{
  "id": 18393,
  "url": "https://arxiv.org/abs/2608.09867",
  "title": "Stealing Reasoning Traces from Proprietary LLM APIs",
  "summary": "Leading large language model providers now conceal their models' step-by-step reasoning, or chain-of-thought, to protect intellectual property and limit information leakage. Rather than storing these traces server-side, providers return them to the client as blocks of encrypted text, which the client passes back with each subsequent request. Building on prior research, we identify an architectural vulnerability: these encrypted blocks are fully compatible and interchangeable across different ses",
  "authors": "Alexander Panfilov, David Schmotz, Ilia Shumailov, Luca Beurer-Kellner, Joachim Schaeffer, Ameya Prabhu",
  "category": "research",
  "topics": "copyright-ip",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-09T20:00:00.000Z",
  "fetched_at": "2026-08-12T05:10:43.828Z",
  "source_slug": "hf-daily",
  "source_name": "HuggingFace Daily Papers",
  "source_homepage": "https://huggingface.co/papers",
  "ethics_ai_record_url": "https://ethics.ai/record/18393",
  "original_url": "https://arxiv.org/abs/2608.09867",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}