Thoughts on the new Identity Threat Protection connector - does it justify the cost?

Having recently completed a phased migration of a multi-cloud security operations setup into Microsoft Sentinel, the announcement of the new Identity Threat Protection connector for Microsoft Entra ID (formerly Azure AD) presented a compelling, yet costly, decision point. My team and I have been evaluating it in a production-like lab environment for the past quarter. The core question is whether the depth of integration and the specific telemetry it provides offer a tangible enough security return to offset the additional licensing and ingestion costs, especially for organizations already invested in a tiered Entra ID plan and a robust Sentinel instance.

From a technical integration standpoint, the connector is undeniably powerful. It moves beyond simple IdentityProtectionLogs by ingesting risk detections and user risk profiles directly into Sentinel as dedicated table sets (`IdentityProtectionLogs_CL` is the legacy, `IdentityUserRiskEvents_CL` and `IdentityRiskEvents_CL` are new). This allows for correlation with other data sources like Defender for Endpoint or custom Office 365 analytics in a way that was previously more cumbersome. For example, you can now more easily build a detection rule that triggers not just on a risky sign-in, but on a *sequence* of a risky sign-in followed by anomalous mailbox activity from the same user principal.

However, the justification hinges entirely on your existing security posture and the granularity of automation you require. Consider the following cost-analysis scenario:

* **Baseline Cost:** Assume you are already on Entra ID P2 ($9/user/month) and Sentinel is ingesting your core logs (Audit, SignInLogs). Your current detection rules use the limited risk indicators available in the SignInLogs schema.
* **Added Cost:** The ITP connector requires **Entra ID P2**. It also significantly increases log volume into your Sentinel workspace. In our test, enabling all risk event types led to a 12-15% increase in overall daily GB ingestion. At Sentinel's pay-as-you-go ingestion rates, this can be substantial.
* **Value Proposition:** The automation and orchestration playbook possibilities are the true differentiator. You can build automated investigation and response workflows that are context-aware. For instance:

```kql
IdentityUserRiskEvents_CL
| where RiskLevel == "high"
| join (SigninLogs
| where TimeGenerated > ago(1h)
| project UserPrincipalName, IPAddress, DeviceDetail, RiskDetail) on $left.UserPrincipalName == $right.UserPrincipalName
| extend RiskEvent = pack("UserRiskEvent", RiskEventType, "SignInRisk", RiskDetail)
| summarize RiskEvents = make_list(RiskEvent), LatestIP = arg_max(TimeGenerated, IPAddress) by UserPrincipalName
```

This query, feeding into an automation rule with a playbook, could automatically trigger a tier-2 analyst review, force a password reset via Graph API, and even temporarily restrict access to specific Azure resources if the user's context matches a high-value asset group.

The pitfalls are predictable but important:
* **Alert Fatigue:** Without careful tuning of the risk detection policies within Entra ID itself, you will flood your SOC with medium/low-risk events that the connector dutifully ingests.
* **Cost Sprawl:** The connector's value is in correlation, but that often means you are incentivized to ingest *more* data (Defender, Office, etc.) to make the most of it, creating a compounding cost effect.
* **Vendor Lock-in:** Your automated playbooks become deeply tied to the Microsoft Graph API and the specific schema of these Sentinel tables, making a future platform shift more complex.

In conclusion, the connector does not justify its implicit cost for organizations with a basic SOC or those already using a third-party Identity Threat Detection and Response (ITDR) solution. However, for a mature Azure-native shop running a sophisticated, automation-driven SOC that is already all-in on the Microsoft security stack, the depth of integration and the potential for highly contextual, automated response workflows can provide a measurable reduction in mean time to respond (MTTR) to identity-based attacks. The justification comes not from the connector alone, but from the advanced automation it enables. My recommendation is to prototype a critical use case—like automated response to a high-risk user compromise—in a lab, measure the increased ingestion volume, and then model the cost against the potential reduction in breach impact.