Unify in Kaseya MDR

Unify is a correlation capability used by Kaseya MDR to associate identity, device, and activity data across connected platforms and help determine whether observed activity can be associated with a known device tied to a specific account.

You may encounter Unify context across multiple Kaseya products. Depending on your environment, device‑to‑account associations may originate from connected platforms that provide identity, SaaS activity, or device telemetry, and then be surfaced within Kaseya MDR to support investigation.

In Kaseya MDR, Unify works by comparing metadata from multiple sources, including identity data, device visibility, and activity observed across connected platforms. By evaluating this data together, Unify assesses whether the activity and the device are likely related. Rather than making binary decisions, Unify produces a confidence score that reflects how strongly the available signals support a device‑to‑account association.

When sufficient correlation data exists, Unify helps analysts answer investigative questions such as:

  • Did this activity occur on a known device associated with the account?

  • Is the observed activity consistent with the expected user, device, and access context?

  • Is there insufficient or ambiguous data, meaning the device should remain unmapped and be observed further?

Unify evaluates multiple signals over time rather than relying on a single indicator.

Unify does not make enforcement decisions in Kaseya MDR. Its role is to enrich investigation context with device and identity associations so analysts can better evaluate observed activity.

Unify role within Kaseya MDR

Unify acts as a correlation and context layer that complements detection, alerting, and investigation workflows.

Using metadata available from connected platforms, Unify evaluates whether activity can be confidently associated with a specific device and account. When sufficient correlation exists, Unify presents that relationship during investigation so analysts can review activity with greater clarity.

This association is informational only and does not change how events are ingested or evaluated. Unify itself does not enforce actions; however, other modules or workflows may use Unify-derived context as an input when determining how to prioritize or respond to activity.

How Unify works

Unify evaluates whether activity and device context are related by comparing metadata observed across connected platforms. Using available identity data, device visibility, and activity signals, Unify continuously assesses whether an association between an account and a device can be established.

These evaluations occur over time rather than at a single point. As environments change and additional activity is observed, association outcomes may strengthen, weaken, or remain unresolved. This allows Unify to operate effectively in environments where identifiers may be shared or ambiguous, such as corporate networks, VPNs, or standardized device configurations. In these scenarios, activity that appears normal in isolation may become notable when evaluated in the context of known device usage and identity relationships.

Unify uses multiple signals and confidence scoring to determine the strength of an association between a device and an account. Rather than relying on a single indicator, Unify evaluates patterns across available data to determine whether sufficient correlation exists.

When sufficient data is available, Unify may present account suggestions representing likely device‑to‑account associations. When data is limited or ambiguous, devices may remain unmapped until additional signals are observed.

Detailed information about correlation signals, confidence scoring, and suggestion behavior is described in the following sections.

Using Unify in Kaseya MDR with other Kaseya security products

When Kaseya MDR is used alongside other Kaseya security products, Unify context can be shared across those products to support investigation.

You may already be familiar with Unify through other Kaseya security products. In those products, Unify is used to establish trust at the source by correlating activity with known, managed devices.

When Kaseya MDR is used alongside other products, Unify‑derived context becomes available within SIEM investigations. Depending on which products are in use, this context may originate from SaaS Alerts, Kaseya MDR, or both.

IMPORTANT  Whether configuration and response actions are performed in Kaseya MDR or in an individual product depends on whether the organization is licensed for SIEM. Organizations without a SIEM license continue to be configured and managed directly in the originating product.

Regardless of the source, Unify provides user and device context as part of cross‑domain investigation in Kaseya MDR. Investigation and response workflows operate consistently, using available context without requiring different configuration paths based on product combinations.

When Unify becomes available

Before Unify can provide meaningful correlation context, required data sources must be connected and actively providing data.

In Kaseya MDR, this typically requires both identity data and device visibility. Identity data is obtained from connected platforms, while device data depends on endpoints that are onboarded and reporting to Kaseya MDR.

Until sufficient identity and device data are available, Unify may have limited ability to associate activity with specific devices and accounts. In these cases, devices may remain unmapped or have lower confidence scores.

As additional data is collected over time, Unify continuously reassesses available signals and may begin to establish associations automatically without further configuration.

Data sources used for Unify context

Unify derives device and account context from data provided by supported integrated platforms connected to Kaseya MDR. This may include device inventory, identity attributes, and access‑related metadata originating from endpoint, security, and management tools.

In Kaseya MDR, Unify context depends on the availability of both identity data and device visibility. This typically includes identity data from connected platforms (such as directory or access providers) and device data from endpoints that are visible to Kaseya MDR.

If device data is not available (for example, if endpoints are not onboarded or agents are not deployed), or if identity data is limited, Unify may not be able to establish associations or may produce lower confidence results.

The specific data sources available depend on the integrations and configurations in your environment.

Correlation signals and confidence scoring

Unify evaluates multiple data points when associating activity with a device and account by comparing metadata observed across connected platforms. Common signals can include network attributes (such as public IP), device identifiers (such as device name or hostname), and identity-related attributes (such as recently observed user information), along with platform-specific metadata where available.

Based on the strength of matching signals, Unify assigns a confidence score indicating how likely it is that the activity occurred on the associated device.

Higher confidence scores indicate stronger correlation across multiple signals. Lower scores indicate partial or ambiguous matches that may require review.

Confidence scoring affects association decisions only and does not influence alert severity or detection outcomes directly. Other workflows may optionally use this context as an input when determining response behavior.

NOTE  Confidence scores reflect observed correlation based on available data. They are recalculated as new activity is observed and do not expire or decay automatically.

Understanding confidence scores and suggestions

Confidence scores represent the likelihood that observed activity is associated with a specific device based on available data. These scores are probabilistic rather than definitive.

Unify may present account suggestions when sufficient data exists to propose likely associations. A higher confidence score indicates stronger correlation, while lower scores indicate weaker or incomplete matches.

When Unify does not have enough data to meet the confidence threshold for suggestions, it may display No Suggestions. This does not indicate an error or misconfiguration, only that insufficient matching data is currently available.

As additional activity is observed and more correlation signals become available, suggestions may appear automatically without configuration changes.

Shared or ambiguous infrastructure

In environments where devices share common characteristics, such as standardized OS images, shared IP addresses, VPNs, or centralized networks, traditional correlation signals may be insufficient.

Where supported by integrated platforms, Unify can incorporate unique device identifiers (for example, Microsoft Entra device ID or similar identifiers provided by identity platforms) to improve correlation accuracy and reduce incorrect associations in shared or homogeneous environments.

Prerequisites for effective Unify association

For Unify to associate activity with devices and accounts, the following conditions must be met:

  • Relevant data sources are connected and actively providing telemetry

  • Organizations are correctly aligned across integrated platforms

  • Devices are visible to Kaseya MDR through supported integrations

  • Sufficient identity and device metadata exists to support correlation

If these conditions are not met, devices may appear unmapped or have lower confidence scores until additional data becomes available.

Investigation context and practical impact

During investigation, Unify enables analysts to:

  • Review whether activity occurred on a known managed device

  • Understand user‑to‑device relationships across platforms

  • Identify activity that appears legitimate but did not originate from an expected device

  • Highlight activity that would otherwise appear low‑risk

This context is especially valuable when reviewing token misuse, credential abuse, or access that bypasses interactive authentication.

For example, a successful login may appear consistent with expected user activity and location, such as access originating from Cauquenes, Chile. When evaluated with Unify context, the same activity may be identified as originating from a device that is not associated with the account. This additional context can highlight activity that would otherwise appear low risk and support further investigation.

Where to access Unify in the UI

Once required data sources are connected, the Unify experience is available directly from the Kaseya MDR interface:

  1. From the side navigation menu, click Unify.

  2. Within the Unify module, you can access the following views:

  • Unify > Unmapped Devices: Review devices that are not yet confidently associated with an account

  • Unify > Mapped Devices: Review devices that have been confidently associated with one or more accounts

  • Unify > Ignored Devices: Review devices that have been explicitly excluded from correlation

  • Unify > Automation: Configure optional mapping and unmapping automation

These views are read‑only until relevant data sources are connected.

Unify association lifecycle

Unify association behavior follows a consistent lifecycle:

Observation and evaluation

Unify observes device, identity, and activity metadata from connected platforms. Using available signals, Unify evaluates whether a device can be confidently associated with an account:

  • If confidence meets the configured threshold, the device becomes eligible for mapping.

  • If confidence is insufficient or ambiguous, the device remains unmapped.

Mapping

When mapping conditions are met, either through automation or manual action, Unify creates a device‑to‑account association:

  • Mapped status reflects current correlation confidence.

  • Mappings provide investigation context only and may change as new data is observed.

Device correlation (propagation layer)

Device correlation evaluates whether multiple devices are logically equivalent based on shared metadata.

When enabled:

  • A mapping applied to one device can propagate to all correlated devices.

  • An unmapping action applied to one device can propagate to all correlated devices.

Device Correlation does not create mappings by itself; it synchronizes outcomes produced by mapping and unmapping rules.

Unmapping

Unify may remove mappings automatically when configured unmapping conditions are met, such as:

  • Confidence for the mapped account drops below the defined threshold.

  • The device has not checked in within the defined time window.

  • A correlated device triggers a propagated unmapping action.

Unmapping returns the device to an unmapped state unless the device is explicitly ignored.

Ignored state (explicit exclusion)

If a device is ignored, it is removed from the association lifecycle entirely.

  • No correlation is performed

  • No mapping or unmapping occurs

  • Device Correlation does not apply

Ignoring a device is an administrative decision and can be reversed.

Together, these components ensure Unify maintains accurate, consistent investigation context as environments and data change.

Unify views and device states

Unify presents device association status through dedicated views. These views are designed to support review and judgment, not to indicate errors.

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