osint-investigation

Cross-linking public records for an OSINT investigation requires normalizing diverse datasets to resolve entities and build verifiable evidence chains. This framework applies cross-source joins and timing analysis across government, legal, and financial data.

To build an evidence chain for due diligence, you can integrate SEC EDGAR, USAspending, OFAC SDN, ICIJ Offshore Leaks, OpenCorporates, CourtListener, and property records like NYC ACRIS. These sources enable cross-source resolution.

Performing entity resolution across sanctions and litigation involves normalizing data from OFAC SDN and CourtListener, then applying cross-source joins. This framework matches entities across these public records to trace connections.

No, this OSINT framework does not require external dependencies to normalize public records. It uses Python standard library scripts for data acquisition, normalization, cross-source joins, and findings generation, ensuring reproducible outputs.

The best way to analyze timing correlations in lobbying disclosures and government contracts is using a normalization-driven workflow. This framework joins USAspending and Senate lobbying data to construct multi-source narratives with timing analysis.

You should use a cross-source resolution workflow for sanctions screening when you need to verify entity identities across OFAC SDN and corporate registry data like OpenCorporates. This approach ensures auditable evidence chains for compliance checks.