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August 17, 2023

Successfully Containing an Admin Credential Attack

Discover how Darktrace's anomaly-based threat detection thwarted a cyber-attack on a customer's network, stopping a malicious actor in their tracks.
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
Zoe Tilsiter
Cyber Analyst
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17
Aug 2023

What is Admin Credential Abuse?

In an effort to remain undetected by increasingly vigilant security teams, malicious actors across the threat landscape often resort to techniques that allow them to remain ‘quiet’ on the network and carry out their objectives subtly. One such technique often employed by attackers is using highly privileged credentials to carry out malicious activity.

This emphasizes the need to be hyper vigilant and not assume that ‘administrative’ activity using privileged credentials is legitimate. In this way, both internal visibility and defense in-depth are needed, as well as a strong understanding of ‘normal’ administrative activity to then identify any deviations from this.  

In one recent example, Darktrace identified a threat actor attempting to use privileged administrative credentials to move laterally through a customer’s network and compromise two further critical servers. Darktrace DETECT™ identified that this activity was unusual and alerted the customer to early signs of compromise, reconnaissance and lateral movement to the other critical devices, while Darktrace RESPOND™ acted autonomously to inhibit the spread of activity and allowed the customer to quarantine the compromised devices.

Attack Overview and Darktrace Coverage

Over the course of a week in late May 2023, Darktrace observed a compromise on the network of a customer in the Netherlands. The threat actors primarily used living off the land techniques, abusing legitimate administrative credentials and executables to perform unexpected activities. This technique is intended to go under the radar of traditional security tools that are often unable to distinguish between the legitimate or malicious use of privileged credentials.

Darktrace was the only security solution in the customer’s stack that way able to detect and contain the attack, preventing it from spreading through their digital estate.

1. Device Reactivated

On May 22, 2023, Darktrace began to observe traffic originating from a File Server device which prior to this, had been been inactive on the network for some time, with no incoming or outgoing traffic recently observed for this IP. Therefore, upon initiating connections again, Darktrace’s AI tagged the device with the “Re-Activated Device” label. It also tagged the device as an “Internet Facing System”, which could represent an initial point of compromise.

Following this, the device was observed using an administrative credential that was commonly used across network, with no clear indications of brute-force activity or successive login failures preceeding this activity. The unusual use of a known credential on a network can be very difficult to detect for traditional security tools. Darktrace’s anomaly-based detection allows it to recognize subtle deviations in device behavior meaning it is uniquely placed to recognize this type of activity.

2. Reconaissance  

On the following day, the affected device began to perform SMB scans for open 445 ports, and writing files such as srvsvc and winreg, both of which are indicative of network  reconnaissance. Srvsvc is used to enumerate available SMB shares on destination devices which could be used to then write malicious files to these shares, while Winreg (Windows Registry) is used to store information that configures users, applications, and hardware devices [1]. Darktrace also observed the device carrying out DCE_RPC activity and making Windows Management Instrumentation (WMI) enumeration requests to other internal devices.

3. Lateral Movement via SMB

On May 24 and May 30, Darktrace observed the same device writing files over SMB to a number of other internal devices, including an SMB server and the Domain Controller. Darktrace identified that these writers were to privileged credential paths, such as C$ and ADMIN$, and it further recognized that the device was using the compromised administrative credential.

The files included remote command executable files (.exe) and batch scripts which execute commands upon clicking in a serial order. This behavior is indicative of a threat actor performing lateral movement in an attempt to infect other devices and strengthen their foothold in the network.

Files written:

·       LogConverter.bat

·       sql.bat

·       Microsoft.NodejsTools.PressAnyKey.exe

·       PSEXESVC.exe

·       Microsoft.NodejsTools.PressAnyKey.lnk

·       CG6oDkyFHl3R.t

5. Reconnaissance Spread

Around the same time as the observed lateral movement activity, between May 24 and May 30, the initially compromised device continued SMB and DCE_RPC activity, mainly involving SMB writes of files such as srvsvc, and PSEXESVC.exe.

Then, on May 28, Darktrace identified another internal Domain Controller engaging in similar suspicious behavior to the original compromised device. This included network scanning, enumeration and service control activity, indicating a spread of further malicious reconnaissance.

Following the successful detection of this activity, Darktrace’s Cyber AI Analyst launched autonomous investigations which was able to correlate incidents from multiple affected devices across the network, in doing so connecting multiple incidents into one security event.

Figure 1: Cyber AI Analyst connecting multiple events into one incident
Figure 2: Cyber AI Analyst investigation process to identify suspicious activity.

6. Lateral Movement

Alongside these SMB writes, the initially compromised device was seen connecting to various internal devices over ports associated with administrative protocols such as Remote Desktop Protocol (RDP). It also made a high volume of NTLM login failures for the credential ‘administrator’, suggesting that the malicious actor was attempting to brute-force an administrative credential.

7. Suspicious External Activity

Following earlier SMB writes from the initially compromised device to the Domain Controller server, the Domain Controller was seen making an unusual volume of external connections to rare endpoints which could indicate malicious command and control (C2) communication.

Alongside this activity, between May 30 and June 1, Darktrace also observed an unusually large number (over 12 million) of incoming connections from external endpoints. This activity is likely indicative of an attempted Denial of Service (DoS) attack.

Endpoints include:

·       45.15.145[.]92

·       198.2.200[.]89

·       162.211.180[.]215

Figure 3: Graphing function in the Darktrace UI showing the observed spike of inbound communication from external endpoints, indicating a potential DoS attack.

8. Reconnaissance and RDP activity

On May 31, the initially compromised device was seen creating an administrative RDP session with cookie ‘Administr’. Using the initially compromised administrative credential, further suspicious SMB activity was observed from the compromised devices on the same day including further SMB Enumeration, service control, PsExec remote command execution, and writes of another suspicious batch script file to various internal devices.

Darktrace RESPOND Coverage

Darktrace RESPOND’s autonomous response capabilities allowed it to take instantaneous preventative action against the affected devices as soon as suspicious activity was identified, consequently inhibiting the spread of this attack.

Specifically, Darktrace RESPOND was able to block suspicious connections to multiple internal devices and ports, among them port 445 which was used by threat actors to perform SMB scanning, for one hour. As a result of the autonomous actions carried out by Darktrace, the attack was stopped at the earliest possible stage.

Figure 4: Autonomous RESPOND actions taken against initially compromised devices.

In addition to these autonomous actions, the customer was able to further utilize RESPOND for containment purposes by manually actioning some of the more severe actions suggested by RESPOND, such as quarantining compromised devices from the rest of the network for a week.

Figure 5: Manually applied RESPOND actions to quarantine compromised devices for one week.

Conclusion

As attackers continue to employ harder to detect living off the land techniques to exploit administrative credentials and move laterally across networks, it is paramount for organizations to have an intelligent decision maker that can recgonize the subtle deviations in device behavior.

Thanks to its Self-Learning AI, Darktrace is uniquely placed to understand its customer’s networks, allowing it to recognize unusual or uncommon activity for individual devices or user credentials, irrespective of whether this activity is typically considered as legitimate.

In this case, Darktrace was the only solution in the customer’s security stack that successfully identified and mitigated this attack. Darktrace DETECT was able to identify the the early stages of the compromise and provide full visibility over the kill chain. Meanwhile, Darktrace RESPOND moved at machine-speed, blocking suspicious connections and preventing the compromise from spreading across the customer’s network.

Appendices

Darktrace DETECT Model Breaches

Anomalous Connection / High Volume of New or Uncommon Service Control

Anomalous Connection / New or Uncommon Service Control

Anomalous Connection / SMB Enumeration

Anomalous Connection / Unusual Admin RDP Session

Anomalous Connection / Unusual Admin SMB Session

Anomalous File / Internal / Executable Uploaded to DC

Anomalous File / Internal / Unusual SMB Script Write

Anomalous Server Activity / Outgoing from Server

Anomalous Server Activity / Possible Denial of Service Activity

Antigena / Network / Insider Threat / Antigena Network Scan Block

Antigena / Network / Insider Threat / Antigena SMB Enumeration Block

Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Server Block

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

Compliance / Outgoing NTLM Request from DC

Compliance / SMB Drive Write

Device / Anomalous NTLM Brute Force

Device / ICMP Address Scan  

Device / Internet Facing Device with High Priority Alert

Device / Large Number of Model Breaches

Device / Large Number of Model Breaches from Critical Network Device

Device / Multiple Lateral Movement Model Breaches

Device / Network Scan

Device / New or Uncommon SMB Named Pipe

Device / New or Uncommon WMI Activity

Device / New or Unusual Remote Command Execution

Device / Possible SMB/NTLM Brute Force

Device / RDP Scan

Device / SMB Lateral Movement

Device / SMB Session Brute Force (Admin)

Device / Suspicious SMB Scanning Activity

Darktrace RESPOND Model Breaches

Antigena / Network / Insider Threat / Antigena Network Scan Block

Antigena / Network / Insider Threat / Antigena SMB Enumeration Block

Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Server Block

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

Cyber AI Analyst Incidents

Extensive Suspicious Remote WMI Activity

Extensive Unusual Administrative Connections

Large Volume of SMB Login Failures from Multiple Devices

Port Scanning

Scanning of Multiple Devices

SMB Writes of Suspicious Files

Suspicious Chain of Administrative Connections

Suspicious DCE_RPC Activity

TCP Scanning of Multiple Devices

MITRE ATT&CK Mapping

‍RECONNAISSANCE
T1595 Active Scanning
T1589.001 Gathering Credentials

CREDENTIAL ACCESS
T1110 Brute Force

LATERAL MOVEMENT
T1210 Exploitation of Remote Services
T1021.001 Remote Desktop Protocol

COMMAND AND CONTROL
T1071 Application Layer Protocol

IMPACT
T1498.001 Direct Network Flood

References

[1] https://learn.microsoft.com/en-us/troubleshoot/windows-server/performance/windows-registry-advanced-users

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
Zoe Tilsiter
Cyber Analyst

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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.

‍

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)

‍

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

‍

Indicators of Compromise (IoCs)

‍

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.

‍

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

‍

‍

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)

‍

‍

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

‍

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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