Blog
/
Network
/
June 23, 2023

How Darktrace Quickly Foiled An Information Stealer

Discover how Darktrace thwarted the CryptBot malware in just 2 seconds. Learn about this fast-moving threat and the defense strategies employed.
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
Alexandra Sentenac
Cyber Analyst
Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
23
Jun 2023

The recent trend of threat actors using information stealer malware, designed to gather and exfiltrate confidential data, shows no sign of slowing. With new or updated info-stealer strains appearing in the wild on a regular basis, it came as no surprise to see a surge in yet another prolific variant in late 2022, CryptBot.

What is CryptBot?

CryptBot is a Windows-based trojan malware that was first discovered in the wild in December 2019. It belongs to the prolific category of information stealers whose primary objective, as the name suggests, is to gather information from infected devices and send it to the threat actor.

ZeuS was reportedly the first info-stealer to be discovered, back in 2006. After its code was leaked, many other variants came to light and have been gaining popularity amongst cyber criminals [1] [2] [3]. Indeed, Inside the SOC has discussed multiple infections across its customer base associated with several types of stealers in the past months [4] [5] [6] [7]. 

The Darktrace Threat Research team investigated CryptBot infections on the digital environments of more than 40 different Darktrace customers between October 2022 and January 2023. Darktrace DETECT™ and its anomaly-based approach to threat detection allowed it to successfully identify the unusual activity surrounding these info-stealer infections on customer networks. Meanwhile, Darktrace RESPOND™, when enabled in autonomous response mode, was able to quickly intervene and prevent the exfiltration of sensitive company data.

Why is info-stealer malware popular?

It comes as no surprise that info-stealers have “become one of the most discussed malware types on the cybercriminal underground in 2022”, according to Accenture’s Cyber Threat Intelligence team [10]. This is likely in part due to the fact that:

More sensitive data on devices

Due to the digitization of many aspects of our lives, such as banking and social interactions, a trend accelerated by the COVID-19 pandemic.

Cost effective

Info-stealers provide a great return on investment (ROI) for threat actors looking to exfiltrate data without having to do the traditional internal reconnaissance and data transfer associated with data theft. Info-stealers are usually cheap to purchase and are available through Malware-as-a-Service (MaaS) offerings, allowing less technical and resourceful threat actors in on the stealing action. This makes them a prevalent threat in the malware landscape. 

How does CryptBot work?

The techniques employed by info-stealers to gather and exfiltrate data as well as the type of data targeted vary from malware to malware, but the data targeted typically includes login credentials for a variety of applications, financial information, cookies and global information about the infected computer [8]. Given its variety and sensitivity, threat actors can leverage the stolen data in several ways to make a profit. In the case of CryptBot, the data obtained is sold on forums or underground data marketplaces and can be later employed in higher profile attacks [9]. For example, stolen login information has previously been leveraged in credential-based attacks, which can successfully bypass authentication-based security measures, including multi-factor authentication (MFA). 

CryptBot functionalities

Like many information stealers, CryptBot is designed to steal a variety of sensitive personal and financial information such as browser credentials, cookies and history information and social media accounts login information, as well as cryptocurrency wallets and stored credit card information [11]. General information (e.g., OS, installed applications) about the infected computer is also retrieved. Browsers targeted by CryptBot include Chrome, Firefox, and Edge. In early 2022, CryptBot’s code was revamped in order to streamline its data extraction capabilities and improve its overall efficiency, an update that coincided with a rise in the number of infections [11] [12].

Some of CryptBot's functionalities were removed and its exfiltration process was streamlined, which resulted in a leaner payload, around half its original size and a quicker infection process [11]. Some of the features removed included sandbox detection and evasion functionalities, the collection of desktop text files and screen captures, which were deemed unnecessary. At the same time, the code was improved in order to include new Chrome versions released after CryptBot’s first appearance in 2019. Finally, its exfiltration process was simplified: prior to its 2022 update, the malware saved stolen data in two separate folders before sending it to two separate command and control (C2) domains. Post update, the data is only saved in one location and sent to one C2 domain, which is hardcoded in the C2 transmission function of the code. This makes the infection process much more streamlined, taking only a few minutes from start to finish. 

Aside from the update to its malware code, CryptBot regularly updates and refreshes its C2 domains and dropper websites, making it a highly fluctuating malware with constantly new indicators of compromise and distribution sites. 

Even though CryptBot is less known than other info-stealers, it was reportedly infecting thousands of devices daily in the first months of 2020 [13] and its continued prevalence resulted in Google taking legal action against its distribution infrastructure at the end of April 2023 [14].  

How is CryptBot obtained?

CryptBot is primarily distributed through malicious websites offering free and illegally modified software (i.e., cracked software) for common commercial programs (e.g., Microsoft Windows and Office, Adobe Photoshop, Google Chrome, Nitro PDF Pro) and video games. From these ‘malvertising’ pages, the user is redirected through multiple sites to the actual payload dropper page [15]. This distribution method has seen a gain in popularity amongst info-stealers in recent months and is also used by other malware families such as Raccoon Stealer and Vidar [16] [17].

A same network of cracked software websites can be used to download different malware strains, which can result in multiple simultaneous infections. Additionally, these networks often use search engine optimization (SEO) in order to make adverts for their malware distributing sites appear at the top of the Google search results page, thus increasing the chances of the malicious payloads being downloaded.

Furthermore, CryptBot leverages Pay-Per-Install (PPI) services such as 360Installer and PrivateLoader, a downloader malware family used to deliver payloads of multiple malware families operated by different threat actors [18] [19] [20]. The use of this distribution method for CryptBot payloads appears to have stemmed from its 2022 update. According to Google, 161 active domains were associated with 360Installer, of which 90 were associated with malware delivery activities and 29 with the delivery of CryptBot malware specifically. Google further identified hundreds of domains used by CryptBot as C2 sites, all of which appear to be hosted on the .top top-level domain [21].

This simple yet effective distribution tactic, combined with the MaaS model and the lucrative prospects of selling the stolen data resulted in numerous infections. Indeed, CryptBot was estimated to have infected over 670,000 computers in 2022 [14]. Even though the distribution method chosen means that most of the infected devices are likely to be personal computers, bring your own device (BYOD) policies and users’ tendency to reuse passwords means that corporate environments are also at risk. 

CryptBot Attack Overview

In some cases observed by Darktrace, after connecting to malvertising websites, devices were seen making encrypted SSL connections to file hosting services such as MediaFire or Mega, while in others devices were observed connecting to an endpoint associated with a content delivery network. This is likely the location from where the malware payload was downloaded alongside cracked software, which is executed by the unsuspecting user. As the user expects to run an executable file to install their desired software, the malware installation often happens without the user noticing.

Some of the malvertising sites observed by Darktrace on customer deployments were crackful[.]com, modcrack[.]net, windows-7-activator[.]com and office-activator[.]com. However, in many cases detected by Darktrace, CryptBot was propagated via websites offering trojanized KMSPico software (e.g., official-kmspico[.]com, kmspicoofficial[.]com). KMSPico is a popular Microsoft Windows and Office product activator that emulates a Windows Key Management Services (KMS) server to activate licenses fraudulently. 

Once it has been downloaded and executed, CryptBot will search the system for confidential information and create a folder with a seemingly randomly generated name, matching the regex [a-zA-Z]{10}, to store the gathered sensitive data, ready for exfiltration. 

Figure 1: Packet capture (PCAP) of an HTTP POST request showing the file with the stolen data being sent over the connection.
Figure 1: Packet capture (PCAP) of an HTTP POST request showing the file with the stolen data being sent over the connection.

This data is then sent to the C2 domain via HTTP POST requests on port 80 to the URI /gate.php. As previously stated, CryptBot C2 infrastructure is changed frequently and many of the domains seen by Darktrace had been registered within the previous 30 days. The domain names detected appeared to have been generated by an algorithm, following the regex patterns [a-z]{6}[0-9]{2,3}.top or [a-z]{6}[0-9]{2,3}.cfd. In several cases, the C2 domain had not been flagged as malicious by other security vendors or had just one detection. This is likely because of the frequent changes in the C2 infrastructure operated by the threat actors behind CryptBot, with new malicious domains being created periodically to avoid detection. This makes signature-based security solutions much less efficient to detect and block connections to malicious domains. Additionally, the fact that the stolen data is sent over regular HTTP POST requests, which are used daily as part of a multitude of legitimate processes such as file uploads or web form submissions, allows the exfiltration connections to blend in with normal and legitimate traffic making it difficult to isolate and detect as malicious activity. 

In this context, anomaly-based security detections such as Darktrace DETECT are the best way to pick out these anomalous connections amidst legitimate Internet traffic. In the case of CryptBot, two DETECT models were seen consistently breaching for CryptBot-related activity: ‘Device / Suspicious Domain’, breaching for connections to 100% rare C2 .top domains, and ‘Anomalous Connection / POST to PHP on New External Host’, breaching on the data exfiltration HTTP POST request. 

In deployments where Darktrace RESPOND was deployed, a RESPOND model breached within two seconds of the first HTTP POST request. If enabled in autonomous mode, RESPOND would block the data exfiltration connections, thus preventing the data safe from being sold in underground forums to other threat actors. In one of the cases investigated by Darktrace’s Threat Research team, DETECT was able to successfully identify and alert the customer about CryptBot-related malicious activity on a device that Darktrace had only begun to monitor one day before, showcasing how fast Darktrace’s Self-Learning AI learns every nuance of customer networks and the devices within it.

In most cases investigated by Darktrace, fewer than 5 minutes elapsed between the first connection to the endpoint offering free cracked software and the data being exfiltrated to the C2 domain. For example, in one of the attack chains observed in a university’s network, a device was seen connecting to the 100% rare endpoint official-kmspico[.]com at 16:53:47 (UTC).

Device Event Log showing SSL connections to the official-kmspico[.]com malvertising website.
Figure 2: Device Event Log showing SSL connections to the official-kmspico[.]com malvertising website.

One minute later, at 16:54:19 (UTC), the same device was seen connecting to two mega[.]co[.]nz subdomains and downloading around 13 MB of data from them. As mentioned previously, these connections likely represent the CryptBot payload and cracked software download.

Device Event Log showing SSL connections to mega[.]com endpoints following the connection to the malvertising site.
Figure 3: Device Event Log showing SSL connections to mega[.]com endpoints following the connection to the malvertising site.

At 16:56:01 (UTC), Darktrace detected the device making a first HTTP POST request to the 100% rare endpoint, avomyj24[.]top, which has been associated with CryptBot’s C2 infrastructure [22]. This initial HTTP POST connection likely represents the transfer of confidential data to the attacker’s infrastructure.

Device Event Log showing HTTP connections made by the infected device to the C2 domain. 
Figure 4: Device Event Log showing HTTP connections made by the infected device to the C2 domain. 

The full attack chain, from visiting the malvertising website to the malicious data egress, took less than three minutes to complete. In this circumstance, the machine-speed detection and response capabilities offered by Darktrace DETECT and RESPOND are paramount in order to stop CryptBot before it can successfully exfiltrates sensitive data. This is an incredibly quick infection timeline, with no lateral movement nor privilege escalation required to carry out the malware’s objective. 

Device Event Log showing the DETECT and RESPOND models breached during the attack. 
Figure 5: Device Event Log showing the DETECT and RESPOND models breached during the attack. 

Darktrace Cyber AI Analyst incidents were also generated as a result of this activity, displaying all relevant information in one panel for easy review by customer security teams.

Cyber AI Analyst event log showing the HTTP connections made by the breach device to the C2 endpoint.
Figure 6: Cyber AI Analyst event log showing the HTTP connections made by the breach device to the C2 endpoint.

Conclusion 

CryptBot info-stealer is fast, efficient, and apt at evading detection given its small size and swift process of data gathering and exfiltration via legitimate channels. Its constantly changing C2 infrastructure further makes it difficult for traditional security tools that really on rules and signatures or known indicators of compromise (IoCs) to detect these infections. 

In the face of such a threat, Darktrace’s anomaly-based detection allows it to recognize subtle deviations in a device’s pattern of behavior that may signal an evolving threat and instantly bring it to the attention of security teams. Darktrace DETECT is able to distinguish between benign activity and malicious behavior, even from newly monitored devices, while Darktrace RESPOND can move at machine-speed to prevent even the fastest moving threat actors from stealing confidential company data, as it demonstrated here by stopping CryptBot infections in as little as 2 seconds.

Credit to Alexandra Sentenac, Cyber Analyst, Roberto Romeu, Senior SOC Analyst

Darktrace Model Detections  

AI Analyst Coverage 

  • Possible HTTP Command and Control  

DETECT Model Breaches  

  • Device / Suspicious Domain 
  • Anomalous Connection / POST to PHP on New External Host 
  • Anomalous Connection / Multiple HTTP POSTs to Rare Hostname 
  • Compromise / Multiple SSL to Rare DGA Domains

List of IOCs

Indicator Type Description
luaigz34[.]top Hostname CryptBot C2 endpoint
watibt04[.]top Hostname CryptBot C2 endpoint
avolsq14[.]top Hostname CryptBot C2 endpoint

MITRE ATT&CK Mapping

Category Technique Tactic
INITIAL ACCESS Drive-by Compromise - T1189 N/A
COMMAND AND CONTROL Web Protocols - T1071.001 N/A
COMMAND AND CONTROL Domain Generation Algorithm - T1568.002 N/A

References

[1] https://www.malwarebytes.com/blog/threats/info-stealers

[2] https://cybelangel.com/what-are-infostealers/

[3] https://ke-la.com/information-stealers-a-new-landscape/

[4] https://darktrace.com/blog/vidar-info-stealer-malware-distributed-via-malvertising-on-google

[5] https://darktrace.com/blog/a-surge-of-vidar-network-based-details-of-a-prolific-info-stealer 

[6] https://darktrace.com/blog/laplas-clipper-defending-against-crypto-currency-thieves-with-detect-respond

[7] https://darktrace.com/blog/amadey-info-stealer-exploiting-n-day-vulnerabilities 

[8] https://cybelangel.com/what-are-infostealers/

[9] https://webz.io/dwp/the-top-10-dark-web-marketplaces-in-2022/

[10] https://www.accenture.com/us-en/blogs/security/information-stealer-malware-on-dark-web

[11] https://www.bleepingcomputer.com/news/security/revamped-cryptbot-malware-spread-by-pirated-software-sites/

[12] https://blogs.blackberry.com/en/2022/03/threat-thursday-cryptbot-infostealer

[13] https://www.deepinstinct.com/blog/cryptbot-how-free-becomes-a-high-price-to-pay

[14] https://blog.google/technology/safety-security/continuing-our-work-to-hold-cybercriminal-ecosystems-accountable/

[15] https://asec.ahnlab.com/en/31802/

[16] https://darktrace.com/blog/the-last-of-its-kind-analysis-of-a-raccoon-stealer-v1-infection-part-1

[17] https://www.trendmicro.com/pt_br/research/21/c/websites-hosting-cracks-spread-malware-adware.html

[18] https://intel471.com/blog/privateloader-malware

[19] https://cyware.com/news/watch-out-pay-per-install-privateloader-malware-distribution-service-is-flourishing-888273be 

[20] https://regmedia.co.uk/2023/04/28/handout_google_cryptbot_complaint.pdf

[21] https://www.bankinfosecurity.com/google-wins-court-order-to-block-cryptbot-infrastructure-a-21905

[22] https://github.com/stamparm/maltrail/blob/master/trails/static/malware/cryptbot.txt

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
Alexandra Sentenac
Cyber Analyst

More in this series

No items found.

Blog

/

Email

/

April 24, 2026

Email-Borne Cyber Risk: A Core Challenge for the CISO in the Age of Volume and Sophistication

Default blog imageDefault blog image

The challenge for CISOs

Despite continuous advances in security technologies, humans continue to be exploited by attackers. Credential abuse and social actions like phishing are major factors, accounting for around 60% of all breaches. These attacks rely less on technical vulnerabilities and more on exploiting human behavior and organizational processes. 

From my perspective as a former CISO, protecting humans concentrates three of today’s most pressing challenges: the sheer volume of email-based threats, their increasing sophistication, and the limitations of traditional employee awareness programs in moving the needle on risk. 

My personal experience of security awareness training as a CISO

With over 20 years’ experience as an ICT and Cybersecurity leader across various international organizations, I’ve seen security awareness training (SAT) in many guises. And while the cyber landscape is evolving in every direction, the effectiveness of SAT is reaching a plateau.  

Most programs I’ve seen follow a familiar pattern. Training is delivered through a combination of eLearning modules and internal sessions designed to reinforce IT policies. Employees are typically required to complete a slide deck or video, followed by a multiple-choice quiz. Occasional phishing simulations are distributed throughout the year.

The content is often static and unpersonalized, based on known threats that may already be outdated. Every employee regardless of role or risk exposure receives the same training and the same simulated phishing templates, from front-desk staff to the CEO.

The problem with traditional SAT programs

The issue with the approach to SAT outlined above is that the distribution of power is imbalanced. Humans will always be fallible, particularly when faced with increasingly sophisticated attacks. Providing generic, low-context training risks creating false confidence rather than genuine resilience. Let’s look at some of the problems in detail.

Timing and delivery

Employees today operate under constant cognitive load, making lots of rapid decisions every day to reduce their email volumes. Yet if employees are completing training annually, or on an ad hoc basis, it becomes a standalone occurrence rather than a continuous habit.  

As a result, retention is low. Employees often forget the lessons within weeks, a phenomenon known as the ‘Ebbinghaus Forgetting Curve.’

The graph illustrates that when you first learn something, the information disappears at an exponential rate without retention. In fact, according to the curve, you forget 50% of all new information within a day, and 90% of all new information within a week.  

Simultaneously, most training is conducted within a separate interface. Because it takes place away from the actual moment of decision-making, the "teachable moment" is lost. There is a cognitive disconnect between the action (clicking a link in Outlook) and the education (watching a video in a browser). 

People

In the context of professional risk management, the risks faced by different users are different. Static learning such as everyone receiving the same ‘Password Reset’ email doesn’t help users prepare for the specific threats they are likely to face. It also contributes to user fatigue, driven by repetitive training. And if users receive tests at the same time, news spreads among colleagues, hurting the efficacy of the test.  

Staff turnover introduces further risk. In many organizations, new employees gain access to systems before receiving meaningful training, reducing onboarding to little more than policy acknowledgment.

Measuring success

In my experience, solutions are standalone, without any correlation to other tools in the security stack. In some cases, the programs are delivered by HR rather than the security team, creating a complete silo.  

As a result, SAT is often perceived as a compliance exercise rather than a capability building function. The result is that poor-quality training does little to reduce the likelihood of compromise, regardless of completion rates or quiz performance.

What a modern SAT solution should look like

For today’s CISO, email represents the convergence point of high-volume, high-impact, and human-centric threats. Despite significant security investments, it remains one of the most difficult channels to secure effectively. Given these constraints, CISOs must evolve their approach to SAT.

Success lies in a balanced strategy one that combines advanced technology, attack surface reduction, and pragmatic user enablement, without over-relying on human vigilance as the final line of defense.

This means moving beyond traditional SAT toward continuous, contextual awareness, realistic simulations, and tight integration with security outcomes.

Three requirements for a modern SAT solution

  • Invisible protection: The optimum security solution is one that assists users without impeding their experience. The objective is to enhance human capabilities, rather than simply delivering a lecture. 
  • Real-time feedback: Rather than a monthly quiz, the ideal system would provide a prompt or warning when a user is about to engage with something suspicious. 
  • Positive culture: Shifting the focus away from a "gotcha" culture, which is a contributing factor to a resentment, and instead empowers employees to serve as "sensors" for the company. 

Discover how personalized security coaching can strengthen your human layer and make your email defenses more resilient. Explore Darktrace / Adaptive Human Defense.

Continue reading
About the author
Karim Benslimane
VP, Field CISO

Blog

/

Network

/

April 21, 2026

How a Compromised eScan Update Enabled Multi‑Stage Malware and Blockchain C2

multi-stage malwareDefault blog imageDefault blog image

The rise of supply chain attacks

In recent years, the abuse of trusted software has become increasingly common, with supply chain compromises emerging as one of the fastest growing vectors for cyber intrusions. As highlighted in Darktrace’s Annual Threat Report 2026, attackers and state-actors continue to find significant value in gaining access to networks through compromised trusted links, third-party tools, or legitimate software. In January 2026, a supply chain compromise affecting MicroWorld Technologies’ eScan antivirus product was reported, with malicious updates distributed to customers through the legitimate update infrastructure. This, in turn, resulted in a multi‑stage loader malware being deployed on compromised devices [1][2].

An overview of eScan exploitation

According to eScan’s official threat advisory, unauthorized access to a regional update server resulted in an “incorrect file placed in the update distribution path” [3]. Customers associated with the affected update servers who downloaded the update during a two-hour window on January 20 were impacted, with affected Windows devices subsequently have experiencing various errors related to update functions and notifications [3].

While eScan did not specify which regional update servers were affected by the malicious update, all impacted Darktrace customer environments were located in the Europe, Middle East, and Africa (EMEA) region.

External research reported that a malicious 32-bit executable file , “Reload.exe”, was first installed on affected devices, which then dropped the 64-bit downloader, “CONSCTLX.exe”. This downloader establishes persistence by creating scheduled tasks such as “CorelDefrag”, which are responsible for executing PowerShell scripts. Subsequently, it evades detection by tampering with the Windows HOSTS file and eScan registry to prevent future remote updates intended for remediation. Additional payloads are then downloaded from its command-and-control (C2) server [1].

Darktrace’s coverage of eScan exploitation

Initial Access and Blockchain as multi-distributed C2 Infrastructure

On January 20, the same day as the aforementioned two‑hour exploit window, Darktrace observed multiple devices across affected networks downloading .dlz package files from eScan update servers, followed by connections to an anomalous endpoint, vhs.delrosal[.]net, which belongs to the attackers’ C2 infrastructure.

The endpoint contained a self‑signed SSL certificate with the string “O=Internet Widgits Pty Ltd, ST=SomeState, C=AU”, a default placeholder commonly used in SSL/TLS certificates for testing and development environments, as well as in malicious C2 infrastructure [4].

Utilizing a multi‑distributed C2 infrastructure, the attackers also leveraged domains linked with the Solana open‑source blockchain for C2 purposes, namely “.sol”. These domains were human‑readable names that act as aliases for cryptocurrency wallet addresses. As browsers do not natively resolve .sol domains, the Solana Naming System (formerly known as Bonfida, an independent contributor within the Solana ecosystem) provides a proxy service, through endpoints such as sol-domain[.]org, to enable browser access.

Darktrace observed devices connecting to blackice.sol-domain[.]org, indicating that attackers were likely using this proxy to reach a .sol domain for C2 activity. Given this behavior, it is likely that the attackers leveraged .sol domains as a dead drop resolver, a C2 technique in which threat actors host information on a public and legitimate service, such as a blockchain. Additional proxy resolver endpoints, such as sns-resolver.bonfida.workers[.]dev, were also observed.

Solana transactions are transparent, allowing all activity to be viewed publicly. When Darktrace analysts examined the transactions associated with blackice[.]sol, they observed that the earliest records dated November 7, 2025, which coincides with the creation date of the known C2 endpoint vhs[.]delrosal[.]net as shown in WHOIS Lookup information [4][5].

WHOIS Look records of the C2 endpoint vhs[.]delrosal[.]net.
Figure 1: WHOIS Look records of the C2 endpoint vhs[.]delrosal[.]net.
 Earliest observed transaction record for blackice[.]sol on public ledgers.
Figure 2: Earliest observed transaction record for blackice[.]sol on public ledgers.

Subsequent instructions found within the transactions contained strings such as “CNAME= vhs[.]delrosal[.]net”, indicating attempts to direct the device toward the malicious endpoint. A more recent transaction recorded on January 28 included strings such as “hxxps://96.9.125[.]243/i;code=302”, suggesting an effort to change C2 endpoints. Darktrace observed multiple alerts triggered for these endpoints across affected devices.

Similar blockchain‑related endpoints, such as “tumama.hns[.]to”, were also observed in C2 activities. The hns[.]to service allows web browsers to access websites registered on Handshake, a decentralized blockchain‑based framework designed to replace centralized authorities and domain registries for top‑level domains. This shift toward decentralized, blockchain‑based infrastructure likely reflects increased efforts by attackers to evade detection.

In outgoing connections to these malicious endpoints across affected networks, Darktrace / NETWORK recognized that the activity was 100% rare and anomalous for both the devices and the wider networks, likely indicative of malicious beaconing, regardless of the underlying trusted infrastructure. In addition to generating multiple model alerts to capture this malicious activity across affected networks, Darktrace’s Cyber AI Analyst was able to compile these separate events into broader incidents that summarized the entire attack chain, allowing customers’ security teams to investigate and remediate more efficiently. Moreover, in customer environments where Darktrace’s Autonomous Response capability was enabled, Darktrace took swift action to contain the attack by blocking beaconing connections to the malicious endpoints, even when those endpoints were associated with seemingly trustworthy services.

Conclusion

Attacks targeting trusted relationships continue to be a popular strategy among threat actors. Activities linked to trusted or widely deployed software are often unintentionally whitelisted by existing security solutions and gateways. Darktrace observed multiple devices becoming impacted within a very short period, likely because tools such as antivirus software are typically mass‑deployed across numerous endpoints. As a result, a single compromised delivery mechanism can greatly expand the attack surface.

Attackers are also becoming increasingly creative in developing resilient C2 infrastructure and exploiting legitimate services to evade detection. Defenders are therefore encouraged to closely monitor anomalous connections and file downloads. Darktrace’s ability to detect unusual activity amidst ever‑changing tactics and indicators of compromise (IoCs) helps organizations maintain a proactive and resilient defense posture against emerging threats.

Credit to Joanna Ng (Associate Principal Cybersecurity Analyst) and Min Kim (Associate Principal Cybersecurity Analyst) and Tara Gould (Malware Researcher Lead)

Edited by Ryan Traill (Content Manager)

Appendices

Darktrace Model Detections

  • Anomalous File::Zip or Gzip from Rare External Location
  • Anomalous Connection / Suspicious Self-Signed SSL
  • Anomalous Connection / Rare External SSL Self-Signed
  • Anomalous Connection / Suspicious Expired SSL
  • Anomalous Server Activity / Anomalous External Activity from Critical Network Device

List of Indicators of Compromise (IoCs)

  • vhs[.]delrosal[.]net – C2 server
  • tumama[.]hns[.]to – C2 server
  • blackice.sol-domain[.]org – C2 server
  • 96.9.125[.]243 – C2 Server

MITRE ATT&CK Mapping

  • T1071.001 - Command and Control: Web Protocols
  • T1588.001 - Resource Development
  • T1102.001 - Web Service: Dead Drop Resolver
  • T1195 – Supple Chain Compromise

References

[1] https://www.morphisec.com/blog/critical-escan-threat-bulletin/

[2] https://www.bleepingcomputer.com/news/security/escan-confirms-update-server-breached-to-push-malicious-update/

[3] hxxps://download1.mwti.net/documents/Advisory/eScan_Security_Advisory_2026[.]pdf

[4] https://www.virustotal.com/gui/domain/delrosal.net

[5] hxxps://explorer.solana[.]com/address/2wFAbYHNw4ewBHBJzmDgDhCXYoFjJnpbdmeWjZvevaVv

Continue reading
About the author
Joanna Ng
Associate Principal Analyst
Your data. Our AI.
Elevate your network security with Darktrace AI