AICM AtlasCSA AI Controls Matrix
I&S · Infrastructure Security
I&S-07Cloud & AI Related

Migration to Hosted Environments

Specification

Use secure and encrypted communication channels when migrating servers, services, applications, or data to hosted environments. Such channels must include only up-to-date and approved protocols.

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

Development

Design

Evaluation

Not applicable

Deployment

Orchestration, AI applications

Delivery

Operations

Retirement

Not applicable

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 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

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. Define Secure Migration Standards.

2. Establish encryption policies for data migration based on NIST and CIS guidelines.

3. Ensure that all cloud migrations follow an approved security framework.

4. Approved Secure Protocols.

5. Use only industry-standard encrypted channels such as TLS 1.2+, IPSec, and SSH.

6. Implement end-to-end encryption for sensitive data transfers.

7. Access Control and Monitoring.

8. Ensure only authorized personnel can initiate migration processes.

9. Implement logging and monitoring mechanisms to track migration activities.

Auditing guidelines

1. Verify the Cloud Service Provider (CSP) documented migration procedures explicitly require secure, encrypted communication channels.

2. Confirm encryption mechanisms adhere to current security standards.(e.g., supporting processing, storage, and network services).
 
3. Check records documenting secure migration processes.

4. Ensure risk assessments conducted before migrating sensitive data to cloud environments.

5. Validate compliance checks post-migration to confirm the security and integrity of data.

6. Confirm clearly defined roles and responsibilities for migration activities.

7. Verify documented incident response plans for issues arising during cloud migration.

Standards mappings

ISO 42001Partial Gap
No Mapping for ISO 42001
ISO/IEC 27001:2022 - A.5.23
27002: 8.25
27002: 8.9
27002: 10.1
Addendum

Contrarily to the AICM control that is characterized by an increased level of specificity and technicality, the ISO/IEC 27001 framework establishes more general requirements that may be interpreted as encompassing the aspects tackled in the control (e.g., no focus on migration to cloud environments and on the type of communication channels to be used during it). There is no mapping to ISO 42001.

EU AI ActFull Gap
No Mapping
Addendum

Full control would have to be added because the EU AI Act does not address these concerns. Add, "Use secure and encrypted communication channels when migrating servers, services, applications, or data to cloud environments. Such channels must include only up-to-date and approved protocols."

NIST AI 600-1Full Gap
No Mapping
Addendum

NIST AI 600-1 is missing reference to encrypted communications channels.

BSI AIC4No Gap
C4 SR-06
C5 CRY-02
C5 COS-05
Addendum

N/A

AI-CAIQ questions (2)

I&S-07.1

Are secure and encrypted communication channels used when migrating servers, services, applications or data to hosted environments?

I&S-07.2

Are such channels including only up-to-date and approved protocols?