Microsoft NVIDIA Whitepaper Offers Shared Taxonomy and Controls for Open-Weight AI Deployment Risks

Microsoft and NVIDIA have jointly published a whitepaper designed to help enterprises manage the risks associated with deploying open-weight artificial intelligence models. The document, released on the Microsoft Security Blog and Azure Blog, provides a shared taxonomy for understanding these risks. It outlines evaluation methods and controls for organisations building or customising increasingly capable models. This resource aims to give security teams a structured approach to handling the complexities of open-weight AI in enterprise environments.

Root cause

The publication addresses the growing AI landscape, which is giving enterprises more choice in how they build, customise, and deploy increasingly capable models. The whitepaper responds to this expansion by providing a shared taxonomy. It helps enterprises manage open-weight AI model risks through evaluations and controls. The source material does not specify a single root cause for these risks, but rather presents the guide as a response to the increased capability and choice available to enterprises in the current AI environment.

Attack path

The source material does not describe a specific attack path or exploit chain. Instead, it focuses on the broader risk management landscape for open-weight models. The whitepaper is intended to help teams understand potential vulnerabilities before they are exploited. It emphasises the need for proactive evaluation and control implementation. By establishing a shared taxonomy, the guide helps organisations identify where risks might emerge in the model lifecycle, from initial building to final deployment, allowing for better preventative measures.

Affected versions

The whitepaper applies to open-weight AI models in general, rather than specific software versions. It is relevant to any enterprise deploying these types of models. The guidance is not tied to a particular release date or version number of a specific product. Instead, it offers a framework that can be applied across various implementations. Organisations using open-weight models, regardless of the specific version or provider, can utilise the shared taxonomy to assess their current posture and identify areas requiring additional controls or evaluation.

Mitigation

• Adopt the shared taxonomy provided by Microsoft and NVIDIA to classify risks.
• Implement the evaluation methods outlined in the whitepaper for your models.
• Apply the recommended controls to secure enterprise deployments.
• Review your current AI building and customisation processes against the guide.

Why it matters

Organisations often struggle to assess AI risks without a common framework. This guide provides a standardised language for discussing vulnerabilities in open-weight models. Teams should use such taxonomies to align security and development efforts. Without shared definitions, risk assessments can be inconsistent, leaving gaps in protection. Evaluating models against a recognised set of criteria helps ensure that security considerations are integrated early. This approach reduces the likelihood of deploying systems with unmanaged risks. It also facilitates clearer communication between technical teams and leadership about the safety of AI initiatives.

What to do and how to stay safe: Microsoft

• Review the joint whitepaper from Microsoft and NVIDIA to understand the shared taxonomy.
• Audit your current open-weight model deployments against the provided risk categories.
• Implement the suggested controls to mitigate identified vulnerabilities in your environment.
• Ensure your evaluation processes incorporate the guidelines for building and customising models.

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General security guidance from the Vector Bulletin newsroom. It is not confirmed advice from the organisations named in this story.

Frequently asked questions

Who published the guide on managing open-weight model risks?

Microsoft and NVIDIA jointly published the whitepaper.

What does the whitepaper provide for enterprises?

It provides a shared taxonomy, evaluations, and controls for managing risks.

Where can I find this publication?

It appeared on the Microsoft Security Blog and the Microsoft Azure Blog.