# model-serving
標記為「model-serving」的 17 篇文章
DNS Rebinding Attacks Against AI Services
Exploiting DNS rebinding to bypass network controls and access internal AI model serving endpoints, training dashboards, and GPU management interfaces
Security Comparison of Model Serving Frameworks
In-depth security analysis of TorchServe, TensorFlow Serving, Triton Inference Server, and vLLM for production AI deployments
Model Serving Infrastructure Attacks
Attacking model serving infrastructure including inference servers, load balancers, and GPU schedulers.
Triton Inference Server Security
Security hardening for NVIDIA Triton Inference Server deployments including model repository protection and API security.
Lab: Model Serving Framework Attacks
Exploit vulnerabilities in TensorFlow Serving, TorchServe, and Triton Inference Server, targeting model loading, API endpoints, and management interfaces.
Model Serving Security
Security hardening for model serving infrastructure — covering vLLM, TGI, Triton Inference Server configuration, API security, resource isolation, and deployment best practices.
GCP Vertex AI Security Testing
End-to-end walkthrough for security testing Vertex AI deployments on Google Cloud: endpoint enumeration, IAM policy analysis, model serving exploitation, pipeline assessment, and Cloud Audit Logs review.
Replicate API Security Testing
End-to-end walkthrough for security testing models on Replicate: model enumeration, prediction API exploitation, webhook security, Cog container assessment, and billing abuse prevention.
章節評量：LLMOps 安全
15 題校準評量，測試你對 LLMOps 安全的理解——模型服務、推論安全、快取風險與 ML 管線安全。
DNS Rebinding 攻擊s Against AI Services
利用ing DNS rebinding to bypass network controls and access internal AI model serving endpoints, training dashboards, and GPU management interfaces
安全 Comparison of 模型 Serving Frameworks
In-depth security analysis of TorchServe, TensorFlow Serving, Triton Inference Server, and vLLM for production AI deployments
模型 Serving Infrastructure 攻擊s
攻擊ing model serving infrastructure including inference servers, load balancers, and GPU schedulers.
Triton Inference Server 安全
安全 hardening for NVIDIA Triton Inference Server deployments including model repository protection and API security.
實驗室: 模型 Serving Framework 攻擊s
利用 vulnerabilities in TensorFlow Serving, TorchServe, and Triton Inference Server, targeting model loading, API endpoints, and management interfaces.
模型服務安全
模型服務基礎設施的安全強化——涵蓋 vLLM、TGI、Triton 推論伺服器設定、API 安全、資源隔離與部署最佳實務。
GCP Vertex AI 安全 Testing
End-to-end walkthrough for security testing Vertex AI deployments on Google Cloud: endpoint enumeration, IAM policy analysis, model serving exploitation, pipeline assessment, and Cloud Audit Logs review.
Replicate API 安全 Testing
End-to-end walkthrough for security testing models on Replicate: model enumeration, prediction API exploitation, webhook security, Cog container assessment, and billing abuse prevention.