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February 23, 2024

Quasar Remote Access Tool and Its Security Risks

Discover how the Quasar remote access tool can become a vulnerability in the wrong hands and strategies to mitigate these risks.
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
Nicole Wong
Cyber Security Analyst
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23
Feb 2024

The threat of interoperability

As the “as-a-Service” market continues to grow, indicators of compromise (IoCs) and malicious infrastructure are often interchanged and shared between multiple malware strains and attackers. This presents organizations and their security teams with a new threat: interoperability.

Interoperable threats not only enable malicious actors to achieve their objectives more easily by leveraging existing infrastructure and tools to launch new attacks, but the lack of clear attribution often complicates identification for security teams and incident responders, making it challenging to mitigate and contain the threat.

One such threat observed across the Darktrace customer base in late 2023 was Quasar, a legitimate remote administration tool that has becoming increasingly popular for opportunistic attackers in recent years. Working in tandem, the anomaly-based detection of Darktrace DETECT™ and the autonomous response capabilities of Darktrace RESPOND™ ensured that affected customers were promptly made aware of any suspicious activity on the attacks were contained at the earliest possible stage.

What is Quasar?

Quasar is an open-source remote administration tool designed for legitimate use; however, it has evolved to become a popular tool used by threat actors due to its wide array of capabilities.  

How does Quasar work?

For instance, Quasar can perform keylogging, take screenshots, establish a reverse proxy, and download and upload files on a target device [1].  A report released towards the end of 2023 put Quasar back on threat researchers’ radars as it disclosed the new observation of dynamic-link library (DLL) sideloading being used by malicious versions of this tool to evade detection [1].  DLL sideloading involves configuring legitimate Windows software to run a malicious file rather than the legitimate file it usually calls on as the software loads.  The evolving techniques employed by threat actors using Quasar highlights defenders’ need for anomaly-based detections that do not rely on pre-existing knowledge of attacker techniques, and can identify and alert for unusual behavior, even if it is performed by a legitimate application.

Although Quasar has been used by advanced persistent threat (APT) groups for global espionage operations [2], Darktrace observed the common usage of default configurations for Quasar, which appeared to use shared malicious infrastructure, and occurred alongside other non-compliant activity such as BitTorrent use and cryptocurrency mining.  

Quasar Attack Overview and Darktrace Coverage

Between September and October 2023, Darktrace detected multiple cases of malicious Quasar activity across several customers, suggesting probable campaign activity.  

Quasar infections can be difficult to detect using traditional network or host-based tools due to the use of stealthy techniques such as DLL side-loading and encrypted SSL connections for command-and control (C2) communication, that traditional security tools may not be able to identify.  The wide array of capabilities Quasar possesses also suggests that attacks using this tool may not necessarily be modelled against a linear kill chain. Despite this, the anomaly-based detection of Darktrace DETECT allowed it to identify IoCs related to Quasar at multiple stages of the kill chain.

Quasar Initial Infection

During the initial infection stage of a Quasar compromise observed on the network of one customer, Darktrace detected a device downloading several suspicious DLL and executable (.exe) files from multiple rare external sources using the Xmlst user agent, including the executable ‘Eppzjtedzmk[.]exe’.  Analyzing this file using open-source intelligence (OSINT) suggests this is a Quasar payload, potentially indicating this represented the initial infection through DLL sideloading [3].

Interestingly, the Xmlst user agent used to download the Quasar payload has also been associated with Raccoon Stealer, an information-stealing malware that also acts as a dropper for other malware strains [4][5]. The co-occurrence of different malware components is increasingly common across the threat landscape as MaaS operating models increases in popularity, allowing attackers to employ cross-functional components from different strains.

Figure 1: Cyber AI Analyst Incident summarizing the multiple different downloads in one related incident, with technical details for the Quasar payload included. The incident event for Suspicious File Download is also linked to Possible HTTP Command and Control, suggesting escalation of activity following the initial infection.  

Quasar Establishing C2 Communication

During this phase, devices on multiple customer networks were identified making unusual external connections to the IP 193.142.146[.]212, which was not commonly seen in their networks. Darktrace analyzed the meta-properties of these SSL connections without needing to decrypt the content, to alert the usage of an unusual port not typically associated with the SSL protocol, 4782, and the usage of self-signed certificates.  Self-signed certificates do not provide any trust value and are commonly used in malware communications and ill-reputed web servers.  

Further analysis into these alerts using OSINT indicated that 193.142.146[.]212 is a Quasar C2 server and 4782 is the default port used by Quasar [6][7].  Expanding on the self-signed certificate within the Darktrace UI (see Figure 3) reveals a certificate subject and issuer of “CN=Quasar Server CA”, which is also the default self-signed certificate compiled by Quasar [6].

Figure 2: Cyber AI Analyst Incident summarizing the repeated external connections to a rare external IP that was later associated with Quasar.
Figure 3: Device Event Log of the affected device, showing Darktrace’s analysis of the SSL Certificate associated with SSL connections to 193.142.146[.]212.

A number of insights can be drawn from analysis of the Quasar C2 endpoints detected by Darktrace across multiple affected networks, suggesting a level of interoperability in the tooling used by different threat actors. In one instance, Darktrace detected a device beaconing to the endpoint ‘bittorrents[.]duckdns[.]org’ using the aforementioned “CN=Quasar Server CA” certificate. DuckDNS is a dynamic DNS service that could be abused by attackers to redirect users from their intended endpoint to malicious infrastructure, and may be shared or reused in multiple different attacks.

Figure 4: A device’s Model Event Log, showing the Quasar Server CA SSL certificate used in connections to 41.233.139[.]145 on port 5, which resolves via passive replication to ‘bittorrents[.]duckdns[.]org’.  

The sharing of malicious infrastructure among threat actors is also evident as several OSINT sources have also associated the Quasar IP 193.142.146[.]212, detected in this campaign, with different threat types.

While 193.142.146[.]212:4782 is known to be associated with Quasar, 193.142.146[.]212:8808 and 193.142.146[.]212:6606 have been associated with AsyncRAT [11], and the same IP on port 8848 has been associated with RedLineStealer [12].  Aside from the relative ease of using already developed tooling, threat actors may prefer to use open-source malware in order to avoid attribution, making the true identity of the threat actor unclear to incident responders [1][13].  

Quasar Executing Objectives

On multiple customer deployments affected by Quasar, Darktrace detected devices using BitTorrent and performing cryptocurrency mining. While these non-compliant, and potentially malicious, activities are not necessarily specific IoCs for Quasar, they do suggest that affected devices may have had greater attack surfaces than others.

For instance, one affected device was observed initiating connections to 162.19.139[.]184, a known Minergate cryptomining endpoint, and ‘zayprostofyrim[.]zapto[.]org’, a dynamic DNS endpoint linked to the Quasar Botnet by multiple OSINT vendors [9].

Figure 5: A Darktrace DETECT Event Log showing simultaneous connections to a Quasar endpoint and a cryptomining endpoint 162.19.139[.]184.

Not only does cryptocurrency mining use a significant amount of processing power, potentially disrupting an organization’s business operations and racking up high energy bills, but the software used for this mining is often written to a poor standard, thus increasing the attack surfaces of devices using them. In this instance, Quasar may have been introduced as a secondary payload from a user or attacker-initiated download of cryptocurrency mining malware.

Similarly, it is not uncommon for malicious actors to attach malware to torrented files and there were a number of examples of Darktrace detect identifying non-compliant activity, like BitTorrent connections, overlapping with connections to external locations associated with Quasar. It is therefore important for organizations to establish and enforce technical and policy controls for acceptable use on corporate devices, particularly when remote working introduces new risks.  

Figure 6: A device’s Event Log filtered by Model Breaches, showing a device connecting to BitTorrent shortly before making new or repeated connections to unusual endpoints, which were subsequently associated to Quasar.

In some cases observed by Darktrace, devices affected by Quasar were also being used to perform data exfiltration. Analysis of a period of unusual external connections to the aforementioned Quasar C2 botnet server, ‘zayprostofyrim[.]zapto[.]org’, revealed a small data upload, which may have represented the exfiltration of some data to attacker infrastructure.

Darktrace’s Autonomous Response to Quasar Attacks

On customer networks that had Darktrace RESPOND™ enabled in autonomous response mode, the threat of Quasar was mitigated and contained as soon as it was identified by DETECT. If RESPOND is not configured to respond autonomously, these actions would instead be advisory, pending manual application by the customer’s security team.

For example, following the detection of devices downloading malicious DLL and executable files, Darktrace RESPOND advised the customer to block specific connections to the relevant IP addresses and ports. However, as the device was seen attempting to download further files from other locations, RESPOND also suggested enforced a ‘pattern of life’ on the device, meaning it was only permitted to make connections that were part its normal behavior. By imposing a pattern of life, Darktrace RESPOND ensures that a device cannot perform suspicious behavior, while not disrupting any legitimate business activity.

Had RESPOND been configured to act autonomously, these mitigative actions would have been applied without any input from the customer’s security team and the Quasar compromise would have been contained in the first instance.

Figure 7: The advisory actions Darktrace RESPOND initiated to block specific connections to a malicious IP and to enforce the device’s normal patterns of life in response to the different anomalies detected on the device.

In another case, one customer affected by Quasar did have enabled RESPOND to take autonomous action, whilst also integrating it with a firewall. Here, following the detection of a device connecting to a known Quasar IP address, RESPOND initially blocked it from making connections to the IP via the customer’s firewall. However, as the device continued to perform suspicious activity after this, RESPOND escalated its response by blocking all outgoing connections from the device, effectively preventing any C2 activity or downloads.

Figure 8: RESPOND actions triggered to action via integrated firewall and TCP Resets.

Conclusion

When faced with a threat like Quasar that utilizes the infrastructure and tools of both legitimate services and other malicious malware variants, it is essential for security teams to move beyond relying on existing knowledge of attack techniques when safeguarding their network. It is no longer enough for organizations to rely on past attacks to defend against the attacks of tomorrow.

Crucially, Darktrace’s unique approach to threat detection focusses on the anomaly, rather than relying on a static list of IoCs or "known bads” based on outdated threat intelligence. In the case of Quasar, alternative or future strains of the malware that utilize different IoCs and TTPs would still be identified by Darktrace as anomalous and immediately alerted.

By learning the ‘normal’ for devices on a customer’s network, Darktrace DETECT can recognize the subtle deviations in a device’s behavior that could indicate an ongoing compromise. Darktrace RESPOND is subsequently able to follow this up with swift and targeted actions to contain the attack and prevent it from escalating further.

Credit to Nicole Wong, Cyber Analyst, Vivek Rajan Cyber Analyst

Appendices

Darktrace DETECT Model Breaches

  • Anomalous Connection / Multiple Failed Connections to Rare Endpoint
  • Anomalous Connection / Anomalous SSL without SNI to New External
  • Anomalous Connection / Application Protocol on Uncommon Port
  • Anomalous Connection / Rare External SSL Self-Signed
  • Compromise / New or Repeated to Unusual SSL Port
  • Compromise / Beaconing Activity To External Rare
  • Compromise / High Volume of Connections with Beacon Score
  • Compromise / Large Number of Suspicious Failed Connections
  • Unusual Activity / Unusual External Activity

List of IoCs

IP:Port

193.142.146[.]212:4782 -Quasar C2 IP and default port

77.34.128[.]25: 8080 - Quasar C2 IP

Domain

zayprostofyrim[.]zapto[.]org - Quasar C2 Botnet Endpoint

bittorrents[.]duckdns[.]org - Possible Quasar C2 endpoint

Certificate

CN=Quasar Server CA - Default certificate used by Quasar

Executable

Eppzjtedzmk[.]exe - Quasar executable

IP Address

95.214.24[.]244 - Quasar C2 IP

162.19.139[.]184 - Cryptocurrency Miner IP

41.233.139[.]145[VR1] [NW2] - Possible Quasar C2 IP

MITRE ATT&CK Mapping

Command and Control

T1090.002: External Proxy

T1071.001: Web Protocols

T1571: Non-Standard Port

T1001: Data Obfuscation

T1573: Encrypted Channel

T1071: Application Layer Protocol

Resource Development

T1584: Compromise Infrastructure

References

[1] https://thehackernews.com/2023/10/quasar-rat-leverages-dll-side-loading.html

[2] https://symantec-enterprise-blogs.security.com/blogs/threat-intelligence/cicada-apt10-japan-espionage

[3]https://www.virustotal.com/gui/file/bd275a1f97d1691e394d81dd402c11aaa88cc8e723df7a6aaf57791fa6a6cdfa/community

[4] https://twitter.com/g0njxa/status/1691826188581298389

[5] https://www.linkedin.com/posts/grjk83_raccoon-stealer-announce-return-after-hiatus-activity-7097906612580802560-1aj9

[6] https://community.netwitness.com/t5/netwitness-community-blog/using-rsa-netwitness-to-detect-quasarrat/ba-p/518952

[7] https://www.cisa.gov/news-events/analysis-reports/ar18-352a

[8]https://any.run/report/6cf1314c130a41c977aafce4585a144762d3fb65f8fe493e836796b989b002cb/7ac94b56-7551-4434-8e4f-c928c57327ff

[9] https://threatfox.abuse.ch/ioc/891454/

[10] https://www.virustotal.com/gui/ip-address/41.233.139.145/relations

[11] https://raw.githubusercontent.com/stamparm/maltrail/master/trails/static/malware/asyncrat.txt

[12] https://sslbl.abuse.ch/ssl-certificates/signature/RedLineStealer/

[13] https://www.botconf.eu/botconf-presentation-or-article/hunting-the-quasar-family-how-to-hunt-a-malware-family/

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
Nicole Wong
Cyber Security Analyst

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February 3, 2026

Introducing Darktrace / SECURE AI: Complete AI Security Across Your Enterprise

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Why securing AI can’t wait

AI is entering the enterprise faster than IT and security teams can keep up, appearing in SaaS tools, embedded in core platforms, and spun up by teams eager to move faster.  

As this adoption accelerates, it introduces unpredictable behaviors and expands the attack surface in ways existing security tools can’t see or control, startup or platform, they all lack one trait. These new types of risks command the attention of security teams and boardrooms, touching everything from business integrity to regulatory exposure.

Securing AI demands a fundamentally different approach, one that understands how AI behaves, how it interacts with data and users, and how risk emerges in real time. That shift is at the core of how organizations should be thinking about securing AI across the enterprise.

What is the current state of securing AI?

In Darktrace’s latest State of AI in Cybersecurity Report research across 1,500 cybersecurity professionals shows that the percentage of organizations without an AI adoption policy grew from 55% last year to 63% this year.

More troubling, the percentage of organizations without any plan to create an AI policy nearly tripled from 3% to 8%. Without clear policies, businesses are effectively accelerating blindfolded.

When we analyzed activity across our own customer base, we saw the same patterns playing out in their environments. Last October alone, we saw a 39% month-over-month increase in anomalous data uploads to generative AI services, with the average upload being 75MB. Given the size and frequency of these uploads, it's almost certain that much of this data should never be leaving the enterprise.

Many security teams still lack visibility into how AI is being used across their business; how it’s behaving, what it’s accessing, and most importantly, whether it’s operating safely. This unsanctioned usage quietly expands, creating pockets of AI activity that fall completely outside established security controls. The result is real organizational exposure with almost no visibility, underscoring just how widespread AI use has already become desipite the existence of formal policies.

This challenge doesn’t stop internally. Shadow AI extends into third-party tools, vendor platforms, and partner systems, where AI features are embedded without clear oversight.

Meanwhile, attackers are now learning to exploit AI’s unique characteristics, compounding the risks organizations are already struggling to manage.

The leader in AI cybersecurity now secures AI

Darktrace brings more than a decade of behavioral AI expertise built on an enterprise‑wide platform designed to operate in the complex, ambiguous environments where today’s AI now lives.  

Other cybersecurity technologies try to predict each new attack based on historical attacks. The problem is AI operates like humans do. Every action introduces new information that changes how AI behaves, its unpredictable, and historical attack tactics are now only a small part of the equation, forcing vendors to retrofit unproven acquisitions to secure AI.  

Darktrace is fundamentally different. Our Self‑Learning AI learns what “normal” looks like for your unique business: how your users, systems, applications, and now AI agents behave, how they communicate, and how data flows. This allows us to spot even the smallest shifts when something changes in meaningful ways. Long before AI agents were introduced, our technology was already interpreting nuance, detecting drift, uncovering hidden relationships, and making sense of ambiguous activity across networks, cloud, SaaS, email, OT, identities, and endpoints.

As AI introduces new behaviors, unstructured interactions, invisible pathways, and the rise of Shadow AI, these challenges have only intensified. But this is exactly the environment our platform was built for. Securing AI isn’t a new direction for Darktrace — it’s the natural evolution of the behavioral intelligence we’ve delivered to thousands of organizations worldwide.

Introducing Darktrace / SECURE AI – Complete AI security across your enterprise

We are proud to introduce Darktrace / SECURE AI, the newest product in the Darktrace ActiveAI Security Platform designed to secure AI across the whole enterprise.

This marks the next chapter in our mission to secure organizations from cyber threats and emerging risks. By combining full visibility, intelligent behavioral oversight, and real-time control, Darktrace is enabling enterprises to safely adopt, manage, and build AI within their business. This ensures that AI usage, data access, and behavior remain aligned to security baselines, compliance, and business goals.

Darktrace / SECURE AI can bring every AI interaction into a single view, helping teams understand intent, assess risk, protect sensitive data, and enforce policy across both human and AI Agent activity. Now organizations can embrace AI with confidence, with visibility to ensure it is operating safely, responsibly, and in alignment with their security and compliance needs.  

Because securing AI spans multiple areas and layers of complexity, Darktrace / SECURE AI is built around four foundational use cases that ensure your whole enterprise and every AI use affecting your business, whether owned or through third parties, is protected, they are:

  • Monitoring the prompts driving GenAI agents and assistants
  • Securing business AI agent identities in real time
  • Evaluating AI risks in development and deployment
  • Discovering and controlling Shadow AI

Monitoring the prompts driving GenAI agents and assistants

For AI systems, prompts are one of the most active and sensitive points of interaction—spanning human‑AI exchanges where users express intent and AI‑AI interactions where agents generate internal prompts to reason and coordinate. Because prompt language effectively is behavior, and because it relies on natural language rather than a fixed, finite syntax, the attack surface is open‑ended. This makes prompt‑driven risks far more complex than traditional API‑based vulnerabilities tied to CVEs.

Whether an attacker is probing for weaknesses, an employee inadvertently exposes sensitive data, or agents generate their own sub‑tasks to drive complex workflows, security teams must understand how prompt behavior shapes model behavior—and where that behavior can go wrong. Without that behavioral understanding, organizations face heightened risks of exploitation, drift, and cascading failures within their AI systems.

Darktrace / SECURE AI brings together all prompt activity across enterprise AI systems, including Microsoft Copilot and ChatGPT Enterprise, low‑code environments like Microsoft Copilot Studio, SaaS providers like Salesforce and Microsoft 365, and high‑code platforms such as AWS Bedrock and SageMaker, into a single, unified layer of visibility.  

Beyond visibility, Darktrace applies behavioral analytics to understand whether a prompt is unusual or risky in the context of the user, their peers, and the broader organization. Because AI attacks are far more complex and conversational than traditional exploits against fixed APIs – sharing more in common with email and Teams/Slack interactions, —this behavioral understanding is essential. By treating prompts as behavioral signals, Darktrace can detect conversational attacks, malicious chaining, and subtle prompt‑injection attempts, and where integrations allow, intervene in real time to block unsafe prompts or prevent harmful model actions as they occur.

Securing business AI agent identities in real time

As organizations adopt more AI‑driven workflows, we’re seeing a rapid rise in autonomous and semi‑autonomous agents operating across the business. These agents operate within existing identities, with the capability to access systems, read and write data, and trigger actions across cloud platforms, internal infrastructure, applications, APIs, and third‑party services. Some identities are controlled, like users, others like the ones mentioned, can appear anywhere, with organizations having limited visibility into how they’re configured or how their permissions evolve over time.  

Darktrace / SECURE AI gives organizations a real‑time, identity‑centric understanding of what their AI agents are doing, not just what they were designed to do. It automatically discovers live agent identities operating across SaaS, cloud, network, endpoints, OT, and email, including those running inside third‑party environments.  

The platform maps how each agent is configured, what systems it accesses, and how it communicates, including activity such as MCP usage or interactions with storage services where sensitive data may reside.  

By continuously observing agent behavior across all domains, Darktrace / SECURE AI highlights when unnecessary or risky permissions are granted, when activity patterns deviate, or when agents begin chaining together actions in unintended ways. This real‑time audit trail allows organizations to evaluate whether agent actions align with intended operational parameters and catch anomalous or risky behavior early.    

Evaluating AI risks in development and deployment

In the build phase, new identities are created, entitlements accumulate, components are stitched together across SaaS, cloud, and internal environments, and logic starts taking shape through prompts and configurations.  

It’s a highly dynamic and often fragmented process, and even small missteps here, such as a misconfiguration in a created agent identity, can become major security issues once the system is deployed. This is why evaluating AI risk during development and deployment is critical.

Darktrace / SECURE AI brings clarity and control across this entire lifecycle — from the moment an AI system starts taking shape to the moment it goes live. It allows you to gain visibility into created identities and their access across hyperscalers, low‑code SaaS, and internal labs, supported by AI security posture management that surfaces misconfigurations, over‑entitlement, and anomalous building events. Darktrace/ SECURE AI then connects these development insights directly to prompt oversight, connecting how AI is being built to how it will behave once deployed.  The result is a safer, more predictable AI lifecycle where risks are discovered early, guardrails are applied consistently, and innovations move forward with confidence rather than guesswork.

Discovering and controlling Shadow AI

Shadow AI has now appeared across every corner of the enterprise. It’s not just an employee pasting internal data into an external chatbot; it includes unsanctioned agent builders, hidden MCP servers, rogue model deployments, and AI‑driven workflows running on devices or services no one expected to be using AI.  

Darktrace / SECURE AI brings this frontier into view by continuously analyzing interactions across cloud, networks, endpoints, OT, and SASE environments. It surfaces unapproved AI usage wherever it appears and distinguishes legitimate activity in sanctioned tools from misuse or high‑risk behavior. The system identifies hidden AI components and rogue agents, reveals unauthorized deployments and unexpected connections to external AI systems, and highlights risky data flows that deviate from business norms.

When the behavior warrants a response, Darktrace / SECURE AI enables policy enforcement that guides users back toward sanctioned options while containing unsafe or ungoverned adoption. This closes one of the fastest‑expanding security gaps in modern enterprises and significantly reduces the attack surface created by shadow AI.

Conclusion

What’s needed now along with policies and frameworks for AI adoption is the right tooling to detect threats based on AI behavior across shadow use, prompt risks, identity misuse, and AI development.  

Darktrace is uniquely positioned to secure AI, we’ve spent over a decade building AI that learns your business – understanding subtle behavior across the entire enterprise long before AI agents arrived. With over 10,000 customers relying on Darktrace as the last line of defense to capture threats others cannot, Securing AI isn’t a pivot for us, it's not an acquisition; it’s the natural extension of the behavioral expertise and enterprise‑wide intelligence our platform was built on from the start.  

To learn more about how to secure AI at your organization we curated a readiness program that brings together IT and security leaders navigating this responsibility, providing a forum to prepare for high-impact decisions, explore guardrails, and guide the business amid growing uncertainty and pressure.

Sign up for the Secure AI Readiness Program here: This gives you exclusive access to the latest news on the latest AI threats, updates on emerging approaches shaping AI security, and insights into the latest innovations, including Darktrace’s ongoing work in this area.

Ready to talk with a Darktrace expert on securing AI? Register here to receive practical guidance on the AI risks that matter most to your business, paired with clarity on where to focus first across governance, visibility, risk reduction, and long-term readiness.  

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Brittany Woodsmall
Product Marketing Manager, AI

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February 1, 2026

ClearFake: From Fake CAPTCHAs to Blockchain-Driven Payload Retrieval

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What is ClearFake?

As threat actors evolve their techniques to exploit victims and breach target networks, the ClearFake campaign has emerged as a significant illustration of this continued adaptation. ClearFake is a campaign observed using a malicious JavaScript framework deployed on compromised websites, impacting sectors such as e‑commerce, travel, and automotive. First identified in mid‑2023, ClearFake is frequently leveraged to socially engineer victims into installing fake web browser updates.

In ClearFake compromises, victims are steered toward compromised WordPress sites, often positioned by attackers through search engine optimization (SEO) poisoning. Once on the site, users are presented with a fake CAPTCHA. This counterfeit challenge is designed to appear legitimate while enabling the execution of malicious code. When a victim interacts with the CAPTCHA, a PowerShell command containing a download string is retrieved and executed.

Attackers commonly abuse the legitimate Microsoft HTML Application Host (MSHTA) in these operations. Recent campaigns have also incorporated Smart Chain endpoints, such as “bsc-dataseed.binance[.]org,” to obtain configuration code. The primary payload delivered through ClearFake is typically an information stealer, such as Lumma Stealer, enabling credential theft, data exfiltration, and persistent access [1].

Darktrace’s Coverage of ClearFake

Darktrace / ENDPOINT first detected activity likely associated with ClearFake on a single device on over the course of one day on November 18, 2025. The system observed the execution of “mshta.exe,” the legitimate Microsoft HTML Application Host utility. It also noted a repeated process command referencing “weiss.neighb0rrol1[.]ru”, indicating suspicious external activity. Subsequent analysis of this endpoint using open‑source intelligence (OSINT) indicated that it was a malicious, domain generation algorithm (DGA) endpoint [2].

The process line referencing weiss.neighb0rrol1[.]ru, as observed by Darktrace / ENDPOINT.
Figure 1: The process line referencing weiss.neighb0rrol1[.]ru, as observed by Darktrace / ENDPOINT.

This activity indicates that mshta.exe was used to contact a remote server, “weiss.neighb0rrol1[.]ru/rpxacc64mshta,” and execute the associated HTA file to initiate the next stage of the attack. OSINT sources have since heavily flagged this server as potentially malicious [3].

The first argument in this process uses the MSHTA utility to execute the HTA file hosted on the remote server. If successful, MSHTA would then run JavaScript or VBScript to launch PowerShell commands used to retrieve malicious payloads, a technique observed in previous ClearFake campaigns. Darktrace also detected unusual activity involving additional Microsoft executables, including “winlogon.exe,” “userinit.exe,” and “explorer.exe.” Although these binaries are legitimate components of the Windows operating system, threat actors can abuse their normal behavior within the Windows login sequence to gain control over user sessions, similar to the misuse of mshta.exe.

EtherHiding cover

Darktrace also identified additional ClearFake‑related activity, specifically a connection to bsc-testnet.drpc[.]org, a legitimate BNB Smart Chain endpoint. This activity was triggered by injected JavaScript on the compromised site www.allstarsuae[.]com, where the script initiated an eth_call POST request to the Smart Chain endpoint.

Example of a fake CAPTCHA on the compromised site www.allstarsuae[.]com.
Figure 2: Example of a fake CAPTCHA on the compromised site www.allstarsuae[.]com.

EtherHiding is a technique in which threat actors leverage blockchain technology, specifically smart contracts, as part of their malicious infrastructure. Because blockchain is anonymous, decentralized, and highly persistent, it provides threat actors with advantages in evading defensive measures and traditional tracking [4].

In this case, when a user visits a compromised WordPress site, injected base64‑encoded JavaScript retrieved an ABI string, which was then used to load and execute a contract hosted on the BNB Smart Chain.

JavaScript hosted on the compromised site www.allstaruae[.]com.
Figure 3: JavaScript hosted on the compromised site www.allstaruae[.]com.

Conducting malware analysis on this instance, the Base64 decoded into a JavaScript loader. A POST request to bsc-testnet.drpc[.]org was then used to retrieve a hex‑encoded ABI string that loads and executes the contract. The JavaScript also contained hex and Base64‑encoded functions that decoded into additional JavaScript, which attempted to retrieve a payload hosted on GitHub at “github[.]com/PrivateC0de/obf/main/payload.txt.” However, this payload was unavailable at the time of analysis.

Darktrace’s detection of the POST request to bsc-testnet.drpc[.]org.
Figure 4: Darktrace’s detection of the POST request to bsc-testnet.drpc[.]org.
Figure 5: Darktrace’s detection of the executable file and the malicious hostname.

Autonomous Response

As Darktrace’s Autonomous Response capability was enabled on this customer’s network, Darktrace was able to take swift mitigative action to contain the ClearFake‑related activity early, before it could lead to potential payload delivery. The affected device was blocked from making external connections to a number of suspicious endpoints, including 188.114.96[.]6, *.neighb0rrol1[.]ru, and neighb0rrol1[.]ru, ensuring that no further malicious connections could be made and no payloads could be retrieved.

Autonomous Response also acted to prevent the executable mshta.exe from initiating HTA file execution over HTTPS from this endpoint by blocking the attempted connections. Had these files executed successfully, the attack would likely have resulted in the retrieval of an information stealer, such as Lumma Stealer.

Autonomous Response’s intervention against the suspicious connectivity observed.
Figure 6: Autonomous Response’s intervention against the suspicious connectivity observed.

Conclusion

ClearFake continues to be observed across multiple sectors, but Darktrace remains well‑positioned to counter such threats. Because ClearFake’s end goal is often to deliver malware such as information stealers and malware loaders, early disruption is critical to preventing compromise. Users should remain aware of this activity and vigilant regarding fake CAPTCHA pop‑ups. They should also monitor unusual usage of MSHTA and outbound connections to domains that mimic formats such as “bsc-dataseed.binance[.]org” [1].

In this case, Darktrace was able to contain the attack before it could successfully escalate and execute. The attempted execution of HTA files was detected early, allowing Autonomous Response to intervene, stopping the activity from progressing. As soon as the device began communicating with weiss.neighb0rrol1[.]ru, an Autonomous Response inhibitor triggered and interrupted the connections.

As ClearFake continues to rise, users should stay alert to social engineering techniques, including ClickFix, that rely on deceptive security prompts.

Credit to Vivek Rajan (Senior Cyber Analyst) and Tara Gould (Malware Research Lead)

Edited by Ryan Traill (Analyst Content Lead)

Appendices

Darktrace Model Detections

Process / New Executable Launched

Endpoint / Anomalous Use of Scripting Process

Endpoint / New Suspicious Executable Launched

Endpoint / Process Connection::Unusual Connection from New Process

Autonomous Response Models

Antigena / Network::Significant Anomaly::Antigena Significant Anomaly from Client Block

List of Indicators of Compromise (IoCs)

  • weiss.neighb0rrol1[.]ru – URL - Malicious Domain
  • 188.114.96[.]6 – IP – Suspicious Domain
  • *.neighb0rrol1[.]ru – URL – Malicious Domain

MITRE Tactics

Initial Access, Drive-by Compromise, T1189

User Execution, Execution, T1204

Software Deployment Tools, Execution and Lateral Movement, T1072

Command and Scripting Interpreter, T1059

System Binary Proxy Execution: MSHTA, T1218.005

References

1.        https://www.kroll.com/en/publications/cyber/rapid-evolution-of-clearfake-delivery

2.        https://www.virustotal.com/gui/domain/weiss.neighb0rrol1.ru

3.        https://www.virustotal.com/gui/file/1f1aabe87e5e93a8fff769bf3614dd559c51c80fc045e11868f3843d9a004d1e/community

4.        https://www.packetlabs.net/posts/etherhiding-a-new-tactic-for-hiding-malware-on-the-blockchain/

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About the author
Vivek Rajan
Cyber Analyst
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