IAM-15Cloud & AI Related

Passwords and Secrets Management

Specification

Define, implement and evaluate processes, procedures and technical measures for the secure management of passwords and other secrets.

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, Guardrails, Supply Chain

Evaluation

Validation/Red Teaming

Deployment

AI Services supply chain, Orchestration

Delivery

Maintenance, Operations

Retirement

Not applicable

Ownership / SSRM

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

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

1. Define and enforce password policies that align with industry standards (e.g., NIST SP 800-63, ISO/IEC 27001), including minimum length, complexity, expiration, and reuse limits.

2. Implement strong hashing algorithms (e.g., bcrypt, Argon2) and salting practices to securely store passwords.

3. Prohibit password sharing, hardcoding in codebases, or storing credentials in plain text across all AI and infrastructure components.

4. Require multi-factor authentication (MFA) for all privileged and sensitive access accounts.

5. Implement privileged access tools such as password vaults that securely store, rotate, and manage passwords. These tools should support automatic password generation, expiry, and access logging.

6. Conduct regular password audits to detect weak, default, or compromised passwords across environments.

7. Enforce secure password reset and recovery processes, including identity verification and logging of all reset activities.

8. Use secrets management tools to securely handle passwords in code, pipelines, or deployment configurations.

9. Educate users and administrators on secure password hygiene as part of access management training.

Auditing guidelines

1. Confirm all infrastructure secrets (SSH keys, service tokens) are managed using a centralized vault.

2. Verify policy mandates encryption and strict access control for all stored passwords.

3. Validate the cloud IAM system enforces key-based access rather than passwords for APIs.

4. Ensure logs are collected for secret creation, access, and deletion events.

5. Confirm alerts are triggered on secret misuse or exposure.

From CCM:
1. Determine if processes, procedures, and technical measures for the secure management of passwords are defined.
2. Determine if processes, procedures, and technical measures for the secure management of passwords 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.8.5 - Secure authentication

Addendum

N/A

EU AI ActNo Gap

Article 9
Article 11
Article 15
Article 16
Article 29

Addendum

N/A

NIST AI 600-1Full Gap

No Mapping

Addendum

No (explicit/implicit) reference to the requirement set by the AICM control is made in the NIST AI 600-1 standard.

BSI AIC4No Gap

C4 SR-06
C5 IDM-08
C5 IDM-09

Addendum

N/A

AI-CAIQ questions (1)

IAM-15.1

Are processes, procedures, and technical measures defined, implemented, and evaluated for the secure management of passwords and other secrets?