Customers' Approval for Agreed Privileged Access Roles
Specification
Define, implement and evaluate processes and procedures for customers to participate, where applicable, in the granting of access for agreed, high risk (as defined by the organizational risk assessment) privileged access roles.
Threat coverage
Architectural relevance
Lifecycle
Data storage, Data collection
Design, Supply Chain
Validation/Red Teaming
Orchestration, AI Services supply chain, AI applications
Operations, Maintenance
Archiving, Data deletion, Model disposal
Ownership / SSRM
PI
Shared Application Provider-AI Customer (Shared AP-AIC)
The AP and AIC both share responsibility and accountability 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 offer and consume.
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)
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.
Application
Owned by the Application Provider (AP)
The Application Provider (AP) is responsible 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. The AP is responsible and accountable for the implementation of the control within its own infrastructure/environment. If the control has downstream implications on the users/customers, the AP is responsible for enabling the customer and/or upstream partner in the implementation/configuration of the control within their risk management approach. The AP is accountable for carrying out the due diligence on its upstream providers (e.g MPs, Orchestrated Services) to verify that they implement the control as it relates to the service/product develop and offered by the AP. These providers build and offer end-user applications that leverage generative AI models for specific tasks such as content creation, chatbots, code generation, and enterprise automation. These applications are often delivered as software-as-a-service (SaaS) solutions. These providers focus on user interfaces, application logic, domain-specific functionality, and overall user experience rather than underlying model development. Example: OpenAI (GPTs,Assistants), Zapier, CustomGPT, Microsoft Copilot (integrated into Office products), Jasper (AI-driven content generation), Notion AI (AI-enhanced productivity tools), Adobe Firefly (AI-generated media), and AI-powered customer service solutions like Amazon Rufus, as well as any organization that develops its AI-based application internally.
Implementation guidelines
Auditing guidelines
1. Ensure that customer-defined roles are honored and not overridden by platform-wide roles. 2. Verify policies requiring approval workflows for infrastructure-level privileged roles. 3. Confirm logs exist for all privileged role assignment actions. 4. Validate escalation paths and emergency access controls are appropriately authorized. 5. Check role lifecycle governance is in place across cloud tenants. From CCM: 1. Determine if processes and procedures for customers to participate, where applicable, in the granting of access for agreed, high risk (as defined by the organizational risk assessment) privileged access roles are defined, implemented and consistently followed in practice.
Standards mappings
42001: A.2.3 - Alignment with other organizational policies 42001: A.2.4 - Review of the AI policy 27001: A.5.1 - Policies for information security 27001: 6.1 - Actions to address risks and opportunities 27001: 8.1 - Operational planning and control 27001: A.5.15 - Access control 27001: A.5.19 - Information security in supplier relationships
Addendum
N/A
Article 9 Article 10 Article 23 Annex IV
Addendum
1. Evidence of Consumer Approval: Verify that consumer approval was obtained for AI provider requests requiring elevated permissions, particularly for training or deploying sensitive models. 2. Include procedural or contractual linkage to external party access governance.
No Mapping
Addendum
No (explicit/implicit) reference to the possibility of allowing AICs' participation in the approval of previously-defined and agreed-upon policies related to privileged access roles, let alone to the requirement of defining, implementing, and evaluating processes and procedures regulating such participation, is made in the NIST AI 600-1.
C5 IMD-06
Addendum
No C4 control speaks to IAM-11 topic of customer access.
AI-CAIQ questions (1)
Are processes and procedures defined, implemented, and evaluated for customers to participate, where applicable, in granting access for agreed high-risk (as defined by the organizational risk assessment) privileged access roles?