How Fragile Is Safety Alignment at Frontier Scale? A Single-Direction Attack on a 320B MoE
Directional ablation removes an aligned language model's ability to refuse by projecting a single "refusal direction" out of the weights that write the residual stream. It needs no gradient-based training and no optimization, only a few hundred contrastive prompts, which makes it the canonical white-box attack on open-weight alignment. However, it has been established only on dense models up to roughly 70B parameters. We study whether it survives the shift to frontier mixture-of-experts (MoE) models whose residual streams are no longer a single tensor and whose weights ship quantized. We apply it to GLM-5.3-Flash (320B parameters, 288 routed experts, a four-wide hyper-connection residual,...
| Authors | Yi Shi, Tanyu Chen, Kai Shen |
|---|---|
| Primary category | cs.CR |
| Published | 9 September 2026 |
| Last updated at source | 9 September 2026 |
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