EchoCoT: Extracting Hidden Chain-of-Thought from Large Reasoning Models
Researchers show hidden reasoning traces can be extracted from proprietary LLMs via black-box queries — an IP-exfiltration vector that enterprises licensing frontier models should monitor.
Summary written by editorial AI · Source link below
arXiv:2608.20055v1 Announce Type: new Abstract: Hidden chain-of-thought (CoT) traces, especially those from frontier proprietary large reasoning models (LRMs), are valuable model assets. Yet whether these hidden CoTs can be directly extracted from black-box models remains largely unexplored. In this work, we systematically study whether hidden CoTs can be extracted near-verbatim from black-box LRMs through API interactions. We identify a previously overlooked reasoning replay surface between to
Editorial Analysis
Organizations relying on proprietary reasoning models face a new risk: competitors or attackers could extract valuable hidden reasoning steps, undermining model IP protections.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
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