MP-2.3: AI system data sources are documented

AI system data sources are documented sits in the map surface, and NIST AI 600-1 rates it high. Inventory + provenance for every training, fine-tune, RAG data source. For teams shipping LLM and agentic features, a control like this is only as good as the evidence that it was actually tested - an unverified control is a finding waiting for an auditor.

Penaxtra turns this NIST AI 600-1 obligation into testable, recurring evidence: scheduled scans and posture checks produce findings tied to MP-2.3, and the append-only audit log records what was tested and when, which is exactly what an assessor asks for. Every relevant finding is created with the NIST AI 600-1 MP-2.3 identifier already attached, so it lands in the audit-evidence pack mapped to the control rather than as a screenshot someone has to translate later. Where the same weakness touches another framework, the cross-framework overlap means one finding satisfies several control cells at once.

Findings for MP-2.3 carry the NIST AI 600-1 MP-2.3 identifier and cross-map to the related controls in the other five frameworks Penaxtra covers.