Darktrace Recognized in the Gartner® Magic Quadrant™ for Email Security Platforms
Darktrace is proud to announce we’ve been recognized as a Challenger in our first appearance in the Gartner® Magic Quadrant™ for Email Security. In the report you’ll get key insights into the evolving email threat landscape, the requirements of a modern email security platform and the role of AI in advanced threat detection.
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.
The Gartner Magic Quadrant for Email Security is designed to help organizations evaluate which email security solutions might be the best fit for their needs by providing a visual representation of the market vendors and the strengths and cautions of different vendors. We encourage our customers to read the full report to get the complete picture.
Darktrace / EMAIL has a unique AI approach to identifying threats, including NLP and behavioral analysis, instead of traditional security measures like signatures and sandboxing – providing protection against advanced attacks like Business Email Compromise (BEC) and spear phishing. We believe our AI-first approach delivers high-quality solutions that our customers trust, allowing them to stay ahead of sophisticated threats that other tools miss.
We’re proud of Darktrace’s rapid growth, geographic scale, and ability to execute effectively in the email security market, which reflect our commitment to delivering high-quality, reliable solutions that meet the evolving needs of our customers.
What do we believe makes Darktrace the fastest growing email security solution on the market?
An AI-first approach to innovation: Catching the threats others miss
As one of the founders of the ICES category, Darktrace has a long history of innovation, backed by over 200 patents. While other email security solutions are only just starting to apply machine learning (ML) techniques to outdated methods like signature analysis, reputation lists, and sandboxing, Darktrace has redefined the approach to email threat detection with its pioneering AI-driven anomaly detection engine.
Traditional ESPs often miss advanced threats because they rely on rules and signatures that focus on payloads and blindly trust known sources. This approach requires constant updates and frequently fails to detect threats like Business Email Compromise and Spear Phishing. In contrast, Darktrace / EMAIL uses advanced anomaly detection to identify the most sophisticated threats by focusing on unusual patterns and behaviors. This innovative approach has consistently delivered superior detection, stopping on average 58% of the threats that other solutions in the security stack miss.1
But our AI-first approach doesn’t stop at the inbox. At Darktrace, we transcend the limitations of traditional email security by leveraging a platform that unifies insights across multiple domains, providing robust protection against multi-domain threats. Our award-winning solutions defend the most popular attack vectors, including email, messaging, network, and identity protection. By combining signals from all domains, we establish unique behavioral profiles for each device and user, significantly enhancing detection precision.
This pioneering approach has led to introducing industry-first advancements like QR code analysis and automated incident investigations, alongside game-changing functionality including:
Microsoft Teams security with advanced messaging analysis: The ability to identify critical early phishing and insider threats across both email and Microsoft Teams messaging.
AI analyst narratives for improved end user reporting: that reduces phishing investigations by 60% by exposing unique narratives that provide the context of each received email and give feedback to each employee as they interact with their mail.2
Mailbox Security Assistant: to perform advanced behavioral browser analysis and stop malicious links within webpages, detecting and remediating 70% more malicious phishing links than traditional tools.3
AI based, autonomous data loss prevention: to immediately secure your organization from misdirected emails, insider threats, and data loss—both classified and unclassified- without any administrative overhead.
Customer trust that fuels exponential growth
With almost 5,000 customers in under 5 years, we've doubled the growth rate of other vendors in the email security market. Our rapid market penetration, fueled by customer satisfaction and pioneering technology, showcases our revolutionary approach and sets new industry standards.
Darktrace’s exceptional customer retention is fueled by an unparalleled customer experience, extensive regional support, dedicated account teams, and cutting-edge scalable technology. We pride ourselves on having a global network with local expertise, consisting of 110 worldwide offices which provide local language and technical support to offer multilingual, in-house assistance to our customer base.
Check it out – Darktrace / EMAIL has the highest percentage of 5-star ratings with a 4.8 rating on Gartner® Peer Insights™.4
Supporting every stage of your email security journey
Darktrace / EMAIL supports your security maturity journey, from first time security buyers to mature security stacks looking to augment their existing ESPs – by handling advanced threats without extensive tuning. And unlike other solutions that create a siloed and parallel solution, it works harmoniously with native email providers to create a modern email security stack. That’s why Darktrace performs well with first-time email security buyers and has strong renewal rates.
Integrating with Microsoft and Google via API, we replace traditional Secure Email Gateways (SEGs) with a modern, comprehensive email security stack. By combining approaches, our solution merges attack-centric analysis, which learns attack patterns and threat intelligence, with a business-centric approach that understands user behavior and inbox activity to deliver a unified stack that defends the entire threat spectrum – leading Darktrace to be recognized as Microsoft Partner of the year UK 2024.
Our user-friendly, self-learning AI solution requires minimal tuning and deployment, making it perfect for customers looking for a highly usable but lightly configurable solution that will accompany them throughout their lifetime as they mature their email security stack in line with the evolving threat landscape.
Learn more
Get complimentary access to the full Gartner® Magic Quadrant™ for Email Security Platforms here.
1 From September 1 – December 31 2023, 58% of the phishing emails analyzed by Darktrace / EMAIL had already passed through native spam filtering and email security controls. (Darktrace End of Year Threat Report 2023)
2 When customers deployed the Darktrace / EMAIL Outlook Add-in there was a 60% decrease in incorrectly reported phishing emails. Darktrace Internal Research, 2024
3 Once a user reports phishing that contains a link, an automated second level triage engages our link analysis infrastructure expanding the signals analyzed. Darktrace Internal Research, 2024
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.
Journey of a Threat: How Multi-Layered AI Works in Darktrace / EMAIL
Follow a malicious email as it moves through Darktrace / EMAIL’s multi-layered AI system, from raw data to final decision. Each layer works together to detect threats, understand intent, and take autonomous action.
How email-delivered prompt injection attacks can target enterprise AI – and why it matters
Prompt injection is a newly emerging threat, with only a handful of confirmed victims so far – targeting how AI systems use data rather than exploiting traditional software vulnerabilities. As agentic AI becomes embedded across enterprise environments, attackers may attempt to manipulate these systems through hidden instructions in everyday email content.
Darktrace Unites Human Behavior and Threat Detection Across Email, Slack, Teams, and Zoom
Introducing the adaptive era of email security: a unified platform that connects personalized coaching, collaboration tools, and user behavior into a self-improving defense system.
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)