OT Asset Discovery Software

OT asset discovery software is designed to identify, catalogue, and maintain visibility of devices and systems operating within industrial environments. Its primary role is to provide a structured view of what exists on OT networks, how assets communicate, and, in some cases, what risks may be present.

Unlike IT asset tools, OT-focused software is built to operate safely around industrial protocols, legacy equipment, and environments where availability and safety take priority over visibility.

This article explains what OT asset discovery software does, how different technical approaches work, and where software fits within a broader discovery process.

What OT asset discovery software does

At a basic level, OT asset discovery software attempts to answer four core questions:

• What devices are present on the OT network
• How those devices communicate
• What protocols and services are in use
• How assets are logically or physically connected

Most tools build an asset inventory by observing network traffic, identifying device fingerprints, and correlating communications into a structured dataset. Depending on the platform, this may include:

• Device type and role (PLC, HMI, historian, engineering workstation)
• Vendor and model information
• Firmware or software versions (where visible)
• Network location and communication paths

In real environments, the output is rarely a perfect inventory on first pass. Asset data quality improves over time as the tool observes more traffic and as findings are reviewed and refined.

Passive monitoring vs scanning tools

OT asset discovery software generally uses one of two technical approaches: passive monitoring or active scanning.

Passive monitoring

Passive tools observe network traffic without sending packets into the OT environment. They rely on mirrored switch ports, network taps, or SPAN sessions to analyse communications as they naturally occur.

Passive monitoring is commonly used in OT because it:

• Avoids interfering with fragile or safety-critical systems
• Works with legacy devices that cannot tolerate scanning
• Provides ongoing visibility rather than a point-in-time snapshot

In operational environments, passive tools tend to discover assets gradually, depending on how frequently devices communicate. Equipment that is rarely used or normally idle may not appear immediately.

Active scanning tools

Scanning tools actively probe networks by sending discovery requests, similar to traditional IT scanning approaches. Some OT tools offer limited or carefully controlled scanning modes.

Active approaches can:

• Identify silent or infrequently used devices more quickly
• Validate IP ranges and network segmentation assumptions

However, scanning carries inherent risk in OT. Even well-designed tools can cause unexpected behaviour on older controllers or poorly documented systems. For this reason, scanning is often restricted, tightly scoped, or avoided entirely in production environments.

Strengths of software-only discovery

OT asset discovery software offers several clear advantages when used appropriately.

It can:

• Scale across large or complex environments
• Provide consistent, repeatable data collection
• Support continuous visibility rather than one-off exercises
• Highlight communication patterns that are difficult to document manually

In practice, software is particularly effective at uncovering unknown connections between systems, shadow assets, or undocumented dependencies that may not appear in drawings or spreadsheets.

For organisations with limited internal visibility, software often provides the first consolidated view of OT assets across sites or networks.

Limitations of software-only approaches

Despite its value, software alone cannot fully describe an OT environment.

Common limitations include:

• Incomplete identification of assets that communicate infrequently
• Misclassification of devices due to protocol ambiguity
• Limited insight into physical location or operational criticality
• Difficulty distinguishing production, test, or retired systems

Observed patterns show that tools often detect “what is talking” rather than “what exists”. Assets powered off, isolated, or operating only during specific processes may be absent from the dataset.

Software also cannot reliably interpret business context, such as which systems are safety-critical, which are externally accessible, or which fall under regulatory scope.

Why tools still require expertise and validation

OT asset discovery outputs should be treated as a starting point, not a final answer.

Interpreting results requires understanding:

• Industrial protocols and vendor-specific behaviours
• Normal versus abnormal communication patterns
• Network architecture and segmentation design
• Operational realities that affect asset usage

In real OT environments, it is common for tools to surface findings that are technically correct but operationally misleading without context. Validation typically involves cross-checking results against drawings, configuration files, maintenance records, and discussions with engineering teams.

Expert review also helps resolve false positives, confirm asset roles, and identify gaps that software alone cannot detect.

How software fits into a broader discovery process

OT asset discovery software is most effective when used as part of a structured discovery approach rather than as a standalone solution.

A broader process typically includes:

• Defining discovery scope and asset categories
• Using software to collect and correlate network data
• Validating findings with engineering and operations teams
• Enriching asset records with operational and risk context
• Establishing processes to keep data current over time

Software provides the technical foundation, but accuracy and usefulness depend on governance, validation, and ongoing maintenance. Asset discovery is not a one-time activity, and tools are most valuable when integrated into continuous visibility and change management processes.

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