, or individuals with indirect or casual contact. The script makes no claims or judgments and surfaces only public-domain records.
Users must download their LinkedIn data, install Python and required libraries, and run the code locally. The release follows Jmail, another viral open source utility, underscoring a broader trend: GitHub-hosted tools are transforming massive public document dumps into actionable, user-driven discovery.
