GOVERN-3.1 / MAP-5.1 NIST AI Risk Management Framework

Licence / IP scanning on AI output

Demonstrate that the organization scans AI-generated outputs for licensed and copyrighted content prior to production use or publication, and that identified IP risks are reviewed and remediated in accordance with policy.

Description

What this control does

This control applies automated or manual scanning processes to AI-generated content outputs to detect embedded copyrighted material, licensed code snippets, or other intellectual property that may trigger legal or licensing obligations. Scanning occurs before AI outputs are incorporated into production systems, published externally, or integrated into organizational codebases. The control prevents inadvertent IP infringement, reduces supply chain legal risk, and ensures compliance with open-source and proprietary licensing terms when AI models reproduce training data or generate derivative works.

Control objective

What auditing this proves

Associated risks

Risks this control addresses

AI models reproduce verbatim copyrighted code or text from training datasets, exposing the organization to copyright infringement litigation
Generated code contains GPL or other copyleft-licensed snippets, creating unintended obligations to release proprietary source code
AI-generated content includes patented algorithms or methods, triggering patent infringement claims
Outputs embed third-party trademarks or brand identifiers without authorization, resulting in trademark disputes
Lack of scanning allows unlicensed content to enter production systems, later discovered during vendor audits or legal discovery
Developers bypass scanning workflows by directly integrating AI outputs, circumventing IP risk assessments
Scanning tools produce false negatives due to paraphrasing or minor modifications of copyrighted material

Testing procedure

How an auditor verifies this control

Obtain and review the organization's policy or procedure governing IP and license scanning of AI-generated outputs, including scope, frequency, and tooling requirements
Identify all AI systems and models currently generating code, text, images, or other content used in organizational operations or products
Request configuration documentation for automated scanning tools (e.g., license scanners, plagiarism detection, code attribution tools) integrated into AI output workflows
Select a sample of 10–15 recent AI-generated artifacts across different content types and verify scanning logs or reports were generated prior to production integration
Inspect scanning tool output for false positive/negative rates, license classification accuracy, and thresholds triggering human review
Interview engineering or legal staff to confirm remediation workflows when prohibited licenses or copyrighted content are detected
Test one live AI output by submitting it through the scanning process and verify detection, reporting, and escalation occur as documented
Review access controls and approval gates preventing unscanned AI outputs from bypassing the scanning workflow

Evidence required Artefacts include IP scanning policy documents, scanning tool configuration files and integration points, scanning reports or logs for sampled AI outputs with timestamps and results, evidence of remediation actions (e.g., removal, replacement, licensing approvals), and workflow diagrams or CI/CD pipeline configurations showing mandatory scanning gates.

Pass criteria The control passes if all sampled AI outputs were scanned prior to production use, scanning tools are correctly configured and integrated into workflows, detected IP risks were documented and remediated per policy, and bypass mechanisms are effectively prevented.

Where this control is tested

Audit programs including this control

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