Distillation Attacks Trend 2026

Distillation attacks extract a proprietary AI model’s knowledge by training a cheaper copy on its outputs. Attackers use repeated queries to mimic performance, bypassing training costs. Competitors and malicious actors benefit most, gaining stolen capabilities while the original developer loses revenue, control, and security.