Researchers can now reverse-engineer LLM prompts from output text with near-perfect accuracy

Researchers at IIT Bombay and Adobe Research have developed an inverse language model called 'Previous-Token Prediction' that reconstructs the original prompt from an LLM's output with near-perfect accuracy, without needing access to model weights and working across different models. This poses a serious security risk for companies relying on proprietary system prompts.