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
Brianna Luong (Leddy)
Sr. Technical Alliances Manager
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20
Oct 2021
In the era of international-scale cyber-warfare, focus has started to move away from small-time cyber thieves toward well-known, well-funded and sometimes government-backed cyber-crime organizations. Cyber-attacks sometimes work on discordant scales, however, and it doesn’t always take big budgets or key players for considerable damage to be dealt.
Numerous stories detail how the criminal and the curious alike have single-handedly breached some of the most secure systems in the world. At the more amusing end, there’s the story of Kristoffer von Hassel who discovered a novel exploit in Microsoft’s Xbox Live system at just five years old. And then of course there are those who hack their way right into promising security careers by breaching systems at major organizations. However, genuine damage has been done by individual threat actors as well.
These might be criminals using second-hand offensive tools, buying botnet armies for as little as $10 on the Dark Web, or using ransomware files downloaded for free. But ultimately, even a single cyber-criminal can inflict crippling damage upon large organizations if they are given the opportunity.
This is especially the case when the tools in their possession have been developed by some of the most notorious names in cyber-crime.
Copycat criminals
In early 2021, Darktrace detected a new instance of the once notorious Ryuk ransomware being launched against a business in the APAC region. The detection was intriguing.
The developers of Ryuk, a prolific cyber-criminal organization given the name ‘Wizard Spider’, had long since abandoned it in favor of a successor called ‘Conti’. Wizard Spider have launched some of the largest cyber-attacks in recent history, allegedly with the support of the Russian government, and are under investigation by Interpol and the FBI. They are not known for using outdated tools.
It soon became clear that this attack was not being launched by Wizard Spider at all, but by small-scale threat actors picking up the tools Wizard Spider left behind. And as the new attackers proved, these tools are still far from defunct.
Ryuk ransomware: A city-stopper for sale
Ryuk ransomware is commonly used to target large enterprise environments, even taking down entire city councils in some instances. Lake City, Florida and the City of Onkaparinga in South Australia are two of its known victims, along with numerous schools and hospitals across the US.
Once active in a system, Ryuk uses a combination of symmetric (AES) and asymmetric (RSA) encryption to encrypt files, disabling Windows’ system restore feature as it does so, and generally demands payment via Bitcoin in return for a private decryption key.
Though Ryuk was not initially sold in the same manner as its predecessor, Hermes, on the Dark Web site ‘exploit[.]in’, it is now believed by some publications that the toolkit must be available somewhere for various threat actors to buy and tailor to their requirements. This explains its recurrence beyond Wizard Spider activities.
New dog, old tricks
Darktrace spotted the new instance of Ryuk during a trial with a real estate business in the APAC region. The first warning sign came when some basic .dat files were downloaded onto one of the business’ devices from an unknown Russian IP address. Darktrace immediately detected that this download was a likely breach and, had Antigena been set up in active mode, would have initiated a targeted response at this early stage.
The .dat files on the infected device allowed the attackers to use RDP (Remote Desktop Protocol) to spread further into the business’ network. Two days after the initial compromise, the threat actor had gained administrative credentials through a bruteforce attack and could begin scanning the network further.
Figure 1: Timeline of the attack
The witching hour
Just an hour after the attacker gained administrative credentials, at approximately 3:30am local time, ransomware files appeared in the business’ network. This timing was not accidental. The attackers knew that the security teams at the target business were home and asleep when the ransomware landed in the small hours of the morning, giving them plenty of time to conduct their attack.
This is precisely the kind of simple tactic which can multiply the scale of an attack without using large budgets or complex toolsets. The Ryuk ransomware rapidly began encrypting corporate files during the night, and by the time the security team returned in the morning, all they could do was shut down the entire network and hope to limit the spread of Ryuk, if only to save a few final devices.
The total attack time, from initial compromise to widespread data encryption, was just two and a half days. Whether due to understaffing or preoccupation, the security team did not find the time in that small window to respond to alerts, and, with Darktrace Antigena in passive mode, the attack was able to go ahead. This business’ need for Autonomous Response, which can protect against old and new attacks around the clock without the need for manual intervention, was painfully apparent.
Autonomous Response: Stop Ryuk before Ryuk stops you
Understanding Ryuk’s history and functionality does little good for organizations when it is still capable of eluding their defenses and catching security teams unawares. Darktrace’s Self-Learning AI is uniquely positioned to address these sophisticated threats, even as they evolve in the hands of different attackers and become unrecognizable to traditional rule-based security approaches.
Utilizing 24/7 Autonomous Response to stop both new and old threats at machine speed gives security teams the best chance of leveling the playing field against attackers. With Darktrace Antigena, the size or status of the attacking organization and their toolset is irrelevant – any anomalous and threatening behavior will be neutralized quickly and accurately, before damage can be done.
Thanks to Darktrace analyst Thomas Nommensen for his insights on the above threat find.
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.
Hola VPN Abuse: From Proxy Traffic to Malware and Cryptomining
Darktrace’s analysis of Hola VPN-related activity across multiple environments reveals how peer-to-peer proxy functionality can enable malware delivery, command-and-control traffic, and cryptomining. Darktrace data highlights consistent patterns, suspicious downloads from rare endpoints, and post-compromise behavior, demonstrating how seemingly benign software can obscure threats and facilitate further malicious activity.
How Attackers Abuse the Chinese Nezha Monitoring Tool
This blog examines how attackers abuse the Chinese-developed Nezha monitoring tool, a legitimate open-source platform with remote access capabilities. Darktrace analysis of a honeypot intrusion highlights malicious deployment via containers, demonstrating how dual-use software enables stealthy operations, trust inversion, and detection challenges in dynamic cloud and enterprise environments modern.
Hola VPN Abuse: From Proxy Traffic to Malware and Cryptomining
Introduction
In enterprise environments, non-compliant software traffic can introduce unexpected exposure by creating unmanaged paths for outbound connectivity. Hola VPN is a notable example because of its peer-to-peer design, which can effectively turn user devices into routing or exit nodes for other parties’ traffic, shifting the risk profile from that of a traditional virtual private network (VPN) to something closer to a distributed proxy.
As a result, the appearance of Hola-related activity, whether from prior installation or unintended background connections, should be treated with caution. Such activity may provide a foothold for malicious behavior, including lateral movement or command-and-control communication.
This blog explores how Hola-associated activity appeared as part of broader patterns of suspicious behavior observed across the Darktrace customer base.
The campaign
In February and March 2026, Darktrace observed similar anomalous activity across multiple customer environments, with affected devices showing consistent behavioral patterns. These included connections to multiple *.hola[.]org endpoints using Hola-related user agents, suggesting interaction with Hola infrastructure rather than isolated or incidental traffic.
Following these connections, affected customer environments showed downloads of suspicious executable files from rare external endpoints 188.241.219[.]55 and 184.241.218[.]111. Both endpoints have been flagged as potentially malicious by open-source intelligence (OSINT) [1][2].
These downloads were conducted using consistent user agents across impacted customers, specifically ‘Hola svc_js_win32/1.249.408’ and ‘Hola svc_js_win32/1.251.389’, suggesting a possible association with Hola-related activity.
Notably, this pattern aligns with recent reporting that, in some cases, Hola distributed an undeclared executable component, me[.]exe, which was later assessed to be a likely Monero-mining binary introduced via a compromised delivery pipeline [3].
Case Study 1
Darktrace first observed a new device on January 19, 2026, within a customer environment based in the Europe, Middle East, and Africa (EMEA) region. On the same day it appeared on the network, the device communicated with multiple pieces of Hola VPN-linked infrastructure before downloading a binary from a hola[.]org subdomain.
Figure 1: Cyber AI Analyst investigation highlighting Hola VPN service activity potentially associated with subsequent HTTP command-and-control (C2) connections.
Subsequent Darktrace telemetry revealed a recurring pattern of activity from the day the device was first observed through to March 4, 2026. During this period, the device repeatedly issued HTTP GET requests to the URI /bwfile?size=1048576, each returning a 200 OK response, indicating successful file retrieval.
This behavior was accompanied by a POST request to /bwfile, followed by an additional GET request for a significantly larger file at /bwfile?size=26214400, suggesting a deliberate and structured file transfer pattern.
Notably, the binary download activity was not tied to a single static host. Instead, it was observed across multiple URLs that changed over time while remaining within the same hola[.]org domain. This pattern suggests the use of rotating or distributed delivery infrastructure rather than a fixed endpoint.
Figure 2: Variation in URLs over time within the same hola[.]org domain, indicating the use of dynamically changing endpoints.
Across these events, the activity was consistently associated with the user agent Hola svc_js_win32/1.249.408, further linking the traffic to Hola-related service components. Amid these persistent and unusual connections, on February 22, Darktrace observed the device connecting to 188.241.219[.]55/proxy-peer-windows-amd64[.]exe, resulting in the download of an executable file.
Figure 3: File transfer event showing the download of an executable from the rare external endpoint 188.241.219[.]55.
Based on its file hash, the downloaded file was assessed as a likely Trojan downloader [4], with import hash (imphash) values showing similarities to samples linked to Vidar, Rhadamanthys, and Stealc according to OSINT [5]. Overall, this sequence of activity suggests that Hola-related connectivity may have been leveraged as part of a broader malware delivery chain.
Darktrace’s Autonomous Response
Due to the highly unusual activity observed, Darktrace Autonomous Response was triggered by the device’s behavior. However, as the customer deployment was configured in “Human Confirmation” mode, manual approval was required before any action could be taken.
Had the deployment been set to “Fully Autonomous” mode, Darktrace would have automatically:
Blocked connections to the associated ports and external endpoints
Prevented all outgoing network connections from the device
Enforced the device’s established ‘pattern of life’, allowing normal activity to continue while restricting any anomalous behavior
Figure 4: Example of a Darktrace Autonomous Response model highlighting the action that would have been taken, demonstrating how the system identifies anomalous behavior and applies targeted containment measures to restrict suspicious network activity.
Case Study 2
While the first case focused on anomalous activity from a newly observed device, Darktrace also identified cases in which devices had already been communicating with Hola-related endpoints prior to the suspected campaign. This may suggest pre-existing Hola usage within the environment, potentially increasing exposure and creating an avenue for subsequent suspicious activity.
One case involved three devices within a customer network based in the Americas (AMS). In this instance, a different payload was identified: me[.]exe, a potentially malicious cryptocurrency miner also referred to as HolaMonitorService[.]exe [6][7]. The downloads were observed from infrastructure similar to that seen in Case 1, including an IP address within the same 188.241.0.0/16 subnet.
Connections to *.hola[.]org, alongside the use of potential Hola-related user agents consistent with those in Case 1, were also identified, further suggesting a link between the observed activity and Hola-associated infrastructure.
Darktrace observed activity indicative of unusual VPN usage on the first affected device on February 2, followed by telemetry suggesting potential Tor usage. This was later followed by the download of me[.]exe on March 10 from 188.241.218[.]111. Notably, this device was the earliest among the three within the deployment to exhibit the presence of the suspicious executable.
Figure 5: Cyber AI Analyst detection highlighting the download of a suspicious executable from a similar external endpoint in a separate deployment.
On March 5, 2026, the second affected device exhibited a slightly different progression, initiating connections to http-test1[.]hola[.]org using the user agent ‘hola_get’. This activity was followed by the download of me[.]exe from the same endpoint on March 13, consistent with the broader pattern of Hola-related downloads observed across the environment.
Figure 6: Example of Hola VPN-related connectivity observed on the network prior to the suspected campaign, indicating pre-existing usage that may have contributed to subsequent activity.
The final affected device within this customer’s network demonstrated a more limited but related pattern, also downloading me[.]exe on March 17 using the same ‘hola_get’ user agent.
While the earlier Hola VPN usage observed across the deployment may not have been directly related to the suspected malware campaign, it may nonetheless have contributed to reduced visibility. The presence of pre-existing Hola-related traffic could have obscured malicious activity, making it more difficult to distinguish legitimate usage from attacker-driven behavior and, in turn, hindering the timely identification of the emerging compromise.
Darktrace’s Autonomous Response
For this deployment, the customer had their Autonomous Response capability configured in “Fully Autonomous” mode, allowing Darktrace to take action without human intervention. As a result, the system was able to autonomously disrupt the activity as soon as relevant events were identified through model detections.
Figure 7: Darktrace Autonomous Response actions taken against suspicious activity linked to Hola VPN.
Suspected cryptomining activity
As previously noted, some of the observed executable payloads appear to be linked to cryptomining malware. Across a subset of affected customer environments, this assessment was further supported by subsequent device activity consistent with Monero mining. Affected devices established follow-on connections to multiple external endpoints aligned with known mining infrastructure, indicating post-download execution.
Considering the broader sequence of activity, this pattern may point to a wider form of abuse in which legitimate VPN-related traffic is used to mask or facilitate malicious behavior following compromise.
On several devices, the download of executable files, including a newly observed peer[.]exe, was followed by alerts indicative of cryptocurrency mining activity. Mining-related credentials such as ‘x’ were observed using the Minergate protocol to communicate with endpoints within the 89.125.255.0/24 subnet and 188.241.218[.]111, the same endpoint involved in earlier download activity. Additional credentials appeared to reflect device-specific CPU identifiers, for example ‘12th Gen Intel(R) Core (TM) i5-1235U’.
Observed mining methods included login, submit, and job, consistent with active participation in a pool-based mining workflow rather than passive or incidental contact. The login method indicates that the host authenticated to the mining service as a worker, job reflects the assignment of computational tasks, and submit shows completed work being returned to the pool [8]. This sequence suggests that affected devices were actively contributing processing resources as part of an unauthorized distributed mining operation.
The presence of unauthorized cryptominers can lead to degraded system performance and reduced device stability. Beyond the immediate resource impact, such activity often serves as an indicator of a broader compromise rather than an isolated issue. This may increase the risk of further malware deployment, persistence mechanisms, and lateral movement, particularly in environments where the initial intrusion has not been fully contained.
Conclusion
Across affected environments, detections such as unusual VPN usage, connections to Hola infrastructure, anomalous HTTP activity, suspicious file downloads, and subsequent cryptomining behavior were linked into a single, evolving incident narrative. This aggregation provided a clearer view of attack progression, enabling security teams to understand not just isolated alerts, but the full sequence of compromise from initial contact through to post-exploitation.
Ultimately, these activities show that the risk posed by non-compliant software such as Hola VPN can extend far beyond simple policy violations. What began as traffic to Hola-related infrastructure was, in multiple cases, followed by behavior suggesting deliberate misuse, including suspicious executable downloads using Hola-related user agents and, in some instances, evidence of active cryptomining. These were not isolated anomalies, but elements of a broader pattern in which seemingly benign proxy or VPN-related communications may have created a pathway for malicious delivery and unauthorized resource exploitation.
The significance of this activity lies not only in the downloads or mining, but in what it reveals about an attacker’s ability to blend malicious operations into traffic associated with software that may already have a foothold in the environment. When unapproved software operates within an enterprise, it can reduce visibility, blur the distinction between legitimate and malicious traffic, and create opportunities to extend compromise in ways that are persistent and difficult to detect. Darktrace’s anomaly-based approach enables these behavioral distinctions to be identified, regardless of whether the device is new or long established within the network.
Credit to Min Kim (Associate Principal Analyst), Priya Thapa (Senior Cyber Analyst) Edited by Ryan Traill (Content Manager)
![Variation in URLs over time within the same hola[.]org domain, indicating the use of dynamically changing endpoints.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/6a304bdeff111215c0436931_Screenshot%202026-06-15%20at%2012.00.43%E2%80%AFPM.png)
![File transfer event showing the download of an executable from the rare external endpoint 188.241.219[.]55.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/6a304c2468d20aeff16a2721_Screenshot%202026-06-15%20at%2012.01.53%E2%80%AFPM.png)
