Key Inventory Management
Specification
Define, implement and evaluate processes, procedures and technical measures in order for the key management system to track and report all cryptographic materials and changes in status, which include provisions for legal and regulatory requirements.
Threat coverage
Architectural relevance
Lifecycle
Data collection, Data curation, Data storage
Training
Evaluation, Validation/Red Teaming, Re-evaluation
Orchestration, AI Services supply chain, AI applications
Operations, Maintenance, Continuous monitoring, Continuous improvement
Archiving, Data deletion, Model disposal
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 ensure the key management system can track and report all cryptographic materials and changes in key status. 2. Confirm that the CSP’s key management system maintains a complete and up-to-date inventory of all cryptographic keys and materials in scope, including key attributes (e.g., type, status, owner, lifecycle stage, algorithm) and usage context. 3. Review whether the inventory includes all cryptographic materials used in CSP-managed services, including those supporting encryption of cloud storage, tenant environments, control planes, and AI-related infrastructure. 4. Validate that the system automatically logs changes in key status (e.g., creation, activation, revocation, suspension, compromise, destruction) with timestamps and source identifiers. 5. Confirm that access to the key inventory system is controlled through role-based access policies and that only authorized personnel can view or modify records. 6. Review archival and retention procedures for historical key metadata to ensure they meet CSP internal policy, contractual obligations, and legal or regulatory requirements. 7. Verify that keys associated with AI-enabling services (e.g., encrypted inference logs, prompt routing, or tenant-specific AI processing environments) are represented and tracked within the inventory system. 8. Confirm that the CSP employs monitoring, alerting, or anomaly detection mechanisms to identify unexpected key lifecycle events (e.g., unauthorized revocation, premature destruction). 9. Validate that periodic internal reviews or audits are performed to ensure completeness, accuracy, and consistency of the key inventory system across cloud service boundaries. 10. Review whether the CSP coordinates key inventory and lifecycle information with upstream providers (if applicable) and downstream entities (e.g., APs, AICs) where shared, inherited, or delegated key responsibilities exist. From CCM: 1. Examine if the organization has defined the key management processes. 2. Review the processes for key lifecycle management (creation, rotation, storage, disposal) with respect to organization and external (regulatory) requirements. 3. Evaluate if the processes and procedures for change management of key management systems provide an overall traceability of lifecycle steps.
Standards mappings
No Mapping for ISO 42001 ISO 27001: A.8.24 A.12.4.1 ISO 27002: 8.24 12.4.1
Addendum
ISO 42001 lacks this detailed requirement for comprehensive tracking and reporting of cryptographic materials in AI systems. Add a control requiring AI systems to define, implement, and evaluate processes, procedures, and technical measures for the key management system to track and report all cryptographic materials and their status changes, incorporating provisions for legal and regulatory requirements. This addresses the gap in ISO 42001:2023’s lack of specific cryptographic tracking and reporting mandates, enhancing ISO 27001 (A.8.24, A.12.4.1) and ISO 27002 (8.24, 12.4.1) with AI-specific inventory and status management
No Mapping
Addendum
Cover the AICM control.
No Mapping
Addendum
No (explicit/implicit) reference to requirements in the domain of key inventory management is made in the NIST AI 600-1 standard.
CRY-04
Addendum
N/A
AI-CAIQ questions (1)
Are key management system processes, procedures, and technical measures defined, implemented, and evaluated to track and report all cryptographic materials and status changes including provisions for legal and regulatory requirements?