Near-Term Enforcement of AI Chip Export Controls Using A Firmware-Based Design for Offline Licensing

TL;DR

This paper proposes a firmware-based Offline Licensing mechanism for AI chips to enforce export controls and prevent unregulated training of dangerous AI models, leveraging existing hardware security features for rapid deployment.

Contribution

It introduces a minimal firmware-based Offline Licensing design that can be implemented within a year on existing AI chips with common security features.

Findings

Supports enforcement of export controls on AI chips

Can be implemented via firmware update without hardware changes

Potential to prevent unregulated training of frontier AI models

Abstract

Offline Licensing is a mechanism for compute governance that could be used to prevent unregulated training of potentially dangerous frontier AI models. The mechanism works by disabling AI chips unless they have an unused license from a regulator. In this report, we present a design for a minimal version of Offline Licensing that could be delivered via a firmware update. Existing AI chips could potentially support Offline Licensing within a year if they have the following (relatively common) hardware security features: firmware verification, firmware rollback protection, and secure non-volatile memory. Public documentation suggests that NVIDIA's H100 AI chip already has these security features. Without additional hardware modifications, the system is susceptible to physical hardware attacks. However, these attacks might require expensive equipment and could be difficult to reliably apply to thousands of AI chips. A firmware-based Offline Licensing design shares the same legal requirements and license approval mechanism as a hardware-based solution. Implementing a firmware-based solution now could accelerate the eventual deployment of a more secure hardware-based solution in the future. For AI chip manufacturers, implementing this security mechanism might allow chips to be sold to customers that would otherwise be prohibited by export restrictions. For governments, it may be important to be able to prevent unsafe or malicious actors from training frontier AI models in the next few years. Based on this initial analysis, firmware-based Offline Licensing could partially solve urgent security and trade problems and is technically feasible for AI chips that have common hardware security features.