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Results for “Trust boundaries”
5 publicationsSecurity evidence for AI release decisions
A release approval should identify the changed application, the claims its tests support and the evidence that expires when a model, prompt, data path or runtime changes.
AI systems · By Cloud Security DeskWhere fine tuning data needs a trust boundary
A training dataset can preserve its checksum and still teach the wrong behavior. Admission controls need to separate origin, transformation, approved use and the model change they produce.
AI systems · By Cloud Security DeskThe telemetry collector is part of the evidence boundary
Review sender identity, tenant routing, processing and export as separate trust boundaries before treating collected telemetry as dependable evidence.
Detection & response · OpenTelemetry · By Cloud Security DeskModel output needs its own trust boundary
A model can produce valid JSON containing an unauthorized identifier, an unsafe link or text that a renderer interprets as code. The application consuming that output owns the next trust decision.
AI systems · OpenAI · By Cloud Security DeskQwen3.8-Flash-Next and GLM-5.3-Flash share a 3:1 long-context pattern
Both models replace most conventional attention layers with recurrent state and reserve sparse attention for periodic retrieval. Their differences lie in where they place capacity, how much neural computation they activate, and what their serving stacks must keep trustworthy.
AI systems · Resilience · By Umair Akbar and Ahmed Elshekh