Paper Reveals Hidden Reasoning Traces Can Be Stolen from Proprietary LLM APIs
TheTuringPost · x · 2026-08-17
A new paper titled 'Stealing Reasoning Traces from Proprietary LLM APIs' exposes security risks in the hidden reasoning processes of commercial LLM APIs. Researchers found that even when reasoning blocks are encrypted, attackers can recover portions of the content without breaking the encryption. Critically, analysis of public agent logs revealed that passwords, API keys, access tokens, and personal information are often hidden within these reasoning blocks, even when the visible conversation appears clean. Furthermore, these blocks can carry instructions, meaning hidden reasoning is not just a log but an active part of the infrastructure that can influence an agent's future actions.
Related event: New Study Exposes Vulnerability in Stealing LLM Reasoning Traces(2 posts)→
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