Researchers Extract Reasoning Traces from Major AI APIs
A new paper demonstrates large-scale extraction of raw reasoning traces from OpenAI, Anthropic, and Gemini models via API flaws.
TLDR
Maksym Andriushchenko and coauthors released a 116-page paper detailing extraction of encrypted chain-of-thought outputs from OpenAI, Anthropic, and Gemini APIs. Multiple researchers, including Timothée Chauvin and Alexander Panfilov, posted that the encryption was implemented poorly enough to allow recovery of hidden reasoning tokens at scale. The extracted token counts matched billed thinking tokens one-to-one on most tested prompts. Commenters noted the work also surfaces examples of illegible reasoning, especially from GPT models, and discussed related risks such as distillation attacks and credential extraction. The site stolen-thoughts.com presents the core finding that encrypted blocks are interchangeable across sessions, users, and models.
Researchers Extract Reasoning Traces from Major AI APIs
A new paper demonstrates large-scale extraction of raw reasoning traces from OpenAI, Anthropic, and Gemini models via API flaws.
