I&S-03Cloud & AI Related

Network Security

Specification

Monitor, encrypt and restrict communications between environments to only authenticated and authorized connections, as justified by the business. Review these configurations at least annually, and support them by a documented justification of all allowed services, protocols, ports, and compensating controls.

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

Guardrails

Evaluation

Not applicable

Deployment

Orchestration, AI Services supply chain, AI applications

Delivery

Operations, Maintenance, Continuous monitoring

Retirement

Not applicable

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. Define Network Security Framework.

2. Implement network segmentation, firewall controls, and encryption protocols.

3. Align security configurations with ISO 27001, NIST 800-53, and CIS benchmarks.

4. Authentication and Access Controls.

5. Enforce multi-factor authentication for all network access points.

6. Implement zero-trust principles for internal and external communications.

7. Encryption and Secure Communications.

8. Enforce encryption for data-in-transit using TLS 1.2+ and IPsec.

9. Implement certificate management and key rotation policies.

Auditing guidelines

1. Examine network policies and procedures for communication between environments in cloud. 

2. Verify network segmentation to ensure proper isolation between security zones and environments.

3. Determine access controls, protocols, and encryption to secure communication between environments, ensuring that only authenticated and authorized connections are permitted.

4. Verify continuous monitoring of network communications and logging to detect and address unauthorized or unusual activities promptly.

5. Verify regular reviews, at least annually with policies update to align with business needs and evolving threats, ensuring structured record-keeping of changes and approvals.

Standards mappings

ISO 42001Partial Gap

ISO/IEC 27001: A.5.15
A.8.24
A.8.27
A.5.35
ISO/IEC 27002: 8.28
8.7
9.4
5.17
10.1

Addendum

Lacks: - Specific network security - Encryption enforcement - Environment-level controls - Configuration baselines and reviews.

EU AI ActFull Gap

No Mapping

Addendum

Full control would have to be added because the EU AI Act does not address these concerns. Add, "Monitor, encrypt, and restrict communications between environments to only authenticated and authorized connections, as justified by the business. Review these configurations at least annually, and support them by a documented justification of all allowed services, protocols, ports, and compensating controls."

NIST AI 600-1Full Gap

No Mapping

Addendum

No mapping for encryption in NIST AI 600-1.

BSI AIC4No Gap

C4 SR-06
C5 COS-02

Addendum

N/A

AI-CAIQ questions (2)

I&S-03.1

Are communications between environments being monitored, encrypted, and restricted to only authenticated and authorized connections, as justified by the business?

I&S-03.2

Are these configurations reviewed at least annually and supported by a documented justification of all allowed services, protocols, ports, and compensating controls?