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May 12, 2021

How AI Protects Critical Infrastructure From Ransomware

Explore the role of AI in safeguarding critical infrastructure from ransomware, as revealed by Darktrace's latest insights.
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
David Masson
VP, Field CISO
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12
May 2021

Modern Threats to OT Environments

At the 2021 RSA cyber security conference, US Secretary of Homeland Security Alejandro Mayorkas made an era-defining statement regarding the cyber security landscape: “Let me be clear: ransomware now poses a national security threat.”

Last weekend, Mayorkas’ words rang true. A ransomware attack on the Colonial Pipeline – responsible for nearly half of the US East Coast’s diesel, gasoline, and jet fuel – resulted in the shutdown of a critical fuel network supplying a number of Eastern states.

The fallout from the attack demonstrated how widespread and damaging the consequences of ransomware can be. Against critical infrastructure and utilities, cyber-attacks have the potential to disrupt supplies, harm the environment, and even threaten human lives.

Though full details remain to be confirmed, the attack is reported to have been conducted by an affiliate of the cyber-criminal group called DarkSide, and likely leveraged common remote desktop tools. Remote access has been enabled as an exploitable vulnerability within critical infrastructure by the shift to remote work that many organizations made last year, including those with Industrial Control Systems (ICS) and Operational Technology (OT).

The rise of industrial ransomware

Ransomware against industrial environments is on the rise, with a reported 500% increase since 2018. Oftentimes, these threats leverage the convergence of IT and OT systems, first targeting IT before pivoting to OT. This was seen with the EKANS ransomware that included ICS processes in its ‘kill list’, as well as the Cring ransomware that compromised ICS after first exploiting a vulnerability in a virtual private network (VPN).

It remains to be seen whether the initial attack vector in the Colonial Pipeline compromise exploited a technical vulnerability, compromised credentials, or a targeted spear phishing campaign. It has been reported that the attack first impacted IT systems, and that Colonial then shut down OT operations as a safety precaution. Colonial confirms that the ransomware “temporarily halted all pipeline operations and affected some of our IT systems,” showing that, ultimately, both OT and IT were affected. This is a great example of how many OT systems depend on IT, such that an IT cyber-attack has the ability to take down OT and ICS processes.

In addition to locking down systems, the threat actors also stole 100GB of sensitive data from Colonial. This kind of double extortion attack — in which data is exfiltrated before files are encrypted — has unfortunately become the norm rather than the exception, with over 70% of ransomware attacks involving exfiltration. Some ransomware gangs have even announced that they are dropping encryption altogether in favor of data theft and extortion methods.

Earlier this year, Darktrace defended against a double extortion ransomware attack waged against a critical infrastructure organization, which also leveraged common remote access tools. This blog will outline the threat find in depth, showing how Darktrace’s self-learning AI responded autonomously to an attack strikingly similar to the Colonial Pipeline incident.

Darktrace threat find

Ransomware against electric utilities equipment supplier

In an attack against a North American equipment supplier for electrical utilities earlier this year, Darktrace/OT demonstrated its ability to protect critical infrastructure against double extortion ransomware that targeted organizations with ICS and OT.

The ransomware attack initially targeted IT systems, and, thanks to self-learning Cyber AI, was stopped before it could spill over into OT and disrupt operations.

The attacker first compromised an internal server in order to exfiltrate data and deploy ransomware over the course of 12 hours. The short amount of time between initial compromise and deployment is unusual, as ransomware threat actors often wait several days to spread stealthily as far across the cyber ecosystem as possible before striking.

Figure 1: A timeline of the attack

How did the attack bypass the rest of the security stack?

The attacker leveraged ‘Living off the Land’ techniques to blend into the business’ normal ‘patterns of life’, using a compromised admin credential and a remote management tool approved by the organization, in its attempts to remain undetected.

Darktrace commonly sees the abuse of legitimate remote management software in attackers’ arsenal of techniques, tactics, and procedures (TTPs). Remote access is also becoming an increasingly common vector of attack in ICS attacks in particular. For example, in the cyber-incident at the Florida water treatment facility last February, attackers exploited a remote management tool in attempts to manipulate the treatment process.

The specific strain of ransomware deployed by this attacker also successfully evaded detection by anti-virus by using a unique file extension when encrypting files. These forms of ‘signatureless’ ransomware easily slip past legacy approaches to security that rely on rules, signatures, threat feeds, and lists of documented Common Vulnerabilities and Exposures (CVEs), as these are methods that can only detect previously documented threats.

The only way to detect never-before-seen threats like signatureless ransomware is for a technology to find anomalous behavior, rather than rely on lists of ‘known bads’. This can be achieved with self-learning technology, which spots even the most subtle deviations from the normal ‘patterns of life’ for all devices, users, and all the connections between them.

Darktrace insights

Initial compromise and establishing foothold

Despite the abuse of a legitimate tool and the absence of known signatures, Darktrace/OT was able to use a holistic understanding of normal activity to detect the malicious activity at multiple points in the attack lifecycle.

The first clear sign of an emerging threat that was alerted by Darktrace was the unusual use of a privileged credential. The device also served an unusual remote desktop protocol (RDP) connection from a Veeam server shortly before the incident, indicating that the attacker may have moved laterally from elsewhere in the network.

Three minutes later, the device initiated a remote management session which lasted 21 hours. This allowed the attacker to move throughout the broader cyber ecosystem while remaining undetected by traditional defences. Darktrace, however, was able to detect unusual remote management usage as another early warning indicative of an attack.

Double threat part one: Data exfiltration

One hour after the initial compromise, Darktrace detected unusual volumes of data being sent to a 100% rare cloud storage solution, pCloud. The outbound data was encrypted using SSL, but Darktrace created multiple alerts relating to large internal downloads and external uploads that were a significant deviation from the device’s normal ‘pattern of life’.

The device continued to exfiltrate data for nine hours. Analysis of the files downloaded by the device, which were transferred using the unencrypted SMB protocol, suggests that they were sensitive in nature. Fortunately, Darktrace was able to pinpoint the specific files that were exfiltrated so that the customer could immediately evaluate the potential implications of the compromise.

Double threat part two: File encryption

A short time later, at 01:49 local time, the compromised device began encrypting files in a SharePoint back-up share drive. Over the next three and a half hours, the device encrypted over 13,000 files on at least 20 SMB shares. In total, Darktrace produced 23 alerts for the device in question, which amounted to 48% of all the alerts produced in the corresponding 24-hour period.

Darktrace’s Cyber AI Analyst then automatically launched an investigation, identifying the internal data transfers and the file encryption over SMB. From this, it was able to present incident reports that connected the dots among these disparate anomalies, piecing them together into a coherent security narrative. This put the security team in a position to immediately take remediating action.

If the customer had been using Darktrace’s autonomous response technology, there is no doubt the activity would have been halted before significant volumes of data could have been exfiltrated or files encrypted. Fortunately, after seeing both the alerts and Cyber AI Analyst reports, the customer was able to use Darktrace’s ‘Ask the Expert’ (ATE) service for incident response to mitigate the impact of the attack and assist with disaster recovery.

Figure 2: AI Analyst Incident reporting an unusual reprogram command using the MODBUS protocol. The incident includes a plain English summary, relevant technical information, and the investigation process used by the AI.  

Detecting the threat before it could disrupt critical infrastructure

The targeted supplier was overseeing OT and had close ties to critical infrastructure. By facilitating the early-stage response, Darktrace prevented the ransomware from spreading further onto the factory floor. Crucially, Darktrace also minimized operational disruption, helping to avoid the domino effect which the attack could have had, affecting not only the supplier itself, but also the electric utilities that this supplier supports.

As both the recent Colonial Pipeline incident and the above threat find reveal, ransomware is a pressing concern for organizations overseeing industrial operations across all forms of critical infrastructure, from pipelines to the power grid and its suppliers. With self-learning AI, these attack vectors can be dealt with before the damage is done through real-time threat detection, autonomous investigations, and — if activated — targeted machine-speed response.

Looking forward: Using Self-Learning AI to protect critical infrastructure across the board

In late April, the Biden administration announced an ambitious effort to “safeguard US critical infrastructure from persistent and sophisticated threats.” The Department of Energy’s (DOE) 100-day plan specifically seeks technologies “that will provide cyber visibility, detection, and response capabilities for industrial control systems of electric utilities.”

The Biden administration’s cyber sprint clearly calls for a technology that protects critical energy infrastructure, rather than merely best practice measures and regulations. As seen in the above threat find, Darktrace AI is a powerful technology that leverages unsupervised machine learning to autonomously safeguard critical infrastructure and its suppliers with machine speed and precision.

Darktrace enhances detection, mitigation, and forensic capabilities to detect  sophisticated and novel attacks, along with insider threats and pre-existing infections, using Self-Learning Cyber AI, without rules, signatures, or lists of CVEs. Incident investigations provided in real time by Cyber AI Analyst jumpstart remediation with actionable insights, containing emerging attacks at their early stages, before they escalate into crisis.

Enable near real-time situational awareness and response capabilities

Darktrace immediately understands, identifies, and investigates all anomalous activity in ICS/OT networks, whether human or machine driven. Additionally, Darktrace actions targeted response where appropriate to neutralize threats, either actively or in human confirmation mode. Because Self-learning AI adapts alongside evolutions in the ecosystem, organizations benefit from real-time awareness with no tuning or human input necessary

Deploy technologies to increase visibility of threats in ICS and OT systems

Darktrace contextualizes security events, adapts to novel techniques, and translates findings into a security narrative that can be actioned by humans in minutes. Delivering a unified view across IT and OT systems.

Darktrace detects, investigates, and responds to threats at higher Purdue levels and in IT systems before they ‘spill over’ into OT. ‘Plug and play’ deployment seamlessly integrates with technological architecture, presenting 3D network topology with granular visibility into all users, devices, and subnets.

Darktrace's asset identification continuously catalogues all ICS/OT devices and identifies and investigates all threatening activity indicative of emerging attacks – be it ICS ransomware, APTs, zero-day exploits, insider threats, pre-existing infections, DDoS, crypto-mining, misconfigurations, or never-before-seen attacks.

Thanks to Darktrace analyst Oakley Cox for his insights on the above threat find.

Darktrace model detections:

  • Initial compromise:
  • User / New Admin Credential on Client
  • Data exfiltration:
  • Anomalous Connection / Uncommon 1 GiB Outbound
  • Anomalous Connection / Low and Slow Exfiltration
  • Device / Anomalous SMB Followed by Multiple Model Breaches
  • Anomalous Connection / Download and Upload
  • File encryption:
  • Compromise / Ransomware / Suspicious SMB Activity
  • Anomalous Connection / SMB Enumeration
  • Device / Anomalous RDP Followed by Multiple Model Breaches
  • Anomalous File / Internal / Additional Extension Appended to SMB File
  • Anomalous Connection / Sustained MIME Type Conversion
  • Anomalous Connection / Suspicious Read Write Ratio
  • Device / Multiple Lateral Movement Model Breaches

Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
David Masson
VP, Field CISO

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May 16, 2025

Catching a RAT: How Darktrace neutralized AsyncRAT

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What is a RAT?

As the proliferation of new and more advanced cyber threats continues, the Remote Access Trojan (RAT) remains a classic tool in a threat actor's arsenal. RATs, whether standardized or custom-built, enable attackers to remotely control compromised devices, facilitating a range of malicious activities.

What is AsyncRAT?

Since its first appearance in 2019, AsyncRAT has become increasingly popular among a wide range of threat actors, including cybercriminals and advanced persistent threat (APT) groups.

Originally available on GitHub as a legitimate tool, its open-source nature has led to widespread exploitation. AsyncRAT has been used in numerous campaigns, including prolonged attacks on essential US infrastructure, and has even reportedly penetrated the Chinese cybercriminal underground market [1] [2].

How does AsyncRAT work?

Original source code analysis of AsyncRAT demonstrates that once installed, it establishes persistence via techniques such as creating scheduled tasks or registry keys and uses SeDebugPrivilege to gain elevated privileges [3].

Its key features include:

  • Keylogging
  • File search
  • Remote audio and camera access
  • Exfiltration techniques
  • Staging for final payload delivery

These are generally typical functions found in traditional RATs. However, it also boasts interesting anti-detection capabilities. Due to the popularity of Virtual Machines (VM) and sandboxes for dynamic analysis, this RAT checks for the manufacturer via the WMI query 'Select * from Win32_ComputerSystem' and looks for strings containing 'VMware' and 'VirtualBox' [4].

Darktrace’s coverage of AsyncRAT

In late 2024 and early 2025, Darktrace observed a spike in AsyncRAT activity across various customer environments. Multiple indicators of post-compromise were detected, including devices attempting or successfully connecting to endpoints associated with AsyncRAT.

On several occasions, Darktrace identified a clear association with AsyncRAT through the digital certificates of the highlighted SSL endpoints. Darktrace’s Real-time Detection effectively identified and alerted on suspicious activities related to AsyncRAT. In one notable incident, Darktrace’s Autonomous Response promptly took action to contain the emerging threat posed by AsyncRAT.

AsyncRAT attack overview

On December 20, 2024, Darktrace first identified the use of AsyncRAT, noting a device successfully establishing SSL connections to the uncommon external IP 185.49.126[.]50 (AS199654 Oxide Group Limited) via port 6606. The IP address appears to be associated with AsyncRAT as flagged by open-source intelligence (OSINT) sources [5]. This activity triggered the device to alert the ‘Anomalous Connection / Rare External SSL Self-Signed' model.

Model alert in Darktrace / NETWORK showing the repeated SSL connections to a rare external Self-Signed endpoint, 185.49.126[.]50.
Figure 1: Model alert in Darktrace / NETWORK showing the repeated SSL connections to a rare external Self-Signed endpoint, 185.49.126[.]50.

Following these initial connections, the device was observed making a significantly higher number of connections to the same endpoint 185.49.126[.]50 via port 6606 over an extended period. This pattern suggested beaconing activity and triggered the 'Compromise/Beaconing Activity to External Rare' model alert.

Further analysis of the original source code, available publicly, outlines the default ports used by AsyncRAT clients for command-and-control (C2) communications [6]. It reveals that port 6606 is the default port for creating a new AsyncRAT client. Darktrace identified both the Certificate Issuer and the Certificate Subject as "CN=AsyncRAT Server". This SSL certificate encrypts the packets between the compromised system and the server. These indicators of compromise (IoCs) detected by Darktrace further suggest that the device was successfully connecting to a server associated with AsyncRAT.

Model alert in Darktrace / NETWORK displaying the Digital Certificate attributes, IP address and port number associated with AsyncRAT.
Figure 2: Model alert in Darktrace / NETWORK displaying the Digital Certificate attributes, IP address and port number associated with AsyncRAT.
Darktrace’s detection of repeated connections to the suspicious IP address 185.49.126[.]50 over port 6606, indicative of beaconing behavior.
Figure 3: Darktrace’s detection of repeated connections to the suspicious IP address 185.49.126[.]50 over port 6606, indicative of beaconing behavior.
Darktrace's Autonomous Response actions blocking the suspicious IP address,185.49.126[.]50.
Figure 4: Darktrace's Autonomous Response actions blocking the suspicious IP address,185.49.126[.]50.

A few days later, the same device was detected making numerous connections to a different IP address, 195.26.255[.]81 (AS40021 NL-811-40021), via various ports including 2106, 6606, 7707, and 8808. Notably, ports 7707 and 8808 are also default ports specified in the original AsyncRAT source code [6].

Darktrace’s detection of connections to the suspicious endpoint 195.26.255[.]81, where the default ports (6606, 7707, and 8808) for AsyncRAT were observed.
Figure 5: Darktrace’s detection of connections to the suspicious endpoint 195.26.255[.]81, where the default ports (6606, 7707, and 8808) for AsyncRAT were observed.

Similar to the activity observed with the first endpoint, 185.49.126[.]50, the Certificate Issuer for the connections to 195.26.255[.]81 was identified as "CN=AsyncRAT Server". Further OSINT investigation confirmed associations between the IP address 195.26.255[.]81 and AsyncRAT [7].

Darktrace's detection of a connection to the suspicious IP address 195.26.255[.]81 and the domain name identified under the common name (CN) of a certificate as AsyncRAT Server
Figure 6: Darktrace's detection of a connection to the suspicious IP address 195.26.255[.]81 and the domain name identified under the common name (CN) of a certificate as AsyncRAT Server.

Once again, Darktrace's Autonomous Response acted swiftly, blocking the connections to 195.26.255[.]81 throughout the observed AsyncRAT activity.

Figure 7: Darktrace's Autonomous Response actions were applied against the suspicious IP address 195.26.255[.]81.

A day later, Darktrace again alerted to further suspicious activity from the device. This time, connections to the suspicious endpoint 'kashuub[.]com' and IP address 191.96.207[.]246 via port 8041 were observed. Further analysis of port 8041 suggests it is commonly associated with ScreenConnect or Xcorpeon ASIC Carrier Ethernet Transport [8]. ScreenConnect has been observed in recent campaign’s where AsyncRAT has been utilized [9]. Additionally, one of the ASN’s observed, namely ‘ASN Oxide Group Limited’, was seen in both connections to kashuub[.]com and 185.49.126[.]50.

This could suggest a parallel between the two endpoints, indicating they might be hosting AsyncRAT C2 servers, as inferred from our previous analysis of the endpoint 185.49.126[.]50 and its association with AsyncRAT [5]. OSINT reporting suggests that the “kashuub[.]com” endpoint may be associated with ScreenConnect scam domains, further supporting the assumption that the endpoint could be a C2 server.

Darktrace’s Autonomous Response technology was once again able to support the customer here, blocking connections to “kashuub[.]com”. Ultimately, this intervention halted the compromise and prevented the attack from escalating or any sensitive data from being exfiltrated from the customer’s network into the hands of the threat actors.

Darktrace’s Autonomous Response applied a total of nine actions against the IP address 191.96.207[.]246 and the domain 'kashuub[.]com', successfully blocking the connections.
Figure 8: Darktrace’s Autonomous Response applied a total of nine actions against the IP address 191.96.207[.]246 and the domain 'kashuub[.]com', successfully blocking the connections.

Due to the popularity of this RAT, it is difficult to determine the motive behind the attack; however, from existing knowledge of what the RAT does, we can assume accessing and exfiltrating sensitive customer data may have been a factor.

Conclusion

While some cybercriminals seek stability and simplicity, openly available RATs like AsyncRAT provide the infrastructure and open the door for even the most amateur threat actors to compromise sensitive networks. As the cyber landscape continually shifts, RATs are now being used in all types of attacks.

Darktrace’s suite of AI-driven tools provides organizations with the infrastructure to achieve complete visibility and control over emerging threats within their network environment. Although AsyncRAT’s lack of concealment allowed Darktrace to quickly detect the developing threat and alert on unusual behaviors, it was ultimately Darktrace Autonomous Response's consistent blocking of suspicious connections that prevented a more disruptive attack.

Credit to Isabel Evans (Cyber Analyst), Priya Thapa (Cyber Analyst) and Ryan Traill (Analyst Content Lead)

Appendices

  • Real-time Detection Models
       
    • Compromise / Suspicious SSL Activity
    •  
    • Compromise / Beaconing Activity To      External Rare
    •  
    • Compromise / High Volume of      Connections with Beacon Score
    •  
    • Anomalous Connection / Suspicious      Self-Signed SSL
    •  
    • Compromise / Sustained SSL or HTTP      Increase
    •  
    • Compromise / SSL Beaconing to Rare      Destination
    •  
    • Compromise / Suspicious Beaconing      Behaviour
    •  
    • Compromise / Large Number of      Suspicious Failed Connections
  •  
  • Autonomous     Response Models
       
    • Antigena / Network / Significant      Anomaly / Antigena Controlled and Model Alert
    •  
    • Antigena / Network / Significant      Anomaly / Antigena Enhanced Monitoring from Client Block

List of IoCs

·     185.49.126[.]50 - IP – AsyncRAT C2 Endpoint

·     195.26.255[.]81 – IP - AsyncRAT C2 Endpoint

·      191.96.207[.]246 – IP – Likely AsyncRAT C2 Endpoint

·     CN=AsyncRAT Server - SSL certificate - AsyncRATC2 Infrastructure

·      Kashuub[.]com– Hostname – Likely AsyncRAT C2 Endpoint

MITRE ATT&CK Mapping:

Tactic –Technique – Sub-Technique  

 

Execution– T1053 - Scheduled Task/Job: Scheduled Task

DefenceEvasion – T1497 - Virtualization/Sandbox Evasion: System Checks

Discovery– T1057 – Process Discovery

Discovery– T1082 – System Information Discovery

LateralMovement - T1021.001 - Remote Services: Remote Desktop Protocol

Collection/ Credential Access – T1056 – Input Capture: Keylogging

Collection– T1125 – Video Capture

Commandand Control – T1105 - Ingress Tool Transfer

Commandand Control – T1219 - Remote Access Software

Exfiltration– T1041 - Exfiltration Over C2 Channel

 

References

[1]  https://blog.talosintelligence.com/operation-layover-how-we-tracked-attack/

[2] https://intel471.com/blog/china-cybercrime-undergrond-deepmix-tea-horse-road-great-firewall

[3] https://www.attackiq.com/2024/08/01/emulate-asyncrat/

[4] https://www.fortinet.com/blog/threat-research/spear-phishing-campaign-with-new-techniques-aimed-at-aviation-companies

[5] https://www.virustotal.com/gui/ip-address/185.49.126[.]50/community

[6] https://dfir.ch/posts/asyncrat_quasarrat/

[7] https://www.virustotal.com/gui/ip-address/195.26.255[.]81

[8] https://www.speedguide.net/port.php?port=8041

[9] https://www.esentire.com/blog/exploring-the-infection-chain-screenconnects-link-to-asyncrat-deployment

[10] https://scammer.info/t/taking-out-connectwise-sites/153479/518?page=26

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About the author
Isabel Evans
Cyber Analyst

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May 13, 2025

Revolutionizing OT Risk Prioritization with Darktrace 6.3

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Powering smarter protection for industrial systems

In industrial environments, security challenges are deeply operational. Whether you’re running a manufacturing line, a power grid, or a semiconductor fabrication facility (fab), you need to know: What risks can truly disrupt my operations, and what should I focus on first?

Teams need the right tools to shift from reactive defense, constantly putting out fires, to proactively thinking about their security posture. However, most OT teams are stuck using IT-centric tools that don’t speak the language of industrial systems, are consistently overwhelmed with static CVE lists, and offer no understanding of OT-specific protocols. The result? Compliance gaps, siloed insights, and risk models that don’t reflect real-world exposure, making risk prioritization seem like a luxury.

Darktrace / OT 6.3 was built in direct response to these challenges. Developed in close collaboration with OT operators and engineers, this release introduces powerful upgrades that deliver the context, visibility, and automation security teams need, without adding complexity. It’s everything OT defenders need to protect critical operations in one platform that understands the language of industrial systems.

additions to darktrace / ot 6/3

Contextual risk modeling with smarter Risk Scoring

Darktrace / OT 6.3 introduces major upgrades to OT Risk Management, helping teams move beyond generic CVE lists with AI-driven risk scoring and attack path modeling.

By factoring in real-world exploitability, asset criticality, and operational context, this release delivers a more accurate view of what truly puts critical systems at risk.

The platform now integrates:

  • CISA’s Known Exploited Vulnerabilities (KEV) database
  • End-of-life status for legacy OT devices
  • Firewall misconfiguration analysis
  • Incident response plan alignment

Most OT environments are flooded with vulnerability data that lacks context. CVE scores often misrepresent risk by ignoring how threats move through the environment or whether assets are even reachable. Firewalls are frequently misconfigured or undocumented, and EOL (End of Life) devices, some of the most vulnerable, often go untracked.

Legacy tools treat these inputs in isolation. Darktrace unifies them, showing teams exactly which attack paths adversaries could exploit, mapped to the MITRE ATT&CK framework, with visibility into where legacy tech increases exposure.

The result: teams can finally focus on the risks that matter most to uptime, safety, and resilience without wasting resources on noise.

Automating compliance with dynamic IEC-62443 reporting

Darktrace / OT now includes a purpose-built IEC-62443-3-3 compliance module, giving industrial teams real-time visibility into their alignment with regulatory standards. No spreadsheets required!

Industrial environments are among the most heavily regulated. However, for many OT teams, staying compliant is still a manual, time-consuming process.

Darktrace / OT introduces a dedicated IEC-62443-3-3 module designed specifically for industrial environments. Security and operations teams can now map their security posture to IEC standards in real time, directly within the platform. The module automatically gathers evidence across all four security levels, flags non-compliance, and generates structured reports to support audit preparation, all in just a few clicks.Most organizations rely on spreadsheets or static tools to track compliance, without clear visibility into which controls meet standards like IEC-62443. The result is hidden gaps, resource-heavy audits, and slow remediation cycles.

Even dedicated compliance tools are often built for IT, require complex setup, and overlook the unique devices found in OT environments. This leaves teams stuck with fragmented reporting and limited assurance that their controls are actually aligned with regulatory expectations.

By automating compliance tracking, surfacing what matters most, and being purpose built for industrial environments, Darktrace / OT empowers organizations to reduce audit fatigue, eliminate blind spots, and focus resources where they’re needed most.

Expanding protocol visibility with deep insights for specialized OT operations

Darktrace has expanded its Deep Packet Inspection (DPI) capabilities to support five industry-specific protocols, across healthcare, semiconductor manufacturing, and ABB control systems.

The new protocols build on existing capabilities across all OT industry verticals and protocol types to ensure the Darktrace Self-Learning AI TM can learn intelligently about even more assets in complex industrial environments. By enabling native, AI-driven inspection of these protocols, Darktrace can identify both security threats and operational issues without relying on additional appliances or complex integrations.

Most security platforms lack native support for industry-specific protocols, creating critical visibility gaps in customer environments like healthcare, semiconductor manufacturing, and ABB-heavy industrial automation. Without deep protocol awareness, organizations struggle to accurately identify specialized OT and IoT assets, detect malicious activity concealed within proprietary protocol traffic, and generate reliable device risk profiles due to insufficient telemetry.

These blind spots result in incomplete asset inventories, and ultimately, flawed risk posture assessments which over-index for CVE patching and legacy equipment.

By combining protocol-aware detection with full-stack visibility across IT, OT, and IoT, Darktrace’s AI can correlate anomalies across domains. For example, connecting an anomaly from a Medical IoT (MIoT) device with suspicious behavior in IT systems, providing actionable, contextual insights other solutions often miss.

Conclusion

Together, these capabilities take OT security beyond alert noise and basic CVE matching, delivering continuous compliance, protocol-aware visibility, and actionable, prioritized risk insights, all inside a single, unified platform built for the realities of industrial environments.

[related-resource]

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About the author
Pallavi Singh
Product Marketing Manager, OT Security & Compliance
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