oss-forensics

To investigate a compromised open-source repository, you must correlate evidence across local git data, GitHub API responses, Wayback Machine archives, and GH Archive BigQuery data. This structured investigation enforces strict evidence-handling rules, SHA-256 integrity checks, and redaction of secrets to determine supply-chain compromise.

The best way to conduct a supply-chain security investigation is using a multi-phase framework that coordinates evidence collection, hypothesis formation, validation, and final reporting. This approach integrates multi-source evidence with anti-hallucination guardrails and provenance tracing to deliver a defensible conclusion regarding repository compromise.

You collect forensic evidence from the GitHub API and Wayback Machine by executing a multi-source evidence collection phase that integrates responses from both platforms. This collection process requires strict provenance tracing and SHA-256 integrity checks to ensure the gathered data is admissible and has not been tampered with.

Yes, you can use GH Archive BigQuery data for open-source security analysis by integrating it as a cross-source evidence stream within a forensic investigation. The data is correlated with local git data and IOC enrichment to form and validate hypotheses about potential supply-chain incidents.

You generate a defensible forensic report for a supply-chain incident by following a structured reporting template after validating your hypotheses. The report includes artifacts and executive summaries derived from cross-source evidence integration, ensuring secrets are redacted and provenance is strictly traced.

A limitation of using git data for supply-chain compromise detection is that local repository data alone may be insufficient to prove compromise. You must cross-reference git data with GitHub API responses, Wayback Machine archives, and IOC enrichment to form a defensible conclusion and avoid hallucinating evidence.