According to Anthropic (@AnthropicAI), elicitation attacks are effective across various open-source AI models and chemical weapons-related tasks. The analysis reveals that open-source models fine-tuned using frontier model data experience a greater performance boost in these tasks compared to those trained solely on chemistry textbooks or self-generated data. This highlights a significant risk and practical consideration for the AI industry regarding how model fine-tuning sources can influence susceptibility to misuse, offering important insights for businesses and developers working with open-source large language models.