Model Theft and Extraction in 2026: Risks and Defense - Blockchain Council

The article details advanced model theft and extraction techniques targeting Large Language Models (LLMs), enabling adversaries to replicate proprietary model behavior through systematic API querying and distillation, or infer sensitive training data via model inversion. These attack vectors lead to significant intellectual property loss, facilitate the discovery of further bypasses, and pose severe privacy and compliance risks through data memorization or Retrieval Augmented Generation (RAG) abuse.