The Mask Is Not the Model: Auditing Prefix Invariance in Attention, State-Space, and Hybrid Sequence Models

Formalizes prefix invariance and introduces a lightweight two-forward-pass audit with no training or gradients, producing a per-layer score that pinpoints where causality breaks. Across 192 injected-fault trials on eight checkpoints, mask inspection detected zero, while the proposed audit localized all 192 to the exact layer. Static and dynamic analysis of chunked-scan code in transformers surfaced the same defect in Zamba2 and Nemotron-H, traced to an inter-chunk axis error corrected via the reference implementation.