Key Suspension
Specification
Define, implement and evaluate processes, procedures and technical measures to monitor, review and approve key transitions from any state to/from suspension, which include provisions for legal and regulatory requirements.
Threat coverage
Architectural relevance
Lifecycle
Data storage
Not applicable
Not applicable
AI Services supply chain
Operations, Maintenance, Continuous monitoring
Archiving
Ownership / SSRM
PI
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 Orchestrated Service Provider-Application Provider (Shared OSP-AP)
The OSP and AP 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. Verify that the CSP defines, implements, and evaluates processes, procedures, and technical measures to monitor, review, and approve cryptographic key transitions to and from suspension, including provisions for legal and regulatory requirements. 2. Confirm that the CSP defines acceptable conditions for suspending keys (e.g., incident response, access anomaly, integration failure, cryptographic violation) and includes these conditions in documented suspension procedures. 3. Review whether cryptographic key suspension and reactivation events follow a formal change control or approval workflow that ensures traceability and oversight. 4. Validate that suspended keys are logically disabled from cryptographic operations while remaining intact for potential reactivation, and are segregated from active key stores. 5. Verify that the ability to suspend or resume cryptographic keys is limited to authorized roles or systems, and that separation of duties is enforced. 6. Review whether CSP monitoring tools, logging infrastructure, or automated alerts are used to detect unauthorized or anomalous key suspension events. 7. Verify that key suspension and reactivation actions are logged and auditable, including details such as timestamp, initiating identity, affected key, reason for action, and downstream impact. 8. Confirm that CSP key suspension procedures incorporate applicable legal, contractual, and regulatory requirements (e.g., uptime guarantees, sectoral encryption mandates, or incident containment policies). 9. Validate that suspended keys related to AI workloads (e.g., inference caching, encrypted logging, model access tokens) are subject to the same suspension governance as other service-layer keys. 10. Review whether the CSP’s suspension procedures include coordination with upstream providers or downstream consumers (e.g., APs, AICs) where suspended keys may impact service continuity, encrypted data access, or shared key responsibilities. From CCM: 1. Confirm the existence of processes and procedures to manage the transition state of keys. 2. Review the access and permissions regarding the transition state of keys and confirm that these are restricted to appropriate individuals. 3. Verify that it is possible to modify a key state and suspend/disable keys when required.
Standards mappings
No Mapping for ISO 42001 ISO 27001: A.8.24 ISO 27002: 8.24
Addendum
Add a control mandating AI systems to define, implement, and evaluate processes, procedures, and technical measures to monitor, review, and approve key transitions to/from suspension, including legal and regulatory provisions, addressing ISO 42001:2023’s gap in key state transition management, enhancing ISO 27001 (A.8.24) and ISO 27002 (8.24).
No Mapping
Addendum
Cover the AICM control.
No Mapping
Addendum
No (explicit/implicit) reference is made in the NIST AI 600-1 standard as to the requirement of defining, implementing, or evaluating processes, procedures, and/or technical measures in the domain of key suspension.
CRY-04
Addendum
N/A
AI-CAIQ questions (1)
Are processes, procedures, and technical measures to monitor, review, and approve key transitions (e.g., from any state to/from suspension) defined, implemented, and evaluated including provisions for legal and regulatory requirements?