AI Activity Investigations: New Microsoft Playbook
Summary
Microsoft has published a new investigator playbook to help security teams reconstruct AI-related activity across Microsoft 365 Copilot and Azure AI services. The guidance brings together telemetry, KQL queries, schema references, and detection logic across Purview, Defender, and Sentinel so investigators can move from isolated signals to a clear incident timeline.
Introduction
As AI tools become part of daily business workflows, security teams need reliable ways to investigate what happened inside them. Microsoft’s new playbook for Microsoft 365 Copilot and Azure AI services is designed to help incident responders reconstruct AI activity using telemetry already available across Microsoft security tools.
What’s new
Microsoft has released an AI investigation playbook that provides a structured methodology for analyzing AI-related activity. The playbook is built around a scope → context → signal model:
- Scope: Identify who interacted with the AI system, when the activity occurred, and which service was involved.
- Context: Determine what resources were accessed, what data may have been exposed, and whether the behavior matched expected usage.
- Signal: Evaluate alerts and detections such as prompt injection attempts, anomalous usage, or credential exposure within the full activity chain.
The playbook also consolidates practical investigation resources into one model, including:
- Schema references
- KQL queries
- Detection patterns and logic
- Configuration guidance across Microsoft security products
Microsoft says this approach works across Microsoft Purview, Microsoft Defender, and Microsoft Sentinel, helping teams reduce ad hoc pivots between tools.
Why this matters for security teams
AI interactions generate metadata-rich telemetry, including identity, timestamps, and resource access details. That makes it possible to reconstruct events—but only if teams have a repeatable process.
For security operations and incident response teams, this playbook helps answer critical questions:
- Who used the AI system?
- What data was accessed during the interaction?
- Was the activity authorized?
- Does the behavior indicate normal use, a policy violation, or a possible compromise?
The guidance also extends to agent-based systems, where investigators may need to review which agents are deployed, how they are configured, and what data they are permitted to access.
Next steps
IT and security administrators should review the playbook and validate that the required telemetry and configurations are enabled across their Microsoft security stack. Teams using Microsoft 365 Copilot or Azure AI services should also consider updating investigation procedures to include AI-specific signals and response workflows.
As AI adoption grows, the ability to reconstruct AI activity is becoming a core incident response capability—not a nice-to-have. Microsoft’s playbook is a practical step toward making those investigations more consistent and defensible.
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