# azure-ml
標記為「azure-ml」的 10 篇文章
Cloud AI Forensics: Azure
Forensic investigation techniques for Azure AI services including Azure OpenAI, Azure ML, and Cognitive Services with diagnostic logging and evidence collection.
Azure ML Exploitation
Red team attack methodology for Azure Machine Learning: workspace security, compute instance attacks, pipeline poisoning, model registry tampering, and data store exploitation.
Azure AI Services Security Overview
Red team methodology for Azure AI services including Azure OpenAI, Azure ML, AI Studio, and Cognitive Services: service enumeration, managed identity abuse, and attack surface mapping.
Azure ML Attack Surface
Security assessment of Azure Machine Learning -- managed identity exploitation, workspace security, compute instance attacks, and endpoint vulnerabilities.
Azure ML Security Testing
End-to-end walkthrough for security testing Azure Machine Learning endpoints: workspace enumeration, managed online endpoint exploitation, compute instance assessment, data store access review, and Azure Monitor analysis.
Cloud AI Forensics: Azure
Forensic investigation techniques for Azure AI services including Azure OpenAI, Azure ML, and Cognitive Services with diagnostic logging and evidence collection.
Azure ML 利用ation
Red team attack methodology for Azure Machine Learning: workspace security, compute instance attacks, pipeline poisoning, model registry tampering, and data store exploitation.
Azure AI 服務安全概觀
為 Azure AI 服務之紅隊方法論，含 Azure OpenAI、Azure ML、AI Studio 與 Cognitive Services：服務列舉、受管身分濫用與攻擊面對應。
Azure ML 攻擊 Surface
安全 assessment of Azure Machine Learning -- managed identity exploitation, workspace security, compute instance attacks, and endpoint vulnerabilities.
Azure ML 安全 Testing
End-to-end walkthrough for security testing Azure Machine Learning endpoints: workspace enumeration, managed online endpoint exploitation, compute instance assessment, data store access review, and Azure Monitor analysis.