SSRM Control Implementation
Specification
Implement, operate, and audit or assess the portions of the SSRM which the organization is responsible for.
Threat coverage
Architectural relevance
Lifecycle
Data storage
Supply Chain
Evaluation, Validation/Red Teaming, Re-evaluation
Orchestration, AI Services supply chain, AI applications
Operations, Maintenance, Continuous monitoring, Continuous improvement
Archiving, Data deletion, Model disposal
Ownership / SSRM
PI
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.
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
Owned by the Application Provider (AP)
The Application Provider (AP) is responsible 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. The AP is responsible and accountable for the implementation of the control within its own infrastructure/environment. If the control has downstream implications on the users/customers, the AP is responsible for enabling the customer and/or upstream partner in the implementation/configuration of the control within their risk management approach. The AP is accountable for carrying out the due diligence on its upstream providers (e.g MPs, Orchestrated Services) to verify that they implement the control as it relates to the service/product develop and offered by the AP. These providers build and offer end-user applications that leverage generative AI models for specific tasks such as content creation, chatbots, code generation, and enterprise automation. These applications are often delivered as software-as-a-service (SaaS) solutions. These providers focus on user interfaces, application logic, domain-specific functionality, and overall user experience rather than underlying model development. Example: OpenAI (GPTs,Assistants), Zapier, CustomGPT, Microsoft Copilot (integrated into Office products), Jasper (AI-driven content generation), Notion AI (AI-enhanced productivity tools), Adobe Firefly (AI-generated media), and AI-powered customer service solutions like Amazon Rufus, as well as any organization that develops its AI-based application internally.
Implementation guidelines
Auditing guidelines
1. Verify through third-party audit reports (e.g., SOC 2, ISO 27001) that the CSP implements, operates, and assesses its assigned SSRM controls such as physical security, hypervisor security, and infrastructure patch management ensuring these are tested and validated by independent assessors. 2. Review the CSP’s shared responsibility matrix and supporting evidence (e.g., compliance mappings, control test results) to confirm that the CSP is actively managing its responsibilities and that these align with the AP’s SSRM expectations.
Standards mappings
42001: A.2.3 Alignment with other organizational policies 42001: A.10.2 Allocating Responsibilities 27001: 8.1 Operational planning and control 27001: A.5.20 Addressing information security within supplier agreements 27001: A.5.21 Managing information security in the information and communication technology (ICT) supply chain 27001: A.5.22 Monitoring review and change management of supplier services 27001: A.5.23 Information security for use of cloud services 27001: 5.20 Addressing information security within supplier agreements 27001: 5.21 Managing information security in the information and communication technology (ICT) supply chain 27001: 5.22 Monitoring review and change management of supplier services 27001: 5.23 Information security for use of cloud services
Addendum
N/A
Article 15 Article(s) 16 to 27 (Section 3) Article 17 Annex VI, VII
Addendum
Implement a formal SSRM policy that defines the division of responsibilities among all stakeholders (e.g., providers, deployers, third parties), including: A responsibility matrix (e.g., RACI), Documented shared controls and their ownership, A policy for periodic review and reassessment, A mechanism for auditing or attesting to SSRM adherence, particularly after significant system changes or incidents.
MG-3.1-002
Addendum
The NIST AI 600-1 control MG-3.1-002 does not mention that the cloud service offerings could be IaaS, PaaS, and SaaS, where responsibilities could be for everything being on-premises to only responsible for the data and access to that data.
C4 PC-01 C4 SR-06 C5 OPS-20 C5 OPS-21 C5 COM-02 C5 SSO-04
Addendum
N/A
AI-CAIQ questions (1)
Are the portions of the SSRM the organization is responsible for implemented, operated, audited, or assessed?