AICM AtlasCSA AI Controls Matrix
DCS · Datacenter Security
DCS-06Cloud & AI Related

Assets Cataloguing and Tracking

Specification

Catalogue and track all relevant physical and logical assets located at all of the service providers sites within a secured system. Review and update the catalogue at least annually or upon significant changes.

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

Resource provisioning

Development

Not applicable

Evaluation

Not applicable

Deployment

AI Services supply chain, 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. Maintaining detailed catalogs of physical and digital assets relevant to each entity's role.

2. Documenting dependencies, connections, and data flows between components.

3. Monitoring assets from creation through deployment to retirement.

4. Implementing appropriate protection mechanisms based on asset classification.

5. Ensuring asset management practices support industry frameworks.

Auditing guidelines

1. Examine the policy relating to defining asset location and disposition.

2. Examine the asset registers and determine if they are stored and accessed securely.

Standards mappings

ISO 42001No Gap
42001: A.4.2 Resource documentation
42001: A.4.3 Data resources
42001: A.4.4 Tooling resources
42001: A.4.5 System and computing resources
42001: A.2.3 Alignment with other organizational policies
27001: A.5.9 - inventory of information and other associated assets
27002: 5.9 - Inventory of information and other associated assets
Addendum

N/A

EU AI ActFull Gap
No Mapping
Addendum

Maintain a secured, up-to-date catalog of all relevant physical and logical assets located at all sites where such systems operate. The catalog should be reviewed and updated at least annually, or whenever significant changes occur, and shall be made available to demonstrate compliance.

NIST AI 600-1Full Gap
No Mapping
Addendum

Inventory at all levels needs to be addressed in the NIST AI 600-1.

BSI AIC4No Gap
AM-01
Addendum

N/A

AI-CAIQ questions (2)

DCS-06.1

Are all relevant physical and logical assets located at service provider sites catalogued and tracked within a secured system?

DCS-06.2

Are catalogues reviewed and updated at least annually or upon significant changes?