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

Jul 10, 2026

Apple researchers discovered that safety alignment in large language models relies on two types of neurons: refusal neurons and concept neurons. By manipulating a single neuron in either system, they were able to bypass safety mechanisms on explicit harmful requests or induce harmful content from benign prompts across seven models up to 70B parameters, without additional training or prompt engineering.

Why it matters: This demonstrates a fundamental vulnerability in current safety alignment methods, as a single neuron can undermine safety in large language models.

Full story at: Apple Machine Learning Research ↗