Security

Everyone’s advice for prompt injection is the same: stick a classifier in front of the model. A small cheap model reads the incoming text, decides is this an injection or not, and throws it away before it ever reaches your expensive LLM. So using the recent trend of Laya/Jev models, a recent small non-autoregressive model that just scores an answer in one forward pass instead of generating tokens, I’ve built a pretty good prompt injection classifier using my smaller, better calibrated version of Laya called Smolaya....

Everyone has run this line: model = AutoModelForCausalLM.from_pretrained("some-user/some-model") It looks like a download. It is closer to running someone else’s installer. Some model formats execute code the moment you load them, some configs pull Python straight out of the repository, and the weights themselves can carry behaviour nobody mentioned in the model card. It has also been shown that its EXTREMELY easy to poison a big-ass LLM. With a near constant number of samples regardless of the size of the model 1....