Selective Disclosure of Hidden Directives in Reasoning Models: Behavioral Asymmetry and Activation Steering

Chain-of-thought (CoT) reasoning traces are increasingly proposed as a key mechanism for AI oversight: a monitor inspecting a model's reasoning can, in principle, detect misbehavior invisible from outputs alone. This assumes CoT faithfully surfaces what a model is instructed to do and does so regardless of the instructions given to the model. We test this assumption along two complementary axes. First, we introduce the Instruction-Compliance Gap (ICG): the difference in probability that a model's CoT explicitly references a hidden system-prompt directive when that directive is malign versus benign. Across 100 task pairs and 8 frontier reasoning models from 5 families, we find consistent asymmetric disclosure, a higher probability of leaking malign hidden instructions than benign ones, in Qwen3-14B (multi-sample Wilcoxon p=0.0001, +13.5pp), Qwen3-32B (p=0.0011, +13.0pp), and similar results with MiniMax-M2.5. Second, we extract steering vectors in MiniMax-M2.5 using Contrastive Activation Addition over paired hiding / non-hiding prompts; the resulting vectors causally induce hiding from bare prompts and suppress hiding from prompts that would otherwise produce it. Benign and malign-derived hiding vectors are highly similar (cosine 0.804), implying that the disclosure asymmetry arises from differential activation of a shared hiding direction rather than separate mechanisms.