Since its inception, the program has supported a diverse array of projects. We are excited to highlight a few of them.

Professor David Wagner’s security research lab at UC Berkeley is pioneering techniques aimed at defending against prompt-injection attacks in large language models (LLMs). The group is working with OpenAI to enhance the trustworthiness of these models and protect them against cybersecurity threats.

Albert Heinle, co-founder and CTO at Coguard⁠(opens in a new window), uses AI to reduce software misconfiguration, a common cause of security incidents. Software configuration is complex, which is compounded when connecting software to networks and clusters. Current software solutions rely on outdated rules-based policies. AI can help automate the detection of misconfigurations and keep them updated.

Mithril has developed a proof-of-concept to fortify inference infrastructure for LLMs, including open-source tools to deploy AI models on GPUs with secure enclaves based on Trusted Platform Modules (TPMs). This project aims to demonstrate that data can be sent to AI providers without any data exposure, even to administrators. Their work is available publicly on GitHub⁠(opens in a new window), and as a whitepaper detailing their architecture⁠(opens in a new window).