osint-investigation

OSINT investigation using public records involves querying sources like SEC EDGAR, USAspending, and OFAC to build structured evidence chains. This skill automates entity resolution and cross-link analysis to connect financial, legal, and ownership data across disparate databases.

Cross-link analysis in open source intelligence identifies and resolves entities across different public records sources even when naming varies. It builds cross-links with explicit confidence levels and applies statistical timing correlation to establish structured evidence chains.

Yes, you can use Python to access ICIJ offshore leaks, property records, and court records for background checks. This skill requires the Python standard library and specific tools to query these diverse data sources and perform global news monitoring.

The best way to analyze a company's financial history and lobbying disclosures is by cross-referencing SEC filings, USAspending contracts, and global news monitoring. This approach aggregates data to identify ownership structures, legal issues, and financial anomalies.

This OSINT investigation skill does not require external database software but relies on the Python standard library including requests, csv, datetime, json, and re. It uses these modules to access public records sources and format the resulting cross-link analysis data.

Statistical timing correlation in a public records investigation is used when you need to validate cross-link analysis confidence levels. It compares dates across SEC EDGAR filings, USAspending contracts, and court records to establish chronological evidence chains linking entities.