Program Foundation
The stage of establishing the foundation of an AI SBOM compliance program. Covers policy, competency, awareness, and scope.
This guide explains, one by one, each requirement of AI System Bill of Materials — Compliance Management Guide for the Supply Chain (Version 1.0), published by the OpenChain AI Work Group. It walks through what verification material each clause requires, how to comply with it, and what samples and tools are ready to use.
This specification carries the same structure as ISO/IEC 5230, the open source license compliance standard — requirements, verification material, and rationale — over into the AI supply chain. It brings into scope not only code but also the licensing and transparency obligations of model weights, training datasets, and the Model Tree.
Author : OpenChain Korea Work Group / CC BY 4.0
All 10 requirements (3.1–3.10) per the specification body have been written. The compare page that positions the standards relative to each other is still being expanded.
The OpenChain specification defines “what must be demonstrated.” This guide fills in “how to achieve it.” Each clause page does more than restate the specification’s requirements — it walks through the actual procedures, samples, tools, and how to handle the parts that tools alone cannot fill.
The content of each clause page falls into two categories.
shall or as verification material.Activities presented alongside a verification material number (e.g., 3.1.1) are
[Specification Requirement]. Enhancements this guide adds, such as automation, tool use, and
intake gates, are [Guide Recommendation].
The original specification’s table of contents and body section numbers are out of sync (the “3.9 AI content review and approval” section listed in the table of contents does not appear in the body, shifting all subsequent numbers down by one). This discrepancy has been reported to the OpenChain AI Work Group. This guide follows the body’s section numbers (3.1–3.10).
The 10 requirements are divided into four phases by implementation priority. Phase 1 establishes the program’s foundation, Phase 2 builds AI-specific compliance processes, Phase 3 puts operational structures in place, and Phase 4 establishes governance.
Goal: Define the program’s scope, establish policy, and secure competence and awareness.
| Done | Verification Material | Description | Detailed Guide |
|---|---|---|---|
| ☐ | 3.4.1 | Program scope statement | 3.4 → |
| ☐ | 3.1.1 | Documented AI SBOM policy | 3.1 → |
| ☐ | 3.1.2 | Policy awareness procedure | 3.1 → |
| ☐ | 3.2.1~3.2.3 | Role list, competence definitions, competence assessment evidence | 3.2 → |
| ☐ | 3.3.1 | Evidence of participant awareness assessment | 3.3 → |
Goal: Build AI-specific licensing, transparency, and SBOM processes that cover not just code but also models, weights, and datasets. This is the area where the AI SBOM Guide expands most on ISO/IEC 5230.
| Done | Verification Material | Description | Detailed Guide |
|---|---|---|---|
| ☐ | 3.5.1 | License obligation review and documentation procedure | 3.5 → |
| ☐ | 3.6.1 | Transparency obligation review procedure | 3.6 → |
| ☐ | 3.9.1 | AI SBOM identification, tracking, review, approval, and archiving procedure | 3.9 → |
| ☐ | 3.9.2 | Records demonstrating procedure compliance | 3.9 → |
Goal: Create a channel for responding to external compliance inquiries, and assign accountability and resources to the program.
| Done | Verification Material | Description | Detailed Guide |
|---|---|---|---|
| ☐ | 3.7.1~3.7.2 | Public inquiry channel, internal response procedure | 3.7 → |
| ☐ | 3.8.1~3.8.5 | Role assignment, resources, legal expertise, remediation procedure | 3.8 → |
Goal: Put in place a governance framework spanning the full AI system lifecycle, and reflect emerging AI regulation.
| Done | Verification Material | Description | Detailed Guide |
|---|---|---|---|
| ☐ | 3.10.1 | AI governance framework and periodic review procedure | 3.10 → |
The body of the AI SBOM Compliance Guide consists of 10 clauses and 19 verification material items in total (by this guide’s verification material numbering).
| Clause | Title | Verification Material | Detail |
|---|---|---|---|
| 3.1 | Policy | 2 items | Go to → |
| 3.2 | Competence | 3 items | Go to → |
| 3.3 | Awareness | 1 item | Go to → |
| 3.4 | Program Scope | 1 item | Go to → |
| 3.5 | License Obligations | 1 item | Go to → |
| 3.6 | Transparency Obligations | 1 item | Go to → |
| 3.7 | Access | 2 items | Go to → |
| 3.8 | Effectively Resourced | 5 items | Go to → |
| 3.9 | AI SBOM | 2 items | Go to → |
| 3.10 | Governance | 1 item | Go to → |
Total: 10 clauses / 19 verification material items
This is an honest breakdown of how far each AI SBOM compliance task is automated by tools today. For “generation,” usable open source tools already exist. Interpreting license obligations and tracking compliance with non-standard licenses, on the other hand, remain the work of people and policy. Each clause page follows this line to distinguish “what a tool handles” from “what a person must fill in.”
| Task | Automation Level | Representative Open Source Tool |
|---|---|---|
| Code/dependency SBOM generation | Mature | cdxgen, Syft |
| AI model/metadata BOM generation | Tools emerging | OWASP AIBOM Generator, cdxgen aibom mode |
| Static analysis of model binaries | Tools emerging | Lab700x AI SBOM Scanner |
| Identifying LLM inference servers and AI packages | Mature | Trivy, Syft |
| SBOM storage and vulnerability monitoring | Mature | Dependency-Track, SW360 |
| Interpreting license obligations, tracking non-standard compliance | Immature (people/policy) | Tool support still developing |
Several tools already generate AI SBOMs automatically. But whether the license fields in a generated BOM are accurate, whether the behavioral use restrictions of non-standard licenses (the RAIL family, the Llama Community License) are respected, and whether obligations propagate downstream without being dropped — a tool cannot automatically guarantee any of this. Policy and human review fill this gap. See 3.5 License Obligations for details.
The installation and use of each tool is covered with execution screens and command output in the Tools section.
AI-SBOM-Compliance/en)The stage of establishing the foundation of an AI SBOM compliance program. Covers policy, competency, awareness, and scope.
The stage of building AI-specific license, transparency, and SBOM processes that extend beyond code to cover models, weights, and datasets.
The stage of establishing a channel to respond to external compliance inquiries and assigning responsibility and resources to the program.
The stage of establishing a governance framework across the full AI system lifecycle and reflecting emerging AI regulations.
Introduces the key features and usage of open source tools that generate and analyze AI SBOMs, with actual execution screens.