用哈希承诺防模型替换,验证更可靠
Committed SAE-Feature Traces for Audited-Session Substitution Detection in Hosted LLMs

- 提前承诺输出特征图,验证时开随机位置
- 三种模型下17种攻击均被检出,阈值稳定
- 适合关注大模型服务可信性的研究人员
托管式大模型服务商有隐性替换动机:宣传强模型却用低成本回复。现有探针后返回方案(如SVIP)存在并行服务侧信道漏洞,恶意服务商可将探针导向宣传模型,而普通用户仍使用替代模型。本文提出一种承诺-开启协议:在任何开启请求前,服务商通过默克尔树承诺其在指定探针层的每位置稀疏自编码器(SAE)特征痕迹草图。验证者随机开启位置,用公开命名电路探针库(经跨后端噪声校准)评分,并以固定阈值联合一致性z分数规则判断。在三个主干模型(Qwen3-1.7B、Gemma-2-2B、Gemma-2-9B,含131k特征SAE)上测试,17类攻击(同族提升、跨族替换、秩≤128自适应LoRA)均在统一、尺度稳定的阈值下被拒绝,而匹配的SVIP基线全部逃逸。白盒端到端攻击(反向传播过冻结SAE编码器)无法缩小差距,特征伪造攻击(从不运行M_hon)则受内在维度约束。承诺开销不超过批量32时前向延迟的2.1%。
原文摘要 · Abstract (English)
Hosted-LLM providers have a silent-substitution incentive: advertise a stronger model while serving cheaper replies. Probe-after-return schemes such as SVIP leave a parallel-serve side-channel, since a dishonest provider can route the verifier's probe to the advertised model while serving ordinary users from a substitute. We propose a commit-open protocol that closes this gap. Before any opening request, the provider commits via a Merkle tree to a per-position sparse-autoencoder (SAE) feature-trace sketch of its served output at a published probe layer. A verifier opens random positions, scores them against a public named-circuit probe library calibrated with cross-backend noise, and decides with a fixed-threshold joint-consistency z-score rule. We instantiate the protocol on three backbones -- Qwen3-1.7B, Gemma-2-2B, and a 4.5x scale-up to Gemma-2-9B with a 131k-feature SAE. Of 17 attackers spanning same-family lifts, cross-family substitutes, and rank-<=128 adaptive LoRA, all are rejected at a shared, scale-stable threshold; the same attackers all evade a matched SVIP-style parallel-serve baseline. A white-box end-to-end attack that backpropagates through the frozen SAE encoder does not close the margin, and a feature-forgery attacker that never runs M_hon is bounded in closed form by an intrinsic-dimension argument. Commitment adds <=2.1% to forward-only wall-clock at batch 32.
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