Why Traditional LLM Audits Are Partially Useless — Logit-Level Security Is the Fix

Short summary

Traditional LLM safeguards filter generated text after sampling, but harmful information already exists in the logit vector before selection. Logit-level security intercepts at the probability distribution, shadow-banning dangerous tokens before sampling in <1ms with zero detectable latency. The open-source resklogits library implements this with GPU-accelerated pattern matching on any HuggingFace model.

• •Logit-level interception blocks harmful tokens before sampling, not after generation
• •Sub-1ms latency with GPU acceleration; pure PyTorch implementation
• •Works with any HuggingFace model; open-source (Apache 2.0)

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