What Does It Mean to Break a Distillation Defense?

Black-box LLMs (accessible only via API) are vulnerable to distillation attacks, in which an attacker queries the model and trains a student on its outputs. A recent line of work proposes output perturbation defenses that modify the teacher's output to reduce student performance while preserving utility for legitimate users. As a relatively new family of approaches, output perturbation defenses lack a shared threat model, making it difficult to compare them, reason about composing them with othe

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ethics.ai (23 June 2026), “What Does It Mean to Break a Distillation Defense?,” evidence record 636, https://ethics.ai/record/636 (originally published by arXiv).

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