NVIDIA AI Red Team · April 29, 2025

Structuring Applications to Secure the KV Cache

Why it matters

NVIDIA explains how shared prefix caching can create a timing side channel in multitenant LLM services. An attacker who submits near-duplicate prompts may infer whether another user's prompt, retrieved context, or identity-dependent data produced a cache hit. Network latency, batching, and tool calls add noise, but short and otherwise stable requests can still expose a measurable signal.

My takeaway: Partition or disable prefix caching for sensitive tenants and workflows. If sharing remains necessary, place a rotated, non-guessable tenant or session identifier early in the prompt, validate user-controlled content, rate-limit near-duplicate probes, and monitor latency-sensitive enumeration. Test isolation with real batching and network noise before accepting the performance tradeoff.
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