NIST AI RMF
Assessor Workpaper

Instructions

This workpaper provides structured test procedures for verifying SWT3 witness anchor evidence during a NIST AI Risk Management Framework (AI 100-1) assessment. Each entry maps an AI RMF subcategory to the SWT3 procedures that produce evidence, defines what to test, what to expect, and how to determine pass/fail.

How to verify an anchor: Paste the anchor string into the public verifier at sovereign.tenova.io/verify (no account required), or recompute the fingerprint yourself using SHA-256. See Verify an Anchor in 5 Seconds for the full procedure.

Coverage badges: Full = SWT3 procedure directly satisfies the subcategory requirement. Partial = procedure covers part of the subcategory; assessor must verify remaining elements through interview or document review.

Sampling guidance: For sample size, red flags, and CSV query instructions, see Assessor Sampling Instructions.

Factor conventions: Factor legends in this workpaper (e.g., "factor_a = policy version") reflect the SWT3 SDK default conventions. Clients may customize factor usage. Before relying on factor interpretations, confirm with the client that their implementation follows these defaults, or request their factor mapping document.

Methodology boundary: This workpaper documents evidence format and suggests evaluation criteria. It does not prescribe assessment methodology. Sufficiency determinations and assessment conclusions remain the assessor's professional responsibility under their applicable accreditation requirements.

Not applicable entries: If a workpaper entry is not applicable to the assessment scope (e.g., the organization does not operate multi-agent systems, so WP-03 supply chain entries do not apply), mark the result as N/A with justification in the Notes field.

Estimated duration: Allow 3-4 hours for a complete workpaper review including verification of 5-10 sample anchors per function. For initial assessments, plan for an additional 1-2 hours of orientation with the provider's factor mapping and ledger access. Periodic reviews with an established baseline typically require 2-3 hours.

Anchor anatomy: Every SWT3 Witness Anchor follows a deterministic format. Here is an annotated example for an AI RMF-relevant procedure:

Govern Govern Function

The Govern function establishes the organizational context, policies, and oversight structures for AI risk management. Entries WP-01 through WP-10 address governance policies, technical environment, supply chain, audit, trust, transparency, roles, governance mechanisms, human oversight, and enforcement.

Map Map Function

The Map function identifies and contextualizes AI risks. Entries WP-11 through WP-16 address system identification, risk identification, fairness and explainability, data governance, data lineage, and impact assessment.

Measure Measure Function

The Measure function addresses metrics, testing, and monitoring of AI systems. Entries WP-17 through WP-19 cover performance and fairness metrics, drift and robustness monitoring, and red team and supply chain testing.

Manage Manage Function

The Manage function addresses operations, incident response, and post-market monitoring. Entries WP-20 through WP-25 cover model lifecycle, cybersecurity, safety and security controls, access control and revocation, incident response and autonomous operations, and post-market monitoring.

How to Cite Verified Evidence

When referencing SWT3 anchor evidence in your AI RMF assessment report, use a consistent citation format. The following templates cover individual anchor verification and workpaper-level summaries.

Common Assessment Questions

Questions that arise during AI RMF assessments, with guidance on how to proceed.

What if the client uses different factor mappings than this workpaper describes?
The factor legends in this workpaper reflect SWT3 SDK defaults. If the client has customized their factor usage, request their factor mapping document. Verify anchors using the client's stated mappings, and note any deviations from SDK conventions in your findings.

What if factor values are redacted or minimal?
SWT3 supports multiple evidence detail levels (clearing levels 0-3). If factors show minimal information (e.g., all values are 0 or 1), ask the client which clearing level they have configured and whether the restriction is appropriate for the system's risk classification. Note the clearing level in your findings.

What if the organization has very few anchors (new deployment)?
For recently deployed systems, the anchor stream will be short. Evaluate based on the time elapsed since deployment. A system deployed 30 days ago with 30 days of anchors demonstrates continuous monitoring from day one. Adjust your temporal continuity expectations to the deployment date, not a fixed 90-day window.

What if an anchor fails fingerprint verification?
A verification failure means the anchor has been modified since minting, or the verification inputs are incorrect. First, confirm you have the correct inputs (tenant ID, procedure ID, factors, millisecond timestamp). If inputs are correct and verification still fails, this is a significant finding -- document it and request the client's explanation.

How do lifecycle chains (v6.0) relate to AI RMF categories?
Lifecycle chains link multiple anchors into a sequence using a shared cycle_id. For the Govern function, chains document governance decision sequences. For Manage, chains link incident detection through response and resolution. When reviewing lifecycle chains, verify the chain is complete (no missing sequence positions) and that the cycle_id is consistent across all anchors in the chain.

What if the organization is assessed against multiple frameworks simultaneously?
SWT3 procedures are framework-agnostic -- the same AI-FAIR.1 anchor satisfies fairness requirements in NIST AI RMF, ISO 42001, EU AI Act, and SR 11-7. When an organization is assessed against multiple frameworks, you can cite the same anchor evidence in each framework's workpaper with the appropriate framework-specific citation. The crosswalk guides at sovereign.tenova.io/guides map procedures to each framework's specific requirements.

Summary Sheet

Record the assessment result for each workpaper entry. Use this as the summary page for audit file documentation.