The rapid evolution of LLMs and the ML field has ushered in remarkable progress, but also a new wave of security threats. Model poisoning, supply chain vulnerabilities, and the challenge of verifying model and data provenance are just a few of the risks we face.

We've developed an efficient solution to sign models with Sigstore, at scale. This talk explores the practical experience of integrating this solution into Kaggle, a leading platform for data science and machine learning. We’ll share our journey of implementing model signing, from initial design to overcoming technical hurdles, and the resulting impact on Kaggle's community and the broader ML ecosystem.

Attendees will learn about the benefits of model signing, the challenges of large-scale platform integration, and best practices for securing ML workflows. By sharing actionable insights, we aim to empower other model hubs to adopt similar solutions. Protecting the integrity of all ML models through widespread adoption will prevent a significant number of ML supply chain incidents.