HITRUST AI Security Assessment and Certification Specification

Version control of AI assets

HITRUST CSF requirement statement [?] (06.10jAISecSystem.1)

AI assets, including
(1) code to create, train, and/or deploy AI models;
(2) training datasets;
(3) fine-tuning datasets;
(4) RAG datasets (if used);
(5) configurations of pipelines used to create, train, and/or deploy AI models;
(6) code used by language model tools such as agents and plugins (if used); and 
(7) models
are versioned and tracked.

Evaluative elements in this requirement statement [?]
1. Code used to create, train, and/or deploy AI models is versioned and tracked.
2. Training datasets are versioned and tracked.
3. Fine-tuning datasets are versioned and tracked.
4. RAG datasets versioned and tracked.
5. Configurations of pipelines used to create, train, and/or deploy AI models are versioned and tracked.
6. Code used by language model tools such as agents and plugins is versioned and tracked.
7. AI models are versioned and tracked.


Illustrative procedures for use during assessments [?]

  • Policy: Examine policies related to each evaluative element within the requirement statement. Validate the existence of a written or undocumented policy as defined in the HITRUST scoring rubric.

  • Procedure: Examine evidence that written or undocumented procedures exist as defined in the HITRUST scoring rubric. Determine if the procedures and address the operational aspects of how to perform each evaluative element within the requirement statement.

  • Implemented: Examine evidence that all evaluative elements within the requirement statement have been implemented as defined in the HITRUST scoring rubric, using a sample based test where possible for each evaluative element. Example test(s):
    • For example, evidence that the AI assets listed in the requirement statement are each versioned and tracked (as applicable).

  • Measured: Examine measurements that formally evaluate and communicate the operation and/or performance of each evaluative element within the requirement statement. Determine the percentage of evaluative elements addressed by the organization’s operational and/or independent measure(s) or metric(s) as defined in the HITRUST scoring rubric. Determine if the measurements include independent and/or operational measure(s) or metric(s) as defined in the HITRUST scoring rubric. Example test(s):
    • For example, measures indicate percentage of the organization’s AI assets which are versioned and tracked of total. Reviews, tests, or audits are completed by the organization to measure the effectiveness of the implemented controls.

  • Managed: Examine evidence that a written or undocumented risk treatment process exists, as defined in the HITRUST scoring rubric. Determine the frequency that the risk treatment process was applied to issues identified for each evaluative element within the requirement statement.

Placement of this requirement in the HITRUST CSF [?]

  • Assessment domain: 06 Configuration Management
  • Control category: 10.0 – Information Systems Acquisition, Development, and Maintenance
  • Control reference: 10.j Access Control to Program Source Code

Specific to which parts of the overall AI system? [?]
AI application layer:
  • AI plugins and agents
  • The deployed AI application (Considered in the associated HITRUST e1, i1, or r2 assessment)
AI platform layer
  • The AI platform and associated APIs (Considered in the associated HITRUST e1, i1, or r2 assessment)
  • Model engineering environment and model pipeline

Discussed in which authoritative AI security sources? [?]

Discussed in which commercial AI security sources? [?]
  • Databricks AI Security Framework
    Sept. 2024, © Databricks
    • Where:
      • Control DASF 10: Version data
      • Control DASF 17: Track and reproduce the training data used for ML model training
      • Control DASF 52: Source code control

Control functions against which AI security threats? [?]
Additional information
  • Q: When will this requirement included in an assessment? [?]
    • This requirement will always be added to HITRUST assessments which include the
      Security for AI systems regulatory factor.
    • No other assessment tailoring factors affect this requirement.

  • Q: When is this requirement applicable, and when could it be inapplicable?
    • This requirement applies regardless of the model’s provenance and regardless of the AI system architecture.
    • Element #2 is only applicable when language model tools such as agents or plugins are used.

  • Q: Will this requirement be externally inheritable? [?] [?]
    • Yes, fully. This requirement may be the sole responsibility of the AI platform provider and/or model creator. Or, depending on the AI system’s architecture, only evaluative elements that are the sole responsibility of the AI platform provider and/or model creator apply.