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January 17, 2024

Detecting Trusted Network Relationship Abuse

Discover how Darktrace DETECT and the SOC team responded to a network compromise via a trusted partner relationship with this case study.
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
Adam Potter
Senior Cyber Analyst
Written by
Taylor Breland
Analyst Team Lead, San Francisco
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17
Jan 2024

Trusted relationships between organizations and third parties have become an increasingly popular target for cyber threat actors to gain access to sensitive networks. These relationships are typically granted by organizations to external or adjacent entities and allow for the access of internal resources for business purposes.1 Trusted network relations can exist between constituent elements of an overarching corporation, IT-service providers and their customers, and even implicitly between IT product vendors and their customers.

Several high-profile compromises have occurred due to the leveraging of privileged network access by such third parties. One prominent example is the 2016 DNC network attack, in which the trust between the Democratic Congressional Campaign Committee (DCCC) and the Democratic National Committee (DNC) was exploited. Supply chain attacks, which also leverage the implicit trust between IT vendors and customers, are also on the rise with some estimates projecting that by 2025, almost half of all organizations will be impact by supply chain compromises.2 These trends may also be attributed to the prevalence of remote work as well as the growth in IT-managed service providers.3

Given the nature of such network relationships and threat techniques, signatures-based detection is heavily disadvantaged in the identification and mitigation of such trust abuses; network administrators cannot as easily use firewalls to block IPs that need access to networks. However, Darktrace DETECT™, and its Self-Learning AI, has proven successful in the identification and mitigation of these compromises. In September 2023, Darktrace observed an incident involving the abuse of such a trusted relationship on the network of a healthcare provider.

Attack Overview

In early September 2023, a Darktrace customer contacted the Darktrace Security Operations Center (SOC) through the Ask the Expert™ (ATE) service requesting assistance with suspicious activity detected on their network. Darktrace had alerted the customer’s security team to an unknown device that had appeared on their network and proceeded to perform a series of unexpected activities, including reconnaissance, lateral movement, and attempted data exfiltration.

Unfortunately for this customer, Darktrace RESPOND™ was not enabled in autonomous response mode at the time of this compromise, meaning any preventative actions suggested by RESPOND had to be applied manually by the customer’s security team after the fact.  Nevertheless, Darktrace’s prompt identification of the suspicious activity and the SOC’s investigation helped to disrupt the intrusion in its early stages, preventing it from developing into a more disruptive compromise.

Initial Access

Darktrace initially observed a new device that appeared within the customers internal network with a Network Address Translated (NAT) IP address that suggested remote access from a former partner organization’s network. Further investigation carried out by the customer revealed that poor credential policies within the partner’s organization had likely been exploited by attackers to gain access to a virtual desktop interface (VDI) machine.

Using the VDI appliance of a trusted associate, the threat actor was then able to gain access to the customer’s environment by utilizing NAT remote access infrastructure. Devices within the customer’s network had previously been utilized for remote access from the partner network when such activity was permitted and expected. Since then, access to this network was thought to have been removed for all parties. However, it became apparent that the remote access functionality remained operational. While the customer also had firewalls within the environment, a misconfiguration at the time of the attack allowed inbound port access to the remote environment resulting in the suspicious device joining the network on August 29, 2023.

Internal Reconnaissance

Shortly after the device joined the network, Darktrace observed it carrying out a string of internal reconnaissance activity. This activity was initiated with internal ICMP address connectivity, followed by internal TCP connection attempts to a range of ports associated with critical services like SMB, RDP, HTTP, RPC, and SSL. The device was also detected attempting to utilize privileged credentials, which were later identified as relating to a generic multi-purpose administrative account. The threat actor proceeded to conduct further internal reconnaissance, including reverse DNS sweeps, while also attempting to use six additional user credentials.

In addition to the widespread internal connectivity, Darktrace observed persistent connection attempts focused on the RDP and SMB protocols. Darktrace also detected additional SMB enumeration during this phase of the attacker’s reconnaissance. This reconnaissance activity largely attempted to access a wide variety of SMB shares, previously unseen by the host to identify available share types and information available for aggregation. As such, the breach host conducted a large spike in SMB writes to the server service (srvsvc) endpoint on a range of internal hosts using the credential: extramedwb. SMB writes to this endpoint traditionally indicate binding attempts.

Beginning on August 31, Darktrace identified a new host associated with the aforementioned NAT IP address. This new host appeared to have taken over as the primary host conducting the reconnaissance and lateral movement on the network taking advantage of the VDI infrastructure. Like the previous host, this one was observed sustaining reconnaissance activity on August 31, featuring elevated SMB enumeration, SMB access failures, RDP connection attempts, and reverse DNS sweeps.  The attackers utilized several credentials to execute their reconnaissance, including generic and possibly default administrative credentials, including “auditor” and “administrator”.

Figure 1: Advanced Search query highlighting anomalous activity from the second observed remote access host over the course of one week surrounding the time of the breach.

Following these initial detections by Darktrace DETECT, Darktrace’s Cyber AI Analyst™ launched an autonomous investigation into the scanning and privileged internal connectivity and linked these seemingly separate events together into one wider internal reconnaissance incident.

Figure 2: Timeline of an AI Analyst investigation carried out between August 29 and August 31, 2023, during which it detected an increased volume of scanning and unusual privileged internal connectivity.

Lateral Movement

Following the reconnaissance activity performed by the new host observed exploiting the remote access infrastructure, Darktrace detected an increase in attempts to move laterally within the customer’s network, particularly via RPC commands and SMB file writes.

Specifically, the threat actor was observed attempting RPC binds to several destination devices, which can be used in the calling of commands and/or the creation of services on destination devices. This activity was highlighted in repeated failed attempts to bind to the ntsvcs named pipe on several destination devices within the network. However, given the large number of connection attempts, Darktrace did also detect a number of successful RPC connections.

Darktrace also detected a spike in uncommon service control (SVCCTL) ExecMethod, Create, and Start service operations from the breach device.

Figure 3: Model breach details noting the affected device performing unsuccessful RPC binds to endpoints not supported on the destination device.

Additional lateral movement activity was performed using the SMB/NTLM protocols. The affected device also conducted a series of anonymous NTLM logins, whereby NTLM authentication attempts occurred without a named client principal, to a range of internal hosts. Such activity is highly indicative of malicious or unauthorized activity on the network. The host also employed the outdated SMB version 1 (SMBv1) protocol during this phase of the kill chain. The use of SMBv1 often represents a compliance issue for most networks due to the high number of exploitable vulnerabilities associated with this version of the protocol.

Lastly, Darktrace identified the internal transfer of uncommon executables, such as ‘TRMtZSqo.exe’, via SMB write. The breach device was observed writing this file to the hidden administrative share (ADMIN$) on a destination server. Darktrace recognized that this activity was highly unusual for the device and may have represented the threat actor transferring a malicious payload to the destination server for further persistence, data aggregation, and/or command and control (C2) operations. Further SMB writes of executable files, and the subsequent delete of these binaries, were observed from the device at this time. For example, the additional executable ‘JAqfhBEB.exe’ was seen being deleted by the breach device. This deletion, paired with the spike in SVCCTL Create and Start operations occurring, suggests the transfer, execution, and removal of persistence and data harvesting binaries within the network.

Figure 4: AI Analyst details highlighting the SMB file writes of the unusual executable from the remote access device during the compromise.

Conclusion

Ultimately, Darktrace was able to successfully identify and alert for suspicious activity being performed by a threat actor who had gained unauthorized access to the customer’s network by abusing one of their trusted relationships.

The identification of scanning, RPC commands and SMB sessions directly assisted the customer in their response to contain and mitigate this intrusion. The investigation carried out by the Darktrace SOC enabled the customer to promptly triage and remediate the attack, mitigating the potential damage and preventing the compromise from escalating further. Had Darktrace RESPOND been enabled in autonomous response mode at the time of the attack, it would have been able to take swift action to inhibit the scanning, share enumerations and file write activity, thereby thwarting the attacker’s network reconnaissance and lateral movement attempts.

By exploiting trusted relationships between organizations, threat actors are often able to bypass traditional signatured-based security methods that have previously been reconfigured to allow and trust connections from and to specific endpoints. Rather than relying on the configurations of specific rules and permitted IP addresses, ports, and devices, Darktrace DETECT’s anomaly-based approach to threat detection meant it was able to identify suspicious network activity at the earliest stage, irrespective of the offending device and whether the domain or relationship was trusted.

Credit to Adam Potter, Cyber Security Analyst, Taylor Breland, Analyst Team Lead, San Francisco.

Darktrace DETECT Model Breach Coverage:

  • Device / ICMP Address Scan
  • Device / Network Scan
  • Device / Suspicious SMB Scanning Activity
  • Device / RDP Scan
  • Device / Possible SMB/NTLM Reconnaissance
  • Device / Reverse DNS Sweep
  • Anomalous Connection / SMB Enumeration
  • Device / Large Number of Model Breaches
  • Anomalous Connection / Suspicious Activity On High Risk Device
  • Unusual Activity / Possible RPC Recon Activity
  • Device / Anonymous NTLM Logins
  • Anomalous Connection / Unusual SMB Version 1 Connectivity
  • Device / Repeated Unknown RPC Service Bind Errors
  • Anomalous Connection / New or Uncommon Service Control
  • Compliance / SMB Drive Write
  • Anomalous File / Internal / Unusual Internal EXE File Transfer
  • Device / Multiple Lateral Movement Model Breaches

AI Analyst Incidents:

  • Scanning of Multiple Devices
  • Extensive Unusual RDPConnections
  • SMB Write of Suspicious File
  • Suspicious DCE-RPC Activity

MITRE ATT&CK Mapping

  • Tactic: Initial Access
  • Technique: T1199 - Trusted Relationship
  • Tactic: Discovery
  • Technique:
  • T1018 - Remote System Discovery
  • T1046 - Network Service Discovery
  • T1135 - Network Share Discovery
  • T1083 - File and Directory Discovery
  • Tactic: Lateral Movement
  • Technique:
  • T1570 - Lateral Tool Transfer
  • T1021 - Remote Services
  • T1021.002 - SMB/Windows Admin Shares
  • T1021.003 - Distributed Component Object Model
  • T1550 - Use Alternate Authentication Material

References

1https://attack.mitre.org/techniques/T1199/

2https://www.cloudflare.com/learning/insights-supply-chain-attacks/

3https://newsroom.cisco.com/c/r/newsroom/en/us/a/y2023/m09/companies-reliance-on-it-managed-services-increases-in-2023-sector-valued-at-us-472-billion-globally.html#:~:text=IT%20channel%20partners%20selling%20managed,US%24419%20billion%20in%202022.

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
Adam Potter
Senior Cyber Analyst
Written by
Taylor Breland
Analyst Team Lead, San Francisco

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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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