A new paper found a way to extract the hidden reasoning of models from OpenAI, Anthropic, and Google without breaking the encryption protecting it.
The trick was surprisingly simple. Let’s discuss it – it’s absolutely fascinating! And begs a few questions about our privacy..
Attention Span is here to show you AI isn’t magic. Sometimes the most important part of an AI interaction is the part you never see.
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🔗 Links mentioned
Stealing Reasoning Traces from Proprietary LLM APIs
https://arxiv.org/abs/2608.09867
Stolen Thoughts, project page and decoded examples
https://stolen-thoughts.com/
Matthew Green, “Let’s talk about encrypted reasoning”
https://blog.cryptographyengineering.com/2026/05/29/fooling-around-with-encrypted-reasoning-blobs/
WIRED, “A New Trick Reveals AI Models’ Inner Thoughts”
https://www.wired.com/story/a-new-trick-reveals-ai-models-inner-thoughts/
#AttentionSpan #AI #HiddenReasoning #ChainOfThought #AIReasoning #AISecurity
