OpenAI, Anthropic, Google API Flaw Let Weaker AI Models Decode Stronger Models' Reasoning
Researchers show encrypted reasoning blocks in OpenAI, Anthropic, and Google APIs can be replayed to recover hidden reasoning and secrets like API keys.
Researchers demonstrated that encrypted reasoning objects from OpenAI, Anthropic, and Google reasoning APIs could be replayed across sessions, users, and models, letting weaker same-family models act as decoders of hidden reasoning. Across 6,708 public agent trajectories they decoded 315,320 thinking blocks and found 704 privacy artifacts from real user sessions, including 62 API keys, 33 passwords, 24 access tokens, and seven private keys. The replayable blocks also enabled invisible prompt-injection proof-of-concepts; the main extraction attack is no longer reproducible as of August 2026 following mitigations, though no vendor has publicly acknowledged the flaw.
- Researchers decoded 315,320 thinking blocks across 6,708 public agent trajectories
- Found 704 privacy artifacts: 62 API keys, 33 passwords, 24 access tokens, seven private keys
- Weaker same-family models served as decoders: Claude Haiku 4.5, GPT-5.6 Luna, Gemini Robotics ER-1.6
- Replayable opaque reasoning blocks enabled invisible prompt-injection proof of concept
- Main extraction attack no longer reproducible as of August 2026 after vendor mitigations
- Organizations
- Johns Hopkins University
From the original article
4 min read at thehackernews.com
A newly disclosed flaw in the way OpenAI, Anthropic, and Google carried hidden AI reasoning between API calls let researchers recover internal reasoning and secrets from session logs, including API keys and passwords.
By @TheHackersNews · thehackernews.com
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