Claim · 2024-07 · publication · Stated in source · Supported

NIST AI 800-1 (initial public draft, 2024) states that it builds on the AI Risk Management Framework in identifying practices to map, measure, manage and govern misuse risks from foundation models.

One recorded claim. The claim panel gives its qualification, the source passages with their place in each source, and how it was checked.

What it connects

NIST AI 800-1 (initial public draft): Managing Misuse Risk for Dual-Use Foundation Models → attributes to → Artificial Intelligence Risk Management Framework (AI RMF 1.0)

Where it appears

No collection page holds this claim. It is listed with its records in the explorer.

Claim and evidence

NIST AI 800-1 (initial public draft): Managing Misuse Risk for Dual-Use Foundation Modelsattributes to ↓Artificial Intelligence Risk Management Framework (AI RMF 1.0)

Machine-checked, not reviewed by an editorStated in sourceSupported

Supporting evidence: primary · 1 source

Subject version: Initial public draft (July 2024) · Published 2024-07 · Effective date not established
Date: 2024-07 · publication Records dated 2024 →
Kind of attribution: Builds on the work

Scope and limitsThe issuing agency's statement about its own guidance series; not evidence of adoption by developers or of how closely the draft follows the framework.

The evidence 01

primary sourceSupports the claim

NIST AI 800-1 Initial Public Draft: Managing Misuse Risk for Dual-Use Foundation Models (July 2024)

National Institute of Standards and Technology · 2024-07

Archived copy, captured 2024-07-27: NIST AI 800-1 Initial Public Draft: Managing Misuse Risk for Dual-Use Foundation Models (July 2024)

Cite the original source

Cite the original document, not Selekoa. Check these details against it.

Source excerpt

“Building on the AI Risk Management Framework,3 this document identifies best practices to map, measure, manage, and govern misuse risks from foundation models”

Location in source PDF p. 5, §1 Introduction, with note 3

Machine-checked · 2026-10-31

Source details and check notes

Authors: U.S. AI Safety Institute (NIST)
Version: Retrieved on 2026-10-27 (SHA-256 30ced091493af421d454ca138a3496a39b8c6079f74223e868325318ffa767e4). The cross-family check of 2026-10-28 opened the Internet Archive capture linked here and matched the quoted wording in it, the release-period expression (decision 9); a capture shows only what the archive retrieved that day. Publisher as printed on the inspected expression: National Institute of Standards and Technology (U.S. AI Safety Institute).
Canonical address: Open the canonical source ↗
Accessed: 2026-10-27
Language: English (en)
Archive copy: Open archived copy, captured 2024-07-27: NIST AI 800-1 Initial Public Draft: Managing Misuse Risk for Dual-Use Foundation Models (July 2024). An archive copy shows only what the archive retrieved on 2024-07-27. It does not prove what the page said earlier, and it can differ from the copy checked on 2026-10-27.
Attribution: U.S. AI Safety Institute (NIST), “NIST AI 800-1 Initial Public Draft: Managing Misuse Risk for Dual-Use Foundation Models (July 2024)”, 2024-07.
Reuse: No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution.
Check notes: Candidate pack passage, key papers (research/key-papers). The quotation (23 words) matched the text retrieved for the candidate pack on 2026-10-28 (research/key-papers/verification.json). Matching ignored differences of whitespace, case, quotation marks, dashes and line-break hyphens, so the source’s typography can differ. A cross-family machine check (2026-10-30, item B025) found the attribution at its locator and in the citing text’s reference entry. No human editorial review.

Status and meaning

Editorial status. Not reviewed by an editor. An exploratory record that no editor has accepted. This status does not say whether a person has read any linked passage. Each evidence record above shows how it was checked.

Relation. A document expressly attributes an argument, concept, term, finding or approach to another work, in its own words; the kind of attribution is recorded. The record is the citing document’s claim. It is not evidence that the cited work originated the idea, that the attribution is accurate, or of influence beyond the passage. Citation alone is recorded as a citation.

Date. Date of the citing text as the dataset records it (July 2024).

Record ID kp-shaping-nist-800-1-nist-rmf