Estimating worst case frontier risks of open weight LLMs
Must ReadOpenAI Blog · 2025-08-05 00:00 UTC AI
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AI Summary
The paper examines worst-case risks of releasing gpt-oss. It introduces malicious fine-tuning (MFT) to maximize capabilities in biology and cybersecurity. The study focuses on potential misuse of open weight LLMs.
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Why should I care?
Because it highlights security risks in open-source LLMs, directly impacting your focus on AI models and open-source AI.
Content
In this paper, we study the worst-case frontier risks of releasing gpt-oss. We introduce malicious fine-tuning (MFT), where we attempt to elicit maximum capabilities by fine-tuning gpt-oss to be as capable as possible in two domains: biology and cybersecurity.