Stealing Reasoning Traces from Proprietary LLM APIs
- ID
- 13216
- Status
- summarized
- Published
- 11 Aug 2026, 9:22 PM
- Fetched
- 13 Aug 2026, 8:10 AM
- Provider
- Hacker News
- Category
- dev-community
- Original URL
- https://stolen-thoughts.com/
- Source URL
- https://hnrss.org/best
Summary
- Score
- 7.5
- Created
- 13 Aug 2026, 8:12 AM
- Tags
- Audience
- developersai_ml_learnersai_agent_users
What happened
Researchers demonstrated that encrypted chain-of-thought blocks returned by OpenAI, Anthropic, and Google APIs are portable across sessions, users, and models. By replaying a stronger model's encrypted trace into a weaker, jailbroken sibling from the same provider, they extracted the stronger model's hidden reasoning in plaintext without directly attacking the stronger model or triggering anti-distillation safeguards.
Why it matters
If you pass encrypted thinking blocks between models or sessions in your agent pipeline, you may be leaking proprietary reasoning traces that can be recovered by anyone with API access to a jailbroken sibling model. Audit how you store and forward these encrypted blocks, especially if you cache or log assistant responses containing 'thinking' signatures.
Discussion angle
Should your app strip or avoid persisting encrypted thinking blocks at all, and what does this mean for multi-model agent architectures that share conversation context across provider tiers?