A New Trick Reveals AI Models’ Inner Thoughts
Researchers have developed a method to extract the hidden reasoning steps of frontier AI models, revealing potential security vulnerabilities and evidence of model distillation. The study suggests that some Chinese models may be mimicking the reasoning patterns of US-based AI systems.
Why it matters
This discovery raises significant concerns regarding AI security, intellectual property theft, and the transparency of 'black box' reasoning in large language models.
Computer scientists recently discovered a way to extract the hidden “thinking” that frontier AI models perform as they work through complex problems.
The findings provide some evidence—although not conclusive proof—that certain Chinese models may have been trained by “distilling” reasoning information from US models that was supposedly hidden because of how closely some of their thinking or reasoning patterns seem to match. The researchers have also demonstrated that the method could be used to recover personal information, like passwords and API keys, from a model’s inner reasoning, although this vulnerability has been fixed.
“All major frontier model providers we tested share this vulnerability,” says Alexander Panfilov, a computer scientist at University of Tübingen in Germany who was involved with the work. “It can lead to personal information leakage, and it enables large-scale reasoning distillation attacks.”
Get smarter about the news
Sign up free for a feed built around what you actually care about, Dive Deeper research on any story, and the full text of every article.
Create free accountAlready have an account? Sign in