Transaction/Activity Logging
Specification
Log and monitor key lifecycle management events to enable auditing and reporting on usage of cryptographic keys.
Threat coverage
Architectural relevance
Lifecycle
Data storage
Training
Re-evaluation
Orchestration, AI Services supply chain, AI applications
Operations, Maintenance, Continuous monitoring, Continuous improvement
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 Model Provider-Orchestrated Service Provider (Shared MP-OSP)
The MP and OSP 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
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.
Implementation guidelines
Auditing guidelines
1. Inquiring with Control Owners 1.1 Conduct interviews with personnel responsible for logging and monitoring key lifecycle management events for cloud infrastructure to understand their processes for capturing, analyzing, and reporting on cryptographic key usage for customer data protection and infrastructure security. Verify their understanding of key lifecycle event logging requirements for cloud operations, monitoring procedures for encryption keys protecting customer workloads, and reporting capabilities that enable auditing and compliance oversight of cryptographic key management activities in AI processing infrastructure. 2. Inspecting Records and Documents 2.1 Verify that cryptographic key usage for cloud infrastructure data encryption, customer workload protection, and compute resource security is logged by the infrastructure management systems. 2.2 Confirm logs include timestamped records of key creation, use, rotation, and destruction for cloud infrastructure operations, customer data protection, and tenant isolation security. 2.3 Ensure visibility into key usage by different cloud infrastructure components, compute cluster services, and customer tenant systems. 2.4 Validate alerts are generated on suspicious or unauthorized key operations affecting cloud infrastructure security or customer data protection. 2.5 Check alignment with internal policy for lifecycle monitoring of keys used within cloud infrastructure for customer isolation and service availability protection. 2.6 Review SIEM or monitoring tool integrations that centralize and analyze cloud infrastructure key-related activities and customer protection events. 2.7 Confirm audit trails exist for every critical key management operation supporting cloud infrastructure functionality and customer data security. 2.8 Examine reporting capabilities and procedures for generating cloud infrastructure key lifecycle management reports to support customer compliance and infrastructure security auditing requirements. 2.9 Review log retention policies and practices to ensure cloud infrastructure key lifecycle event records are maintained for customer protection and regulatory compliance timeframes. 2.10 Validate that key lifecycle monitoring covers all cloud infrastructure cryptographic operations including customer data encryption, compute security, and infrastructure backup protection activities. 2.11 Verify cloud KMS and HSM services generate logs for all key operations (create, use, rotate, delete). 2.12 Confirm customer access to logs through secure APIs or dashboards. 2.13 Review policies ensuring that all key usage is auditable and traceable to specific identities. 2.14 Check real-time alerting is in place for abnormal or failed key transactions. 2.15 Ensure audit logs support chain-of-custody for regulatory compliance. 2.16 Confirm backup and retention policies preserve transaction logs for cryptographic events. 2.17 Validate internal reviews of key usage logs are conducted regularly.
Standards mappings
No Mapping for ISO 42001 ISO 27001 8.24 ISO 27001 9.1 ISO 27001 9.2
Addendum
No ISO 42001 control maps to LOG-11 topic.
No Mapping
Addendum
The EU AI Act does not provide for the monitoring of the use of encryption keys and/or cryptographic operations.
MP-2.3-003
Addendum
Specifically requiring lifecycle management events.
C4 DM-03 C4 RE-02 C5 CRY-04
Addendum
N/A
AI-CAIQ questions (1)
Are key lifecycle management events logged and monitored to enable auditing and reporting on cryptographic keys' usage?