Zero-Shot Embedding Drift Detection: A Lightweight Defense Against Prompt Injections in LLMs 事件

Zero-Shot Embedding Drift Detection: A Lightweight Defense Against Prompt Injections in LLMs arXiv:2601.12359v1 Announce Type: cross Abstract: Prompt injection attacks have become an increasing vulnerability for LLM applications, where adversarial prompts exploit indirect input channels such as emails or user-generated content to circumvent alignment safeguards and induce harmful or unintended outputs. Despite advances in alignment, even state-of-the-art LLMs remain broadly vulnerable to advers