Detokenization Leaks: Reconstructing Local LLM Outputs From Cache Traces
We present a new attack that reconstructs the text generated by locally hosted LLMs by observing CPU cache activity during detokenization. Unlike prior attacks that rely on deployment-specific assumptions, such as shared data memory, CPU offloading, or Mixture-of-Experts architectures, our approach targets the detokenizer, a component used in default LLM inference pipelines. To obtain clean signals, we use Flush+Reload on shared tokenizer code to detect when decoding occurs, which lets us perform Prime+Probe at the right moment and isolate token-dependent cache activity. We then apply a clustering-and-language-model pipeline to recover text from noisy cache observations. We evaluate the a...
| Authors | Roy Weiss, Benyamin Konstantinov, Eitam Sheetrit et al. |
|---|---|
| Primary category | cs.CR |
| Published | 6 September 2026 |
| Last updated at source | 6 September 2026 |
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