HRS-10Cloud & AI Related

Non-Disclosure Agreements

Specification

Identify, document, and review, at planned intervals, requirements for non-disclosure/confidentiality agreements reflecting the organization's needs for the protection of data and operational details.

Threat coverage

Model manipulation

Data poisoning

Sensitive data disclosure

Model theft

Model/Service Failure

Insecure supply chain

Insecure apps/plugins

Denial of Service

Loss of governance

Architectural relevance

Physical infrastructure

Network

Compute

Storage

Application

Data

Lifecycle

Preparation

Team and expertise

Development

Supply Chain

Evaluation

Not applicable

Deployment

AI Services supply chain

Delivery

Not applicable

Retirement

Not applicable

Ownership / SSRM

Shared Cloud Service Provider-Model Provider (Shared CSP-MP)

The CSP and MP are jointly responsible and accountable for the design, development, implementation, and enforcement of the control to mitigate security, privacy, or compliance risks associated with Large Language Model (LLM)/GenAI technologies in the context of the services or products they develop and offer.

Model

Owned by the Model Provider (MP)

The model provider (MP) designs, develops, and implements the control as part of their services or products to mitigate security, privacy, or compliance risks associated with the Large Language Model (LLM). Model Providers are entities that develop, train, and distribute foundational and fine-tuned AI models for various applications. They create the underlying AI capabilities that other actors build upon. Model Providers are responsible for model architecture, training methodologies, performance characteristics, and documentation of capabilities and limitations. They operate at the foundation layer of the AI stack and may provide direct API access to their models. Examples: OpenAI (GPT, DALL-E, Whisper), Anthropic(Claude), Google(Gemini), Meta(Llama), as well as any customized model.

Orchestrated

Shared Cloud Service Provider-Model Provider (Shared CSP-MP)

Application

Shared across the supply chain

Shared control ownership refers to responsibilities and activities related to LLM security that are distributed across multiple stakeholders within the AI supply chain, including the Cloud Service Provider (CSP), Model Provider (MP), Orchestrated Service Provider (OSP), Application Provider (AP), and Customer (AIC). These controls require coordinated actions, communication, and governance across all involved parties to ensure their effectiveness.

Implementation guidelines

[All Actors]
1. Create NDA templates to meet the security, privacy, ethics and regulatory needs of the organization. The agreement should include: a. Clear information on protected information b. Duration of the agreement c. Parties involved and ownership d. Responsibilities of each party e. Definitions f. Obligations g. Exclusions h. Restrictions on unauthorized access i. Restrictions on unauthorized usage j. Data destruction terms k. Breach consequences.

2. Periodically review them to ensure they remain effective and relevant, reflect changes in business operations, adapt to technological advances, ensure compliance with regulations, and incorporate feedback and lessons learned. 

3. Mandatory NDA and confidentiality training should be provided to all stakeholders. 

4. Employees, contractors, and interns should be required to sign the NDA during hiring and onboarding, before accessing sensitive information, and after employment ends, depending on the specific terms outlined in the agreement. 

5. NDAs should be enforced before sharing confidential information with suppliers and vendors, during partnerships and collaborations, before research and development, during mergers and acquisitions, and before product launches.

Auditing guidelines

1. Evaluate whether the Cloud Service Provider has clearly defined and documented its non-disclosure and confidentiality requirements, with specific focus on protecting hosted data, virtual infrastructure, and customer workloads; ensuring confidentiality of customer information, metadata, and service usage patterns; and controlling third-party access, including subcontractors, integrations, and managed services, through contractual and technical safeguards.

2. Confirm that these non-disclosure and confidentiality agreements are reviewed at scheduled intervals, ensuring they comply with internal policies and applicable legal/regulatory standards; adapt to evolving technologies, threat landscapes, and service offerings; and undergo timely updates and formal re-approval as needed.

Standards mappings

ISO 42001No Gap

42001: A.2.3 Alignment with other organizational policies
27001: A.6.2 Terms and conditions of employment
27001: A.6.6 Confidentiality or non-disclosure agreements Control
27002: 6.2 Terms and conditions of employment
27002: 6.6 Confidentiality or non-disclosure agreements Control

Addendum

N/A

EU AI ActFull Gap

No Mapping

Addendum

NIST AI 600-1No Gap

MP-4.1-003

Addendum

N/A

BSI AIC4No Gap

HR-06

Addendum

N/A

AI-CAIQ questions (1)

HRS-10.1

Are requirements for non-disclosure/confidentiality agreements reflecting organizational data protection needs and operational details identified, documented, and reviewed at planned intervals?