AICM AtlasCSA AI Controls Matrix
SEF · Security Incident Management, E-Discovery, & Cloud Forensics
SEF-03Cloud & AI Related

Incident Response Plans

Specification

Establish, document, approve, communicate, apply, evaluate and maintain a security incident response plan, which includes but is not limited to: a communication strategy for notifying relevant internal departments, impacted AICs, and other business critical relationships (such as supply-chain) that may be impacted.

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

Development

Guardrails, Supply Chain

Evaluation

Validation/Red Teaming

Deployment

Orchestration, AI Services supply chain, AI applications

Delivery

Operations, Maintenance, Continuous monitoring, Continuous improvement

Retirement

Archiving, Data deletion, Model disposal

Ownership / SSRM

PI

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. Create detailed incident response plans specific to AI workloads, covering detection, containment, eradication, recovery, and post-incident analysis.

2. Include AI-specific threats like prompt injection, model evasion, data poisoning, and output misclassification.

3. Define thresholds and escalation paths for different severity levels, including regulatory breach thresholds.

4. Integrate these plans with enterprise-wide security incident response functions and business continuity processes.

Auditing guidelines

1. Verify the CSP has incident response plans clearly documented and approved.

2. Confirm incident response plans cover critical scenarios for executing cloud services comprehensively.

3. Check plans define specific roles and escalation procedures.

4. Ensure regular reviews and updates of incident response documentation.

5. Confirm testing and drills of incident response plans performed periodically.

6. Verify documented corrective actions following response plan testing.

Standards mappings

ISO 42001Partial Gap
42001: B.8.4
27001: A.5.24
27001: A.16.1.2
27001: A.16.1.5
27002: 16.1.2 and 16.1.5
Addendum

Add a dedicated control requiring formal incident response planning, Procedures for AI-related threat scenarios, communications, and escalation, Stakeholder notification policies, including for supply chain and AICs, A regular IRP testing and review cycle.

EU AI ActFull Gap
No Mapping
Addendum

The EU AI Act doesn't explicitly require establishing a formal incident response plan that specifically addresses internal departments, impacted AICs (Assets, Inventory, and Configuration), and critical business relationships such as supply chain.

NIST AI 600-1No Gap
MG-2.3-001
MG-2.4-002
MG-2.4-003
MG-4.2-002
GV-4.1-003
Addendum

N/A

BSI AIC4No Gap
C4 RE-05
C4 BC-04
C5 SIM-01
C5 OPS-21
C5 INQ-04
Addendum

N/A

AI-CAIQ questions (1)

SEF-03.1

Is a security incident response plans which includes but is not limited to a communication strategy for notifying relevant internal departments, impacted AICs, and other business critical relationships (such as supply-chain) that may be impacted, established, documented, approved, communicated, applied, evaluated, and maintained?