# aws
29 artikelengetagd met “aws”
Cloud-AI-forensiek: AWS
Forensische onderzoekstechnieken voor AWS AI-diensten waaronder SageMaker, Bedrock en bijbehorende infrastructuurlogging en bewijsverzameling.
Cloud-AI-beveiliging oefenexamen 1
Practice exam covering AWS Bedrock, Azure OpenAI, and GCP Vertex AI security assessments.
Geavanceerd beveiligingsassessment van cloud-AI
15-question advanced assessment covering cloud AI attack surfaces across AWS, Azure, and GCP: guardrail bypass, knowledge base exploitation, managed identity abuse, model customization risks, and multi-cloud attack paths.
Beveiligingsassessment van cloud-AI
Test your knowledge of AWS, Azure, and GCP AI service security with 15 intermediate-level questions covering cloud-specific attack surfaces and misconfigurations.
Capstone: beveiligingsassessment van cloud-AI
Assess AI deployment security across AWS, Azure, and GCP cloud platforms, producing a comprehensive cloud AI security assessment report.
Beveiliging van cloud-ML-platforms (AWS/Azure/GCP)
Security comparison of cloud ML platforms including AWS SageMaker, Azure Machine Learning, and Google Vertex AI. IAM configuration, data security, model serving, and platform-specific attack surfaces.
Aanvalsoppervlak van Bedrock
Comprehensive red team methodology for Amazon Bedrock: model invocation API abuse, guardrails bypass techniques, custom model endpoint exploitation, IAM misconfigurations, knowledge base poisoning, and Bedrock Agents exploitation.
AWS IAM voor 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.
Overzicht van AWS AI Services-beveiliging
Red team methodology for AWS AI services including Bedrock, SageMaker, Comprehend, and Rekognition: service enumeration, attack surface mapping, and exploitation techniques.
Misbruik van SageMaker
Red team attack methodology for Amazon SageMaker: endpoint exploitation, notebook instance attacks, training job manipulation, model artifact tampering, and VPC misconfigurations in ML workloads.
Beveiligingsassessment van AWS Bedrock-agents
Security assessment of AWS Bedrock Agents including action groups, knowledge bases, and guardrail configurations.
Beveiliging van AWS Bedrock Agents
Security assessment of AWS Bedrock Agents including action groups, knowledge bases, and guardrail integration.
Red team-testen van AWS Bedrock Guardrails
Red team testing of AWS Bedrock Guardrails including content filters, denied topics, and PII handling.
AWS Bedrock Security Deep Dive
Geavanceerde beveiligingsbeoordeling van AWS Bedrock met aandacht voor controles op modelaanroepen, het testen van guardrails-bypasses, VPC-configuraties en red team-methodologieën voor foundation-model-API's.
Beveiligingsgids voor AWS Bedrock
Comprehensive security guide for AWS Bedrock including guardrails, IAM policies, and model access controls.
Beveiligingsassessment van AWS SageMaker
Security assessment of AWS SageMaker including model hosting, endpoint security, and notebook vulnerabilities.
IAM-best practices voor cloud-AI-services
Cross-cloud IAM best practices for securing AI services on AWS, Azure, and GCP, covering least privilege, service identity management, cross-account access, and policy automation.
Shared responsibility-model voor cloud AI-beveiliging
Understanding the division of security responsibilities between cloud providers and customers for AI/ML workloads across AWS, Azure, and GCP, with specific guidance for LLM deployments.
Beveiliging van cloud-AI
Comprehensive overview of cloud AI security for red teamers: shared responsibility models, attack surfaces across AWS, Azure, and GCP AI services, threat models for model APIs, data pipelines, and inference endpoints.
Vergelijkingsmatrix van beveiligingscontroles
Side-by-side comparison of AWS, Azure, and GCP AI security controls: IAM patterns, content filtering, guardrails, network isolation, logging, and threat detection across cloud providers.
Aanvallen op cloud-AI-infrastructuur
Beveiligingsbeoordeling van cloud-gehoste AI/ML-platforms zoals AWS SageMaker, Azure ML en GCP Vertex AI -- IAM-misconfiguraties, modeldiefstal en datablootstelling.
Het aanvalsoppervlak van AWS SageMaker
Beveiligingsbeoordeling van AWS SageMaker -- exploitatie van IAM-rollen, misbruik van endpoints, aanvallen op notebookservers en manipulatie van trainingspipelines.
Lab: AWS Bedrock-guardrails testen
Hands-on lab for systematically testing and bypassing AWS Bedrock's built-in guardrails including content filters, denied topics, and word filters.
Cheatsheet voor cloud-AI-beveiliging
Snelle referentie die AI-beveiligingscontroles vergelijkt tussen AWS, Azure en GCP -- met IAM, netwerken, encryptie, monitoring en AI-specifieke diensten.
Redteaming van AWS SageMaker
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.
Walkthrough: AWS Bedrock red team
Complete guide to red teaming AWS Bedrock deployments: testing guardrails bypass techniques, knowledge base data exfiltration, agent prompt injection, model customization abuse, and CloudTrail evasion.
Walkthrough: AWS Bedrock red team (platform-walkthrough)
End-to-end walkthrough for red teaming AI systems on AWS Bedrock: setting up access, invoking models via the Converse API, testing Bedrock Guardrails, exploiting knowledge bases, and analyzing CloudTrail logs.
Walkthroughs van cloud-AI-platforms
Hands-on walkthroughs for red teaming AI systems deployed on major cloud platforms: AWS Bedrock, Azure OpenAI, Google Vertex AI, and Hugging Face Hub.
AWS Bedrock-deployments testen
Red team testing guide for models deployed via AWS Bedrock including guardrails and access controls.