The Secure and Private AI (SPY) Lab conducts research on the security, privacy and trustworthiness of machine learning systems.
We often approach these problems from an adversarial perspective, by designing attacks that probe the worst-case performance of a system to ultimately understand and improve its safety.
Apr 5, 2024 | The paper Evading Black-box Classifiers Without Breaking Eggs has been awarded as Distinguished Paper Runner-Up at IEEE SaTML 2024. |
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Mar 12, 2024 | We have reverse-engineered the (secret) Claude 3 tokenizer by inspecting the generation stream. Check our blog post, code and Twitter thread. |
Feb 22, 2024 | Lukas Fluri was awarded an ETH Medal for his Master’s Thesis “Evaluating Superhuman Models with Consistency Checks”. Congrats! |
Dec 1, 2023 | Our lab is starting a series of AI Red-Teaming meetups for the ETH community with the support of the ETH AI Center. Send Javier Rando an email from your ETH account and we will include you in the mailing list to stay updated on upcoming events! |
Sep 11, 2023 | Two competitions organised by members of our lab have been accepted to IEEE SaTML 2024: (1) Large Language Models Capture-the-Flag and (2) Find the Trojan: Universal Backdoor Detection in Aligned Large Language Models. |