osint-investigation

Cross-source evidence chains are built by running this framework's Python stdlib scripts to fetch public records from government filings, corporate registries, and news, then resolving entities across sources with confidence scores and outputting normalized CSVs and a findings JSON payload.

Entity resolution in open-source intelligence is the process of linking entities across diverse public-record sources like sanctions lists and corporate registries. This framework applies confidence scores to correlate and resolve these entities for traceable reporting.

Yes, you can investigate corporate registries and sanctions lists using only Python stdlib. The framework relies entirely on standard library scripts for data ingestion and resolution, requiring no external dependencies.

To collect public-record data from sources like SEC EDGAR and OFAC SDN, run the provided fetch scripts. The workflow-driven acquisition gathers filings, sanctions, and lobbying data, outputting normalized CSVs for audit and journalism.

The best way to normalize OSINT data for audit reporting is using a framework that outputs structured findings JSON and traceable cross-links. This framework generates normalized CSVs and a findings.json payload from diverse public records.

A limitation of a stdlib-only framework for public-record investigation is the lack of built-in asynchronous HTTP libraries or advanced parsing modules, meaning ingestion and resolution scripts rely solely on Python's standard library components.