Forensic Victory: Catching the Ransomware EDR Couldn't See
This blog details a simulation of a ransomware attack that bypassed EDR, simulated via a ClickFix social engineering technique. The attack used an obfuscated HTML and custom C++ binary to encrypt files and establish a reverse shell. Cado's forensic platform then demonstrated how to trace the attack chain, highlighting the need for robust DFIR beyond EDR.
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
Nate Bill
Threat Researcher
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13
Feb 2025
Introduction: Catching the ransomware EDR couldn't see
Endpoint Detection & Response (EDR) is frequently used by organizations as the first line of defense against cyberattacks. EDR platforms monitor organizations’ endpoints (servers, employee laptops, etc.) and detect and contain malicious activity running where possible. This blog will explore a ransomware attack in a lab environment, using payloads inspired from real attacks.
The incident
For this experiment, Cado Security Labs (now part of Darktrace) set up an up-to-date Windows machine, with a mainstream EDR tool installed, and simulated a ClickFix attack [1] against the user, which relies on socially engineering the user into running malicious commands.
During the first stage of the attack, the fake end user receives a phishing email with a ClickFix attachment:
Figure 1: Test Email
As this is a test, the email was kept fairly short. However, an attacker in a real-world setting would make the email far more convincing to view. In the real world, this type of attack is often seen being used with fake invoices being sent to finance staff.
After opening up the HTML, the end user is presented with the following page:
Figure 2: The ClickFix HTML the user is presented with as part of our simulated attack
This is taken from a real attack where a Microsoft Word online page is mimicked, prompting the user to interact with it. The user needs to interact with the button, as most browsers will block clipboard writes unless the user has interacted with an element. Clicking the button copies a command to the user’s clipboard, and updates the instructions to tell them to press Win + R, Ctrl + V, and then Enter. If the user does this, it will open the run dialog, paste in the command, and execute it. This approach capitalizes on the typical user's lack of comprehension or uncritical adherence to directives, a tactic that has demonstrated efficacy in real-world cyberattacks.
It is worth noting that the EDR tool flagged this stage during initial testing. However, adding a layer of obfuscation to the HTML allowed for bypass detection. The page was able to be encoded, decoded and then written to the document using reflection to access methods that would normally be flagged.
Once the command is executed, PowerShell is invoked to download and run an .exe file from an attacker-controlled server.
The payload is a custom C++ binary that was developed for the purpose of this test. The binary spawns a reverse shell, as well as encrypting all of the files in the Documents folder for ransom. This binary was iteratively tested against the EDR tool, and the functionality was tweaked each time to bypass elements that were getting detected. Bypassing the EDR tool did not require any fancy techniques. Simply using a different Windows API to accomplish a goal that was previously flagged by the EDR tool, or altering the behavior, timing, and ordering of activities performed was sufficient to evade detection. This may seem surprising that sophisticated techniques aren’t strictly required to be undetected.
The aftermath of the attack can be seen in the images below, with a ransom note being written, and our important documents no longer being readable.
Figure 3: The Ransom Note
Figure 4: The aftermath of trying to open one of the PDFs
With no alerts to investigate from the EDR tool - how could a blue team uncover this attack chain after the fact for incident response?
Investigating the artifacts with cado
Using Cado (acquired by Darktrace), we can import the affected VM directly with just a few clicks.
Figure 5: Import the affect VM
The ransom note is a good starting point for the investigation. The timeline search feature quickly finds entries that show what process made the readme.txt file.
Figure 6: Timeline search feature
It shows that the ransom note was created by the process fix.exe, which can be used to pivot off and build a better understanding of what else the malware did, and how it got onto the system.
Reviewing events relating to the fix.exe payload shows that an event established a connection to a server, in this case, an attacker-controlled C2 server. It also spawned a command prompt instance, which provides a remote shell to the attacker.
Figure 7: Event Information
Figure 8: Event Information showing ransomware
Looking at the event information, it’s easy to spot the ransom attacks against the files. For example, the ransom attack modified the internal_draft_important.pdf document, which was seen before it can no longer be opened.
Figure 9: Event information showing the modified document
And finally reaching the start of the log trail relating to the payload, it shows it initially being executed by PowerShell.
Figure 10: Event information showing PowerShell
However, this does not definitively show what caused the malware to run in the first place, and so the next step is running the pivot feature to find related events.
Pivoting off the event allows for quickly figuring out this was precipitated by a visit to obfuscated.html, which was downloaded from an email in Outlook online:
Figure 11: Related events showing that the attack was precipiated by a visit to a obfuscated.html
The Cado Platform [2] also allows for directly jumping to the file in the file browser to conduct further analysis:
Figure 12: File seen in file browser
An EDR platform usually only provides an alert, process snapshot, and event details for a singular moment in time, missing the vital context needed to successfully understand the attack. Cado provides the vital context needed to successfully understand the full scope of the attack, not just its entry point.
Key takeaways
This research covered how Cado can provide the ability to forensically analyze systems and fully understand how attacks have occurred and unfolded. Defense-in-depth is a core component of cybersecurity, and being entirely reliant on an EDR platform as your only line of defense and insight into attacks can leave you without full context.
This was an example only, and a finely tuned EDR platform would likely detect an attack similar to this. However, many organizations may overlook the forensics side of Digital Forensics and Incident Response [3], and remediate incidents solely using their EDR platform. This can result in organizations missing out on the complete picture of an attack, potentially leaving them open to re-infection. A DFIR platform is vital to respond quickly to incidents across Cloud, SaaS, and on-prem.
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.
React2Shell Reflections: Cloud Insights, Finance Sector Impacts, and How Threat Actors Moved So Quickly
This blog breaks down how attackers rapidly weaponized the React2Shell vulnerability, with a particular focus on cloud‑native financial environments. Drawing on Darktrace’s honeypot research, it explores emerging threat actor tooling, exploitation timelines, and why behavioral‑anomaly‑led security is critical in today’s cloud landscape.
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.avif)
![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.avif)
