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NIST AI RMF 1.0 — Attestix coverage

How Attestix's signed audit chains, Verifiable Credentials, and provenance records map to the NIST AI Risk Management Framework 1.0 GOVERN-MAP-MEASURE-MANAGE functions. Honest per-subcategory coverage — Attestix is evidence tooling for AI RMF operationalisation, not an AI RMF conformance attestation.

The NIST AI Risk Management Framework 1.0 (NIST AI 100-1), released January 2023, is the most widely-referenced non-EU AI governance framework. Its four core functions — GOVERN, MAP, MEASURE, MANAGE — give organisations a vocabulary for AI risk management that US Federal agencies are required to align with under OMB Memo M-24-10. This page shows how Attestix's signed audit chains, Verifiable Credentials, and provenance records map to the AI RMF subcategories.

Why this matters

The AI RMF is voluntary guidance, not a regulation. There is no "AI RMF certified" mark. NIST itself uses the language "operationalising the AI RMF" — using it as a structuring framework for an organisation's own AI risk-management programme. Attestix is evidence tooling an organisation operationalising the AI RMF can use to gather signed evidence for specific subcategories — particularly those that touch the AI lifecycle where signed audit trails + provenance + impact-assessment records reduce manual evidence-gathering. The AI RMF Playbook + AI 600-1 Generative AI Profile are NIST's complementary operational guides; Attestix slots underneath both as the cryptographic evidence layer.

The honest coverage table

The table below covers 20 representative subcategories spanning the four functions. The complete inventory (72 subcategories across GOVERN-MAP-MEASURE-MANAGE) and the per-function tally is in §4 of the internal mapping doc.

SubcategoryMitigation surface in AttestixCoverageEvidence shape
GOVERN-1.1 Legal + regulatory requirements understoodProfile-level regulatory_jurisdiction declaration; cross-walk to v0.5 EU AI Act Art 6 risk-classificationrecord-onlyProviderAssertionCredential
GOVERN-1.4 Risk-management accountability assignedPer-role DID; every state change signed by actor DID — accountability is forensic by constructionrecord-onlyProviderAssertionCredential + actor-signed audit chain
GOVERN-1.5 Continuous monitoring + periodic reviewcompliance_service checks re-run on cron; each run produces a signed VerifiableCheckResultpartialAudit chain + per-re-run VerifiableCheckResult
GOVERN-4.1 Safety-first cultureNone. A tool does not author organisational cultureout-of-scope
MAP-1.1 Intended purposes + contexts + capabilities + expectationsintended_purpose + deployment_context (v0.5) + signed agent card with capability declarationstrong-partialAgentIdentityCredential + ProviderAssertionCredential
MAP-2.3 Scientific integrity + TEVV considerationsTraining-data lineage + representativeness assertions; v0.5 Art 15 accuracy/robustness checks; TEVV pointer in model lineagestrong-partialHash-chained provenance + ModelEvalCredential (v0.5)
MAP-3.4 Third-party risk identifiedThird-party signed AgentIdentityCredential acceptance; v0.5 record_third_party_dependencystrong-partialUCAN chain + supplier AgentIdentityCredential
MAP-4.1 Approaches for mapping legal + IP risksLicense + license-review records per data + model assetpartialHash-chained provenance entries
MAP-5.1 Likelihood + magnitude of impactFRIA template (see FRIA page); structured record_impact_assessmentstrong-partialImpactAssessmentCredential
MEASURE-1.1 Approaches + metrics for AI risk measurementv0.5 Art 15 metric declarations; signed ProviderAssertionCredential recording chosen metricsrecord-onlyProviderAssertionCredential
MEASURE-2.1 Test sets + metrics + tool documentationTest-set fingerprint + ModelEvalCredential (v0.5) wrapping the operator's eval outputsstrong-partialHash-chained provenance + ModelEvalCredential
MEASURE-2.3 Performance + assurance criteria measuredv0.5 Art 15 accuracy/robustness check produces structured VerifiableCheckResult; v0.5 record_performance_measurementstrong-partialVerifiableCheckResult + audit chain
MEASURE-2.7 Security + resilience evaluated + documentedv0.5 Art 15.5 cybersec check; cross-walk to OWASP ASI mapping; operator's pen-test / red-team / garak results signedstrong-partialVerifiableCheckResult + SecurityCheckCredential (OWASP ASI tags)
MEASURE-2.8 Transparency + accountability evaluatedEvery audit event signed + chain-hashed — accountability is forensic by construction; agent cards + DoC are transparency artefactsfullAgentIdentityCredential + EUAIActComplianceCredential (DoC)
MEASURE-2.10 Privacy risk evaluated + documentedGDPR Art 17 right-to-erasure (already in v0.3.0); privacy_assessment wrapper field (v0.5)partialProviderAssertionCredential + audit chain
MEASURE-3.2 Risk tracking for emergent risksOperator-recorded emergent-behaviour observations; reputation-score drift signalpartialAudit chain + ReputationScoreCredential
MANAGE-1.1 Go/no-go determination of contextual + societal impactsExplicit record_go_no_go_decision signed by approver DID (v0.5)record-onlyProviderAssertionCredential signed by approver
MANAGE-1.2 Treatment of documented AI risksv0.5 record_risk_treatment ledger; cross-walk to EU AI Act Art 9 risk-management systemstrong-partialAudit chain + VerifiableCheckResult
MANAGE-2.3 Mechanisms to supersede + disengage + deactivaterevoke_identity + revoke_credential kill-switch; UCAN expiry; v0.5 Art 14.4 stop-button checkstrong-partialRevocation VC + audit event + VerifiableCheckResult
MANAGE-4.1 Post-deployment monitoringPer-agent audit log IS the post-deployment monitoring substrate; v0.5 incident-reporting collection; user-feedback log; reputation driftstrong-partialHash-chained audit + IncidentReportCredential (v0.5) + ReputationScoreCredential

Tally (across all 72 subcategories)

The 20 rows above are representative; for the complete count we estimate (per §4 of the internal mapping doc):

  • strong-partial+: 18 (1 of which is full — MEASURE-2.8 transparency + accountability)
  • partial: 18
  • record-only: 22
  • out-of-scope: 14 (cluster in GOVERN organisational + cultural subcategories)

Important caveat — security_check_id ships in v0.5.0. As of Attestix v0.4.0 the underlying events are emitted today, but they are NOT yet tagged with the nist.airmf.* discriminator. The v0.5.0 release registers the prefix in FRAMEWORK_REGISTRY; per-subcategory emission tagging is incremental.

What we don't do

  • We do not author your organisational culture. GOVERN-4.1 (safety-first culture), GOVERN-2.1 (workforce diversity), and similar GOVERN subcategories are organisational and cultural. Any tool that claims to "verify culture" is overclaiming.
  • We do not run TEVV ourselves. MEASURE-1.x and MEASURE-2.x expect your eval pipeline (Weights & Biases, MLflow, Inspect AI, garak, promptfoo). We wrap signatures around the outputs.
  • We do not assess third-party risk. MAP-3.4 + CC9.2 (SOC 2) expect Vanta / Drata / UpGuard / SecurityScorecard style vendor-risk assessment. We record relationships + signed claims.
  • We are not the AI RMF Playbook. NIST's AI RMF Playbook is the authoritative subcategory-by-subcategory implementation guide. We point at evidence shapes; the Playbook tells you what to do.
  • We do not detect emergent behaviour. MEASURE-3.2 emergent-risk tracking points at research-grade interpretability work (Anthropic interpretability, white-box probes). We record the operator's observations.
  • We do not auto-promote assertions to verifications. When a human asserts "yes, this met the criterion", the result transitions to assertion_recorded (rendered blue), NOT to passed=true (rendered green).

How to verify our coverage yourself

Python / CLI

# List every audit event tagged with an AI RMF subcategory (v0.5.0+)
attestix audit list --security-check nist.airmf.MEASURE.2.8.transparency_artefact_published

# Export a bundle scoped to AI RMF evidence (v0.5.0+)
attestix bundle export --controls nist.airmf --out my-airmf-evidence.atxbundle

# Verify chain integrity for an agent's audit log (today)
attestix verify-chain <agent-did>

JavaScript / browser

npm install attestix
import { verifyCredential } from "attestix";

const result = await verifyCredential(verifiableCheckResultJson);
// result.valid === true if the Ed25519 signature over the JCS-canonical body
// matches the issuer DID's public key.

On-chain anchor (Base L2 Sepolia testnet)

attestix anchor audit-batch --agent <did> --network base-sepolia

Mainnet schema registration is planned; testnet is the default target today.

Comparable disclosure

How other tools position themselves on AI RMF alignment.

ToolStated AI RMF positionWhere to read more
Microsoft Agent Governance ToolkitPublishes docs/compliance/nist-ai-rmf-alignment.md; toolkit-feature-to-subcategory mapping; CloudEvents-to-Azure-Monitor evidencegithub.com/microsoft/agent-governance-toolkit
NIST AI RMF PlaybookAuthoritative subcategory-by-subcategory implementation guide. Complementary to Attestix; we provide evidence shapes the Playbook recommendsairc.nist.gov/AI_RMF_Knowledge_Base/Playbook
NIST AI 600-1 Generative AI ProfileNIST's domain-specific overlay for generative AI risk. Informs MEASURE-1 / MEASURE-2 / MANAGE-4 for agentic systemsnvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf
Weights & Biases / MLflow / Inspect AIEval + experiment tracking; complementary — they measure, we signwandb.ai, mlflow.org, github.com/UKGovernmentBEIS/inspect_ai
Vanta + Drata + SecureframeGRC platforms with AI RMF profiles; auditor coordination + continuous monitoring. We slot underneath as the cryptographic evidence layervanta.com, drata.com, secureframe.com

See also


Attestix is evidence tooling for organisations operationalising the NIST AI RMF 1.0. Attestix does not issue AI RMF conformance attestations (no such attestation exists; the AI RMF is voluntary guidance), does not replace the organisation's risk-management programme, and a passing tag against a subcategory is one signal in the overall risk posture.