Securing Azure AI Workloads: Community Support Session
Following the publication of the technical article “Securing Azure AI Workloads Against Prompt Injection, Data Exposure, and Unsafe Agentic Access,” this online community support activity is available for professionals who want to discuss practical security questions around Azure AI workloads.
The focus is not on general AI awareness. The support is intended for technical readers, cloud architects, developers, AI engineers, and security professionals who are reviewing how Azure AI applications interact with enterprise data, APIs, automation, identities, retrieval sources, and hybrid systems.
Community members can raise questions or discussion points around prompt injection, retrieval boundaries, data exposure, unsafe agentic access, managed identities, private connectivity, tool and API permissions, logging, monitoring, and governance. The goal is to help participants think through AI workload security as a full architecture and operating model issue, not only as a model configuration topic.
This activity is suitable for professionals who are designing, reviewing, securing, or governing AI-enabled workloads in Azure and want practical guidance on reducing security risks before these systems move deeper into production use.
Led by:
Waseem Awwad – Microsoft MVP, Security and Azure
Format:
Online community technical support
Technology areas:
Cloud Security
Azure Hybrid & Migration
Relevant topics:
Azure AI workload security
Prompt injection
Data exposure
Unsafe agentic access
Retrieval boundaries
Managed identities
Private connectivity
Tool and API permissions
Logging and monitoring
Governance for AI-enabled workloads