多租戶 AI 服務隔離失敗

Risk Description

In multi-tenant AI service platforms, inadequate isolation mechanisms between different tenants models, data, and inference environments lead to cross-tenant information leakage or resource interference. Examples include residual data in shared GPU memory, information leaks from shared model caches, or service quality degradation from resource contention. Cloud AI platform multi-tenant architectures make this issue particularly acute.