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November 27, 2023

Darktrace Uncovers Persistent PurpleFox Rootkit

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27
Nov 2023
Explore Darktrace's successful hunt for the PurpleFox rootkit. Understand the techniques used to detect and defeat this sophisticated threat.

Versatile Malware: PurpleFox

As organizations and security teams across the world move to bolster their digital defenses against cyber threats, threats actors, in turn, are forced to adopt more sophisticated tactics, techniques and procedures (TTPs) to circumvent them. Rather than being static and predictable, malware strains are becoming increasingly versatile and therefore elusive to traditional security tools.

One such example is PurpleFox. First observed in 2018, PurpleFox is a combined fileless rootkit and backdoor trojan known to target Windows machines. PurpleFox is known for consistently adapting its functionalities over time, utilizing different infection vectors including known vulnerabilities (CVEs), fake Telegram installers, and phishing. It is also leveraged by other campaigns to deliver ransomware tools, spyware, and cryptocurrency mining malware. It is also widely known for using Microsoft Software Installer (MSI) files masquerading as other file types.

The Evolution of PurpleFox

The Original Strain

First reported in March 2018, PurpleFox was identified to be a trojan that drops itself onto Windows machines using an MSI installation package that alters registry values to replace a legitimate Windows system file [1]. The initial stage of infection relied on the third-party toolkit RIG Exploit Kit (EK). RIG EK is hosted on compromised or malicious websites and is dropped onto the unsuspecting system when they visit browse that site. The built-in Windows installer (MSIEXEC) is leveraged to run the installation package retrieved from the website. This, in turn, drops two files into the Windows directory – namely a malicious dynamic-link library (DLL) that acts as a loader, and the payload of the malware. After infection, PurpleFox is often used to retrieve and deploy other types of malware.  

Subsequent Variants

Since its initial discovery, PurpleFox has also been observed leveraging PowerShell to enable fileless infection and additional privilege escalation vulnerabilities to increase the likelihood of successful infection [2]. The PowerShell script had also been reported to be masquerading as a .jpg image file. PowerSploit modules are utilized to gain elevated privileges if the current user lacks administrator privileges. Once obtained, the script proceeds to retrieve and execute a malicious MSI package, also masquerading as an image file. As of 2020, PurpleFox no longer relied on the RIG EK for its delivery phase, instead spreading via the exploitation of the SMB protocol [3]. The malware would leverage the compromised systems as hosts for the PurpleFox payloads to facilitate its spread to other systems. This mode of infection can occur without any user action, akin to a worm.

The current iteration of PurpleFox reportedly uses brute-forcing of vulnerable services, such as SMB, to facilitate its spread over the network and escalate privileges. By scanning internet-facing Windows computers, PurpleFox exploits weak passwords for Windows user accounts through SMB, including administrative credentials to facilitate further privilege escalation.

Darktrace detection of PurpleFox

In July 2023, Darktrace observed an example of a PurpleFox infection on the network of a customer in the healthcare sector. This observation was a slightly different method of downloading the PurpleFox payload. An affected device was observed initiating a series of service control requests using DCE-RPC, instructing the device to make connections to a host of servers to download a malicious .PNG file, later confirmed to be the PurpleFox rootkit. The device was then observed carrying out worm-like activity to other external internet-facing servers, as well as scanning related subnets.

Darktrace DETECT™ was able to successfully identify and track this compromise across the cyber kill chain and ensure the customer was able to take swift remedial action to prevent the attack from escalating further.

While the customer in question did have Darktrace RESPOND™, it was configured in human confirmation mode, meaning any mitigative actions had to be manually applied by the customer’s security team. If RESPOND had been enabled in autonomous response mode at the time of the attack, it would have been able to take swift action against the compromise to contain it at the earliest instance.

Attack Overview

Figure 1: Timeline of PurpleFox malware kill chain.

Initial Scanning over SMB

On July 14, 2023, Darktrace detected the affected device scanning other internal devices on the customer’s network via port 445. The numerous connections were consistent with the aforementioned worm-like activity that has been reported from PurpleFox behavior as it appears to be targeting SMB services looking for open or vulnerable channels to exploit.

This initial scanning activity was detected by Darktrace DETECT, specifically through the model breach ‘Device / Suspicious SMB Scanning Activity’. Darktrace’s Cyber AI Analyst™ then launched an autonomous investigation into these internal connections and tied them into one larger-scale network reconnaissance incident, rather than a series of isolated connections.

Figure 2: Cyber AI Analyst technical details summarizing the initial scanning activity seen with the internal network scan over port 445.

As Darktrace RESPOND was configured in human confirmation mode, it was unable to autonomously block these internal connections. However, it did suggest blocking connections on port 445, which could have been manually applied by the customer’s security team.

Figure 3: The affected device’s Model Breach Event Log showing the initial scanning activity observed by Darktrace DETECT and the corresponding suggested RESPOND action.

Privilege Escalation

The device successfully logged in via NTLM with the credential, ‘administrator’. Darktrace recognized that the endpoint was external to the customer’s environment, indicating that the affected device was now being used to propagate the malware to other networks. Considering the lack of observed brute-force activity up to this point, the credentials for ‘administrator’ had likely been compromised prior to Darktrace’s deployment on the network, or outside of Darktrace’s purview via a phishing attack.

Exploitation

Darktrace then detected a series of service control requests over DCE-RPC using the credential ‘admin’ to make SVCCTL Create Service W Requests. A script was then observed where the controlled device is instructed to launch mshta.exe, a Windows-native binary designed to execute Microsoft HTML Application (HTA) files. This enables the execution of arbitrary script code, VBScript in this case.

Figure 4: PurpleFox remote service control activity captured by a Darktrace DETECT model breach.
Figure 5: The infected device’s Model Breach Event Log showing the anomalous service control activity being picked up by DETECT.

There are a few MSIEXEC flags to note:

  • /i : installs or configures a product
  • /Q : sets the user interface level. In this case, it is set to ‘No UI’, which is used for “quiet” execution, so no user interaction is required

Evidently, this was an attempt to evade detection by endpoint users as it is surreptitiously installed onto the system. This corresponds to the download of the rootkit that has previously been associated with PurpleFox. At this stage, the infected device continues to be leveraged as an attack device and scans SMB services over external endpoints. The device also appeared to attempt brute-forcing over NTLM using the same ‘administrator’ credential to these endpoints. This activity was identified by Darktrace DETECT which, if enabled in autonomous response mode would have instantly blocked similar outbound connections, thus preventing the spread of PurpleFox.

Figure 6: The infected device’s Model Breach Event Log showing the outbound activity corresponding to PurpleFox’s wormlike spread. This was caught by DETECT and the corresponding suggested RESPOND action.

Installation

On August 9, Darktrace observed the device making initial attempts to download a malicious .PNG file. This was a notable change in tactics from previously reported PurpleFox campaigns which had been observed utilizing .MOE files for their payloads [3]. The .MOE payloads are binary files that are more easily detected and blocked by traditional signatured-based security measures as they are not associated with known software. The ubiquity of .PNG files, especially on the web, make identifying and blacklisting the files significantly more difficult.

The first connection was made with the URI ‘/test.png’.  It was noted that the HTTP method here was HEAD, a method similar to GET requests except the server must not return a message-body in the response.

The metainformation contained in the HTTP headers in response to a HEAD request should be identical to the information sent in response to a GET request. This method is often used to test hypertext links for validity and recent modification. This is likely a way of checking if the server hosting the payload is still active. Avoiding connections that could possibly be detected by antivirus solutions can help keep this activity under-the-radar.

Figure 7: Packet Capture from an affected customer device showing the initial HTTP requests to the payload server.
Figure 8: Packet Capture showing the HTTP requests to download the payloads.

The server responds with a status code of 200 before the download begins. The HEAD request could be part of the attacker’s verification that the server is still running, and that the payload is available for download. The ‘/test.png’ HEAD request was sent twice, likely for double confirmation to begin the file transfer.

Figure 9: PCAP from the affected customer device showing the Windows Installer user-agent associated with the .PNG file download.

Subsequent analysis using a Packet Capture (PCAP) tool revealed that this connection used the Windows Installer user agent that has previously been associated with PurpleFox. The device then began to download a payload that was masquerading as a Microsoft Word document. The device was thus able to download the payload twice, from two separate endpoints.

By masquerading as a Microsoft Word file, the threat actor was likely attempting to evade the detection of the endpoint user and traditional security tools by passing off as an innocuous text document. Likewise, using a Windows Installer user agent would enable threat actors to bypass antivirus measures and disguise the malicious installation as legitimate download activity.  

Darktrace DETECT identified that these were masqueraded file downloads by correctly identifying the mismatch between the file extension and the true file type. Subsequently, AI Analyst was able to correctly identify the file type and deduced that this download was indicative of the device having been compromised.

In this case, the device attempted to download the payload from several different endpoints, many of which had low antivirus detection rates or open-source intelligence (OSINT) flags, highlighting the need to move beyond traditional signature-base detections.

Figure 10: Cyber AI Analyst technical details summarizing the downloads of the PurpleFox payload.
Figure 11 (a): The Model Breach generated by the masqueraded file transfer associated with the PurpleFox payload.
Figure 11 (b): The Model Breach generated by the masqueraded file transfer associated with the PurpleFox payload.

If Darktrace RESPOND was enabled in autonomous response mode at the time of the attack it would have acted by blocking connections to these suspicious endpoints, thus preventing the download of malicious files. However, as RESPOND was in human confirmation mode, RESPOND actions required manual application by the customer’s security team which unfortunately did not happen, as such the device was able to download the payloads.

Conclusion

The PurpleFox malware is a particularly dynamic strain known to continually evolve over time, utilizing a blend of old and new approaches to achieve its goals which is likely to muddy expectations on its behavior. By frequently employing new methods of attack, malicious actors are able to bypass traditional security tools that rely on signature-based detections and static lists of indicators of compromise (IoCs), necessitating a more sophisticated approach to threat detection.  

Darktrace DETECT’s Self-Learning AI enables it to confront adaptable and elusive threats like PurpleFox. By learning and understanding customer networks, it is able to discern normal network behavior and patterns of life, distinguishing expected activity from potential deviations. This anomaly-based approach to threat detection allows Darktrace to detect cyber threats as soon as they emerge.  

By combining DETECT with the autonomous response capabilities of RESPOND, Darktrace customers are able to effectively safeguard their digital environments and ensure that emerging threats can be identified and shut down at the earliest stage of the kill chain, regardless of the tactics employed by would-be attackers.

Credit to Piramol Krishnan, Cyber Analyst, Qing Hong Kwa, Senior Cyber Analyst & Deputy Team Lead, Singapore

Appendices

Darktrace Model Detections

  • Device / Increased External Connectivity
  • Device / Large Number of Connections to New Endpoints
  • Device / SMB Session Brute Force (Admin)
  • Compliance / External Windows Communications
  • Anomalous Connection / New or Uncommon Service Control
  • Compromise / Unusual SVCCTL Activity
  • Compromise / Rare Domain Pointing to Internal IP
  • Anomalous File / Masqueraded File Transfer

RESPOND Models

  • Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block
  • Antigena / Network / External Threat / Antigena Suspicious Activity Block
  • Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block
  • Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Client Block
  • Antigena / Network / External Threat / Antigena Suspicious File Block
  • Antigena / Network / External Threat / Antigena File then New Outbound Block

List of IoCs

IoC - Type - Description

/C558B828.Png - URI - URI for Purple Fox Rootkit [4]

5b1de649f2bc4eb08f1d83f7ea052de5b8fe141f - File Hash - SHA1 hash of C558B828.Png file (Malware payload)

190.4.210[.]242 - IP - Purple Fox C2 Servers

218.4.170[.]236 - IP - IP for download of .PNG file (Malware payload)

180.169.1[.]220 - IP - IP for download of .PNG file (Malware payload)

103.94.108[.]114:10837 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)

221.199.171[.]174:16543 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)

61.222.155[.]49:14098 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)

178.128.103[.]246:17880 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)

222.134.99[.]132:12539 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)

164.90.152[.]252:18075 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)

198.199.80[.]121:11490 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)

MITRE ATT&CK Mapping

Tactic - Technique

Reconnaissance - Active Scanning T1595, Active Scanning: Scanning IP Blocks T1595.001, Active Scanning: Vulnerability Scanning T1595.002

Resource Development - Obtain Capabilities: Malware T1588.001

Initial Access, Defense Evasion, Persistence, Privilege Escalation - Valid Accounts: Default Accounts T1078.001

Initial Access - Drive-by Compromise T1189

Defense Evasion - Masquerading T1036

Credential Access - Brute Force T1110

Discovery - Network Service Discovery T1046

Command and Control - Proxy: External Proxy T1090.002

References

  1. https://blog.360totalsecurity.com/en/purple-fox-trojan-burst-out-globally-and-infected-more-than-30000-users/
  2. https://www.trendmicro.com/en_us/research/19/i/purple-fox-fileless-malware-with-rookit-component-delivered-by-rig-exploit-kit-now-abuses-powershell.html
  3. https://www.akamai.com/blog/security/purple-fox-rootkit-now-propagates-as-a-worm
  4. https://www.foregenix.com/blog/an-overview-on-purple-fox
  5. https://www.trendmicro.com/en_sg/research/21/j/purplefox-adds-new-backdoor-that-uses-websockets.html
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.
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Piramol Krishnan
Cyber Security Analyst
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January 16, 2025

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Reimagining Your SOC: How to Achieve Proactive Network Security

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Introduction: Challenges and solutions to SOC efficiency

For Security Operation Centers (SOCs), reliance on signature or rule-based tools – solutions that are always chasing the latest update to prevent only what is already known – creates an excess of false positives. SOC analysts are therefore overwhelmed by a high volume of context-lacking alerts, with human analysts able to address only about 10% due to time and resource constraints. This forces many teams to accept the risks of addressing only a fraction of the alerts while novel threats go completely missed.

74% of practitioners are already grappling with the impact of an AI-powered threat landscape, which amplifies challenges like tool sprawl, alert fatigue, and burnout. Thus, achieving a resilient network, where SOC teams can spend most of their time getting proactive and stopping threats before they occur, feels like an unrealistic goal as attacks are growing more frequent.

Despite advancements in security technology (advanced detection systems with AI, XDR tools, SIEM aggregators, etc...), practitioners are still facing the same issues of inefficiency in their SOC, stopping them from becoming proactive. How can they select security solutions that help them achieve a proactive state without dedicating more human hours and resources to managing and triaging alerts, tuning rules, investigating false positives, and creating reports?

To overcome these obstacles, organizations must leverage security technology that is able to augment and support their teams. This can happen in the following ways:

  1. Full visibility across the modern network expanding into hybrid environments
  2. Have tools that identifies and stops novel threats autonomously, without causing downtime
  3. Apply AI-led analysis to reduce time spent on manual triage and investigation

Your current solutions might be holding you back

Traditional cybersecurity point solutions are reliant on using global threat intelligence to pattern match, determine signatures, and consequently are chasing the latest update to prevent only what is known. This means that unknown threats will evade detection until a patient zero is identified. This legacy approach to threat detection means that at least one organization needs to be ‘patient zero’, or the first victim of a novel attack before it is formally identified.

Even the point solutions that claim to use AI to enhance threat detection rely on a combination of supervised machine learning, deep learning, and transformers to

train and inform their systems. This entails shipping your company’s data out to a large data lake housed somewhere in the cloud where it gets blended with attack data from thousands of other organizations. The resulting homogenized dataset gets used to train AI systems — yours and everyone else’s — to recognize patterns of attack based on previously encountered threats.

While using AI in this way reduces the workload of security teams who would traditionally input this data by hand, it emanates the same risk – namely, that AI systems trained on known threats cannot deal with the threats of tomorrow. Ultimately, it is the unknown threats that bring down an organization.

The promise and pitfalls of XDR in today's threat landscape

Enter Extended Detection and Response (XDR): a platform approach aimed at unifying threat detection across the digital environment. XDR was developed to address the limitations of traditional, fragmented tools by stitching together data across domains, providing SOC teams with a more cohesive, enterprise-wide view of threats. This unified approach allows for improved detection of suspicious activities that might otherwise be missed in siloed systems.

However, XDR solutions still face key challenges: they often depend heavily on human validation, which can aggravate the already alarmingly high alert fatigue security analysts experience, and they remain largely reactive, focusing on detecting and responding to threats rather than helping prevent them. Additionally, XDR frequently lacks full domain coverage, relying on EDR as a foundation and are insufficient in providing native NDR capabilities and visibility, leaving critical gaps that attackers can exploit. This is reflected in the current security market, with 57% of organizations reporting that they plan to integrate network security products into their current XDR toolset[1].

Why settling is risky and how to unlock SOC efficiency

The result of these shortcomings within the security solutions market is an acceptance of inevitable risk. From false positives driving the barrage of alerts, to the siloed tooling that requires manual integration, and the lack of multi-domain visibility requiring human intervention for business context, security teams have accepted that not all alerts can be triaged or investigated.

While prioritization and processes have improved, the SOC is operating under a model that is overrun with alerts that lack context, meaning that not all of them can be investigated because there is simply too much for humans to parse through. Thus, teams accept the risk of leaving many alerts uninvestigated, rather than finding a solution to eliminate that risk altogether.

Darktrace / NETWORK is designed for your Security Operations Center to eliminate alert triage with AI-led investigations , and rapidly detect and respond to known and unknown threats. This includes the ability to scale into other environments in your infrastructure including cloud, OT, and more.

Beyond global threat intelligence: Self-Learning AI enables novel threat detection & response

Darktrace does not rely on known malware signatures, external threat intelligence, historical attack data, nor does it rely on threat trained machine learning to identify threats.

Darktrace’s unique Self-learning AI deeply understands your business environment by analyzing trillions of real-time events that understands your normal ‘pattern of life’, unique to your business. By connecting isolated incidents across your business, including third party alerts and telemetry, Darktrace / NETWORK uses anomaly chains to identify deviations from normal activity.

The benefit to this is that when we are not predefining what we are looking for, we can spot new threats, allowing end users to identify both known threats and subtle, never-before-seen indicators of malicious activity that traditional solutions may miss if they are only looking at historical attack data.

AI-led investigations empower your SOC to prioritize what matters

Anomaly detection is often criticized for yielding high false positives, as it flags deviations from expected patterns that may not necessarily indicate a real threat or issues. However, Darktrace applies an investigation engine to automate alert triage and address alert fatigue.

Darktrace’s Cyber AI Analyst revolutionizes security operations by conducting continuous, full investigations across Darktrace and third-party alerts, transforming the alert triage process. Instead of addressing only a fraction of the thousands of daily alerts, Cyber AI Analyst automatically investigates every relevant alert, freeing up your team to focus on high-priority incidents and close security gaps.

Powered by advanced machine-learning techniques, including unsupervised learning, models trained by expert analysts, and tailored security language models, Cyber AI Analyst emulates human investigation skills, testing hypotheses, analyzing data, and drawing conclusions. According to Darktrace Internal Research, Cyber AI Analyst typically provides a SOC with up to  50,000 additional hours of Level 2 analysis and written reporting annually, enriching security operations by producing high level incident alerts with full details so that human analysts can focus on Level 3 tasks.

Containing threats with Autonomous Response

Simply quarantining a device is rarely the best course of action - organizations need to be able to maintain normal operations in the face of threats and choose the right course of action. Different organizations also require tailored response functions because they have different standards and protocols across a variety of unique devices. Ultimately, a ‘one size fits all’ approach to automated response actions puts organizations at risk of disrupting business operations.

Darktrace’s Autonomous Response tailors its actions to contain abnormal behavior across users and digital assets by understanding what is normal and stopping only what is not. Unlike blanket quarantines, it delivers a bespoke approach, blocking malicious activities that deviate from regular patterns while ensuring legitimate business operations remain uninterrupted.

Darktrace offers fully customizable response actions, seamlessly integrating with your workflows through hundreds of native integrations and an open API. It eliminates the need for costly development, natively disarming threats in seconds while extending capabilities with third-party tools like firewalls, EDR, SOAR, and ITSM solutions.

Unlocking a proactive state of security

Securing the network isn’t just about responding to incidents — it’s about being proactive, adaptive, and prepared for the unexpected. The NIST Cybersecurity Framework (CSF 2.0) emphasizes this by highlighting the need for focused risk management, continuous incident response (IR) refinement, and seamless integration of these processes with your detection and response capabilities.

Despite advancements in security technology, achieving a proactive posture is still a challenge to overcome because SOC teams face inefficiencies from reliance on pattern-matching tools, which generate excessive false positives and leave many alerts unaddressed, while novel threats go undetected. If SOC teams are spending all their time investigating alerts then there is no time spent getting ahead of attacks.

Achieving proactive network resilience — a state where organizations can confidently address challenges at every stage of their security posture — requires strategically aligned solutions that work seamlessly together across the attack lifecycle.

References

1.       Market Guide for Extended Detection and Response, Gartner, 17thAugust 2023 - ID G00761828

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About the author
Mikey Anderson
Product Manager, Network Detection & Response

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January 15, 2025

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Ransomware

RansomHub Ransomware: Darktrace’s Investigation of the Newest Tool in ShadowSyndicate's Arsenal

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What is ShadowSyndicate?

ShadowSyndicate, also known as Infra Storm, is a threat actor reportedly active since July 2022, working with various ransomware groups and affiliates of ransomware programs, such as Quantum, Nokoyawa, and ALPHV. This threat actor employs tools like Cobalt Strike, Sliver, IcedID, and Matanbuchus malware in its attacks. ShadowSyndicate utilizes the same SSH fingerprint (1ca4cbac895fc3bd12417b77fc6ed31d) on many of their servers—85 as of September 2023. At least 52 of these servers have been linked to the Cobalt Strike command and control (C2) framework [1].

What is RansomHub?

First observed following the FBI's takedown of ALPHV/BlackCat in December 2023, RansomHub quickly gained notoriety as a Ransomware-as-a-Service (RaaS) operator. RansomHub capitalized on the law enforcement’s disruption of the LockBit group’s operations in February 2024 to market themselves to potential affiliates who had previously relied on LockBit’s encryptors. RansomHub's success can be largely attributed to their aggressive recruitment on underground forums, leading to the absorption of ex-ALPHV and ex-LockBit affiliates. They were one of the most active ransomware operators in 2024, with approximately 500 victims reported since February, according to their Dedicated Leak Site (DLS) [2].

ShadowSyndicate and RansomHub

External researchers have reported that ShadowSyndicate had as many as seven different ransomware families in their arsenal between July 2022, and September 2023. Now, ShadowSyndicate appears to have added RansomHub’s their formidable stockpile, becoming an affiliate of the RaaS provider [1].

Darktrace’s analysis of ShadowSyndicate across its customer base indicates that the group has been leveraging RansomHub ransomware in multiple attacks in September and October 2024. ShadowSyndicate likely shifted to using RansomHub due to the lucrative rates offered by this RaaS provider, with affiliates receiving up to 90% of the ransom—significantly higher than the general market rate of 70-80% [3].

In many instances where encryption was observed, ransom notes with the naming pattern “README_[a-zA-Z0-9]{6}.txt” were written to affected devices. The content of these ransom notes threatened to release stolen confidential data via RansomHub’s DLS unless a ransom was paid. During these attacks, data exfiltration activity to external endpoints using the SSH protocol was observed. The external endpoints to which the data was transferred were found to coincide with servers previously associated with ShadowSyndicate activity.

Darktrace’s coverage of ShadowSyndicate and RansomHub

Darktrace’s Threat Research team identified high-confidence indicators of compromise (IoCs) linked to the ShadowSyndicate group deploying RansomHub. The investigation revealed four separate incidents impacting Darktrace customers across various sectors, including education, manufacturing, and social services. In the investigated cases, multiple stages of the kill chain were observed, starting with initial internal reconnaissance and leading to eventual file encryption and data exfiltration.

Attack Overview

Timeline attack overview of ransomhub ransomware

Internal Reconnaissance

The first observed stage of ShadowSyndicate attacks involved devices making multiple internal connection attempts to other internal devices over key ports, suggesting network scanning and enumeration activity. In this initial phase of the attack, the threat actor gathers critical details and information by scanning the network for open ports that might be potentially exploitable. In cases observed by Darktrace affected devices were typically seen attempting to connect to other internal locations over TCP ports including 22, 445 and 3389.

C2 Communication and Data Exfiltration

In most of the RansomHub cases investigated by Darktrace, unusual connections to endpoints associated with Splashtop, a remote desktop access software, were observed briefly before outbound SSH connections were identified.

Following this, Darktrace detected outbound SSH connections to the external IP address 46.161.27[.]151 using WinSCP, an open-source SSH client for Windows used for secure file transfer. The Cybersecurity and Infrastructure Security Agency (CISA) identified this IP address as malicious and associated it with ShadowSyndicate’s C2 infrastructure [4]. During connections to this IP, multiple gigabytes of data were exfiltrated from customer networks via SSH.

Data exfiltration attempts were consistent across investigated cases; however, the method of egress varied from one attack to another, as one would expect with a RaaS strain being employed by different affiliates. In addition to transfers to ShadowSyndicate’s infrastructure, threat actors were also observed transferring data to the cloud storage and file transfer service, MEGA, via HTTP connections using the ‘rclone’ user agent – a command-line program used to manage files on cloud storage. In another case, data exfiltration activity occurred over port 443, utilizing SSL connections.

Lateral Movement

In investigated incidents, lateral movement activity began shortly after C2 communications were established. In one case, Darktrace identified the unusual use of a new administrative credential which was quickly followed up with multiple suspicious executable file writes to other internal devices on the network.

The filenames for this executable followed the regex naming convention “[a-zA-Z]{6}.exe”, with two observed examples being “bWqQUx.exe” and “sdtMfs.exe”.

Cyber AI Analyst Investigation Process for the SMB Writes of Suspicious Files to Multiple Devices' incident.
Figure 1: Cyber AI Analyst Investigation Process for the SMB Writes of Suspicious Files to Multiple Devices' incident.

Additionally, script files such as “Defeat-Defender2.bat”, “Share.bat”, and “def.bat” were also seen written over SMB, suggesting that threat actors were trying to evade network defenses and detection by antivirus software like Microsoft Defender.

File Encryption

Among the three cases where file encryption activity was observed, file names were changed by adding an extension following the regex format “.[a-zA-Z0-9]{6}”. Ransom notes with a similar naming convention, “README_[a-zA-Z0-9]{6}.txt”, were written to each share. While the content of the ransom notes differed slightly in each case, most contained similar text. Clear indicators in the body of the ransom notes pointed to the use of RansomHub ransomware in these attacks. As is increasingly the case, threat actors employed double extortion tactics, threatening to leak confidential data if the ransom was not paid. Like most ransomware, RansomHub included TOR site links for communication between its "customer service team" and the target.

Figure 2: The graph shows the behavior of a device with encryption activity, using the “SMB Sustained Mimetype Conversion” and “Unusual Activity Events” metrics over three weeks.

Since Darktrace’s Autonomous Response capability was not enabled during the compromise, the ransomware attack succeeded in its objective. However, Darktrace’s Cyber AI Analyst provided comprehensive coverage of the kill chain, enabling the customer to quickly identify affected devices and initiate remediation.

Figure 3: Cyber AI Analyst panel showing the critical incidents of the affected device from one of the cases investigated.

In lieu of Autonomous Response being active on the networks, Darktrace was able to suggest a variety of manual response actions intended to contain the compromise and prevent further malicious activity. Had Autonomous Response been enabled at the time of the attack, these actions would have been quickly applied without any human interaction, potentially halting the ransomware attack earlier in the kill chain.

Figure 4: A list of suggested Autonomous Response actions on the affected devices."

Conclusion

The Darktrace Threat Research team has noted a surge in attacks by the ShadowSyndicate group using RansomHub’s RaaS of late. RaaS has become increasingly popular across the threat landscape due to its ease of access to malware and script execution. As more individual threat actors adopt RaaS, security teams are struggling to defend against the increasing number of opportunistic attacks.

For customers subscribed to Darktrace’s Security Operations Center (SOC) services, the Analyst team promptly investigated detections of the aforementioned unusual and anomalous activities in the initial infection phases. Multiple alerts were raised via Darktrace’s Managed Threat Detection to warn customers of active ransomware incidents. By emphasizing anomaly-based detection and response, Darktrace can effectively identify devices affected by ransomware and take action against emerging activity, minimizing disruption and impact on customer networks.

Credit to Kwa Qing Hong (Senior Cyber Analyst and Deputy Analyst Team Lead, Singapore) and Signe Zahark (Principal Cyber Analyst, Japan)

Appendices

Darktrace Model Detections

Antigena Models / Autonomous Response:

Antigena / Network / Insider Threat / Antigena Network Scan Block

Antigena / Network / Insider Threat / Antigena SMB Enumeration Block

Antigena / Network / Insider Threat / Antigena Internal Anomalous File Activity

Antigena / Network / Insider Threat / Antigena Large Data Volume Outbound Block

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

Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block

Antigena / Network / Significant Anomaly / Antigena Controlled and Model Breach

Antigena / Network / Significant Anomaly / Antigena Significant Server Anomaly Block

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

Antigena / Network / External Threat / Antigena Suspicious Activity Block

Antigena / Network / External Threat / Antigena Suspicious File Pattern of Life Block

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


Network Reconnaissance:

Device / Network Scan

Device / ICMP Address Scan

Device / RDP Scan
Device / Anomalous LDAP Root Searches
Anomalous Connection / SMB Enumeration
Device / Spike in LDAP Activity

C2:

Enhanced Monitoring - Device / Lateral Movement and C2 Activity

Enhanced Monitoring - Device / Initial Breach Chain Compromise

Enhanced Monitoring - Compromise / Suspicious File and C2

Compliance / Remote Management Tool On Server

Anomalous Connection / Outbound SSH to Unusual Port


External Data Transfer:

Enhanced Monitoring - Unusual Activity / Enhanced Unusual External Data Transfer

Unusual Activity / Unusual External Data Transfer

Anomalous Connection / Data Sent to Rare Domain

Unusual Activity / Unusual External Data to New Endpoint

Compliance / SSH to Rare External Destination

Anomalous Connection / Application Protocol on Uncommon Port

Enhanced Monitoring - Anomalous File / Numeric File Download

Anomalous File / New User Agent Followed By Numeric File Download

Anomalous Server Activity / Outgoing from Server

Device / Large Number of Connections to New Endpoints

Anomalous Connection / Multiple HTTP POSTs to Rare Hostname

Anomalous Connection / Uncommon 1 GiB Outbound

Lateral Movement:

User / New Admin Credentials on Server

Anomalous Connection / New or Uncommon Service Control

Anomalous Connection / High Volume of New or Uncommon Service Control

Anomalous File / Internal / Executable Uploaded to DC

Anomalous Connection / Suspicious Activity On High Risk Device

File Encryption:

Compliance / SMB Drive Write

Anomalous File / Internal / Additional Extension Appended to SMB File

Compromise / Ransomware / Possible Ransom Note Write

Anomalous Connection / Suspicious Read Write Ratio

List of Indicators of Compromise (IoCs)

IoC - Type - Description + Confidence

83.97.73[.]198 - IP - Data exfiltration endpoint

108.181.182[.]143 - IP - Data exfiltration endpoint

46.161.27[.]151 - IP - Data exfiltration endpoint

185.65.212[.]164 - IP - Data exfiltration endpoint

66[.]203.125.21 - IP - MEGA endpoint used for data exfiltration

89[.]44.168.207 - IP - MEGA endpoint used for data exfiltration

185[.]206.24.31 - IP - MEGA endpoint used for data exfiltration

31[.]216.148.33 - IP - MEGA endpoint used for data exfiltration

104.226.39[.]18 - IP - C2 endpoint

103.253.40[.]87 - IP - C2 endpoint

*.relay.splashtop[.]com - Hostname - C2 & data exfiltration endpoint

gfs***n***.userstorage.mega[.]co.nz - Hostname - MEGA endpoint used for data exfiltration

w.api.mega[.]co.nz - Hostname - MEGA endpoint used for data exfiltration

ams-rb9a-ss.ams.efscloud[.]net - Hostname - Data exfiltration endpoint

MITRE ATT&CK Mapping

Tactic - Technqiue

RECONNAISSANCE – T1592.004 Client Configurations

RECONNAISSANCE – T1590.005 IP Addresses

RECONNAISSANCE – T1595.001 Scanning IP Blocks

RECONNAISSANCE – T1595.002 Vulnerability Scanning

DISCOVERY – T1046 Network Service Scanning

DISCOVERY – T1018 Remote System Discovery

DISCOVERY – T1083 File and Directory Discovery
INITIAL ACCESS - T1189 Drive-by Compromise

INITIAL ACCESS - T1190 Exploit Public-Facing Application

COMMAND AND CONTROL - T1001 Data Obfuscation

COMMAND AND CONTROL - T1071 Application Layer Protocol

COMMAND AND CONTROL - T1071.001 Web Protocols

COMMAND AND CONTROL - T1573.001 Symmetric Cryptography

COMMAND AND CONTROL - T1571 Non-Standard Port

DEFENSE EVASION – T1078 Valid Accounts

DEFENSE EVASION – T1550.002 Pass the Hash

LATERAL MOVEMENT - T1021.004 SSH

LATERAL MOVEMENT – T1080 Taint Shared Content

LATERAL MOVEMENT – T1570 Lateral Tool Transfer

LATERAL MOVEMENT – T1021.002 SMB/Windows Admin Shares

COLLECTION - T1185 Man in the Browser

EXFILTRATION - T1041 Exfiltration Over C2 Channel

EXFILTRATION - T1567.002 Exfiltration to Cloud Storage

EXFILTRATION - T1029 Scheduled Transfer

IMPACT – T1486 Data Encrypted for Impact

References

1.     https://www.group-ib.com/blog/shadowsyndicate-raas/

2.     https://www.techtarget.com/searchsecurity/news/366617096/ESET-RansomHub-most-active-ransomware-group-in-H2-2024

3.     https://cyberint.com/blog/research/ransomhub-the-new-kid-on-the-block-to-know/

4.     https://www.cisa.gov/sites/default/files/2024-05/AA24-131A.stix_.xml

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About the author
Qing Hong Kwa
Senior Cyber Analyst and Deputy Analyst Team Lead, Singapore
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