redaction-and-evidence-auditor

To audit CodeBuddy packets for privacy risks, scan artifact roots and run manifests across audience contexts like local_only, customer_private, and public_candidate. This deterministic scanning identifies secret-like values and private host paths, yielding a structured redaction_report.json and redaction_report.md.

Evidence-boundary risk evaluation identifies privacy and publication safety threats in final reports before customer-facing use. It applies deterministic gatekeeping to downgrade readiness or halt sharing, generating a redaction_report.md with recommended actions.

Mask secrets in CodeBuddy review packets by running an automated privacy audit across artifact roots. The deterministic scanning process identifies secret-like values and automatically masks them within the output findings in the redaction_report.json.

Yes, the redaction audit works with specialist bundles and final reports. It evaluates privacy, safety, and evidence-boundary risks across various artifact roots and audience contexts to determine publication readiness.

The best way to determine publication readiness is applying a deterministic gatekeeping scan across audience contexts like customer_private and public_candidate. This prevents unsafe publication by downgrading readiness or halting sharing based on detected risks.

Avoid relying solely on automated redaction audits when custom, non-standard secret patterns exist that deterministic scanning might miss. The audit enforces baseline publication safety by masking known secret-like values, but complex edge cases may require manual review.