A Single Neuron Is Sufficient to Bypass Safety Alignment in Large Language Models

A single neuron can bypass safety alignment in LLMs. Researchers discovered that by targeting specific neurons, they can either suppress harmful content from explicit requests or induce harmful content from innocent prompts across multiple model families and sizes, without retraining. This work highlights a vulnerability in current safety alignment methods, demonstrating that a fundamental component can be exploited.

Opening Kapyn…