# gcp
標記為「gcp」的 52 篇文章
Cloud AI Security Practice Exam 1
Practice exam covering AWS Bedrock, Azure OpenAI, and GCP Vertex AI security assessments.
Advanced Cloud AI Security Assessment
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.
Cloud AI Security Assessment
Test your knowledge of AWS, Azure, and GCP AI service security with 15 intermediate-level questions covering cloud-specific attack surfaces and misconfigurations.
Capstone: Cloud AI Security Assessment
Assess AI deployment security across AWS, Azure, and GCP cloud platforms, producing a comprehensive cloud AI security assessment report.
Cloud ML Platform Security (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.
IAM Best Practices for 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 for Cloud AI Security
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.
GCP IAM for AI Services
IAM exploitation patterns for GCP AI services: service account exploitation, Workload Identity abuse, VPC Service Controls for AI, and privilege escalation through Vertex AI permissions.
GCP AI Services Security Overview
Red team methodology for GCP AI services including Vertex AI, Model Garden, and AI Platform: service enumeration, service account exploitation, and attack surface mapping.
Model Garden Risks
Security risks of deploying models from GCP Model Garden: third-party model trust, model provenance verification, deployment from untrusted sources, and supply chain attack vectors.
Vertex AI Attack Surface
Red team methodology for Vertex AI: prediction endpoint abuse, custom training security gaps, feature store poisoning, model monitoring evasion, and pipeline exploitation.
GCP AI Platform Threat Analysis
Threat analysis of GCP AI platform services including AutoML, custom training, and prediction endpoints.
GCP Model Garden Security
Security assessment of GCP Model Garden including model deployment, versioning, and access control.
GCP Vertex AI Agent Builder Security
Security assessment of Google Vertex AI Agent Builder including grounding, tool use, and safety settings.
GCP Vertex AI Security Assessment
Security assessment methodology for GCP Vertex AI covering IAM bindings, VPC Service Controls, Model Garden risks, and detection strategies for Gemini API abuse.
GCP Vertex AI Security Guide
Security guide for GCP Vertex AI including model garden, endpoints, and Gemini API security.
Cloud AI Security
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.
Security Controls Comparison Matrix
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.
Cloud AI Infrastructure Attacks
Security assessment of cloud-hosted AI/ML platforms including AWS SageMaker, Azure ML, and GCP Vertex AI -- IAM misconfigurations, model theft, and data exposure.
GCP Vertex AI Attack Surface
Security assessment of Google Cloud Vertex AI -- service account exploitation, endpoint security, notebook attacks, and pipeline manipulation.
Cloud AI Security Cheat Sheet
Quick reference comparing AI security controls across AWS, Azure, and GCP -- covering IAM, networking, encryption, monitoring, and AI-specific services.
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.
Cloud AI Platform Walkthroughs
Hands-on walkthroughs for red teaming AI systems deployed on major cloud platforms: AWS Bedrock, Azure OpenAI, Google Vertex AI, and Hugging Face Hub.
Vertex AI Red Team Walkthrough
End-to-end walkthrough for red teaming Google Cloud Vertex AI: prediction endpoint testing, Model Garden security assessment, Feature Store probing, and Cloud Logging analysis.
Vertex AI Red Team Walkthrough (Platform Walkthrough)
Complete red team walkthrough for Google Vertex AI: testing prediction endpoints, Model Garden assessments, Feature Store probing, and exploiting Vertex AI Agents and Extensions.
Testing GCP Vertex AI Deployments
Red team testing guide for models deployed via GCP Vertex AI including Model Garden and custom endpoints.
Cloud AI 安全 Practice Exam 1
Practice exam covering AWS Bedrock, Azure OpenAI, and GCP Vertex AI security assessments.
進階 Cloud AI 安全 評量
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.
紅隊演練雲端 AI 服務：實務指南
在 AWS、Azure 與 GCP 上紅隊演練 AI 服務的實務指南——涵蓋共享責任邊界、服務特定攻擊面與雲端原生安全控制。
Capstone: Cloud AI 安全 評量
Assess AI deployment security across AWS, Azure, and GCP cloud platforms, producing a comprehensive cloud AI security assessment report.
Cloud ML Platform 安全 (AWS/Azure/GCP)
安全 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.
IAM Best Practices for 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 模型 for Cloud AI 安全
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.
GCP IAM for AI Services
IAM exploitation patterns for GCP AI services: service account exploitation, Workload Identity abuse, VPC Service Controls for AI, and privilege escalation through Vertex AI permissions.
GCP AI 服務安全概觀
GCP AI 服務（包括 Vertex AI、Model Garden 與 AI Platform）之紅隊方法論：服務枚舉、服務帳號攻擊，以及攻擊面繪製。
Model Garden 風險
自 GCP Model Garden 部署模型之安全風險：第三方模型信任、模型來源驗證、自未受信任來源之部署，與供應鏈攻擊向量。
Vertex AI 攻擊面
為 Vertex AI 之紅隊方法論：預測端點濫用、自訂訓練安全缺口、特徵儲存投毒、模型監控逃避與管線利用。
GCP AI Platform Threat Analysis
Threat analysis of GCP AI platform services including AutoML, custom training, and prediction endpoints.
GCP 模型 Garden 安全
安全 assessment of GCP 模型 Garden including model deployment, versioning, and access control.
GCP Vertex AI 代理 Builder 安全
安全 assessment of Google Vertex AI 代理 Builder including grounding, tool use, and safety settings.
GCP Vertex AI 安全 評量
安全 assessment methodology for GCP Vertex AI covering IAM bindings, VPC Service Controls, 模型 Garden risks, and detection strategies for Gemini API abuse.
GCP Vertex AI 安全 指南
安全 guide for GCP Vertex AI including model garden, endpoints, and Gemini API security.
雲端 AI 安全
給紅隊員的雲端 AI 安全完整概覽：共同責任模型、跨 AWS、Azure 與 GCP AI 服務的攻擊面、模型 API、資料管線與推論端點的威脅模型。
安全 Controls Comparison Matrix
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.
雲端 AI 基礎設施攻擊
雲端託管 AI/ML 平台的安全評估，包含 AWS SageMaker、Azure ML 與 GCP Vertex AI——IAM 設定錯誤、模型竊取與資料暴露。
GCP Vertex AI 攻擊 Surface
安全 assessment of Google Cloud Vertex AI -- service account exploitation, endpoint security, notebook attacks, and pipeline manipulation.
雲端 AI 安全速查表
跨 AWS、Azure 與 GCP 的 AI 安全控制快速參考——涵蓋 IAM、網路、加密、監控與 AI 特定服務。
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.
雲端 AI 平台導覽
在主要雲端平台上紅隊演練 AI 系統的動手導覽：AWS Bedrock、Azure OpenAI、Google Vertex AI 與 Hugging Face Hub。
Vertex AI 紅隊 導覽
End-to-end walkthrough for red teaming Google Cloud Vertex AI: prediction endpoint testing, 模型 Garden security assessment, Feature Store probing, and Cloud Logging analysis.
Vertex AI 紅隊 導覽 (Platform 導覽)
Complete red team walkthrough for Google Vertex AI: testing prediction endpoints, 模型 Garden assessments, Feature Store probing, and exploiting Vertex AI 代理s and Extensions.
Testing GCP Vertex AI Deployments
Red team testing guide for models deployed via GCP Vertex AI including 模型 Garden and custom endpoints.