# model-serving
8 articlestagged with “model-serving”
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.