AI RESEARCH
CacheProbe: Auditing Prompt Cache Isolation in Gateway APIs
arXiv CS.LG
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ArXi:2605.30613v1 Announce Type: cross Over the past year, prompt caching in Large Language Models (LLMs) has become increasingly popular across inference APIs. Prompt caching helps save precious compute resources and speeds up response times by reusing parts of the KV cache of a specific prompt for another request. However, many implementations of prompt caching are not secure against timing attacks or even basic metadata disclosure. Gu (ICML 2025) develop a method to audit prompt caching in LLMs. This paper investigates whether OpenRouter's API gateway architecture