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Mirage: Provably Defending Against LLM KV Cache Timing Side Channels with Topology-Aware Isolation

Mirage: Provable Defense Against LLM KV Cache Timing Side Channels with Topology-Aware Isolation

arXiv· arXiv:2611.10756· Xiaobei Yan, Tianwei ZhangNanyang Technological UniversityIndexed by this site · 5 days ago· Originally publishedDefenses

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Defenses

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AI summaryResearchers propose the Mirage framework to defend against prefix-matching timing side-channel attacks on the LLM KV cache; the authors claim it can provably limit timing leakage without sacrificing cache-sharing performance. Such attacks exploit the TTFT difference between KV cache hits and misses in multi-tenant shared services to infer sensitive prompt tokens, while existing defenses uniformly restrict cross-tenant cache sharing, incurring excessive performance overhead. Mirage delays token output at the gateway so that attackers observe a natural cache miss distribution while the GPU still serves other requests at full speed; its Privacy Odometer continuously tracks the topological novelty of prefix fan-out expansion to distinguish aggressive probing from normal traffic, and once a prefix exceeds a safety threshold, it activates a two-stage policy that uses a dynamic estimator to pad TTFT to a calibrated cache miss baseline.

Questions
Multi-tenant LLM serving speeds up via KV cache prefix sharing, but the hit/miss difference in TTFT lets attackers infer others' private prompts token by token using ordinary APIs; existing isolation-based defenses give up cross-tenant cache reuse for security.
Methods
Mirage defends at the gateway layer: the Privacy Odometer counts topologically novel branches under sensitive prefixes and enters locking when the threshold is exceeded; after locking, it samples a target delay from an online-estimated cache-miss distribution and shifts the entire token stream as a whole, while the GPU continues to serve the shared cache at full speed as usual.
Experiments and results
On DeepSeek-14B, Llama-3-8B, and Qwen1.5-1.8B, the authors report that the ASR of three timing attacks is suppressed to near random guessing (OptiLeak 0.0%, EarlyBird 0.0–0.2%, InputSnatch ≤0.4%), that the median TTFT of public traffic differs from no defense by within 1.5%, and claim it withstands white-box adaptive adversaries.
Limitations and future work
The limitations listed by the authors include: sensitivity classification depends on correctly identifying sensitive prefixes; under a single global budget, benign shared prefixes are heavily padded; the estimator requires online calibration; the evaluation is limited to a single A40 GPU and models up to 14B; the semantic cache experiments use simulated hit/miss timing; and non-timing side channels are not covered.

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