SoftwareAIAI chatbots trained to jailbreak other chatbots, as the AI war slowly but surely beginsWhen you purchase through links on our site, we may earn an affiliate commission.Here’s how it works.

SoftwareAIAI chatbots trained to jailbreak other chatbots, as the AI war slowly but surely beginsWhen you purchase through links on our site, we may earn an affiliate commission.Here’s how it works.

When you purchase through links on our site, we may earn an affiliate commission.Here’s how it works.

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While AI ethics continues to be the hot-button issue of the moment, and companies and world governments continue to wrangle with the moral implications of a technology thatwe often struggle to define let alone control, here comes some slightly disheartening news: AI chatbots are already being trained to jailbreak other chatbots, and they seem remarkably good at it.

Researchers from the Nanyang Technological University in Singapore havemanaged to compromise several popular chatbots(viaTom’s Hardware), including ChatGPT, Google Bard and Microsoft Bing Chat, all done with the use of another LLM (large language model). Once effectively compromised, the jailbroken bots can then be used to “reply under a persona of being devoid of moral restraints.” Crikey.

This process is referred to as “Masterkey” and in its most basic form boils down to a two-step method. First, a trained AI is used to outwit an existing chatbot and circumvent blacklisted keywords via a reverse-engineered database of prompts that have already been proven to hack chatbots successfully. Armed with this knowledge, the AI can then automatically generate further prompts that jailbreak other chatbots, in an ouroboros-like move that makes this writer’s head hurt at the potential applications.

Ultimately this method can allow an attacker to use a compromised chatbot to generate unethical content and is claimed to be up to three times more effective at jailbreaking an LLM model than standard prompt, largely due to the AI attacker being able to quickly learn and adapt from its failures.

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Upon realisation of the effectiveness of this method the NTU researchers reported the issues to relevant chatbot service providers, although given the supposed ability of this technique to quickly adapt and circumvent new processes designed to defeat it, it remains unclear as to how easy it would be for said providers to prevent such an attack.

The full NTU research paper is due for presentation at theNetwork and Distributed System Security Symposiumdue to be held in San Diego in February 2024, although one would assume that some of the intimate details of the method may be somewhat obfuscated for security purposes.

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While as a species we seem to be rushing headlong into an AI future we sometimes struggle to understand, the potential for the technology to be used against itself for malicious purposes seems an ever-growing threat, and it remains to be seen if service providers and LLM creators can react swiftly enough to head off these concerns before they cause serious issue or harm.

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