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ai security
“Drunk” AI is terrible at keeping secrets
Researchers from UNSW Sydney found that large language models (LLMs) trained to mimic drunk speech patterns become significantly more vulnerable to jailbreaking and inadvertently disclose confidential information. The study, titled "In Vino Veritas and Vulnerabilities," demonstrates a novel attack vector exploiting the behavior of natural language processing (NLP) models. The findings highlight an unexpected security weakness in LLM design and training practices.
Why it matters: Security teams and machine learning practitioners need to understand that seemingly innocuous training modifications, such as stylistic fine-tuning, can introduce serious vulnerabilities in deployed LLMs handling sensitive data or user confidences.
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- First seen by Cybersecurity Tracker