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The Sensors experience covers sensor status and health, sensor details, updates for v2.x and v3.x, and proxy configuration. A sensor details pane exposes health information and provides paths to manage configuration or reopen closed health issues.
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Defender for Identity supports excluding specific IP addresses, computers, domains, or users from a number of detections. Microsoft recommends Defender XDR alert-tuning rules instead of exclusions because tuning supports more granular conditions and lets analysts review tuned alerts.
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The Defender for Identity About page reports the workspace ID and name, latest available sensor version, assigned license count, and identities active during the preceding 28 days.
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Microsoft documents sensor removal for domain-controller decommissioning, orphaned or duplicate sensor cleanup, and intentionally stopping monitoring on a server. Deleting a v3.x sensor removes its software and stops Defender for Identity monitoring on that domain controller.
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Defender for Identity scoping can focus monitoring and visibility on specified Active Directory domains or organizational units. Scoped access is configured with a custom Microsoft Defender unified RBAC role that assigns users or Entra groups to the selected directory scope.
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Defender for Identity VPN integration is supported only by sensor v2.x. The integration listens to forwarded RADIUS accounting events and can add connection IP address and location context plus an abnormal-VPN-connection detection.
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Defender for Identity supports tagging accounts as sensitive or honeytokens and tagging devices as Exchange servers. Some detections depend on the sensitive tag, while any sign-in from a tagged honeytoken account triggers an alert.
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Custom correlation rules target accounts that do not share strong identifiers such as account ID, SID, object ID, or UPN.
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Defender for Identity notifications are supported only by sensor v2.x. The service can notify on health issues and security alerts through email or a Syslog server.
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Some Defender for Identity alerts use learning periods to build activity profiles and distinguish legitimate from suspicious behavior.
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