AI-driven cybersecurity systems often fail under cross-environment deployment due to fragmented, event-centric telemetry representations. We introduce the Canonical Security Telemetry Substrate (CSTS), an entity-relational abstraction that enforces identity persistence, typed relationships, and temporal state invariants. Across heterogeneous environments, CSTS improves cross-topology transfer for identity-centric detection and prevents collapse under schema perturbation. For zero-day detection, CSTS isolates semantic orientation instability as a modeling, not schema, phenomenon, clarifying layered portability requirements.

翻译：AI驱动的网络安全系统常因碎片化、以事件为中心的遥测表示方式，在跨环境部署时遭遇失败。我们提出规范安全遥测基板（CSTS），这是一种实体关系抽象，强制执行身份持久性、类型化关系和时间状态不变性。在异构环境中，CSTS提升了以身份为中心的检测的跨拓扑迁移能力，并防止在模式扰动下发生系统崩溃。针对零日检测，CSTS将语义定向不稳定性隔离为建模现象而非模式现象，从而厘清了分层可移植性需求。