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August 22, 2023

Darktrace’s Detection of Unattributed Ransomware

Leveraging anomaly-based detection, we successfully identified an ongoing ransomware attack on the network of a customer and the activity that preceded it.
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
Natalia Sánchez Rocafort
Cyber Security Analyst
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Aug 2023

In the current threat landscape, much of the conversation around ransomware focusses on high-profile strains and notorious threat groups. While organizations and their security teams are justified in these concerns, it is important not to underestimate the danger posed by smaller scale, unattributed ransomware attacks.

Unlike attributed ransomware strains, there are often no playbooks or lists of previously observed indicators of compromise (IoCs) that security teams can consult to help them shore up their cyber defenses. As such, anomaly detection is critical to ensure that emerging threats can be detected based on their abnormality on the network, rather than relying heavily on threat intelligence.

In mid-March 2023, a Darktrace customer requested analytical support from the Darktrace Security Operations Center (SOC) after they had been hit by a ransomware attack a few hours earlier. Darktrace was able to uncover a myriad of malicious activity that preceded the eventual ransomware deployment, ultimately assisting the customer to identify compromised devices and contain the ransomware attack.

Attack Overview

While there were a small number of endpoints that had been flagged as malicious by open-source intelligence (OSINT), Darktrace DETECT™ focused on the unusualness of the activity surrounding this emerging ransomware attack. This provided unparalleled visibility over this ransomware attack at every stage of the cyber kill chain, whilst also revealing the potential origins of the compromise which came months area.

Initial Compromise

Initial investigation revealed that several devices that Darktrace were observed performing suspicious activity had previously engaged in anomalous behavior several months before the ransomware event, indicating this could be a part of a repeated compromise or the result of initial access brokers.

Most notably, in late January 2023 there was a spike in unusual activity when some of the affected devices were observed performing activity indicative of network and device scanning.

Darktrace DETECT identified some of the devices establishing unusually high volumes of internal failed connections via TCP and UDP, and the SMB protocol. Various key ports, such as 135, 139, and 445, were also scanned.

Due to the number of affected devices, the exact initial attack vector is unclear; however, one likely scenario is associated with an internet-facing DNS server. Towards the end of January 2023, the server began to receive unusual TCP DNS requests from the rare external endpoint, 103.203.59[.]3, which had been flagged as potentially malicious by OSINT [4]. Based on a portion of the hostname of the device, dc01, we can assume that this server served as a gateway to the domain controller. If a domain controller is compromised, a malicious actor would gain access to usernames and passwords within a network allowing attackers to obtain administrative-level access to an organization’s digital estate.

Around the same time as the unusual TCP DNS requests, Darktrace DETECT observed the domain controller engaging in further suspicious activity. As demonstrated in Figure 1, Darktrace recognized that this server was not responding to common requests from multiple internal devices, as it would be expected to. Following this, the device was observed carrying out new or uncommon Windows Management Instrumentation (WMI) activity. WMI is typically used by network administrators to manage remote and local Windows systems [3].

Figure 1: Device event log depicting the possible Initial attack vector.


Had Darktrace RESPOND™ been enabled in autonomous response mode, it would have to blocked connections originating from the compromised internal devices as soon as they were detected, while also limiting affected devices to their pre-established patterns of file to prevent them from carrying out any further malicious activity.

Darktrace subsequently observed multiple devices establishing various chains of connections that are indicative of lateral movement activity, such as unusual internal RDP and WMI requests. While there may be devices within an organization that do regularly partake these types of connections, Darktrace recognized that this activity was extremely unusual for these devices.

Darktrace’s Self-Learning AI allows for a deep understanding of customer networks and the devices within them. It’s anomaly-based threat detection capability enables it to recognize subtle deviations in a device’s normal patterns of behavior, without depending on known IoCs or signatures and rules to guide it.

Figure 2: Observed chain of possible lateral movement.


Persistence

Darktrace DETECT observed several affected devices communicating with rare external endpoints that had also been flagged as potentially malicious by OSINT tools. Multiple devices were observed performing activity indicative of NTLM brute-forcing activity, as seen in the Figure 3 which highlights the event log of the aforementioned domain controller. Said domain controller continuously engaged in anomalous behavior throughout the course of the attack. The same device was seen using a potentially compromise credential, ‘cvd’, which was observed via an SMB login event.

Figure 3: Continued unusual external connectivity.


Affected devices, including the domain controller, continued to engage in consistent communication with the endpoints prior to the actual ransomware attack. Darktrace identified that some of these malicious endpoints had likely been generated by Domain Generation Algorithms (DGA), a classic tactic utilized by threat actors. Subsequent OSINT investigation revealed that one such domain had been associated with malware such as TrojanDownloader:Win32/Upatre!rfn [5].

All external engagements were observed by Darktrace DETECT and would have been actioned on by Darktrace RESPOND, had it been configured in autonomous response mode. It would have blocked any suspicious outgoing connections originating from the compromised devices, thus preventing additional external engagement from taking place. Darktrace RESPOND works in tandem with DETECT to autonomously take action against suspicious activity based on its unusualness, rather than relying on static lists of ‘known-bads’ or malicious IoCs.

Reconnaissance

On March 14, 2023, a few days before the ransomware attack, Darktrace observed multiple internal devices failing to establish connections in a manner that suggests SMB, RDP and network scanning. Among these devices once more was the domain controller, which was seen performing potential SMB brute-forcing, representing yet another example of malicious activity carried out by this device.

Lateral Movement

Immediately prior to the attack, many compromised devices were observed mobilizing to conduct an array of high-severity lateral movement activity. Darktrace detected one device using two administrative credentials, namely ‘Administrator’ and ‘administrator’, while it also observed a notable spike in the volume of successful SMB connections from the device around the same time.

At this point, Darktrace DETECT was observing the progression of this attack along the cyber kill chain. What had started as internal recognisance, had escalated to exploitation and ensuing command-and-control activity. Following an SMB brute-force attempt, Darktrace DETECT identified a successful DCSync attack.

A DCSync attack occurs when a malicious actor impersonates a domain controller in an effort to gather sensitive information, such as user credentials and passwords hashes, by replicating directory services [1]. In this case, a device sent various successful DRSGetNCChanges operation requests to the DRSUAPI endpoint.

Data Exfiltration

Around the same time, Darktrace detected the compromised server transferring a high volume of data to rare external endpoints associated with Bublup, a third-party project management application used to save and share files. Although the actors attempted to avoid the detection of security tools by using a legitimate file storage service, Darktrace understood that this activity represented a deviation in this device’s expected pattern of life.

In one instance, around 8 GB of data was transferred, and in another, over 4 GB, indicating threat actors were employing a tactic known as ‘low and slow’ exfiltration whereby data is exfiltrated in small quantities via multiple connections, in an effort to mask their suspicious activity. While this tactic may have evaded the detection of traditional security measures, Darktrace’s anomaly-based detection allowed it to recognize that these two incidents represented a wider exfiltration event, rather than viewing the transfers in isolation.

Impact

Finally, Darktrace began to observe a large amount of suspicious SMB activity on the affected devices, most of which was SMB file encryption. DETECT observed the file extension ‘uw9nmvw’ being appended to many files across various internal shares and devices. In addition to this, a potential ransom note, ‘RECOVER-uw9nmvw-FILES.txt’, was detected on the network shortly after the start of the attack.

Figure 4: Depiction of the high-volume of suspicious SMB activity, including file encryption.


Conclusion

Ultimately, this incident show cases how Darktrace was able to successfully identify an emerging ransomware attack using its unrivalled anomaly-based detection capabilities, without having to rely on any previously established threat intelligence. Not only was Darktrace DETECT able to identify the ransomware at multiple stages of the kill chain, but it was also able to uncover the anomalous activity that took place in the buildup to the attack itself.

As the attack progressed along the cyber kill chain, escalating in severity at every juncture, DETECT was able to provide full visibility over the events. Through the successful identification of compromised devices, anomalous administrative credentials usage and encrypted files, Darktrace was able to greatly assist the customer, ensuring they were well-equipped to contain the incident and begin their incident management process.

Darktrace would have been able to aid the customer even further had they enabled its autonomous response technology on their network. Darktrace RESPOND would have taken targeted, mitigative action as soon as suspicious activity was detected, preventing the malicious actors from achieving their goals.

Credit to: Natalia Sánchez Rocafort, Cyber Security Analyst, Patrick Anjos, Senior Cyber Analyst.

MITRE Tactics/Techniques Mapping

RECONNAISSANCE

Scanning IP Blocks  (T1595.001)

RECONNAISSANCE

Vulnerability Scanning  (T1595.002)

IMPACT

Service Stop  (T1489)

LATERAL MOVEMENT

Taint Shared Content (T1080)

IMPACT

Data Encrypted for Impact (T1486)

INITIAL ACCESS

Replication Through Removable Media (T1200)

DEFENSE EVASION

Rogue Domain Controller (T1207)

COMMAND AND CONTROL

Domain Generation Algorithms (T1568.002)

EXECUTION

Windows Management Instrumentation (T1047)

INITIAL ACCESS

Phishing (T1190)

EXFILTRATION

Exfiltration Over C2 Channel (T1041)

IoC Table

IoC ----------- TYPE ------------- DESCRIPTION + PROBABILITY

CVD --------- credentials -------- Possible compromised credential

.UW9NMVW - File extension ----- Possible appended file extension

RECOVER-UW9NMVW-FILES.TXT - Ransom note - Possible ransom note observed

84.32.188[.]186 - IP address ------ C2 Endpoint

AS.EXECSVCT[.]COM - Hostname - C2 Endpoint

ZX.EXECSVCT[.]COM - Hostname - C2 Endpoint

QW.EXECSVCT[.]COM - Hostname - C2 Endpoint

EXECSVCT[.]COM - Hostname ------ C2 Endpoint

15.197.130[.]221 --- IP address ------ C2 Endpoint

AS59642 UAB CHERRY SERVERS - ASN - Possible ASN associated with C2 Endpoints

108.156.28[.]43

108.156.28[.]22

52.84.93[.]26

52.217.131[.]241

54.231.193[.]89 - IP addresses - Possible IP addresses associated with data exfiltration

103.203.59[.]3 -IP address ---- Possible IP address associated with initial attack vector

References:

[1] https://blog.netwrix.com/2021/11/30/what-is-dcsync-an-introduction/

[2] https://www.easeus.com/computer-instruction/delete-system32.html#:~:text=System32%20is%20a%20folder%20on,DLL%20files%2C%20and%20EXE%20files.

[3] https://www.techtarget.com/searchwindowsserver/definition/Windows-Management-Instrumentation#:~:text=WMI%20provides%20users%20with%20information,operational%20environments%2C%20including%20remote%20systems.

[4] https://www.virustotal.com/gui/ip-address/103.203.59[.]3

[5] https://otx.alienvault.com/indicator/ip/15.197.130[.]221

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
Natalia Sánchez Rocafort
Cyber Security Analyst

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June 9, 2026

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

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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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June 9, 2026

Always On, Always Defending: Inside the AI-Driven SOC

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Today’s SOC: A system under pressure

The SOC has been described as the:

  • Control center for security systems management  
  • Operations center for log analysis and alert response
  • Command center for network monitoring and investigation

But the CISO at a manufacturer of industrial power solutions says today’s SOC is far more dynamic:

“The SOC is an active player in a never-ending chess match where the pieces are always moving, the rules are constantly changing, and we’re continuously adjusting our tactical and strategic approaches to keep up.”

This has created a balancing act for cybersecurity professionals:

  • Support expanding digital estates to fuel innovation…or risk limiting business growth
  • Stop advanced cyberattacks at scale…or risk severe financial and reputational impacts

But balancing these responsibilities is increasingly difficult. Attackers are operating at machine speed and scale using sophisticated, adaptive techniques that overwhelm teams and bypass legacy defenses. At the same time, more than half of cybersecurity teams are understaffed, and 65% have unfilled cybersecurity positions (ISACA).

“The SOC is hitting its breaking point,” admits the VP of IT at a U.S.-based risk management services provider.”

“That’s the hard reality,” affirms a Chief Digital and Technology Officer at a North American financial services organization. “SOC teams are drowning in alerts, wasting time researching the most benign incidents while missing critical threats.”

Traditional tools lack the context and autonomous reasoning needed to determine which ones are truly dangerous, requiring analysts to manually review and respond. But with thousands of alerts hitting SOCs daily, the task exceeds human capacity, with recent industry research revealing that 40% to 42% of security alerts now go uninvestigated.

“Our old governance models of throwing bodies at it, that’s not going to work,” says the Group CIO of a multinational holding company. “Attackers move at machine speed, and our defenses have to operate at the same pace. Using AI for cybersecurity is the only way to do that.”

Why AI is essential

AI is about speed, scale, and context.

SOC teams are still expected to find the proverbial “needle in a haystack”, but the haystack keeps growing. As digital infrastructures expand and threat actors use AI to rapidly scale attacks and exploit vulnerabilities, success isn’t about keeping up but changing the approach.

This is where AI comes in, enabling security teams to operate at machine speed and scale by:

  • Analyzing vast amounts of data and correlating signals across domains within seconds
  • Detecting possible threats in real time and taking immediate action to mitigate risk
  • Prioritizing threats by severity and uncovering contextual details for rapid triage

The power of AI isn’t theoretical; it is transforming how today’s businesses operate.

The Chief Digital and Technology Officer at a financial services firm says within a single month of using Darktrace, the solution tracked billions of network events, autonomously investigated tens of millions of those incidents, and added the equivalent of 1,000 analyst hours of investigation. It also found threats that bypassed traditional tools, autonomously responding to contain or disrupt the threat on over 30,000 emails, including 18,000 the firm’s native email filter missed.

When Darktrace says it “takes action on a threat,” it generally means its platform can move beyond just detecting suspicious activity and automatically respond to contain or disrupt the threat—such as isolating a device, slowing or blocking suspicious network traffic, disabling risky user activity, or triggering security workflows—depending on how the system is configured.

AI isn’t about displacing humans.

AI is a powerful tool for handling large-scale data analysis, pattern detection, and repetitive tasks, but it cannot replace human critical thinking. By removing mindless work that does not require judgment, AI frees analysts to focus on what humans do best: applying reasoning, context, and sound decision-making to complex threats.

“AI is a workforce maximizer,” says the Chief Digital and Technology Officer. “It augments our team by monitoring and detecting threats at a scale beyond human capacity while providing the critical context we need to make faster, more confident decisions.

Rather than replacing people, AI is changing how security professionals work. Analysts can reclaim time previously spent on tedious, manual triage to focus on higher priorities and proactive initiatives like advanced threat hunting, strategic risk management, and security enablement and training.

“Aside from risk mitigation, our biggest ROI is in efficiency,” says the Head of Security at global business services provider. “What used to take 90% of our investigation time is now handled automatically, so we can focus on the final 10%, which requires critical thinking."

For SOC teams under pressure, the impact can be transformative, with security leaders reporting significant real-world outcomes using Darktrace Self-Learning AITM, including:

  • Phishing emails reduced by 99%
  • 1 million+ emails autonomously analyzed each month, with no email-based incidents reported
  • Potential threats autonomously neutralized in under four seconds, on average  
  • 99% of investigations conducted autonomously, surfacing only the high-priority 1% of threats for analyst review

How AI optimizes the SOC

To protect the modern enterprise, you absolutely need the right tools,” says CTO at leading European fashion brand. “Without them you’re a victim. With them, you’re a defender. AI and the machine speed detect/response it enables makes it the most critical tool.”

Replacing chaos with clarity and control  

It’s important to note that different AI solutions address different needs. Companies should clearly understand their specific use case and select the solution that best aligns with their goals, requirements, and operational needs.  

When it comes to choosing cybersecurity in a machine-speed threat landscape, time is the most valuable resource. Organizations require AI that can move from insight to action by:

  • Learning an organization’s unique behavioral patterners
  • Correlating signals across domains to detect anomalous activity
  • Prioritizing events and autonomously responding at scale to the vast majority
  • Quarantining high-impact threats until the SOC can investigate
  • Arming analysts with deep, contextual information to accelerate investigations

“Darktrace AI gives us threat detections based on facts, not guesses,” says the Group CIO. “It moves the SOC beyond alert overload to confident, informed decision-making. When Darktrace flags something, we pay attention. False positives are very rare, so we act with speed and confidence without second-guessing.”

Replacing anxiety with confidence and peace of mind

Every missed alert can have real-world consequences.

The strain of maintaining constant vigilance at scale without holistic visibility and automation is taking its toll on security professionals: 66% report increased stress, and nearly half say it’s the reason they’re leaving the field (ISACA).

The CIO at a professional sports organization says that’s not surprising: “If you don’t know what’s going on, anything could be happening. Operating with that level of uncertainty and control is incredibly stressful.”

AI gives SOCs the power to be proactive by unifying telemetry across network, email, identity, and cloud environments to provide a complete picture and a stronger foundation for action. The benefits for analysts, both personally and professionally, are significant:

  • Achieve greater work-life balance: “Knowing that Darktrace has our backs 24/7 and will take immediate action to stop threats  means we can now work normal hours and take vacations without worrying,” says the Chief Digital and Technology Officer.
  • Feel in control with deeper insights: “It not only stops and quarantines threats but also provides the deep context we need to quickly investigate and respond,” explains the Head of Security.  
  • Gain confidence the business is protected 24/7: “We can sleep at night. With Darktrace I’m confident that even with a small team we can protect the business 24/7,” adds the former retail CIO.

The modern SOC: A system of balance

Elevated to a core pillar of business strategy, the modern SOC is now considered:

  • The nerve center of cyber risk and proactive defense
  • The AI-powered command center for operational resilience
  • The strategic hub for contextual decision-making at scale

The SOC has evolved from a reactive center responsible for managing systems into a proactive, frontline defender and strategic business enabler—integral to innovation and growth.

AI is the key to balancing these responsibilities.

“We can only grow as fast as we can secure the business,” says the Head of Security. “AI gives us the speed, scale, and confidence to do both.”

*Metrics are based on the customer’s interview, data and sourced from its monthly Cyber AI Insights reporting.

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