Researchers reconstruct LLM prompts from outputs, near-perfect accuracy

Researchers at IIT Bombay and Adobe Research built an inverse language model, called Previous-Token Prediction, that reconstructs a model's original prompt from its output text alone. The technique needs no access to model weights and works across different models.

Why it matters: Companies that treat system prompts as proprietary IP or a security layer now face a concrete extraction technique, not just a theoretical risk. Expect this to accelerate interest in prompt-obfuscation and output-filtering defenses for commercial large language model (LLM) products.