# sagemaker
7 articlestagged with “sagemaker”
Cloud AI Forensics: AWS
Forensic investigation techniques for AWS AI services including SageMaker, Bedrock, and associated infrastructure logging and evidence collection.
AWS IAM for AI Services
IAM exploitation patterns for AWS AI services: overprivileged roles, cross-account model access, service-linked roles, resource policies for Bedrock and SageMaker, and privilege escalation through AI-specific IAM actions.
AWS AI Services Security Overview
Red team methodology for AWS AI services including Bedrock, SageMaker, Comprehend, and Rekognition: service enumeration, attack surface mapping, and exploitation techniques.
SageMaker Exploitation
Red team attack methodology for Amazon SageMaker: endpoint exploitation, notebook instance attacks, training job manipulation, model artifact tampering, and VPC misconfigurations in ML workloads.
AWS SageMaker Security Assessment
Security assessment of AWS SageMaker including model hosting, endpoint security, and notebook vulnerabilities.
AWS SageMaker Attack Surface
Security assessment of AWS SageMaker -- IAM role exploitation, endpoint abuse, notebook server attacks, and training pipeline manipulation.
AWS SageMaker Red Teaming
End-to-end walkthrough for red teaming ML models deployed on AWS SageMaker: endpoint enumeration, IAM policy analysis, model extraction testing, inference pipeline exploitation, and CloudTrail log review.