How Can You Improve IoT Device Visibility on My Network?

Your Network Has Blind Spots—Here's How to Find Them

You can't secure what you can't see. And right now, most manufacturing plants, hospitals, and industrial facilities can't see a significant chunk of what's connected to their networks.

Shadow IoT devices, legacy controllers, and sensors that connect only intermittently all create gaps that security teams struggle to close. Vendors install "temporary" gateways that become permanent fixtures. Clinical engineering adds medical devices without security review. Facilities deploy environmental sensors that never show up in the CMDB. Sound familiar?

NIST SP 800-82 Rev. 3 calls this out directly: OT environments have unique constraints around performance, reliability, and safety that change how discovery and monitoring must work. Many critical devices can't run endpoint agents. Some can't tolerate aggressive scanning. These aren't obstacles—they're realities that demand a different approach.

According to Ericsson's mobility forecasts, cellular IoT connections will approach 8 billion by 2030. Meanwhile, Dragos's annual Year in Review reports continue documenting escalating OT-targeted threat activity. More connected devices plus more sophisticated threats equals a visibility problem that compounds if ignored.

Here's what makes improving IoT device visibility particularly challenging: many devices can't run agents, can't be scanned aggressively, and can't be patched on typical IT timelines. Good news? Modern discovery approaches have evolved to handle exactly these constraints—providing full visibility without requiring agents on every endpoint.

Why Visibility Gaps Cost You More Than You Think

Poor visibility creates three types of risk that compound over time:

Colonial Pipeline shut down operations proactively during their ransomware attack—not because attackers hit OT systems directly, but because they couldn't be sure what was compromised. WannaCry's impact on the NHS showed how legacy technology in complex environments enables widespread disruption. Both incidents share a common thread: limited visibility into what was connected and how to isolate problems fast.

Claroty's Team82 research analyzed close to one million OT devices and found that 12% contain known exploited vulnerabilities (KEVs). Even more concerning: 40% of analyzed organizations have these vulnerable assets insecurely connected to the internet, and 7% of devices have KEVs linked to known ransomware samples. More than 12% of industrial organizations had OT assets communicating with malicious domains—proving that this risk isn't theoretical.

What "Visibility" Actually Means (Beyond a Device List)

A spreadsheet of IP addresses isn't visibility. Mature IoT device visibility answers five questions that together enable both security and operational outcomes.

1. Identification: What Is It?

Vendor, model, device type (PLC vs. HMI vs. camera vs. medical device), MAC/IP, serial number. Strong device classification spans IT, OT, and IoT because you can't apply the right controls without knowing what you're protecting.

Consider the difference between a generic "unknown device" and knowing you have a Rockwell ControlLogix PLC running firmware v32.011 with remote programming enabled. One is a mystery. The other tells you exactly what's at stake and what controls to apply.

2. Location and Ownership: Where Is It, and Who Owns It?

Physical location (site, building, line, cell) plus network location (VLAN, subnet, switchport, zone). Just as important: who's the business owner? Engineering? Facilities? Biomed? IT?

Ownership matters because when something goes wrong—or when a device needs patching—someone has to make decisions. Without clear ownership, devices fall through the cracks. A device that "belongs to everyone" effectively belongs to no one.

3. Communication Paths: Who Talks to Whom?

Source-to-destination flows, protocols, ports, and direction. Where does traffic cross zone boundaries? What remote access paths exist into OT segments?

Understanding flows serves both cybersecurity and troubleshooting. When production goes down, knowing what talks to what helps you find the problem faster. When a threat actor gains access, understanding flows helps you contain them.

4. Configuration Posture: How Risky Is It?

Firmware version, patch level, configuration state. Does it have remote access enabled? Weak authentication? Legacy services exposed?

Some discovery platforms provide safe protocol-aware enrichment—queries using native industrial protocols to pull device attributes without disrupting operations. These "safe queries" communicate with devices in ways they expect, rather than arbitrary probing that might confuse or crash them.

5. Behavioral Baseline: What's Normal?

Expected communication patterns, timing, and schedules. Without a baseline, you can't spot anomalies—a new device appearing, unexpected protocol usage, traffic at 2 AM when production is offline.

Baselining isn't just about security. Understanding normal behavior helps operations teams distinguish between "something broke" and "someone is attacking us." Different problems require different responses.

Why You Probably Lack IoT Device Visibility Right Now

Four factors create most visibility gaps. Most organizations deal with multiple issues simultaneously.

Shadow Devices Multiply Fast

Local teams optimize for speed. Facilities adds sensors to fix building problems. Biomed adds clinical devices to support patient care. OT engineering adds gateways to keep production running. Contractors add "temporary" equipment that stays forever.

Without identity-based access control pinning devices to ports, these assets never make it into your CMDB. A study commissioned by Armis and conducted by Forrester Consulting found that 78% of manufacturing organizations believe unmanaged and IoT devices are more vulnerable to cyberattack than corporate-managed computers. Yet those devices keep appearing on networks without proper onboarding.

Legacy Controllers Don't Support Modern Tools

Many OT and IoT devices can't run EDR agents, endpoint management tools, or vulnerability scanners. NIST emphasizes that OT's performance, reliability, and safety constraints often require passive monitoring rather than endpoint instrumentation.

OT devices in industrial and manufacturing environments often have no built-in security and can't accommodate security agents. They were designed with the assumption they'd operate on isolated networks. That assumption no longer holds.

Segmentation Creates Blind Spots

Segmentation improves security, but some solutions also limits what centralized discovery tools can see. NIST recommends DMZs and separate authentication between corporate and OT networks. That architecture reduces lateral movement risk, but legacy microsegmentation solutions require you to deploy sensors in each zone; you're flying blind in segmented areas.

Air gaps and segmentation are sometimes necessary for safety and uptime. They reduce reach of centralized discovery unless instrumented intentionally. A device in a segmented zone that rarely communicates outbound may never appear in your central monitoring—even if it's critical to operations.

Siloed Tools Create Partial Pictures

Facilities has their BMS tool, OT has their monitoring tool, IT has their CMDB discovery. None share a common data model. Your "complete inventory" becomes three inconsistent inventories that nobody trusts.

ServiceNow's Discovery documentation acknowledges that CMDBs are only as complete as the discovery signals fed into them—OT and IoT sources must be integrated, not assumed. Don't replace these specialized tools; correlate their data into a unified view.

Modern Approaches to IoT Device Visibility

Discovery approaches have evolved significantly. Today's leading platforms use multiple techniques simultaneously, correlating data from various sources to build complete device profiles—without requiring agents on every endpoint.

Passive Discovery: See Everything Without Disruption

Passive discovery listens to network traffic without injecting probes. Some solutions require sensors positioned at key choke points (using SPAN ports, TAPs, or packet brokers) analyze mirrored traffic to detect devices, classify them by type, and map their communication patterns.

This approach works for any IP-connected device regardless of its ability to run software agents or support authentication protocols. Claroty, Nozomi Networks, Dragos, Armis, Forescout, and Microsoft Defender for IoT all use passive monitoring as a core discovery method.

Where to place passive sensors:

• OT zone uplinks
• IoT zone uplinks
• DMZ legs
• Remote access gateways

Multi-Source Data Correlation: Triangulate Device Identity

Few solutions see everything. However, modern platforms aggregate and correlate metadata from multiple authoritative sources—Active Directory, CMDBs, EDR solutions, specialized asset discovery platforms, vulnerability scanners, and native traffic analysis.

This "triangulation and correlation" approach verifies device identity by cross-referencing attributes across independent sources. When multiple systems agree on a device's classification, you can trust it. When they disagree, you've identified a device requiring investigation.

Leading platforms calculate "consistency scores" that quantify agreement between different data sources. High consistency enables automated policy creation; low consistency flags devices for manual review.

Safe Active Enrichment: Query Without Disruption

Once you understand which devices can tolerate queries, layer in protocol-aware, read-only discovery. Safe queries use native industrial protocols (Modbus, EtherNet/IP, BACnet) to pull firmware versions and configuration data.

Claroty's "Safe Queries" and Nozomi's "Smart Polling" exemplify this approach. A targeted query to a PLC using its native protocol retrieves attributes without disrupting operations—unlike a vulnerability scanner blasting ports with unexpected traffic.

Machine Learning Classification: Scale Beyond Manual Effort

With thousands of device types across IT, OT, and IoT, manual classification doesn't scale. Machine learning algorithms classify devices based on behavioral patterns, protocol usage, and hardware characteristics.

Modern platforms classify devices into hierarchical categories: Device Genre (IT, OT, IoT, IoMT), Device Class, Device Type, Vendor, Model, and Operating System. This multi-level taxonomy enables policies at appropriate abstraction levels—from broad (all building automation) to specific (Siemens S7-1500 PLCs running firmware version X).

These models continuously improve through exposure to diverse environments, addressing a critical weakness of static fingerprinting databases that become outdated as new device models enter production.

Building Your First 30 Days: An IoT Visibility Implementation Plan

Don't try to cover everything immediately. Start with your highest-risk segments and expand methodically. Every device you discover reduces your blind spots.

Fill the Gaps: Multi-Sensor Coverage

Passive discovery at choke points provides a foundation, but some devices stay invisible to single-sensor approaches.

Flow Telemetry (NetFlow/IPFIX)

Provides high-scale "who talks to whom" without full packet capture. Cisco describes IPFIX as enabling comprehensive traffic analysis with lower storage costs than pcap. Especially useful for:

• East-west visibility across routed domains
• Tracking cross-zone communications
• Long-term baselining at scale

Access-Layer Visibility: Traditional NAC vs. Modern Approaches

Understanding what's plugged into which port matters for both security and operations. You need to map device → MAC/IP → switchport → closet → building → zone. Essential for large campuses and distributed plants.

The traditional approach—NAC—creates significant challenges. Legacy solutions require extensive infrastructure: 802.1X supplicants on devices, RADIUS servers, certificate management, VLAN restructuring, and ongoing maintenance. One healthcare system estimated traditional NAC deployment would require 14 additional FTEs and 300 hours per site. Many IoT and OT devices can't participate in 802.1X authentication at all, forcing security teams to whitelist them—defeating the purpose.

Modern microsegmentation platforms take a different approach. Instead of requiring complex NAC infrastructure, these platforms deploy lightweight virtual appliances that connect to existing network switches—Cisco Catalyst, Arista, Juniper, and others. The virtual appliance gathers identity metadata from traffic flows (MAC/IP mappings, DHCP snooping, ARP data, port information), then translates policies into enforcement mechanisms native to your switches.

This approach provides comprehensive visibility—device identifiers, switchport locations, communication patterns—without requiring endpoint agents, 802.1X infrastructure, or network redesigns. Organizations keep their existing switch infrastructure and deploy in hours per location, gaining full visibility across managed and unmanaged devices alike.

Configuration and Backup Parsing

Some of the best OT asset data lives in configuration artifacts—not network traffic:

• PLC/SCADA project files and backups
• BMS databases with controller lists
• Historian tags
• Switch/router configs and ARP/MAC tables
• Vendor management system exports

A device that rarely communicates won't appear in traffic analysis, but it will show up in engineering project files that define its configuration.

Map Communications and Baseline Normal Behavior

Knowing what devices exist isn't enough. You need to know who talks to whom, over which protocols, and when.

Three Ways to Map Communications

Use all three where possible. Protocol-aware packet analysis shows you what devices are saying. Flow telemetry shows patterns at scale. Firewall logs show what crosses boundaries.

Baselining Makes Anomalies Obvious

Define what "normal" looks like:

• PLCs talk to their HMIs and SCADA servers—not random enterprise hosts
• Building automation controllers talk to BAS servers—not OT control VLANs
• Cameras talk to NVRs—not PLC networks
• Remote access lands in jump zones—not directly into Level 1/2 segments

Once you've baselined, anomalies stand out: new devices appearing, unexpected connection paths, new protocols in a zone, traffic at 2 AM when production is offline.

Industry-Specific Baseline Considerations

Manufacturing: Baseline by production schedules, batch windows, shift changes. Watch for new engineering workstation connections, vendor remote access outside maintenance windows, lateral flows between lines that suggest flat networks.

Energy/Utilities: Baseline by SCADA polling frequency and remote site update windows. Watch for unexpected outbound internet traffic from OT segments, changes in remote site talkers, new VPN terminations into OT.

Healthcare: Baseline by clinical workflows and building operations. Watch for medical devices communicating to unexpected destinations, building automation crossing into clinical networks, vendor remote access pattern changes.

From Visibility to Protection: Segmentation Strategies

Better IoT segmentation reduces what you need to monitor. Better visibility shows you what actually needs to communicate. They work together.

Zones and Conduits (IEC 62443)

A zone groups systems with common security requirements—all lab instruments on a control network, for example. A conduit is a controlled path between zones. FDA guidance on OT security for medical manufacturing recommends this architecture.

Under least-privilege principles, OT assets communicate only within their zone. Cross-zone communication requires defined policies and flows through specified conduits. CISA's guidance aligns with IEC 62443, organizing assets into zones and conduits to focus security efforts.

Consider a pharmaceutical fill-finish operation. Equipment from one production line shouldn't interact with equipment from other lines—there's no operational reason for it. But information about products being filled and capacity utilization may need to flow between lines. Placing each line in its own zone, with specific conduits for authorized data flows, limits system-wide impact if equipment in one zone gets compromised.

Implementing zones and conduits requires an accurate inventory of all connected assets and clear understanding of their communication needs. You can't segment what you don't know exists, and you can't define appropriate conduits without understanding legitimate traffic patterns. Visibility enables segmentation; segmentation simplifies visibility.

Why VLANs Alone Fall Short

VLANs separate traffic, but operational reality complicates clean designs. Each new device forces an impossible choice: put it in an existing VLAN where it doesn't fit, or create another VLAN just for this device type.

A hospital that started with 10 well-planned VLANs might end up managing 4,000 or more. Each VLAN requires configuration, documentation, and ongoing maintenance—complexity grows exponentially.

Bigger problem: VLANs care about where a device connects, not what it is. Healthcare networks have devices using hundreds of proprietary protocols. A device that moves to a different port or building may lose its security policies entirely.

Identity-Based Microsegmentation

Modern microsegmentation focuses on device identity—what it is, who's using it, what it needs to do—rather than network location. Policies follow devices regardless of what IP or subnet they're on.

This approach provides several advantages for IoT device visibility and security:

• Full coverage: Policies apply to managed and unmanaged devices alike, including IoT, OT, and IoMT that can't run agents
• Dynamic adaptation: When devices move or change IPs, policies follow automatically
• Simplified management: Policy based on device type rather than thousands of individual IP rules
• Visibility as prerequisite: Implementing microsegmentation forces complete discovery—you must identify devices before applying policies

Healthcare's Unique Challenge: IoMT Device Visibility

Healthcare networks look nothing like traditional corporate IT. Medical devices create visibility and security challenges that require specialized approaches.

Scale of the Problem

Large hospitals may have tens of thousands of connected assets spanning clinical devices, building systems, and IT. Medical devices range from infusion pumps to MRI machines. Each is a potential entry point, yet many run embedded operating systems that can't be patched without lengthy FDA recertification. Unlike IT systems refreshed every 3-5 years, medical devices often operate for 10-15 years.

Medical devices communicate using hundreds of different protocols, many proprietary to specific manufacturers. Traditional security tools struggle to understand and protect these communications.

How Lateral Movement Exploits Visibility Gaps

After attackers gain initial access—usually through phishing or compromised credentials—they don't stay put. They move laterally, exploring the network, mapping devices, and seeking higher-value targets. With over 70% of successful breaches leveraging lateral movement techniques, visibility gaps enable this progression at every step.

During reconnaissance, attackers explore and map the network, devices, and users. Devices you can't see are devices you can't protect—and attackers will find them.

BlackCat ransomware's attack on a healthcare organization in February 2024 demonstrates the pattern. Attackers used stolen credentials to traverse the network, moving laterally through multiple systems before deploying ransomware. Microsegmentation would have meant each system compromise triggered alerts or got blocked, rather than enabling free movement across the enterprise.

What Healthcare Leaders Report

IoMT Security Lifecycle

Healthcare Discovery Best Practices

Prefer passive discovery for clinical networks—HICP guidance warns that vulnerability scans can disrupt medical devices. Scanning systems should be restricted from clinical settings.

Normalize device identity: make, model, OS version, serial, MAC/IP, location, department, biomed owner. Tie inventory to workflows:

• CMMS/HTM for lifecycle and maintenance
• ITSM/ServiceNow for incidents and changes
• Network systems for segmentation policy enforcement

Integrate IT and OT Security Operations

Visibility tools should feed into existing SOC workflows, SIEM, and ITSM—not create another silo.

SIEM Integration

Splunk, QRadar, and Microsoft Sentinel integrations let OT asset data, alerts, and communication patterns appear alongside IT security events. Claroty, Nozomi, and Dragos all offer certified integrations with major SIEM platforms.

When your SIEM sees an unusual authentication attempt from an IT workstation and anomalous OT zone communications at the same time, it can correlate them into one incident. Without integration, they're separate alerts in different tools that nobody connects.

ITSM and CMDB Integration

ServiceNow Service Graph Connectors and Vulnerability Response integrations let OT/IoT asset data flow into the CMDB and incident workflows automatically:

• Discovered devices create/update configuration items
• Vulnerabilities create tickets assigned to appropriate owners
• OT asset changes follow the same change management process as IT

Analytics and Machine Learning: Scale Your Visibility

Machine learning helps classify devices, detect anomalies, and prioritize risk at scale. But AI augments solid foundations—it doesn't replace good inventories, baselines, and segmentation.

Automated classification: ML models identify device types from network behavior and protocol patterns. BACnet at regular intervals? Probably building automation. DICOM to a PACS server? Probably imaging equipment. Reduces manual effort for inventory maintenance.

Anomaly detection at scale: With thousands of devices generating communication patterns, humans can't review everything. Analytics platforms baseline device types and alert on deviations—a PLC suddenly talking to an internet address, a medical device initiating unexpected connections, a building controller using protocols it's never used before.

Risk prioritization: Not every vulnerability needs the same response. Analytics combine vulnerability data with network exposure, device criticality, and compensating controls. A critical vulnerability on an internet-facing device demands immediate action. That same vulnerability on a device reachable only from a monitored jump host can wait.

Governance and Continuous Improvement

Visibility isn't a one-time project. Build recurring processes that keep your inventory current and your gaps closing.

Establish Cross-Functional Governance

Answer these questions explicitly:

• Who owns device risk acceptance? Often a joint decision—clinical leadership (healthcare), operations leadership (manufacturing), and InfoSec.
• How are device changes approved? Change management with operational go/no-go gates.
• How do you handle vendor-managed devices and remote access? Contract language + technical controls + monitoring.
• What's minimum acceptable security at procurement? Define MDS2, SBOM, patchability, logging, and remote access requirements before buying.

Run a Continuous Visibility Cycle

Metrics That Matter

Track these to drive accountability:

• % of devices inventoried with owner, location, and type (discovery coverage)
• % of network flows visible (communication mapping completeness)
• % of network segmented (lateral movement risk reduction)
• Mean time to identify and contain suspicious lateral movement (incident response capability)
• Network-related production outages and downtime hours (operational impact)

Your First Month: A Practical Checklist

Week 1 – Instrument

• ☐ Select 1-2 highest-risk segments (production floor, clinical imaging, building automation)
• ☐ Deploy passive monitoring at the uplink/aggregation point
• ☐ Configure flow telemetry export from core network devices

Week 2 – Discover and Classify

• ☐ Review discovered device inventory from passive monitoring
• ☐ Validate classifications with OT, facilities, or clinical engineering teams
• ☐ Identify and flag unknown devices
• ☐ Document device owners and criticality levels

Week 3 – Map Communications

• ☐ Generate initial communication maps (who talks to whom)
• ☐ Identify cross-zone communications and unexpected talkers
• ☐ Document normal patterns to establish baseline

Week 4 – Plan Expansion

• ☐ Prioritize additional segments for monitoring based on risk
• ☐ Plan segmentation improvements from discovered communication patterns
• ☐ Establish recurring review cadence with operational teams

Selecting the Right Visibility and Segmentation Platform

When evaluating solutions to improve IoT device visibility on your network, look for platforms that combine multiple capabilities:

Specialized asset discovery platforms like Armis, Claroty, Nozomi Networks, and Dragos, provide deep device intelligence. Modern microsegmentation platforms like Elisity aggregate this intelligence and add enforcement capabilities—translating visibility into least privilege access security policies that prevent lateral movement.

Elisity's IdentityGraph™ technology correlates device data from over 25 security vendors, building complete profiles that enable identity-based microsegmentation across IT, IoT, OT, and IoMT. Organizations like Main Line Health, Shaw Industries, and GSK have deployed Elisity quickly, not in the years typical of traditional approaches—achieving 99% device discovery and implementing enforceable segmentation policies as quickly as the day after the first deployment.

Frequently Asked Questions About IoT Device Visibility

What is passive discovery and why is it important for IoT networks?

Passive discovery identifies devices by observing existing network traffic rather than sending probes or scans. Elisity's Virtual Edge appliances connect directly to network switches and leverage switch-native features (DHCP snooping, ARP tables, flow data) to gather identity metadata from traffic—device identifiers, MAC-to-IP mappings, switchport locations, and communication patterns—without injecting any traffic or intercepting packets.

This approach matters for IoT and OT environments because many industrial devices can malfunction or crash when they receive unexpected network traffic. Security teams consider passive discovery the safest starting point for building IoT asset inventories. Elisity can also integrate with specialized IoT discovery solutions like Claroty, Nozomi Networks, Armis, and Microsoft Defender for IoT to enrich visibility across sensitive networks.

How long does it take to get visibility into IoT devices on a network?

You can achieve comprehensive visibility into a network segment within hours with a modern microsegmentation platform that features a virtual appliance connecting directly to switch control plane data. A practical deployment approach works as follows: Initial deployment takes hours per location with no network outages; within minutes, the platform gathers identity metadata from existing switch features (DHCP snooping, ARP tables, MAC/IP mappings, flow data); within the first hour, you can validate discovered devices and begin creating policies; Day 2 expands coverage to additional switches and begins CMDB correlation.

Enterprise-wide visibility with legacy solutions typically takes 3-6 months depending on network size, number of sites, and segmentation complexity. Modern microsegmentation platforms can achieve 99% device discovery within hours of deployment per location, with policy enforcement beginning the same day. Enterprise-wide rollouts complete in days to weeks depending on number of sites and deployment resources. Because the platform extracts data directly from switch infrastructure rather than passive monitoring, discovery happens in minutes per location—not weeks of traffic collection. Start with highest-risk segments rather than attempting complete coverage immediately.

Why can't I use standard vulnerability scanners on IoT and OT devices?

Standard vulnerability scanners send probing traffic that can disrupt or crash IoT and OT devices. Engineers designed industrial controllers, PLCs, and embedded systems for reliability in isolated environments—not to handle unexpected network requests. Tenable's own OT security guidance explicitly warns against scanning fragile devices and recommends passive monitoring instead.

Specific risks include: devices freezing or rebooting when scanned, production processes stopping unexpectedly, safety systems becoming unresponsive, and false readings from sensors during active probing. For IoT/OT environments, use passive discovery first, then add targeted "safe queries" that use native industrial protocols (Modbus, EtherNet/IP, BACnet) to collect device information without disruption.

What's the difference between asset discovery and microsegmentation?

Asset discovery identifies what devices exist on your network—their type, location, owner, and communication patterns. Microsegmentation controls what those devices can communicate with, enforcing least-privilege access policies that prevent lateral movement.

Discovery answers: "What's on my network?" Microsegmentation answers: "What should this device be allowed to do?"

They work together. You can't segment what you don't know exists, and you can't define appropriate policies without understanding legitimate traffic patterns. Many organizations use specialized discovery platforms (Armis, Claroty, Nozomi) for deep device intelligence, then feed that data into microsegmentation platforms for policy enforcement.

How does identity-based microsegmentation improve IoT device visibility?

Identity-based microsegmentation improves visibility by requiring explicit definition of all allowed communications. When you implement microsegmentation, you must first discover every device and map its legitimate traffic patterns—creating complete visibility as a prerequisite to policy enforcement.

Discovery typically surfaces shadow devices, rogue connections, and undocumented communication paths that traditional tools miss. For security, microsegmentation limits lateral movement by enforcing least-privilege access at the network level. Even if an attacker compromises one device, they cannot freely move to other systems.

Identity-based approaches (versus VLAN-based) provide additional benefits: policies follow device identity rather than IP address, enabling consistent security even when devices move or change addresses. This eliminates the complexity explosion that VLAN-based segmentation creates in large IoT/OT environments.

What to Do Next

You can't apply least-privilege access to devices you don't know exist. You can't contain breaches in segments you haven't mapped. You can't prove compliance for assets that aren't inventoried.

Organizations seeing the best results—reduced breach impact, faster incident response, improved compliance posture—treat visibility as the foundation for Zero Trust maturity. They've learned that visibility isn't just a security project; it's an operational capability that pays dividends across downtime reduction, troubleshooting efficiency, and change management confidence.

Ask yourself three questions:

1. Do you have a continuously updated inventory of every connected device?
2. Do you know who talks to whom across your IoT and OT segments?
3. Could you quickly isolate a compromised device without disrupting critical operations?

If any answer is uncertain, improved IoT device visibility should be a priority. Technology alone won't solve the problem—you also need processes for maintaining inventories, governance for managing exceptions, and people who respond when anomalies appear.

Blind spots won't close themselves—but with the right approach, they don't have to stay blind spots for long.

Ready to assess where you stand? Request a free IoT/OT visibility POV to identify your highest-impact next steps.