Open Source Summit + Embedded Linux Conference North America 2026

As AI systems become deeply embedded in critical infrastructure and enterprise operations, ensuring the security, integrity, and provenance of machine learning models has become a fundamental challenge for the open source ecosystem.

This session will provide an overview of the OpenSSF AI/ML Security Working Group's focus on practical solutions that bring software supply chain security best practices to AI.

1. End-to-End Model Provenance: Detect unintended changes and ensure verifiable audit trails throughout the entire model lifecycle.

2. Model Signing: Provide verifiable claims about model integrity by establishing cryptographic signing patterns.

3. GPU-Based Model Integrity: Address the scalability of authenticating very large ML models by leveraging GPU acceleration in a vendor-agnostic API.

4. Frameworks for Securing AI Agent Communications: A comprehensive security framework to secure AI agent-tool orchestration against emerging threats.

5. Cyber Reasoning System (CRS): AI-for-Security systems to identify and submit patches for software vulnerabilities.

Panelists:
Marcela Melara, Intel
Mihai Maruseac, OpenAI
Jay White, Microsoft

Moderator:
Christopher Robinson, OpenSSF