AICM AtlasCSA AI Controls Matrix
IAM · Identity & Access Management
IAM-14Cloud & AI Related

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

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 collection, Resource provisioning

Development

Design, Supply Chain, Guardrails

Evaluation

Validation/Red Teaming

Deployment

Orchestration, AI Services supply chain

Delivery

Operations, Maintenance

Retirement

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

[ALL Actors - AICM - CSP]
1. Authentication Management: 
i. A centralized authentication system that can manage identities, authentication credentials, and access control permissions across all AI service components should be implemented 
ii. Users that require privileged access (e.g.,administrators and IT staff) should be identified to establish stricter authentication measures 
iii. Specific authentication factors and technical measures should be defined and implemented for each access level, including MF A for privileged identities and sensitive data access 

2. MFA Usage Scope: 
i. Sensitive Data Access: Strong authentication should be enforced at all user accounts, requiring a combination of something the user: Knows (such as a password); Has (such as a mobile device or token); Is (such as biometrics); MFA for all users should be enabled, including non-privileged users who access sensitive data. 
ii. Administrative Access: MFA should be enforced for all administrative access (e.g., access to management consoles, AI lifecycle components, and other critical AI infrastructure elements). If MFA cannot be implemented in a particular situation, the risk should be formally registered 
iii. Third-Party Access: MFA should be enforced for third-party access, such as through APIs or AI services, to protect against unauthorized access by external entities.

3. Second Factor Authentication: Second factor authentication should be leveraged in addition to passwords to add an extra layer of security by requiring a second factor of: 
i. Time-Based One-Time Passwords (TOTPs) to allow users to generate temporary codes via email or a smartphone app synchronized with an authentication server. 
ii. Hardware tokens or USB keys that generate unique codes for authentication. 

4. Passwordless Authentication: Passwordless authentication solutions should be implemented that replace traditional passwords with secure alternatives such as phishing-resistant MFA and FIDO2-compliant security keys or biometrics. 

5. Authentication Credentials Protection: All authentication credentials should be transmitted through secure channels (e.g., TLS/HTTPS) and never stored in plaintext but rendered unreadable in storage on all system components using strong cryptography. 

6. Authentication Credentials Change Approval: Requests to change or modify authentication credentials (i.e., performing password resets, provisioning new tokens, generating new keys) should be approved only after verification of the user’s identity. 

7. Continuous User Authentication (CUA): CUA should be leveraged as a method of maintaining user authentication throughout their session, requiring periodic reauthentication to ensure that the user is still authorized and has not been compromised. 

8. Single Sign-On (SSO): SSO should be implemented for accessing multiple services and applications with a single login credential to simplify the authentication process for users. 

9. Digital Certificates: Digital certificates should be utilized for authentication and authorization purposes, especially for system identities. 

10. CRL and OCSP Checks: Certificate Revocation Lists (CRLs) and Online Certificate Status Protocol (OCSP) checks should be implemented to verify the validity and revocation status of digital certificates. 

11. Certificate Lifecycle: The lifecycle of digital certificates should be securely managed including issuance, renewal, and revocation. 

12. Certificate Storage: Digital certificates should be stored securely, using encryption and access control mechanisms. 

13. Authentication Usage Monitoring: 
i. All authentication mechanisms and enabled features should be properly installed, configured, and authentication logs monitored for the desired and expected results. 
ii. MFA, credentials, and digital certificate usage patterns should be continuously monitored and reviewed to proactively identify potential vulnerabilities or compromises. 

[All Actors]
1. Implement risk-based authentication controls that evaluate host and user risk (examples: IP reputation and requesting device posture).

2. Enforce the use of phish-resistant MFA (Hardware Key, Certificate Based) for high-risk systems where possible.

3. Provide self-service MFA enrollment for AI service users, supporting FIDO2 security keys, TOTP apps, biometrics, and more.

[OSP & AP]
1. Support secure machine and Agent-Based system authentication such as certificate and token based.

2. Support integration of AIC federated authentication methods (OIDC/OAuth).

3. Disable the usage of insecure protocols and methods by default.

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

ISO 42001No Gap
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

EU AI ActPartial Gap
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

NIST AI 600-1Full Gap
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.

BSI AIC4No Gap
C4 SR-06
C5 IDM-09
C5 PSS-05
Addendum

N/A

AI-CAIQ questions (2)

IAM-14.1

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?

IAM-14.2

Are digital certificates or alternatives adopted that achieve an equivalent level of security for system identities?