A new paper evaluates the jailbreaking vulnerabilities of large language models when used in smart grid operations, testing OpenAI's GPT-4o mini, Google's Gemini 2.0 Flash-Lite, and Anthropic's Claude 3.5 Haiku against NERC Reliability Standards. The study found an overall attack success rate of 33.1%, with Gemini 2.0 Flash-Lite being the most susceptible and Claude 3.5 Haiku showing complete resistance. Researchers noted that subtle prompt modifications could improve the effectiveness of simpler jailbreaking methods. AI
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IMPACT Highlights potential security risks for LLMs deployed in critical infrastructure, necessitating robust safety evaluations.
RANK_REASON Academic paper evaluating LLM vulnerabilities against industry standards.