# Treat endpoint anomaly correlations as investigation leads

> What should an administrator establish before acting on an anomaly correlation group?

- Canonical URL: https://update.dsesecurity.com/updates/dse-20260909-263-treat-endpoint-anomaly-correlations-as-investigation-leads/
- Publisher: Detection Systems & Engineering (DSE Security)
- Author: DSE Security Editorial Team
- Published: 2026-09-10T00:27:33+00:00
- Modified: 2026-09-10T01:23:48+00:00
- Last reviewed by DSE: 2026-09-09
- Resource type: Guide
- DSE priority: Information
- Topics: Business Continuity, IT
- Reading time: 2 minutes

## What you need to know

What should an administrator establish before acting on an anomaly correlation group?

## Potentially affected

Check the reported anomaly, severity, first detection, and last occurrence. Identify the business workflow affected before deciding how much investigation priority the alert deserves.

## DSE recommendation

Write a testable explanation for the shared attribute instead of treating correlation as a demonstrated cause.

## Article

## Source facts

Advanced Analytics flags application hangs, crashes, and Stop Error Restarts. Its device correlation groups use shared attributes such as app version, driver update, operating system, or model, and show affected and at-risk devices. Cohorts are identified only for medium- and high-severity anomalies. The threshold-based model’s thresholds are predetermined rather than administrator-adjustable. [Microsoft Learn](https://learn.microsoft.com/en-us/intune/advanced-analytics/anomalies).

## Applicability

Check the reported anomaly, severity, first detection, and last occurrence. Identify the business workflow affected before deciding how much investigation priority the alert deserves.

## DSE recommendation

Write a testable explanation for the shared attribute instead of treating correlation as a demonstrated cause. Compare an affected example with a suitable unaffected one, and ask the relevant owner about recent changes. Use the device timeline and supporting resource evidence to challenge the explanation. Record competing causes and any missing observations rather than forcing every incident into the first suggested group.

## Verification

Reproduce the suspected failure in an approved test population and evaluate a bounded remedy there. Check that the relevant user workflow improves before expanding that remedy to devices merely classified as at risk. Revisit the anomaly report and retain the affected population, shared attribute, observation window, and outcome. If the evidence does not support the proposed cause, close or redirect that hypothesis without presenting the original correlation as a confirmed diagnosis.

## Official references

[Microsoft Learn: Anomalies Report for Proactive Device Issue Detection](https://learn.microsoft.com/en-us/intune/advanced-analytics/anomalies).

## Primary reference

- Name: Anomalies Report for Proactive Device Issue Detection - Microsoft Intune | Microsoft Learn
- Authority: Microsoft Learn
- URL: https://learn.microsoft.com/en-us/intune/advanced-analytics/anomalies
- Source publication date: Not stated by the source

## Citation and use

Preferred citation: “Treat endpoint anomaly correlations as investigation leads,” DSE Security, https://update.dsesecurity.com/updates/dse-20260909-263-treat-endpoint-anomaly-correlations-as-investigation-leads/
Publishing principles: https://update.dsesecurity.com/updates/dse-updates-editorial-methodology/
Usage and citation policy: https://update.dsesecurity.com/usage/
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