Threat and Vulnerability Management Policy and Procedures
Specification
Establish, document, approve, communicate, apply, evaluate and maintain policies and procedures to identify, report and prioritize the remediation of vulnerabilities and threats, in order to protect systems against vulnerability exploitation. Review and update the policies and procedures at least annually or upon significant changes.
Threat coverage
Architectural relevance
Lifecycle
Data storage, Resource provisioning
Training
Validation/Red Teaming, Re-evaluation
Orchestration, AI Services supply chain, AI applications
Operations, Maintenance, Continuous monitoring, Continuous improvement
Data deletion
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
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 that the CSP has established and documented TVM policies and procedures defining scope, objectives, roles, and responsibilities. 2. Inspect whether the policies are compliant with regulatory requirements, industry best practices, and relevant threat scenarios. 3. Verify formal approval of the policies by authorized management. 4. Verify communication of the policies to all relevant stakeholders and their understanding. 5. Confirm that the policies are effectively applied in daily operations. 6. Verify that metrics are established and monitored to evaluate effectiveness and identify areas for improvement. 7. Inspect evidence that the policies are reviewed and updated at least annually or upon significant changes. 8. Verify that the TVM policy explicitly covers all layers of the cloud infrastructure — physical, hypervisor, network, and managed services. 9. Review the CSP’s public‑facing documentation (e.g., cloud security white papers, SOC 2 reports) describing vulnerability scanning, patching, and remediation practices. 10. Confirm that the CSP provides customers with tools, guidance, or best practices to help them manage vulnerabilities in their own cloud environments as part of the shared responsibility model. 11. Verify that policies and procedures include formalized mechanisms and dedicated communication channels for Vulnerability Disclosure activities. From CCM: 1. Examine policy for adequacy, currency, communication, and effectiveness. 2. Examine policy and procedures for evidence of review at least annually.
Standards mappings
A.2.4 Review of AI Policy (42001) 6.1.1 General (42001 - Actions to address risks and opportunities) 6.1.3 AI risk treatment (42001) 7.4 Communication (42001) 7.5 Documented Information (42001)
Addendum
N/A
Article 15 (4) Article 15 (5)
Addendum
Contrarily to the AICM control that provides an increased level of technical details, the EU AI Act establishes more general security principles that encompass the aspects tackled in the control.
MG-2.4-003
Addendum
NIST AI 600-1 should reference review and update of the policies and procedures at least annually.
C4 PC-02 C4 SR-01 C5 OPS-18
Addendum
N/A
AI-CAIQ questions (2)
Are policies and procedures that identify, report, and prioritize the remediation of vulnerabilities and threats in order to protect systems against vulnerability exploitation, established, documented, approved, communicated, applied, evaluated, and maintained?
Are threats and vulnerabilities policies and procedures reviewed and updated at least annually or upon significant changes?