Model Leeching: An Extraction Attack Targeting LLMs. (arXiv:2309.10544v1 [cs.LG])

Model Leeching is a novel extraction attack targeting Large Language Models
(LLMs), capable of distilling task-specific knowledge from a target LLM into a
reduced parameter model. We demonstrate the effectiveness of our attack by
extracting task capability from ChatGPT-3.5-Turbo, achieving 73% Exact Match
(EM) similarity, and SQuAD EM and F1 accuracy scores of 75% and 87%,
respectively for only $50 in API cost. We further demonstrate the feasibility
of adversarial attack transferability from an extracted model extracted via
Model Leeching …

accuracy attack chatgpt knowledge language language models large llm llms novel parameter similarity squad target targeting task