SpliceLeak is the first end-to-end side-channel attack on non-prefix KV cache in RAG, using Step-Wave timing leaks to fingerprint private prompt lengths and extract tokens with up to 100% success using 63 requests per token on vLLM+LMCache.
Selective kv-cache sharing to mitigate timing side-channels in llm inference
5 Pith papers cite this work. Polarity classification is still indexing.
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GaitProtector optimizes diffusion model latents to impersonate target identities in gait sequences, dropping Rank-1 identification accuracy from 89.6% to 15.0% on CASIA-B while keeping scoliosis diagnostic accuracy at 74.2%.
PrefixWall mitigates APC side channels in multi-tenant LLM systems via selective prefix isolation, delivering up to 70% higher cache reuse and 30% lower latency than full-isolation baselines.
No existing AI security framework covers a majority of the 193 identified multi-agent system threats in any category, with OWASP Agentic Security Initiative achieving the highest overall coverage at 65.3%.
MarginGate triggers verification only on low-margin decode steps to achieve 100% deterministic batch inference at 15-50% of the cost of always-on verification across tested models and datasets.
citing papers explorer
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Agent-Assisted Side-Channel Attacks on Non-Prefix KV Cache in RAG
SpliceLeak is the first end-to-end side-channel attack on non-prefix KV cache in RAG, using Step-Wave timing leaks to fingerprint private prompt lengths and extract tokens with up to 100% success using 63 requests per token on vLLM+LMCache.
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GaitProtector: Impersonation-Driven Gait De-Identification via Training-Free Diffusion Latent Optimization
GaitProtector optimizes diffusion model latents to impersonate target identities in gait sequences, dropping Rank-1 identification accuracy from 89.6% to 15.0% on CASIA-B while keeping scoliosis diagnostic accuracy at 74.2%.
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PrefixWall: Mitigating Prefix Caching Side Channels in Shared LLM Systems
PrefixWall mitigates APC side channels in multi-tenant LLM systems via selective prefix isolation, delivering up to 70% higher cache reuse and 30% lower latency than full-isolation baselines.
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Security Considerations for Multi-agent Systems
No existing AI security framework covers a majority of the 193 identified multi-agent system threats in any category, with OWASP Agentic Security Initiative achieving the highest overall coverage at 65.3%.
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MarginGate: Sparse Margin-Triggered Verification for Batch-Invariant LLM Inference
MarginGate triggers verification only on low-margin decode steps to achieve 100% deterministic batch inference at 15-50% of the cost of always-on verification across tested models and datasets.