AICM AtlasCSA AI Controls Matrix
BCR · Business Continuity Management and Operational Resilience
BCR-08Cloud & AI Related

Backup

Specification

Periodically perform backups. Ensure the confidentiality, integrity and availability of the backup, and verify restoration from backup for resiliency.

Threat coverage

Model manipulation
Data poisoning
Sensitive data disclosure
Model theft
Model/Service Failure
Insecure supply chain
Insecure apps/plugins
Denial of Service
Loss of governance

Architectural relevance

Physical infrastructure
Network
Compute
Storage
Application
Data

Lifecycle

Preparation

Data storage, Resource provisioning, Team and expertise

Development

Not applicable

Evaluation

Not applicable

Deployment

AI applications, Orchestration

Delivery

Operations, Maintenance, Continuous monitoring

Retirement

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

[All Actors]
1. Core Backup Principles:
a. Implement comprehensive version control for all critical configurations and code.
b. Maintain immutable snapshots with point-in-time recovery capabilities.
c. Create geographically distributed copies with at least one offline storage location.
d. Establish clear boundaries defining backup responsibilities between entities.
e. Document dependencies that affect restoration sequences and procedures.

2. Implementation Methodology:
a. Deploy automated daily snapshots for frequently changing components.
b. Implement weekly full backups capturing complete system states.
c. Create monthly archives stored in physically separate locations.
d. Structure backups to support rapid retrieval of specific components.
e. Maintain metadata linking related assets for coordinated recovery.

3. Data Security:
a. Encrypt all backup data both in transit and at rest.
b. Implement least-privilege access controls for backup management.
c. Establish separation between production and backup infrastructure.
d. Apply appropriate classification and handling standards to backup media.

4. Verification & Validation:
a. Conduct automated integrity checks immediately after backup creation.
b. Conduct quarterly(at least) recovery exercises in isolated environments.
c. Validate cross-entity restoration through coordinated testing.

5. Recovery Documentation:
a. Document step-by-step restoration procedures for various scenarios.
b. Establish clear prioritization frameworks for sequential recovery.

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

ISO 42001No Gap
42001: A.4.3 (Data resources)
27001: A.8.13 (Information backup)
Addendum

N/A

EU AI ActPartial Gap
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.

NIST AI 600-1Partial Gap
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.

BSI AIC4No Gap
C4 RE-06
C5 OPS-06
OPS-07
OPS-08
Addendum

N/A

AI-CAIQ questions (2)

BCR-08.1

Are backups periodically performed?

BCR-08.2

Is the confidentiality, integrity and availability of the backup, ensured and data restoration from backup verified for resiliency?