I&S-04Cloud & AI Related

OS Hardening and Base Controls

Specification

Harden host and guest OS, hypervisor or infrastructure control plane, according to their respective best practices, and supported by technical controls, as part of a security baseline.

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 storage, Resource provisioning

Development

Training

Evaluation

Not applicable

Deployment

Orchestration, AI Services supply chain, AI applications

Delivery

Operations, Maintenance, Continuous monitoring, Continuous improvement

Retirement

Data deletion

Ownership / SSRM

Shared across the supply chain

Shared control ownership refers to responsibilities and activities related to LLM security that are distributed across multiple stakeholders within the AI supply chain, including the Cloud Service Provider (CSP), Model Provider (MP), Orchestrated Service Provider (OSP), Application Provider (AP), and Customer (AIC). These controls require coordinated actions, communication, and governance across all involved parties to ensure their effectiveness.

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 Orchestrated Service Provider-Application Provider (Shared OSP-AP)

The OSP and AP 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.

Implementation guidelines

[All Actors]
1. Establish OS Hardening Standards.

2. Apply CIS benchmarks and vendor security guidelines for host and guest OS.

3. Implement least privilege principles and disable unnecessary services.

4. Hypervisor and Control Plane Security.

5. Secure hypervisor configurations and implement logging for hypervisor activity.

6. Enforce hypervisor patching and vulnerability management policies.

7. Automation and Compliance Monitoring.

8. Deploy automated scripts to enforce security baselines.

9. Continuously monitor compliance with configuration management tools.

Auditing guidelines

1. Examine documented policies and hardening security baselines alignment with business needs and industry best practices.

2. Determine if appropriate technical controls are in place to enforce and verify system hardening (e.g., CIS Cloud Benchmarks, AWS and Azure Security Baselines).

3. Verify regular assessments conducted against established security baselines, ensuring promptly addressing any identified deviations or vulnerabilities.

4. Verify an annual review of hardening configurations for hosts, guest OS, and hypervisors, ensuring documented results are reviewed and approved by authorities.

5. Determine if emerging threats are monitored and hardening procedures are updated accordingly, ensuring all changes are systematically documented and approved.

Standards mappings

ISO 42001Partial Gap

No Mapping for ISO 42001
ISO/IEC 27001:2022 - A.8.9 (Configuration management)

Addendum

Contrarily to the AICM control that provides an increased level of technical details, the ISO/IEC 27001 framework establishes more general security principles and requirements that encompass the aspects tackled in the control.

EU AI ActPartial Gap

Article 15

Addendum

Full control would have to be added because the EU AI Act does not address these concerns. Add, "Harden host and guest OS, hypervisor or infrastructure control plane according to their respective best practices, and supported by technical controls, as part of a security baseline."

NIST AI 600-1Full Gap

No Mapping

Addendum

NIST AI 600-1 should include references to the hardening systems or infrastructure that support GenAI.

BSI AIC4No Gap

C4 SR-06
C5 OPS-23

Addendum

N/A

AI-CAIQ questions (1)

I&S-04.1

Are the host and guest OS, hypervisor, or infrastructure control plane, being hardened according to their respective best practices and supported by technical controls as part of a security baseline?