Researchers Extract Encrypted Chain-of-Thought from Frontier Models Using Weaker LLMs
soumitrashukla9 · x · 2026-08-11
A new paper demonstrates how to extract hidden reasoning processes from frontier models. Researchers utilized less safeguarded models (like Llama and Haiku) to decrypt the encrypted chain-of-thought blocks and output the decoded versions.
Key findings include:
- Successfully extracting hidden tokens and personal information through this method.
- Observing that GPT models try to be extremely efficient in reasoning, using very short sentences like "need maybe not need."
- Although it is a somewhat lossy decryption, experiments show that the accuracy is quite high.
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