Having operated Microsoft Sentinel in a large, multi-cloud environment for over two years, I have a complex relationship with the Fusion detection rules. The short answer is yes, they can generate critically useful incidents, but they operate more as a high-fidelity, low-volume early warning system than a primary detection workhorse. Their utility is entirely dependent on the maturity and scope of your data ingestion.
The core value proposition of Fusion is its ability to perform cross-product, cross-table correlation that would be incredibly labor-intensive to build and maintain as custom scheduled analytics rules. It looks for weak signals across disparate data sources—like an Azure AD identity risk event followed shortly by an anomalous Azure resource deployment—and stitches them into a single incident with a documented MITRE ATT&CK tactic.
However, the out-of-the-box experience often leads to frustration for several reasons:
* **Data Source Dependency:** Fusion scenarios are only active if you are ingesting the specific, required data types. A scenario requiring "Azure Activity" and "Microsoft Defender for Cloud" will not trigger if you are only ingesting one of them. The portal's interface for which scenarios are active can be unclear.
* **Alert Fatigue vs. Critical Ignition:** In environments with broad data ingestion, you may see a handful of Fusion incidents per month. In my experience, 80% of these were false positives or required significant investigation. However, the remaining 20% represented sophisticated, multi-stage attack patterns we would have otherwise missed by reviewing discrete alerts. It's a high-signal, high-investment tool.
* **Limited Customization:** While you can disable specific Fusion scenarios, you cannot tune their sensitivity thresholds or logic directly within Sentinel. This black-box nature makes it difficult to adapt them to your specific risk model without resorting to building your own parallel logic using scheduled analytics rules.
A concrete example from a recent incident response: Fusion generated an incident titled "Suspected credential theft followed by anomalous Azure AD Graph API call." It correlated:
1. A medium-risk user risk event detected by Azure AD Identity Protection (source: `AADUserRiskEvents`).
2. An anomalous application consent grant event via the Microsoft Graph API (source: `AuditLogs`).
This single incident pointed my investigation directly to a compromised service principal attempting to escalate permissions, a chain I would have had to piece together manually from two separate alert queues. The investigation time was cut significantly.
For teams starting with Sentinel, I recommend:
* First, map your enabled Fusion scenarios against your connected data sources in a spreadsheet to set realistic expectations.
* Treat Fusion incidents as P1 for investigation due to their cross-domain nature, but ensure your SOC has the context to investigate them (e.g., knowledge of Azure AD, cloud infrastructure).
* Consider building simplified, more verbose custom analytics rules that mimic the Fusion scenarios you find most valuable, giving you greater control and visibility into the detection logic while you build confidence in the system.
Ultimately, Fusion is not a "set and forget" detection layer. It's a specialized correlation engine that becomes increasingly valuable as your telemetry coverage expands across identity, cloud infrastructure, and endpoint security. Its low volume is a feature, not a bug, but it requires a SOC capable of deep investigation to realize its value.
-jf
That data source dependency is a huge pain point. It feels like you need a near-perfect, enterprise-grade data ingestion setup just to get Fusion off the ground. I've seen teams with decent coverage still miss events because one required log table had a slight schema mismatch or was filtered out during ingestion.
The high-fidelity claim rings true, though. When it *does* fire, you're usually looking at something genuinely suspicious that slipped past your other layered defenses. I've had one catch a compromised service principal attempting lateral movement between subscriptions, stitching together the anomalous sign-in from an unusual IP and the subsequent, frantic creation of new VMs. Without that cross-table correlation, those two events reviewed in isolation might have been dismissed as noise.
Do you find tuning the alert logic possible, or is it mostly a black box you just have to enable/disable? I've always wondered if you can adjust the timing windows or sequence logic to better fit your environment's normal "noise" patterns.
pipeline all the things