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May 20, 2025

Adapting to new USCG cybersecurity mandates: Darktrace for ports and maritime systems

Darktrace uses AI-led OT, IoT, and IT Network Security to help secure maritime transportation systems. This blog describes some of the new mandated requirements by the USCG and demonstrates Darktrace’s security capabilities.
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
Daniel Simonds
Director of Operational Technology
Cargo ships at a portDefault blog image
20
May 2025

What is the Marine Transportation System (MTS)?

Marine Transportation Systems (MTS) play a substantial roll in U.S. commerce, military readiness, and economic security. Defined as a critical national infrastructure, the MTS encompasses all aspects of maritime transportation from ships and ports to the inland waterways and the rail and roadways that connect them.

MTS interconnected systems include:

  • Waterways: Coastal and inland rivers, shipping channels, and harbors
  • Ports: Terminals, piers, and facilities where cargo and passengers are transferred
  • Vessels: Commercial ships, barges, ferries, and support craft
  • Intermodal Connections: Railroads, highways, and logistics hubs that tie maritime transport into national and global supply chains

The Coast Guard plays a central role in ensuring the safety, security, and efficiency of the MTS, handling over $5.4 trillion in annual economic activity. As digital systems increasingly support operations across the MTS, from crane control to cargo tracking, cybersecurity has become essential to protecting this lifeline of U.S. trade and infrastructure.

Maritime Transportation Systems also enable international trade, making them prime targets for cyber threats from ransomware gangs to nation-state actors.

To defend against growing threats, the United States Coast Guard (USCG) has moved from encouraging cybersecurity best practices to enforcing them, culminating in a new mandate that goes into effect on July 16, 2025. These regulations aim to secure the digital backbone of the maritime industry.

Why maritime ports are at risk

Modern ports are a blend of legacy and modern OT, IoT, and IT digitally connected technologies that enable crane operations, container tracking, terminal storage, logistics, and remote maintenance.

Many of these systems were never designed with cybersecurity in mind, making them vulnerable to lateral movement and disruptive ransomware attack spillover.

The convergence of business IT networks and operational infrastructure further expands the attack surface, especially with the rise of cloud adoption and unmanaged IoT and IIoT devices.

Cyber incidents in recent years have demonstrated how ransomware or malicious activity can halt crane operations, disrupt logistics, and compromise safety at scale threatening not only port operations, but national security and economic stability.

Relevant cyber-attacks on maritime ports

Maersk & Port of Los Angeles (2017 – NotPetya):
A ransomware attack crippled A.P. Moller-Maersk, the world’s largest shipping company. Operations at 17 ports, including the Port of Los Angeles, were halted due to system outages, causing weeks of logistical chaos.

Port of San Diego (2018 – Ransomware Attack):
A ransomware attack targeted the Port of San Diego, disrupting internal IT systems including public records, business services, and dockside cargo operations. While marine traffic was unaffected, commercial activity slowed significantly during recovery.

Port of Houston (2021 – Nation-State Intrusion):
A suspected nation-state actor exploited a known vulnerability in a Port of Houston web application to gain access to its network. While the attack was reportedly thwarted, it triggered a federal investigation and highlighted the vulnerability of maritime systems.

Jawaharlal Nehru Port Trust, India (2022 – Ransomware Incident):
India’s largest container port experienced disruptions due to a ransomware attack affecting operations and logistics systems. Container handling and cargo movement slowed as IT systems were taken offline during recovery efforts.

A regulatory shift: From guidance to enforcement

Since the Maritime Transportation Security Act (MTSA) of 2002, ports have been required to develop and maintain security plans. Cybersecurity formally entered the regulatory fold in 2020 with revisions to 33 CFR Part 105 and 106, requiring port authorities to assess and address computer system vulnerabilities.

In January 2025, the USCG finalized new rules to enforce cybersecurity practices across the MTS. Key elements include (but are not limited to):

  • A dedicated cyber incident response plan (PR.IP-9)
  • Routine cybersecurity risk assessments and exercises (ID.RA)
  • Designation of a cybersecurity officer and regular workforce training (section 3.1)
  • Controls for access management, segmentation, logging, and encryption (PR.AC-1:7)
  • Supply chain risk management (ID.SC)
  • Incident reporting to the National Response Center

Port operators are encouraged to align their programs with the NIST Cybersecurity Framework (CSF 2.0) and NIST SP 800-82r3, which provide comprehensive guidance for IT and OT security in industrial environments.

How Darktrace can support maritime & ports

Unified IT + OT + Cloud coverage

Maritime ports operate in hybrid environments spanning business IT systems (finance, HR, ERP), industrial OT (cranes, gates, pumps, sensors), and an increasing array of cloud and SaaS platforms.

Darktrace is the only vendor that provides native visibility and threat detection across OT/IoT, IT, cloud, and SaaS environments — all in a single platform. This means:

  • Cranes and other physical process control networks are monitored in the same dashboard as Active Directory and Office 365.
  • Threats that start in the cloud (e.g., phishing, SaaS token theft) and pivot or attempt to pivot into OT are caught early — eliminating blind spots that siloed tools miss.

This unification is critical to meeting USCG requirements for network-wide monitoring, risk identification, and incident response.

AI that understands your environment. Not just known threats

Darktrace’s AI doesn’t rely on rules or signatures. Instead, it uses Self-Learning AI TM that builds a unique “pattern of life” for every device, protocol, user, and network segment, whether it’s a crane router or PLC, SCADA server, Workstation, or Linux file server.

  • No predefined baselines or manual training
  • Real-time anomaly detection for zero-days, ransomware, and supply chain compromise
  • Continuous adaptation to new devices, configurations, and operations

This approach is critical in diverse distributed OT environments where change and anomalous activity on the network are more frequent. It also dramatically reduces the time and expertise needed to classify and inventory assets, even for unknown or custom-built systems.

Supporting incident response requirements

A key USCG requirement is that cybersecurity plans must support effective incident response.

Key expectations include:

  • Defined response roles and procedures: Personnel must know what to do and when (RS.CO-1).
  • Timely reporting: Incidents must be reported and categorized according to established criteria (RS.CO-2, RS.AN-4).
  • Effective communication: Information must be shared internally and externally, including voluntary collaboration with law enforcement and industry peers (RS.CO-3 through RS.CO-5).
  • Thorough analysis: Alerts must be investigated, impacts understood, and forensic evidence gathered to support decision-making and recovery (RS.AN-1 through RS.AN-5).
  • Swift mitigation: Incidents must be contained and resolved efficiently, with newly discovered vulnerabilities addressed or documented (RS.MI-1 through RS.MI-3).
  • Ongoing improvement: Organizations must refine their response plans using lessons learned from past incidents (RS.IM-1 and RS.IM-2).

That means detections need to be clear, accurate, and actionable.

Darktrace cuts through the noise using AI that prioritizes only high-confidence incidents and provides natural-language narratives and investigative reports that explain:

  • What’s happening, where it’s happening, when it’s happening
  • Why it’s unusual
  • How to respond

Result: Port security teams often lean and multi-tasked can meet USCG response-time expectations and reporting needs without needing to scale headcount or triage hundreds of alerts.

Built-for-edge deployment

Maritime environments are constrained. Many traditional SaaS deployment types often are unsuitable for tugboats, cranes, or air-gapped terminal systems.

Darktrace builds and maintains its own ruggedized, purpose-built appliances and unique virtual deployment options that:

  • Deploy directly into crane networks or terminal enclosures
  • Require no configuration or tuning, drop-in ready
  • Support secure over-the-air updates and fleet management
  • Operate without cloud dependency, supporting isolated and air-gapped systems

Use case: Multiple ports have been able to deploy Darktrace directly into the crane’s switch enclosure, securing lateral movement paths without interfering with the crane control software itself.

Segmentation enforcement & real-time threat containment

Darktrace visualizes real-time connectivity and attack pathways across IT, OT, and IoT it and integrates with firewalls (e.g., Fortinet, Cisco, Palo Alto) to enforce segmentation using AI insights alongside Darktrace’s own native autonomous and human confirmed response capabilities.

Benefits of autonomous and human confirmed response:

  • Auto-isolate rogue devices before the threat can escalate
  • Quarantine a suspicious connectivity with confidence operations won’t be halted
  • Autonomously buy time for human responders during off-hours or holidays
  • This ensures segmentation isn't just documented but that in the case of its failure or exploitation responses are performed as a compensating control

No reliance on 3rd parties or external connectivity

Darktrace’s supply chain integrity is a core part of its value to critical infrastructure customers. Unlike solutions that rely on indirect data collection or third-party appliances, Darktrace:

  • Uses in-house engineered sensors and appliances
  • Does not require transmission of data to or from the cloud

This ensures confidence in both your cyber visibility and the security of the tools you deploy.

See examples here of how Darktrace stopped supply chain attacks:

Readiness for USCG and Beyond

With a self-learning system that adapts to each unique port environment, Darktrace helps maritime operators not just comply but build lasting cyber resilience in a high-threat landscape.

Cybersecurity is no longer optional for U.S. ports its operationally and nationally critical. Darktrace delivers the intelligence, automation, and precision needed to meet USCG requirements and protect the digital lifeblood of the modern port.

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
Daniel Simonds
Director of Operational Technology

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September 3, 2026

Darktrace Advances Incident Investigation and AI-Agent Security with OpenAI Daybreak Models

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Earlier this year, Darktrace joined OpenAI’s Daybreak Defense Network to explore how their cyber capabilities can be integrated within Darktrace products and services to transform how security teams move from signal to action.

At the heart of this work is Darktrace's behavioral understanding of customer environments and identification of complex security incidents, combined with OpenAI models that can add context to help explain why an incident matters and its potential impact on the business. By bringing these capabilities into defensive workflows security teams already use, the goal is to give defenders not just greater visibility, but the context and guidance they need to act with confidence.

Since joining the program, we've been working with OpenAI to explore how these capabilities can address specific security challenges for defenders.

The problem we're solving

Attackers continue to change how they operate, including by using AI to increase the speed and scale of some techniques. Security teams are already managing a large volume of alerts, and the question isn't just what's happening, but how it could affect the organization. Even when an incident is fully investigated and correlated, technical severity alone doesn't tell a security team how much it actually matters to the business. That same challenge extends to internal AI adoption. As organizations adopt more AI systems and agents, security teams need visibility into their behavior, access and activity, along with the broader business context needed to identify and investigate potential risk.

Darktrace's Adaptive AI™ builds a detailed, organization-specific picture of what's normal for each environment, and uses that picture to investigate threats and identify complex security activity across domains. OpenAI's models can build on Darktrace's correlated, technically prioritized incidents by adding context that can help defenders understand what may be at stake.

What we're building

Our work is focused on two areas: supporting security investigation and response, and helping defenders identify risky behavior across enterprise AI systems and agents.

The first aligns Darktrace's behavioral understanding with OpenAI models to support  security investigation and prioritization. Darktrace's Adaptive AI continuously learns the unique patterns of normal behavior within each customer it protects, creating a deep, organization-specific understanding of its digital estate. When unusual activity emerges, OpenAI's models can draw on that context to help analysts investigate the incident, understand its significance and assess potential business consequences — reducing the need to manually assemble context from fragmented signals.

Second, we are exploring how these capabilities can support AI-agent and runtime security through Darktrace / SECURE AI™. OpenAI’s Daybreak models can build on the detections and visibility Darktrace / SECURE AI provides, connecting signals across a customer's environment and help defenders identify potentially risky behavior involving AI systems and agents. Activity that might appear isolated can instead be connected with related signals, helping defenders investigate the broader context and determine appropriate remediation.

Darktrace brings deep cybersecurity expertise, an evolving understanding of each customer's environment, and AI-driven identification of threats across the digital estate. Through the Daybreak Defense Network, Darktrace is exploring how OpenAI models can augment those capabilities in defensive security workflows — supporting incident investigation and response and improving visibility into AI-agent and runtime risk.

These capabilities are still in development, and we're excited to continue building on this work.

To learn more about how Darktrace continues to innovate to meet today's most pressing security challenges, register for our upcoming launch broadcast here.

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September 3, 2026

Botnet Behind the Camera: Mirai Katana Activity on a Video Recording Device

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Key takeaways

  • Darktrace identified a camera device infected with the Mirai/Katana botnet in a sports-sector customer environment, showing how exposed IoT devices can become active participants in wider attack chains.
  • The compromise involved suspicious Wget behavior, file downloads from rare external IPs, unusual incoming HTTP connections to video recorder management interfaces, and large outbound data transfers to infrastructure associated with botnet activity.
  • The incident highlights the importance of extending visibility and response beyond traditional endpoints, as unmanaged or overlooked connected devices can be exploited for command-and-control, malware delivery, and data exfiltration.

Mirai and the Katana variant

Mirai is a botnet that first emerged in August 2016 and is well known for launching large-scale distributed-denial-of-service (DDoS) attacks, typically targeting exposed Internet of Things (IoT) devices. It identifies vulnerable IoT devices ,often by abusing default credentials or exposed services, and recruiting them into a remotely controlled botnet that can be used in DDoS campaigns [1].

Katana, one of the many variants that arose after Mirai’s source code was released publicly, was first observed in late 2020 and has been seen using more advanced capabilities, including custom command-and-control (C2), persistence mechanisms, and DDoS functionality [2].

In March 2026, research from the Nokia Deepfield Emergency Response Team (ERT) identified Katana as a Mirai-derived DDoS botnet targeting Android-based TV set-top boxes through exposed Android Debug Bridge (ADB) access.  Observed capabilities included custom C2, runtime domain rotation, multiple DDoS methods, and an on-device compiled kernel rootkit used for persistence and stealth [3].

Darktrace’s detection of Mirai Botnet activity on a camera device

In early 2026, Darktrace identified a Network/Digital Video Recorder (NVR/DVR) on the network of a sports-sector customer that had been infected with the Mirai Katana botnet and subsequently used to exfiltrate data from the customer’s environment. Seemingly related follow-up activity was observed on the same device several months later.

In both instances, the Darktrace Security Operations Centre (SOC) alerted the customer as part of the Managed Threat Detection (MTD) service. However, as Darktrace’s Autonomous Response capability was not fully enabled on the affected device, Darktrace was unable to proactively block the suspicious activity or prevent the compromise from continuing and recurring.

The initial compromise appears to have occurred when the affected device was seen using Wget to download Linux-based Executable and Linkable Format (ELF) files from a rare external IP, 195.177.94[.]105, which had not previously been observed in the customer’s network. Further analysis downloaded file hashes identified files related to the Mirai botnet.

Figure 1: Darktrace’s Real-Time AI Analyst investigation into the unusual outbound connection where the ELF files were downloaded.

Within a few hours, Darktrace detected the device uploading close to 3GB of data to another external IP, 50.7.49[.]4:3017 (ASN AS30058 FDCSERVERS), suggesting that the activity was likely routed via a virtual private server (VPS) hosted by FDC Servers [2]. Attackers often abuse VPS infrastructure from legitimate cloud providers to blend in with legitimate traffic and evade IP reputation and geolocation-based detections.

Figure 2:  Darktrace’s detection of the unusual data upload activity by the affected camera device.

Darktrace continued to observe similar data transfers to multiple rare endpoints  including 171.225.223[.]53, 95.161.128[.]62, 61.7.209[.]88, 95.161.128[.]62, which have been linked to Mirai by open-source intelligence (OSINT).

Figure 3: Darktrace’s detection of spikes in unusual external data transfer activity from the camera device.

Exploitation continued

Several months later, Darktrace identified the same exfiltration pattern on the device again, this time with stronger indications of associations with Mirai Katana botnet infection.

The device received incoming HTTP connections from 129.121.114[.]124, an external IP known to be associated with the Katana botnet IP [3]. The connections targeted the ‘/dvr/cmd’ path using the root username and user agent Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/42.0.2311.135 Safari/537.36 Edge/12.246.

The ‘/dvr/cmd’ path appears to be associated with the affected device’s web management functionality. This API endpoint has historically been targeted by Mirai and other IoT botnets through the exploitation of critical command injection vulnerabilities and automated botnet exploitation [4].

Figure 4: Darktrace’s  detection of HTTP connectivity from the external IP associated with Mirai Katana Botnet.

A few days later, Darktrace observed the Wget utility being used to download ELF files, including “/lil”,  from the IP 129.121.114[.]124. OSINT reporting has since associated this IP address with the Mirai Katana botnet. Notably, the IP observed earlier in the year, 195.177.94[.]105, had also hosted a file named “lil”, indicating a link between the observed activity.

Over the following days, the device received a sudden spike in connections from multiple rare external endpoints, suggesting a possible successful brute force attack. Darktrace also observed the device exfiltrating just under 4GB of data to another Mirai-associated IP address,  66.92.198[.]194, over ports 3344, 954922, and 80. Finally, the device was seen uploading data to the Mirai botnet IP 5.175.249[.]53 over port138 and exhibited an increase in UDP connections to 34.18.28[.]10 over port 9068.

Following both file download events, Darktrace identified spikes in external data transfers and connection attempts to rare destinations. While Darktrace’s Threat Research team could not confirm with high confidence that this to activity was directly associated with Mirai, it may indicate that Mirai Katana includes data exfiltration functionality.

Darktrace’s threat researchers also identified an internet-facing NTP server belonging to a separate customer receiving incoming connection attempts from the same initially observed IP, 195.177.94[.]105,over the port 123. This suggests that Mirai Katana may not exclusively target IoT devices.

Conclusion

This case demonstrates how threat actors can exploit overlooked IoT and OT devices to support broader malicious objectives. Here, a camera device infected with a botnet was used to exfiltrate data from the customer's environment, showing how peripheral assets can become active participants in an attack chain.

This case also reinforces a challenge many organizations face today: extending security visibility beyond traditional endpoints and servers. Cameras, sensors, and other connected devices often operate with limited monitoring and may fall outside established security processes, despite maintaining network connectivity and access to potentially sensitive environments. This is particularly relevant in the sports sector, where growing reliance on connected cameras, smart stadium technologies, and other IoT devices continues to expand the attack surface, as highlighted in Darktrace's Sports Sector Threat Report.

As botnets like Kata and Mirai continue to evolve, defenders need visibility across unmanaged IoT and edge devices, as well as security solutions that can recognize subtle deviations in device behavior that may indicate an emerging compromise.

Credit to Parvatha Ananthakannan (Cyber Analyst), Signe Zaharka (Principal Analyst)

Edited by Ryan Traill (Content Manager)

Appendices

Darktrace Model Detections

·      Anomalous File / EXE from Rare External Location

·      Anomalous File / Multiple EXE from Rare External Locations

·      Device / Initial Attack Chain Activity

·      Unusual Activity / Unusual External Data to New Endpoint

·      Anomalous Connection / Data Sent to Rare Domain

·      Unusual Activity / Enhanced Unusual External Data Transfer

·      Anomalous Connection / Uncommon 1 GiB Outbound

·      Device / Significant UDP Increase

·      Anomalous Connection / Low and Slow Exfiltration to IP

·      Compromise / Large Number of Suspicious Failed Connections

·      Compromise / Large Number of Suspicious Successful Connections

·      Unusual Activity / Unusual External Activity

·      Compliance / SSH to Rare External Destination

·      Unusual Activity / Unusual DNS

·      Device / External Network Scan

·      Device / Suspicious DNS Activity

·      Device / Large Number of Model Alerts

List of Indicators of Compromise (IoCs)

Indicator of Compromise Type Description
195.177.94[.]105 IP C2 endpoint
50.7.49[.]4:30171 IP Possible C2 endpoint
129.121.114[.]124 IP C2 endpoint
hxxp://195.177.94[.]105/n3 URL Likely C2 endpoint
hxxp://195.177.94[.]105/n2 URL Likely C2 endpoint
hxxp://129.121.114[.]124/lil URL Likely C2 endpoint
hxxp://129.121.114[.]124/HHn URL Possible C2 endpoint
hxxp://129.121.114[.]124/JFc URL Possible C2 endpoint
hxxp://129.121.114[.]124/jum URL Likely C2 endpoint
hxxp://129.121.114[.]124/OaSf URL Likely C2 endpoint
hxxp://129.121.114[.]124/OPWg URL Possible C2 endpoint
hxxp://129.121.114[.]124/vHwK URL Possible C2 endpoint
hxxp://129.121.114[.]124/VLv URL Possible C2 endpoint
hxxp://129.121.114[.]124/WbJ URL Possible C2 endpoint
hxxp://129.121.114[.]124/zkR URL Possible C2 endpoint
Ab17883ae4c3bc6afa18c439166eeeb4b03186e3093d984e3a95f573e0fcb7d8 SHA-256 Mirai payload
3d587e809dac49d34a3f717e072fd0aebe5e71db63333e45c81577d6b4266f87 SHA-256 Mirai payload
Bf6e81733a7e209d3dce80d15bf3c5d300752d961fae6b45d90c9bbe7f8c89a2 SHA-256 Possible payload
f25488303813ab1ec0eaa71562938601aac185e8aaf93adb84522557f7cf4dd6 SHA-256 Possible payload
0cb4ff6b71f4423184bfa35c34e9090297637208b0e30205d4b224e56abde2ef SHA-256 Possible payload
19c24cbeaf06b2e7697083f33a85521a9315105c784691bde7420fde4cc69410 SHA-256 Likely Mirai payload
1e74f734fff8df91f4f7172d0de10c421eca78aeb800e8a48e16bc5dbde5d20e SHA-256 Possible payload
6e71f7763d1f29d5712106ebb122e281c32787540aa2342b0fe5351d585d18d7 SHA-256 Possible payload
71f4ff7cdb6d6a7d2673c543c5d2535093afbd707b20a5b9ddf735466c1105c1 SHA-256 Possible payload
76db7ee73ebf15e48a3cb24a074d92248671ef2c6ed3bc3e708377341fb7674d SHA-256 Possible payload
da87a65f7beb438e61f0b61964fed8aa305a380f569042f84c55eca8fa7929b8 SHA-256 Possible payload
e15809eb6ba66477175270d62cfa53e4bf278595f69938708c81c4bc457930fe SHA-256 Mirai payload

MITRE ATT&CK Mapping

Tactic Technique ID Technique / Sub-technique
Initial Access T1659 Content Injection
T1189 Drive-by Compromise
Exfiltration T1041 Exfiltration Over C2 Channel
T1048.003 Exfiltration Over Unencrypted Non-C2 Protocol
Command and Control T1105 Ingress Tool Transfer
T1095 Non-Application Layer Protocol
T1571 Non-Standard Port
Reconnaissance T1595.001 Scanning IP Blocks
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About the author
Parvatha Ananthakannan
Cyber Analyst
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