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September 21, 2023

How Darktrace Detected Black Basta Ransomware

Discover how Darktrace uncovered Black Basta ransomware. Learn about its tactics, techniques, and how to protect your network from this threat.
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
Matthew John
Director of Operations, SOC
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21
Sep 2023

What is Black Basta?

Over the past year, security researchers have been tracking a new ransomware group, known as Black Basta, that has been observed targeted organizations worldwide to deploy double extortion ransomware attacks since early 2022. While the strain and group are purportedly new, evidence seen suggests they are an offshoot of the Conti ransomware group [1].

The group behind Black Basta run a Ransomware as a Service (RaaS) model. They work with initial access brokers who will typically already have a foothold in company infrastructure to begin their attacks. Once inside a network, they then pivot internally using numerous tools to further their attack.

Black Basta Ransomware

Like many other ransomware actors, Black Basta uses double extortion as part of its modus operandi, exfiltrating sensitive company data and using the publication of this as a second threat to affected companies. This is also advertised on a dark web site, setup by the group to apply further pressure for affected companies to make ransom payments and avoid reputational damage.

The group also seems to regularly take advantage of existing tools to undertake the earlier stages of their attacks. Notably, the Qakbot banking trojan, seems to be the malware often used to gain an initial foothold within compromised environments.

Analysis of the tools, procedures and infrastructure used by Black Basta belies a maturity to the actors behind the ransomware. Their models and practices suggest those involved are experienced individuals, and security researchers have drawn possible links to the Conti ransomware group.

As such, Black Basta is a particular concern for security teams as attacks will likely be more sophisticated, with attackers more patient and able to lie low on digital estates for longer, waiting for the opportune moment to strike.

Cyber security is an infinite game where defender and attacker are stuck as cat and mouse; as new attacks evolve, security vendors and teams respond to the new indicators of compromise (IoCs), and update their existing rulesets and lists. As a result, attackers are forced to change their stripes to evade detection or sometimes even readjust their targets and end goals.

Anomaly Based Detection

By using the power of Darktrace’s Self-Learning AI, security teams are able to detect deviations in behavior. Threat actors need to move through the kill chain to achieve their aims, and in doing so will cause affected devices within networks to deviate from their expected pattern of life. Darktrace’s anomaly-based approach to threat detection allows it recognize these subtle deviations that indicate the presence of an attacker, and stop them in their tracks.

Additionally, the ecosystem of cyber criminals has matured in the last few decades. It is well documented how many groups now operate akin to legitimate companies, with structure, departments and governance. As such, while new attack methods and tactics do appear in the wild, the maturity in their business models belie the experience of those behind the attack.

As attackers grow their business models and develop their arsenal of attack vectors, it becomes even more critical for security teams to remain vigilant to anomalies within networks, and remain agnostic to underlying IoCs and instead adopt anomaly detection tools able to identify tactics, techniques, and procedures (TTPs) that indicate attackers may be moving through a network, ahead of deployment of ransomware and data encryption.

Darktrace’s Coverage of Black Basta

In April 2023, the Darktrace Security Operations Center (SOC) assisted a customer in triaging and responding to an ongoing ransomware infection on their network. On a Saturday, the customer reached out directly to the Darktrace analyst team via the Ask the Expert service for support after they observed encrypted files and locked administrative accounts on their network. The analyst team were able to investigate and clarify the attack path, identifying affected devices and assisting the customer with their remediation. Darktrace DETECT™ observed varying IoCs and TTPs throughout the course of this attack’s kill chain; subsequent analysis into these indicators revealed this had likely been a case of Black Basta seen in the wild.

Initial Intrusion

The methods used by the  group to gain an initial foothold in environments varies – sometimes using phishing, sometimes gaining access through a common vulnerability exposed to the internet. Black Basta actors appear to target specific organizations, as opposed to some groups who aim to hit multiple at once in a more opportunistic fashion.

In the case of the Darktrace customer likely affected by Black Basta, it is probable that the initial intrusion was out of scope. It may be that the path was via a phishing email containing an Microsoft Excel spreadsheet that launches malicious powershell commands; a noted technique for Black Basta. [3][4]  Alternatively, the group may have worked with access brokers who already had a foothold within the customer’s network.

One particular device on the network was observed acting anomalously and was possibly the first to be infected. The device attempted to connect to multiple internal devices over SMB, and connected to a server that was later found to be compromised and is described throughout the course of this blog. During this connection, it wrote a file over SMB, “syncro.exe”, which is possibly a legitimate Remote Management software but could in theory be used to spread an infection laterally. Use of this tool otherwise appears sporadic for the network, and was notably unusual for the environment.

Given these timings, it is possible this activity is related to the likely Black Basta compromise. However, there is some evidence online that use of Syncro has been seen installed as part of the execution of loaders such as Batloader, potentially indicating a separate or concurrent attack [5].

Internal Reconnaissance + Lateral Movement

However the attackers gained access in this instance, the first suspicious activity observed by Darktrace originated from an infected server. The attacker used their foothold in the device to perform internal reconnaissance, enumerating large portions of the network. Darktrace DETECT’s anomaly detection noted a distinct rise in connections to a large number of subnets, particularly to closed ports associated with native Windows services, including:

  • 135 (RPC)
  • 139 (NetBIOS)
  • 445 (SMB)
  • 3389 (RDP)

During the enumeration, SMB connections were observed during which suspiciously named executable files were written:

  • delete.me
  • covet.me

Data Staging and Exfiltration

Around 4 hours after the scanning activity, the attackers used their knowledge gained during enumeration about the environment to begin gathering and staging data for their double extortion attempts. Darktrace observed the same infected server connecting to a file storage server, and downloading over 300 GiB of data. Darktrace DETECT identified that the connections had been made via SMB and was able to present a list of filenames to the customer, allowing their security team to determine the data that had likely been exposed to the attackers.

The SMB paths detected by Darktrace showed a range of departments’ file areas being accessed by threat actors. This suggests they were interested in getting as much varied data as possible, presumably in an attempt to ensure a large amount of valuable information was at their disposal to make any threats of releasing them more credible, and more damaging to the company.

Shortly after the download, the device made an external connection over SSH to a rare domain, dataspt[.]com, hosted in the United States. The connection itself was made over an unusual port, 2022, and Darktrace recognized that the domain was new for the network.

During this upload, the threat actors uploaded a similar volume of data to the 300GiB that had been downloaded internally earlier. Darktrace flagged the usual elements of this external upload, making the identification and triage of this exfiltration attempt easier for the customer.

On top of this, Darktrace’s autonomous investigation tool Cyber AI Analyst™ launched an investigation into this on-going activity and was able to link the external upload events to the internal download, identifying them as one exfiltration incident rather than two isolated events. AI Analyst then provided a detailed summary of the activity detected, further speeding up the identification of affected files.

Preparing for Exploitation

All the activity documented so far had occurred on a Wednesday evening. It was at this point that the burst of activity calmed, and the ransomware lay in wait within the environment. Other devices around the network, particularly those connected to by the original infected server and a domain controller, were observed performing some elements of anomalous activity, but the attack seemed to largely take a pause.

However, on the Saturday morning, 3 days later, the compromised server began to change the way it communicated with attackers by reaching out to a new command and control (C2) endpoint. It seemed that attackers were gearing up for their attack, taking advantage of the weekend to strike while security teams often run with a reduced staffing.

Darktrace identified connections to a new endpoint within 4 minutes of it first being seen on the customer’s environment. The server had begun making repeated SSL connections to the new external endpoint, faceappinc[.]com, which has been flagged as malicious by various open-source intelligence (OSINT) sources.

The observed JA3 hash (d0ec4b50a944b182fc10ff51f883ccf7) suggests that the command-line tool BITS Admin was being used to launch these connections, another suggestion of the use of mature tooling.

In addition to this, Darktrace also detected the server using an administrative credential it had never previously been associated with. Darktrace recognized that the use of this credential represented a deviation from the device’s usual activity and thus could be indicative of compromise.

The server then proceeded to use the new credential to authenticate over Keberos before writing a malicious file (“management.exe”) to the Temp directory on a number of internal devices.

Encryption

At this point, the number of anomalous activities detected from the server increased massively as the attacker seems to connect networkwide in an attempt to cause as quick and destructive an encryption effort as possible. Darktrace observed numerous files that had been encrypted by a local process. The compromised server began to write ransom notes, named “instructions_read_me.txt” to other file servers, which presumably also had successfully deployed payloads. While Black Basta actors had initially been observed dropping ransom notes named “readme.txt”, security researchers have since observed and reported an updated variant of the ransomware that drops “instructions_read_me_.txt”, the name of the file detected by Darktrace, instead [6].

Another server was also observed making repeated SSL connections to the same rare external endpoint, faceappinc[.]com. Shortly after beginning these connections, the device made an HTTP connection to a rare IP address with no hostname, 212.118.55[.]211. During this connection, the device also downloaded a suspicious executable file, cal[.]linux. OSINT research linked the hash of this file to a Black Basta Executable and Linkable File (ELF) variant, indicating that the group was highly likely behind this ransomware attack.

Of particular interest again, is how the attacker lives off the land, utilizing pre-installed Windows services. Darktrace flagged that the server was observed using PsExec, a remote management executable, on multiple devices.

Darktrace Assistance

Darktrace DETECT was able to clearly detect and provide visibility over all stages of the ransomware attack, alerting the customer with multiple model breaches and AI Analyst investigation(s) and highlighting suspicious activity throughout the course of the attack.

For example, the exfiltration of sensitive data was flagged for a number of anomalous features of the meta-data: volume; rarity of the endpoint; port and protocol used.

In total, the portion of the attack observed by Darktrace lasted about 4 days from the first model breach until the ransomware was deployed. In particular, the encryption itself was initiated on a Saturday.

The encryption event itself was initiated on a Saturday, which is not uncommon as threat actors tend to launch their destructive attacks when they expect security teams will be at their lowest capacity. The Darktrace SOC team regularly observes and assists in customer’s in the face of ransomware actors who patiently lie in wait. Attackers often choose to strike as security teams run on reduced hours of manpower, sometimes even choosing to deploy ahead of longer breaks for national or public holidays, for example.

In this case, the customer contacted Darktrace directly through the Ask the Expert (ATE) service. ATE offers customers around the clock access to Darktrace’s team of expert analysts. Customers who subscribe to ATE are able to send queries directly to the analyst team if they are in need of assistance in the face of suspicious network activity or emerging attacks.

In this example, Darktrace’s team of expert analysts worked in tandem with Cyber AI Analyst to investigate the ongoing compromise, ensuring that the investigation and response process were completed as quickly and efficiently as possible.

Thanks to Darktrace’s Self-Learning AI, the analyst team were able to quickly produce a detailed report enumerating the timeline of events. By combining the human expertise of the analyst team and the machine learning capabilities of AI Analyst, Darktrace was able to quickly identify anomalous activity being performed and the affected devices. AI Analyst was then able to collate and present this information into a comprehensive and digestible report for the customer to consult.

Conclusion

It is likely that this ransomware attack was undertaken by the Black Basta group, or at least using tools related to their method. Although Black Basta itself is a relatively novel ransomware strain, there is a maturity and sophistication to its tactics. This indicates that this new group are actually experienced threat actors, with evidence pointing towards it being an offshoot of Conti.

The Pyramid of Pain is a well trodden model in cyber security, but it can help us understand the various features of an attack. Indicators like static C2 destinations or file hashes can easily be changed, but it’s the underlying TTPs that remain the same between attacks.

In this case, the attackers used living off the land techniques, making use of tools such as BITSAdmin, as well as using tried and tested malware such as Qakbot. While the domains and IPs involved will change, the way these malware interact and move about systems remains the same. Their fingerprint therefore causes very similar anomalies in network traffic, and this is where the strength of Darktrace lies.

Darktrace’s anomaly-based approach to threat detection means that these new attack types are quickly drawn out of the noise of everyday traffic within an environment. Once attackers have gained a foothold in a network, they will have to cause deviation from the usual pattern of a life on a network to proceed; Darktrace is uniquely placed to detect even the most subtle changes in a device’s behavior that could be indicative of an emerging threat.

Machine learning can act as a force multiplier for security teams. Working hand in hand with the Darktrace SOC, the customer was able to generate cohesive and comprehensive reporting on the attack path within days. This would be a feat for humans alone, requiring significant resources and time, but with the power of Darktrace’s Self-Learning AI, these deep and complex analyses become as easy as the click of a button.

Credit to: Matthew John, Director of Operations, SOC, Paul Jennings, Principal Analyst Consultant

Get the latest insights on emerging cyber threats

Attackers are adapting, are you ready? This report explores the latest trends shaping the cybersecurity landscape and what defenders need to know in 2025.

  • Identity-based attacks: How attackers are bypassing traditional defenses
  • Zero-day exploitation: The rise of previously unknown vulnerabilities
  • AI-driven threats: How adversaries are leveraging AI to outmaneuver security controls

Stay ahead of evolving threats with expert analysis from Darktrace. Download the report here.

‍

Appendices

Darktrace DETECT Model Breaches

Internal Reconnaissance

Device / Multiple Lateral Movement Model Breaches

Device / Large Number of Model Breaches

Device / Network Scan

Device / Anomalous RDP Followed by Multiple Model Breaches

Device / Possible SMB/NTLM Reconnaissance

Device / SMB Lateral Movement

Anomalous Connection / SMB Enumeration

Anomalous Connection / Possible Share Enumeration Activity

Device / Suspicious SMB Scanning Activity

Device / RDP Scan

Anomalous Connection / Active Remote Desktop Tunnel

Device / Increase in New RPC Services

Device / ICMP Address Scan

Download and Upload

Unusual Activity / Enhanced Unusual External Data Transfer

Unusual Activity / Unusual External Data Transfer

Anomalous Connection / Uncommon 1 GiB Outbound

Anomalous Connection / Data Sent to Rare Domain

Anomalous Connection / Download and Upload

Compliance / SSH to Rare External Destination

Anomalous Server Activity / Rare External from Server

Anomalous Server Activity / Outgoing from Server

Anomalous Connection / Application Protocol on Uncommon Port

Anomalous Connection / Multiple Connections to New External TCP Port

Device / Anomalous SMB Followed By Multiple Model Breaches

Unusual Activity / SMB Access Failures

Lateral Movement and Encryption

User / New Admin Credentials on Server

Compliance / SMB Drive Write

Device / Anomalous RDP Followed By Multiple Model Breaches

Anomalous Connection / High Volume of New or Uncommon Service Control

Anomalous Connection / New or Uncommon Service Control

Device / New or Unusual Remote Command Execution

Anomalous Connection / SMB Enumeration

Additional Beaconing and Tooling

Device / Initial Breach Chain Compromise

Device / Multiple C2 Model Breaches

Compromise / Large Number of Suspicious Failed Connections

Compromise / Sustained SSL or HTTP Increase

Compromise / SSL or HTTP Beacon

Compromise / Suspicious Beaconing Behavior

Compromise / Large Number of Suspicious Successful Connections

Compromise / High Volume of Connections with Beacon Score

Compromise / Slow Beaconing Activity To External Rare

Compromise / SSL Beaconing to Rare Destination

Compromise / Beaconing Activity To External Rare

Compromise / Beacon to Young Endpoint

Compromise / Agent Beacon to New Endpoint

Anomalous Server Activity / Rare External from Server

Anomalous Connection / Multiple Failed Connections to Rare Endpoint

Anomalous File / EXE from Rare External Location

IoC - Type - Description + Confidence

dataspt[.]com - Hostname - Highly Likely Exfiltration Server

46.22.211[.]151:2022 - IP Address and Unusual Port - Highly Likely Exfiltration Server

faceappinc[.]com - Hostname - Likely C2 Infrastructure

Instructions_read_me.txt - Filename - Almost Certain Ransom Note

212.118.55[.]211 - IP Address - Likely C2 Infrastructure

delete[.]me - Filename - Potential lateral movement script

covet[.]me - Filename - Potential lateral movement script

d0ec4b50a944b182fc10ff51f883ccf7 - JA3 Client Fingerprint - Potential Windows BITS C2 Process

/download/cal.linux - URI - Likely BlackBasta executable file

1f4dcfa562f218fcd793c1c384c3006e460213a8 - Sha1 File Hash - Likely BlackBasta executable file

References

[1] https://blogs.blackberry.com/en/2022/05/black-basta-rebrand-of-conti-or-something-new

[2] https://www.cybereason.com/blog/threat-alert-aggressive-qakbot-campaign-and-the-black-basta-ransomware-group-targeting-u.s.-companies

[3] https://www.trendmicro.com/en_us/research/22/e/examining-the-black-basta-ransomwares-infection-routine.html

[4] https://unit42.paloaltonetworks.com/atoms/blackbasta-ransomware/

[5] https://www.trendmicro.com/en_gb/research/23/a/batloader-malware-abuses-legitimate-tools-uses-obfuscated-javasc.html

[6] https://www.pcrisk.com/removal-guides/23666-black-basta-ransomware

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
Matthew John
Director of Operations, SOC

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September 30, 2026

AI-Assisted Attacks Still Leave a Behavioral Trace  

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Key Insights

  • Darktrace identified behavioral indicators associated with two campaigns linked to AI-assisted threat activity, highlighting the growing role of AI in modern cyber-attacks.
  • Observed activity involved suspicious WebDAV file transfers, disguised executable downloads, beaconing to rare infrastructure, unusual process execution, and communications with C2 infrastructure linked to active intrusion campaigns.

Introduction

Just as organizations are incorporating AI into their operations to take advantage of its benefits, threat actors are doing the same, creating new challenges for defenders.

Much of the discussion around AI risk has focused on the expanding attack surface created by AI systems within organizations. These systems are often granted privileged access and heightened permissions to carry out their duties, introducing new security risks and unintended consequences.

At the same time, threat actors are learning to leverage AI to enable malicious activities such as vulnerability discovery, exploit creation, and progressing through the Cyber Kill Chain more quickly. By accelerating development, adaptation, and scaling, AI enables attackers to operate more efficiently while making some capabilities more accessible to less skilled operators.

Whether AI is the target or the enabler, the resulting activity still manifests through networks, identities, endpoints and cloud services. Those interactions create observable signals that defenders can investigate, regardless of how the attack was developed.

AI as part of the attacker’s workflow

Darktrace has previously documented how threat actors are increasingly incorporating AI into offensive operations [1]. Two recent investigations from open-source intelligence (OSINT) illustrate this. In both cases, researchers identified the role of AI within malicious operations. Separately, Darktrace detected activity in customer environments that aligned with the infrastructure and techniques reported in those campaigns. These perspectives provide a view of both attacker workflow and operational consequences.

Although AI played different roles in each campaign, it did not remove the need for the attackers to interact with their targets. Payloads still had to be delivered, processes executed, and command-and-control (C2) connections established, creating behavioral anomalies that Darktrace was able to identify.

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Case 1: A Mexican government impersonation campaign with LLM-assisted malware development

Rapid7 reported on a malware delivery operation that used generative AI to assist development, testing, documentation and refinement of attacker infrastructure. Between May and June 2026, Darktrace similarly observed two chains of suspicious activity across customer environments in the Americas that exhibited clear similarities in behavior.

In both cases Darktrace observed:

  • WebDAV communication with onedrive[.]cv·138.124.123[.]87, retrieving a file from the path /Downloads/CURP/
  • Transfer of a masqueraded .scr executable
  • Subsequent communication with google.services[.]ug·77.110.127[.]205 over unusual high ports
  • Additional Darktrace detections correlating the unusual behavior seen spanning payload delivery and C2 communication
  • Darktrace’s Autonomous Response capability alerted across multiple stages of the attack

The infrastructure and behavior observed by Darktrace closely aligned with a campaign reported by Rapid7, in which a WebDAV malware delivery environment was exposed. Rapid7 assessed that threat actors had used generative AI to support the development, testing, documentation and refinement of the operation. The observed activity also aligned with reporting on a campaign in which impersonation of Mexico’s government Unique Population Registry Code (CURP) identity-record service led to delivery of PureRAT, a .NET-based information stealer and remote access trojan (RAT) [2]. The infrastructure overlap and consistent behavioural sequence provides strong alignment and offers a view of how an AI-assisted development pipeline ultimately manifested inside target environments.

Case 2: A suspected China-linked intrusion campaign with AI-assisted automation

In July 2026, Hunt.io published research into a suspected China-based intrusion operation targeting government and financial services organizations [3]. Material recovered from exposed attacker infrastructure by Hunt.io indicated that Claude Code and DeepSeek-v4-pro were being used as active components of the attacker’s workflow. According to the research, the models supported activities including attack reasoning, script generation, execution, exploit adaptation, and phishing-page development.

The investigation identified 192.229.115[.]229 and 192.229.115[.]230 as infrastructure associated with suspected TencShell operations and a possible second C2 framework known as Gshell [3].

Darktrace identified likely related activity within a financial services customer environment involving a newly observed laptop running the Windows 11 Pro operating system. Over a six-day period in July, the device made repeated outbound connections to 192.229.115[.]229 over port 8083.

Darktrace recognized the destination was highly rare for the environment, and the connectivity exhibited beaconing characteristics. During the same timeframe, Darktrace also identified suspicious process behavior associated with process chains involving svchost.exe and cmd.exe. The device repeatedly communicated with infrastructure identified in the Hunt.io research while exhibiting beaconing characteristics and suspicious process activity, strengthening the assessment that the activity likely was associated with the same operation.

Unlike many previous examples of AI-assisted cybercrime, the Hunt.io investigation provided rare visibility into how large language models were being incorporated directly into operational workflows rather than being used solely for content generation. Darktrace, meanwhile, observed how activity associated with that operation ultimately manifested inside a target environment, providing a complementary view of its operational impact.

Operational consequences of AI-assisted attacks

These investigations provide two complementary perspectives on AI-assisted cyber operations. OSINT research revealed how AI was incorporated into attacker workflows, while Darktrace observed the resulting activity within customer environments.

Although AI played different roles in each campaign, it did not remove the need for attackers to interact with their targets, deliver payloads, execute processes, and communicate with C2, all of which generated observable signals.

In these cases, Darktrace identified suspicious file delivery, unusual process behavior, beaconing activity, and communication with rare external infrastructure that aligned with campaigns later linked to AI-assisted operations. While AI may influence how attacks are developed, adapted, and scaled, it does not make them operationally invisible.

For defenders, the broader lesson extends beyond these specific campaigns. As AI becomes increasingly embedded within both enterprise operations and attacker workflows, understanding what a model was asked to do is often less important than understanding the actions it ultimately took and the consequences those actions produced. Whether the actor is human, AI-assisted, or increasingly autonomous, activity still manifests through identities, endpoints, applications, cloud services and network infrastructure.

Credit to Angel Arribas Lopez (Associate Principal Cyber Analyst), Emma Foulger (Global Threat Research Operations Lead), Nathaniel Jones, SVP Global Threat Intelligence
Edited by Ryan Traill (Content Manager)

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Appendices

Darktrace Model Detections

Case 1

Anomalous File / Masqueraded File Transfer from New External Endpoint

Anomalous File / Script from Rare External Location

Anomalous File / EXE from Rare External Location

Anomalous File / Script and EXE from Rare External

Anomalous Connection / Multiple Failed Connections to Rare Endpoint

Anomalous Connection / Rare External SSL Self-Signed

Compromise / New or Repeated to Unusual SSL Port

Compromise / Large Number of Suspicious Failed Connections

Device / Initial Attack Chain Activity

Antigena / Network / External Threat::Antigena Suspicious File Block

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

Antigena / Network / Significant Anomaly::Antigena Controlled and Model Alert

Antigena / Network / External Threat::Antigena File then New Outbound Block

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

Antigena / Network / Significant Anomaly::Antigena Alerts Over Time Block

Case 2

Anomalous Connection / Multiple Failed Connections to Rare Endpoint

Compromise / High Volume of Connections with Beacon Score

Compromise / Large Number of Suspicious Failed Connections

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Indicators of Compromise (IoCs)

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Case 1

                                                                                                                                                                                                                                                 
IoCTypeDescription + Confidence
onedrive[.]cvHostnameLikely C2 server
138.124.123[.]87IP AddressPossible C2 server
hXXp://onedrive[.]cv/Downloads/CURP/ReportFinal.%E2%80%AE%E1%BA%9D%D4%81%EF%BD%90.scrURIPossible payload
google.services[.]ugHostnameLikely C2 server
77.110.127[.]205IP AddressLikely C2 server
google.services[.]ug:57666Hostname + PortLikely C2 communication
google.services[.]ug:57888Hostname + PortLikely C2 communication
google.services[.]ug:56001Hostname + PortLikely C2 communication

‍

Case 2

IoC Type Description + Confidence
192.229.115[.]229 IP Address Likely C2 communication
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About the author
Angel Arribas Lopez
Associate Principal Cyber Analyst

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September 30, 2026

A Chain Reaction: Blockchain-Hosted Infostealer Campaign Targets Windows and macOS

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Key Insights

  • Darktrace detected a blockchain-hosted infostealer campaign targeting Windows and macOS devices across multiple customer environments.
  • The campaign combined ClickFix social engineering with trusted services and decentralized blockchain infrastructure to support malware delivery and C2 activity.
  • Compromised devices were observed connecting to rare and unusual external endpoints, including DGA C2 domains, blockchain-related endpoints, and cryptocurrency mining infrastructure.
  • The activity was associated with information-stealing malware strains including Atomic macOS Stealer (AMOS), Lumma, Rhadamanthys, Vidar, and Phexia.
  • Darktrace identified anomalous device behavior, beaconing patterns, rare external connections, cryptomining activity, and suspicious TLS/SSL communications without relying solely on prior knowledge or static indicators of compromise.
  • The campaign highlights how attackers are increasingly using legitimate and decentralized infrastructure to make detection, disruption, and attribution more challenging for defenders.

The Infostealer Ecosystem

The information stealer malware ecosystem continues to grow in value for threat actors across the digital threat landscape. Infostealers are increasingly delivered through Malware-as-a-Service (MaaS) operating models, distributed through affiliate networks, and designed to withstand infrastructure takedowns. This resilience was demonstrated by the recent takedown of Lumma Stealer malicious domains by Microsoft’s Digital Crimes Unit (DCU) [1].

Infostealers are used to gather and exfiltrate sensitive information, including non-human identity (NHI) data, from compromised systems across cloud, Software-as-a-Service (SaaS), Virtual Private Network (VPN), and development environments. They can also support ransomware operations by expanding the credentials and access paths available to threat actors, contributing to the high volume of identity-based attacks observed across the broader threat landscape [2][3].

Darktrace’s Observations of ClickFix and Infostealers

Throughout 2026, Darktrace has observed multiple campaigns using ClickFix social engineering to trick users into carrying out malicious actions and downloading initial payloads, including information stealers. More recently, Darktrace’s Threat Research team identified a specific ClickFix campaign involving a blockchain-hosted infostealer targeting Windows and macOS devices.

Darktrace identified affected customer environments across Europe, the United States, Asia, and the Middle East where blockchain-hosted infostealer malware appears to have been delivered to compromised systems following likely ClickFix-driven initial access. Darktrace investigated the activity and found that decentralized blockchain infrastructure, alongside widely trusted legitimate services, was used to support malware delivery and information theft across Windows and macOS systems.

Following initial access, compromised systems established C2 communication, with C2 configuration and payloads hosted on public blockchain infrastructure. The ultimate objective appears to be credential and cryptocurrency theft through the deployment of information stealers such as Atomic macOS Stealer (AMOS), Lumma, Rhadamanthys, and Vidar [5][6][7].

Darktrace’s Investigation

Affected devices across the Darktrace customer base were observed making outbound connections to rare external endpoints in patterns consistent with beaconing and C2 activity. Darktrace primarily detected devices making repeated connections to algorithmically generated domains (DGA) such as hf98x4d[.]site [8]. In many cases, these domains were linked through open-source intelligence (OSINT) to information-stealing malware families including AMOS and Phexia [5][6][7][8][9].

In multiple cases, devices were also observed connecting to blockchain-related endpoints, such as polygon[.]drpc[.]org, as well as legitimate public services, including GitHub. The use of decentralized blockchain infrastructure and trusted services such as GitHub to facilitate malware distribution and C2 activity can make disruption and attribution significantly more difficult for defenders.

Darktrace also detected a significant proportion of impacted devices making outbound connections to cryptocurrency mining infrastructure associated with the legitimate open-source XMRig mining software and the HashVault mining pool, including pool.hashvault[.]pro and donate[.]ssl[.]xmrig[.]com, which were abused by the attackers, indicating, including pool.hashvault[.]pro and donate[.]ssl[.]xmrig[.]com, indicating active cryptomining on compromised systems.

In one case, mining activity was observed before and during connections to the DGA endpoint hf98x4d[.]site. Due to its highly anomalous nature, Darktrace's Real-Time AI Analyst autonomously investigated the activity as it occurred, correlating the two events into a single cryptocurrency mining incident and providing comprehensive visibility into the broader attack.

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Figure 1: Real-Time AI Analyst investigation of suspicious SSL and C2 communications with hf98x4d[.]site over port 443.

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Figure 2: Real-Time AI Analyst investigation into cryptocurrency mining activity involving pool[.]hashvault[.]pro over SSL on port 443.

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Around the same time, Darktrace identified the same device initiating connections to the GitHub endpoint release-assets[.]githubusercontent[.]com while continuing to make repeated connections to hf98x4d[.]site.

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Figure 3: Darktrace's detection of an affected device connecting to a GitHub endpoint between repeated connections to the anomalous external endpoint hf98x4d[.]site.

On the network of another customer, Darktrace observed an affected device making highly unusual outbound connections consistent with beaconing activity. The device initiated multiple connections over port 443 to the external hostname polygon[.]drpc[.]org. According to OSINT, this hostname is a Remote Procedure Call (RPC) endpoint provided by dRPC, a legitimate service enabling decentralized applications (dApps), cryptocurrency wallets, and developer tools to interact with the Polygon blockchain [10].

The same device was later observed making repeated TLS/SSL connections to the previously mentioned DGA C2 domain. In addition, it made outbound connections to the external IP 195.242.214[.]34 over destination port 51820, an endpoint associated with the ProtonVPN service. Collectively, these connections to blockchain-related infrastructure, the DGA C2 domain, and ProtonVPN-associated infrastructure suggested the device had been affected by the campaign.

Conclusion

This campaign demonstrates how attackers can combine ClickFix social engineering with trusted services and decentralized blockchain infrastructure to create a resilient, cross-platform malware delivery chain. By using services such as GitHub alongside blockchain RPC endpoints and rapidly replaceable DGA domains, the activity can blend into legitimate traffic while making infrastructure disruption and attribution more difficult.

For defenders, it’s a reminder that trusted infrastructure does not automatically mean trusted activity. Security teams should look for the behaviors surrounding these connections, including unusual outbound communication, repeated beaconing, unexpected access to blockchain services, suspicious TLS/SSL activity and cryptomining. In this campaign, Darktrace identified and correlated these deviations without depending solely on previously known indicators, providing visibility as affected devices moved between legitimate services, decentralized infrastructure and malicious C2 endpoints

Credit to Nahisha Nobregas (Associate Principal Cyber Analyst), Manoel Kadja (Senior Cyber Analyst)

Edited by Ryan Traill (Content Manager)

Appendices

Darktrace Model Detections

▪ Compromise / Beaconing Activity To External Rare

▪ Compromise / Beacon to Young Endpoint

▪ Compromise / Fast Beaconing to DGA

▪ Compromise / High Volume of Connections with Beacon Score

▪ Compromise / DGA Beacon

▪ Compromise / Slow Beaconing Activity To External Rare

▪ Compromise / Agent Beacon (Long Period)

▪ Compromise / Agent Beacon (Medium Period)

▪ Compromise / Sustained SSL or HTTP Increase

▪ Compromise / Large Number of Suspicious Failed Connections

▪ Compromise / SSL Beaconing to Rare Destination

▪ Compromise / Beacon for 4 Days

▪ Compromise / High Priority Crypto Currency Mining

▪ Compromise / Monero Mining

▪ Device / Long Agent Connection to New Endpoint

▪ Device / New Connections On Suspicious Port

▪ Anomalous Connection / High Volume of Connections to Rare Domain

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List of Indicators of Compromise (IoCs)

 
Indicator Description
hf98x4d[.]site C2 Endpoint (Hostname)
sj98xe4[.]xyz C2 Endpoint (Hostname)
citcix6[.]xyz C2 Endpoint (Hostname)
bduwih8[.]pro C2 Endpoint (Hostname)

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MITRE ATT&CK Mapping

 
Tactic (ID) Technique
Persistence (T1176) Browser Extensions (T1176.001)
Persistence (T1176) Software Extensions
Command and Control (T1071) Web Protocols (T1071.001)
Command and Control (T1568) Domain Generation Algorithms (T1568.002)
Command and Control (T1071) Application Layer Protocol
Command and Control (T1102) One-Way Communication (T1102.003)
Command and Control (T1571) Non-Standard Port
Command and Control (T1104) Multi-Stage Channels
Command and Control (T1573) Encrypted Channel
Command and Control (T1008) Fallback Channels
Initial Access ICS (T0862) Supply Chain Compromise
Command and Control ICS (T0885) Commonly Used Port
Collection (T1185) Browser Session Hijacking
Impact (T1496) Compute Hijacking (T1496.001)
Impact (T1496) Resource Hijacking
Command and Control (T1071) Publish/Subscribe Protocols (T1071.001)
Lateral Movement (T1210) Exploitation of Remote Services

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References:

1.        https://www.microsoft.com/en-us/security/blog/2025/05/21/lumma-stealer-breaking-down-the-delivery-techniques-and-capabilities-of-a-prolific-infostealer/

2.        https://spycloud.com/resource/report/spycloud-annual-identity-exposure-report-2026/

3.        https://www.darktrace.com/blog/why-trust-is-the-new-attack-surface-darktraces-mid-year-threat-update-2026

4.        https://www.darktrace.com/blog/unpacking-clickfix-darktraces-detection-of-a-prolific-social-engineering-tactic

5.        https://abekweng.medium.com/inside-a-blockchain-hosted-malware-campaign-targeting-windows-and-macos-f5bcdeffed66

6.        https://cloud.google.com/blog/topics/threat-intelligence/unc5142-etherhiding-distribute-malware

7.        https://haveibeensquatted.com/blog/from-typosquatting-to-macos-backdoor-clickfix-blockchain-c2

8.        https://www.virustotal.com/gui/domain/hf98x4d.site/community

9.        https://x.com/FABO97662188/status/2074125545026244795

10.  https://www.virustotal.com/gui/url/b0e5c51a411065864119c305fddf218b7c120731f655932cc1c3307ad5b43f94/gti-summary

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About the author
Nahisha Nobregas
SOC Analyst
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