Strong Authentication
Specification
Define, implement and evaluate processes, procedures and technical measures for authenticating access to systems, application and data assets, including multifactor authentication for at least privileged user and sensitive data access. Adopt digital certificates or alternatives which achieve an equivalent level of security for system identities.
Threat coverage
Architectural relevance
Lifecycle
Data collection, Resource provisioning
Design, Supply Chain, Guardrails
Validation/Red Teaming
Orchestration, AI Services supply chain
Operations, Maintenance
Archiving, Data deletion, Model disposal
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
Shared Application Provider-AI Customer (Shared AP-AIC)
The AP and AIC both share responsibility and accountability 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 offer and consume.
Implementation guidelines
Auditing guidelines
1. Verify cloud console and management APIs enforce MFA and hardware-backed credentials. 2. Confirm authentication enforcement across all IAM roles with model/data access privileges. 3. Ensure that service-to-service authentication (e.g., between AI pipeline components) uses workload identity federation or OIDC tokens. 4. Validate logging of all authentication events and support for anomaly-based detection. 5. Confirm alignment of authentication mechanisms with regulatory compliance standards (e.g., NIST SP 800-63B). From CCM: 1. Determine if processes, procedures, and technical measures for authenticating access to systems, applications and sensitive data are defined and maintained. 2. Determine if processes, procedures, and technical measures for authenticating access to systems, applications and sensitive data include organization-defined requirements for specific use cases of multifactor authentication, digital certificates and/or alternative security measures. 3. Determine if processes, procedures, and technical measures for authenticating access to systems, applications and sensitive data are implemented and consistently followed in practice.
Standards mappings
42001: A.2.3 - Alignment with other organizational policies 42001: A.2.4 - Review of the AI policy 27001: A.5.1 - Policies for information security 27001:A.5.17 - Authentication information
Addendum
N/A
Article 9 Article 10 Article 15 Article 17 Annex IV
Addendum
MFA Requirement, Digital Certificate Guidance, Authentication Governance, Credential Lifecycle Controls, System-to-System Authentication, Evaluation/Audit of Authentication Controls
No Mapping
Addendum
No (explicit/implicit) reference to the requirement of implementing strong authentication methods for the access to systems, applications, and data assets—let alone to the definition, implementation, and/or evaluation of related processes and procedures—is made in the NIST AI 600-1 standard.
C4 SR-06 C5 IDM-09 C5 PSS-05
Addendum
N/A
AI-CAIQ questions (2)
Are processes, procedures, and technical measures defined, implemented, and evaluated for authenticating access to systems, applications, and data assets, including multifactor authentication for at least privileged user and sensitive data access?
Are digital certificates or alternatives adopted that achieve an equivalent level of security for system identities?