Well, the very coarse filters that are tripping on this are before the model even loads the text into VRAM, so hopefully it is less sickening to you to know that it's very likely a "if str.contains(`suicide`) { refuseAndSuggestHotline(); }" is thinking about your message on the CPU instead of a chain of `fuzzyWeightAddMulX` commands on the GPU.
If things were implemented that way, you would see vastly more complaints about overeager refusals. For at least some deployments, the safety classifiers are based on internal LLM activations, so the input does get processed by the model.
The point is that something like this exists, or had to have existed. What lengths a person took to prevent de-obfuscation of code. The commenter above is saying it's sickening that a LLM has to "think" about this in order to not analyze the code, and I think it's equally sickening that, if someone wants to achieve said goal, they must think about stuff like that
