Brain-Prompt Injection: A Route-Safety Audit for BCI-LLM Agents 文章

ArXiv CS.AI2026-06-09NEWSen作者: Jianwei Tai

详细信息

来源站点
ArXiv CS.AI
作者
Jianwei Tai
文章类型
NEWS
语言
en
发布日期
2026-06-09

摘要

arXiv:2606.09315v1 Announce Type: cross Abstract: BCI-to-agent pipelines turn decoded neural activity into an authorization channel for tool-use agents, exposing a new attack surface we call \emph{brain-prompt injection}: signal-side perturbations, context-only injections, and adaptive dual-decoder attacks can all change the routed action while EEG-side or text-side monitors remain blind. Route safety in this stack depends on what the audit log can observe, not on decoder accuracy or agreement alone. We define a Route-Safety Audit Contract: a minimal log schema, denominator hierarchy, and endpoint specification, and prove an audit-schema separation theorem together with a C3 attacked-dependence decomposition; clean agreement and marginal robustness do not identify the joint term that controls C3 routing.

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