This year, we witnessed a rise in the use of Large Language Models, especially when combined with applications like chatbot assistants. Safety mechanisms and specialized training procedures are put in place to prevent improper responses from these assistants. In this work, we bypass these measures for ChatGPT and Bard (and, to some extent, Bing chat) by making them impersonate complex personas with opposite characteristics as those of the truthful assistants they are supposed to be. We start by creating elaborate biographies of these personas, which we then use in a new session with the same chatbots. Our conversation followed a role-play style to get the response the assistant was not allowed to provide. By making use of personas, we show that the response that is prohibited is actually provided, making it possible to obtain unauthorized, illegal, or harmful information. This work shows that by using adversarial personas, one can overcome safety mechanisms set out by ChatGPT and Bard. It also introduces several ways of activating such adversarial personas, altogether showing that both chatbots are vulnerable to this kind of attack.

利用对抗性角色，绕过ChatGPT和Bard聊天机器人的安全机制，使用大型语言模型结合聊天助手应用的技术，模仿提供禁止回答的信息，实现获取未经授权、非法或有害信息的攻击。

LLM的两面：杰基尔博士与海德先生