Large Language Models (LLMs), exemplified by ChatGPT, have found diverse applications, yet concerns persist regarding their susceptibility to generati

Combating LLM Jailbreaks and Uncovering Security Flaws

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2024-02-10 14:30:04

Large Language Models (LLMs), exemplified by ChatGPT, have found diverse applications, yet concerns persist regarding their susceptibility to generating unintended outputs. Constructed on trillions of gigabytes of data, these models face risks such as adversarial inputs, commonly known as “jailbreaks,” challenging their intended training objectives. Despite ongoing efforts to implement safety measures during both training and post hoc phases, a comprehensive analysis of this phenomenon remains elusive.

The impact of these adverse responses extends beyond mere inconvenience, raising significant ethical concerns. Filtering out objectionable content in the vast dataset poses a challenge, and avoiding the introduction of bias during the process is difficult, developers implement guardrails to minimise the chances of generating objectionable or biased content.

To address these security concerns, developers and companies are actively working on advancing safety measures. An article by “The Wired” underscores ongoing efforts by companies like Google and OpenAI in addressing jailbreaking and prompt injections, emphasising the need for a comprehensive approach. Further, we will delve into the various ways LLMs are subjected to jailbreak and examine some recent advances designed to combat these illicit manipulations.