Search the publicly released Epstein court documents for mentions of your LinkedIn connections.
- Python 3.6+
requestslibrary
git clone [email protected]:cfinke/EpsteIn.git
cd EpsteIn/
python3 -m venv project_venv
source project_venv/bin/activate
pip install -r requirements.txt- Go to linkedin.com and log in.
- Click your profile icon in the top right.
- Select Settings & Privacy.
- Click Data privacy in the left sidebar.
- Under "How LinkedIn uses your data", click Get a copy of your data.
- Select Connections (or click "Want something in particular?" and check Connections). If Connections isn't listed as an option, choose the Download larger data archive option.
- Click Request archive.
- Wait for LinkedIn's email; it may take up to 24 hours.
- Download and extract the ZIP file.
- Locate the
Connections.csvfile.
python EpsteIn.py --connections /path/to/Connections.csv| Flag | Description |
|---|---|
--connections, -c |
Path to LinkedIn Connections.csv export (required) |
--output, -o |
Output HTML file path (default: EpsteIn.html) |
Basic usage:
python EpsteIn.py --connections ~/Downloads/Connections.csvCustom output file:
python EpsteIn.py --connections ~/Downloads/Connections.csv --output my_report.htmlThe script generates an HTML report (EpsteIn.html by default) that you can open in any web browser.
The report contains:
- Summary: Total contacts searched and how many had mentions
- Contact cards: Each contact with mentions is displayed as a card showing:
- Name, position, and company
- Total number of mentions across all documents
- Excerpts from each matching document
- Links to the source PDFs on justice.gov
Contacts are sorted by number of mentions (highest first).
- The search uses exact phrase matching on full names, so "John Smith" won't match documents that only contain "John" or "Smith" separately.
- Common names may produce false positives; review the context excerpts to verify relevance.
- Epstein files indexed by DugganUSA.com