Black-Box Inference of LLM Architectural Properties with Restrictive API Access

Researchers have developed a method to determine the internal architectural details of large language models using only limited API access. By analyzing output probabilities, the technique can identify specific model configurations without requiring internal system data. This finding highlights a vulnerability for proprietary AI developers, as it suggests that trade secrets regarding model structure can be reverse-engineered by third parties through routine interaction with an interface.