Resk-Logits Tool Blocks Harmful LLM Tokens Before They Are Generated

A new open-source library called resk-logits proposes intercepting a language model's logit vectors — the raw probability scores produced before any text is sampled — to block harmful tokens before they ever enter a conversation. The tool, published by Resk Security on PyPI and GitHub under the Apache 2.0 license, uses a GPU-accelerated Aho-Corasick automaton to match over 10,000 dangerous token patterns in under one millisecond on modern hardware. The core argument is that traditional post-generation filters and prompt-engineering defenses are structurally reactive: by the time a harmful token is detected in output text, it has already influenced the model's context window. By setting matched token logits to negative infinity, the library makes those tokens mathematically impossible to sample, offering a hard guarantee rather than a probabilistic one. The tool is compatible with any HuggingFace-based PyTorch model pipeline and can be integrated with a few lines of code.