# cloud-ai
22 artikelengetagd met “cloud-ai”
Oefenexamen 2: geavanceerde AI-beveiliging
25-question advanced practice exam covering multimodal attacks, training pipeline security, cloud AI security, forensics, and governance.
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.
Geavanceerd beveiligingsassessment van cloud-AI (assessment)
Advanced assessment on multi-cloud AI security, IAM misconfigurations, and endpoint hardening.
Studiegids cloud-AI-beveiliging
Study guide for cloud AI security covering AWS, Azure, GCP, and multi-cloud assessment strategies.
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.
Red team-testen van AWS Bedrock Guardrails
Red team testing of AWS Bedrock Guardrails including content filters, denied topics, and PII handling.
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.
Beveiligingsassessment van Azure AI Studio
Security assessment of Azure AI Studio including prompt flow, model catalog, and deployment security.
Beveiligingsgids voor Azure OpenAI
Security guide for Azure OpenAI Service including content filtering, managed identity, and network isolation.
Dataresidentie en -soevereiniteit bij cloud-AI
Managing data residency and sovereignty requirements for cloud-based AI systems across jurisdictions.
IAM-misconfiguraties bij cloud-AI
Common IAM misconfigurations in cloud AI services and their exploitation for unauthorized model access.
Logging en forensics voor cloud-AI
Setting up comprehensive logging and forensic capabilities for cloud-deployed AI systems.
Beveiliging van cloud-modelendpoints
Securing model endpoints in cloud deployments including authentication, authorization, and traffic management.
Beveiligingsoverzicht van GCP AI-services
Red team methodology for GCP AI services including Vertex AI, Model Garden, and AI Platform: service enumeration, service account exploitation, and attack surface mapping.
Dreigingsanalyse van GCP AI Platform
Threat analysis of GCP AI platform services including AutoML, custom training, and prediction endpoints.
Beveiligingsgids voor GCP Vertex AI
Security guide for GCP Vertex AI including model garden, endpoints, and Gemini API security.
Strategie voor multi-cloud AI-beveiliging (cloud AI-beveiliging)
Security strategy for organizations using AI services across multiple cloud providers.
Beveiligingsoverwegingen voor serverless AI
Security considerations for AI workloads running on serverless platforms including Lambda, Cloud Functions, and Azure Functions.
AI Infrastructure Exploitation
Methodologie voor het exploiteren van GPU-clusters, model-serving-frameworks (Triton, vLLM, Ollama), Kubernetes ML-platforms, cloud-AI-services en cost-amplification-aanvallen.
Lab: ontwijking van het Azure-contentfilter
Hands-on lab for mapping and testing Azure OpenAI Service content filtering categories, severity levels, and bypass techniques.
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.