Equipment Identification
Specification
Use equipment identification as a method for connection authentication.
Threat coverage
Architectural relevance
Lifecycle
Not applicable
Not applicable
Not applicable
Not applicable
Operations
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
Auditing guidelines
1. Examine the policy relating to equipment classification and identification. 2. Determine if appropriate methods are implemented. 3. Confirm the existence of a process or procedure to track and maintain a list of appropriate equipment permitted for authorized connections.
Standards mappings
42001: A.2.3 Alignment with other organizational policies 42001: A.6.2.6 AI System Operation and Monitoring 27001: A.8.1 - User endpoint devices 27001: A.8.5 - Secure authentication 27001: A.8.16 - Monitoring activities 27001: A.8.20 - Network security 27002: 8.1 - User endpoint devices 27002: 8.5 - Secure Authentication 27002: 8.16 - Monitoring activities 27002: 8.20 - Network security
Addendum
N/A
No Mapping
Addendum
The EU AI Act should require additional controls in areas such as algorithm testing, data governance, human oversight, and resilience design. Require equipment/device-level authentication. Require assessing risks from unauthorized devices and documenting mitigation controls such as device authentication mechanisms. Document the equipment identification/authentication mechanisms implemented. List approved/authorized device identities and describe how they are managed and updated.
No Mapping
Addendum
Use equipment identification as a method for connection authentication.
AM-06
Addendum
AIC4 mentions different authentication methods (independently if its hard or software authentication)
AI-CAIQ questions (1)
Is equipment identification used as a method for connection authentication?