Backup
Specification
Periodically perform backups. Ensure the confidentiality, integrity and availability of the backup, and verify restoration from backup for resiliency.
Threat coverage
Architectural relevance
Lifecycle
Data storage, Resource provisioning, Team and expertise
Not applicable
Not applicable
AI applications, Orchestration
Operations, Maintenance, Continuous monitoring
Archiving
Ownership / SSRM
PI
Owned by the Cloud Service Provider (CSP)
The Cloud Service Provider (CSP) is responsible for the design, development, implementation, and enforcement of the control to mitigate security, privacy, or compliance risks associated with cloud computing (processing, storage, and networking) technologies in the context of the services or products they develop and offer. The CSP is responsible and accountable for implementing the control within its own infrastructure/environment. The CSP is responsible for enabling the customer and/or upstream partner to implement/configure the control within their risk management approach. The CSP is accountable for ensuring that its providers upstream implement the control related to the service/product developed and offered by the CSP.
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. Examine the policy for identifying data for which a backup is required. 2. Examine the requirements for the security of such backups. 3. Evaluate the effectiveness of the backup and restore. 4. Verify implementation of infrastructure-level backup mechanisms through configuration reviews and system logs, confirming automated execution according to defined schedules. 5. Assess encryption and access control mechanisms protecting backup confidentiality, including encryption of backup data at rest and in transit, key management procedures, and identity and access management controls. 6. Review backup storage redundancy and geographic distribution practices to confirm backups are protected from regional disasters or infrastructure failures affecting primary systems. 7. Examine documentation and test results verifying successful restoration procedures, including complete infrastructure recovery tests performed at least annually. 8. Verify monitoring and alerting systems for backup failures, reviewing incident logs and remediation procedures when backup processes encounter errors. 9. Assess backup performance metrics against recovery point objectives (RPOs) to confirm backup frequency aligns with data criticality and business requirements.
Standards mappings
42001: A.4.3 (Data resources) 27001: A.8.13 (Information backup)
Addendum
N/A
Article 15 (1) Article 9 (2) Article 9 (6) Article 17 Annex IV Recital 51
Addendum
Periodically backup data stored in the cloud. Ensure the confidentiality, integrity, and availability of the backup, and verify data restoration from backup for resiliency.
GV-1.5-003 GV-6.2-006
Addendum
Add a new suggested action so that explicit backup requirements are addressed. For example, the action could be to implement and verify a process for the periodic backup of cloud stored data—including restoring tests—to ensure data confidentiality, integrity, and availability.
C4 RE-06 C5 OPS-06 OPS-07 OPS-08
Addendum
N/A
AI-CAIQ questions (2)
Are backups periodically performed?
Is the confidentiality, integrity and availability of the backup, ensured and data restoration from backup verified for resiliency?