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July 4, 2024

A Busy Agenda: Darktrace’s Detection of Qilin Ransomware-as-a-Service Operator

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04
Jul 2024
This blog examines the tactics, techniques and procedures associated with the notorious Ransomware-as-a-Service operator Qilin. Darktrace’s Threat Research team investigated several examples of Qilin actors targeting Darktrace customers between 2022 and 2024.

Qilin ransomware has recently dominated discussions across the cyber security landscape following its deployment in an attack on Synnovis, a UK-based medical laboratory company. The ransomware attack ultimately affected patient services at multiple National Health Service (NHS) hospitals that rely on Synnovis diagnostic and pathology services. Qilin’s origins, however, date back further to October 2022 when the group was observed seemingly posting leaked data from its first known victim on its Dedicated Leak Site (DLS) under the name Agenda[1].

The Darktrace Threat Research team investigated network artifacts related to Qilin and identified three probable cases of the ransomware across the Darktrace customer base between June 2022 and May 2024.

Qilin Ransomware-as-a-Service Operator

Qilin operates as a Ransomware-as-a-Service (RaaS) that employs double extortion tactics, whereby harvested data is exfiltrated and threatened of publication on the group's DLS, which is hosted on Tor. Qilin ransomware has samples written in both the Golang and Rust programming languages, making it compilable with various operating systems, and is highly customizable. When building Qilin ransomware variants to be used on their target(s), affiliates can configure settings such as the encryption mode (i.e., skip-step, percent, and speed), the file extension being appended, files, extensions and directories to be skipped during the encryption, and the processes and services to be terminated, among others[1] [2].  

Trend Micro analysts, who were the first to discover Qilin samples in August 2022, when the name "Agenda" was still used in ransom notes, found that each analyzed sample was customized for the intended victims and that "unique company IDs were used as extensions of encrypted files" [3]. This information is configurable from within the Qilin's affiliate panel's 'Targets' section, shown below. The panel's background image features the eponym Chinese legendary chimerical creature Qilin (pronounced “Ke Lin”). Despite this Chinese mythology reference, Russian language was observed being used by a Qilin operator in an underground forum post aimed at hiring affiliates and advertising their RaaS operation[2].

Figure 1: Qilin ransomware’s affiliate panel.

Qilin's RaaS program purportedly has an attractive affiliates' payment structure, with affiliates allegedly able to earn 80% of ransom payments of USD 3m or less and 85% for payments above that figure[2], making it a possibly appealing option in the RaaS ecosystem.  Publication of stolen data and ransom payment negotiations are purportedly handled by Qilin operators. Qilin affiliates have been known to target companies located around the world and within a variety of industries, including critical sectors such as healthcare and energy.

As Qilin is a RaaS operation, the choice of targets does not necessarily reflect Qilin operators' intentions, but rather that of its affiliates.  Similarly, the tactics, techniques, procedures (TTPs) and indicators of compromise (IoC) identified by Darktrace are associated with the given affiliate deploying Qilin ransomware for their own purpose, rather than TTPs and IoCs of the Qilin group. Likewise, initial vectors of infection may vary from affiliate to affiliate. Previous studies show that initial access to networks were gained via spear phishing emails or by leveraging exposed applications and interfaces.

Differences have been observed in terms of data exfiltration and potential C2 external endpoints, suggesting the below investigations are not all related to the same group or actor(s).

Darktrace’s Threat Research Investigation

June 2022

Darktrace first detected an instance of Qilin ransomware back in June 2022, when an attacker was observed successfully accessing a customer’s Virtual Private Network (VPN) and compromising an administrative account, before using RDP to gain access to the customer’s Microsoft System Center Configuration Manager (SCCM) server

From there, an attack against the customer's VMware ESXi hosts was launched. Fortunately, a reboot of their virtual machines (VM) caught the attention of the security team who further uncovered that custom profiles had been created and remote scripts executed to change root passwords on their VM hosts. Three accounts were found to have been compromised and three systems encrypted by ransomware.  

Unfortunately, Darktrace was not configured to monitor the affected subnets at the time of the attack. Despite this, the customer was able to work directly with Darktrace analysts via the Ask the Expert (ATE) service to add the subnets in question to Darktrace’s visibility, allowing it to monitor for any further unusual behavior.

Once visibility over the compromised SCCM server was established, Darktrace observed a series of unusual network scanning activities and the use of Kali (a Linux distribution designed for digital forensics and penetration testing). Furthermore, the server was observed making connections to multiple rare external hosts, many using the “[.]ru” Top Level Domain (TLD). One of the external destinations the server was attempting to connect was found to be related to SystemBC, a malware that turns infected hosts into SOCKS5 proxy bots and provides command-and-control (C2) functionality.

Additionally, the server was observed making external connections over ports 993 and 143 (typically associated with the use of the Interactive Message Access Protocol (IMAP) to multiple rare external endpoints. This was likely due to the presence of Tofsee malware on the device.

After the compromise had been contained, Darktrace identified several ransom notes following the naming convention “README-RECOVER-<extension/company_id>.txt”” on the network. This naming convention, as well as the similar “<company_id>-RECOVER-README.txt” have been referenced by open-source intelligence (OSINT) providers as associated with Qilin ransom notes[5] [6] [7].

April 2023

The next case of Qilin ransomware observed by Darktrace took place in April 2023 on the network of a customer in the manufacturing sector in APAC. Unfortunately for the customer in this instance, Darktrace's Autonomous Response was not active on their environment and no autonomous actions were taken to contain the compromise.

Over the course of two days, Darktrace identified a wide range of malicious activity ranging from extensive initial scanning and lateral movement attempts to the writing of ransom notes that followed the aforementioned naming convention (i.e., “README-RECOVER-<extension/company_id>.txt”).

Darktrace observed two affected devices attempting to move laterally through the SMB, DCE-RPC and RDP network protocols. Default credentials (e.g., UserName, admin, administrator) were also observed in the large volumes of SMB sessions initiated by these devices. One of the target devices of these SMB connections was a domain controller, which was subsequently seen making suspicious WMI requests to multiple devices over DCE-RPC and enumerating SMB shares by binding to the ‘server service’ (srvsvc) named pipe to a high number of internal devices within a short time frame. The domain controller was further detected establishing an anomalously high number of connections to several internal devices, notably using the RDP administrative protocol via a default admin cookie.  

Repeated connections over the HTTP and SSL protocol to multiple newly observed IPs located in the 184.168.123.0/24 range were observed, indicating C2 connectivity.  WebDAV user agent and a JA3 fingerprint potentially associated with Cobalt Strike were notably observed in these connections. A few hours later, Darktrace detected additional suspicious external connections, this time to IPs associated with the MEGA cloud storage solution. Storage solutions such as MEGA are often abused by attackers to host stolen data post exfiltration. In this case, the endpoints were all rare for the network, suggesting this solution was not commonly used by legitimate users. Around 30 GB of data was exfiltrated over the SSL protocol.

Darktrace did not observe any encryption-related activity on this customer’s network, suggesting that encryption may have taken place locally or within network segments not monitored by Darktrace.

May 2024

The most recent instance of Qilin observed by Darktrace took place in May 2024 and involved a customer in the US. In this case, Darktrace initially detected affected devices using unusual administrative and default credentials, before additional internal systems were observed making extensive suspicious DCE-RPC requests to a range of internal locations, performing network scanning, making unusual internal RDP connections, and transferring suspicious executable files like 'a157496.exe' and '83b87b2.exe'.  SMB writes of the file "LSM_API_service" were also observed, activity which was considered 100% unusual by Darktrace; this is an RPC service that can be abused to enumerate logged-in users and steal their tokens. Various repeated connections likely representative of C2 communications were detected via both HTTP and SSL to rare external endpoints linked in OSINT to Cobalt Strike use. During these connections, HTTP GET requests for the following URIs were observed:

/asdffHTTPS

/asdfgdf

/asdfgHTTP

/download/sihost64.dll

Notably, this included a GET request a DLL file named "sihost64.dll" from a domain controller using PowerShell.  

Over 102 GB of data may have been transferred to another previously unseen endpoint, 194.165.16[.]13, via the unencrypted File Transfer Protocol (FTP). Additionally, many non-FTP connections to the endpoint could be observed, over which more than 783 GB of data was exfiltrated. Regarding file encryption activity, a wide range of destination devices and shares were targeted.

Figure 2: Advanced Search graph displaying the total volume of data transferred over FTP to a malicious IP.

During investigations, Darktrace’s Threat Research team identified an additional customer, also based in the United States, where similar data exfiltration activity was observed in April 2024. Although no indications of ransomware encryption were detected on the network, multiple similarities were observed with the case discussed just prior. Notably, the same exfiltration IP and protocol (194.165.16[.]13 and FTP, respectively) were identified in both cases. Additional HTTP connectivity was further observed to another IP using a self-signed certificate (i.e., CN=ne[.]com,OU=key operations,O=1000,L=,ST=,C=KM) located within the same ASN (i.e., AS48721 Flyservers S.A.). Some of the URIs seen in the GET requests made to this endpoint were the same as identified in that same previous case.

Information regarding another device also making repeated connections to the same IP was described in the second event of the same Cyber AI Analyst incident. Following this C2 connectivity, network scanning was observed from a compromised domain controller, followed by additional reconnaissance and lateral movement over the DCE-RPC and SMB protocols. Darktrace again observed SMB writes of the file "LSM_API_service", as in the previous case, activity which was also considered 100% unusual for the network. These similarities suggest the same actor or affiliate may have been responsible for activity observed, even though no encryption was observed in the latter case.

Figure 3: First event of the Cyber AI Analyst investigation following the compromise activity.

According to researchers at Microsoft, some of the IoCs observed on both affected accounts are associated with Pistachio Tempest, a threat actor reportedly associated with ransomware distribution. The Microsoft threat actor naming convention uses the term "tempest" to reference criminal organizations with motivations of financial gain that are not associated with high confidence to a known non-nation state or commercial entity. While Pistachio Tempest’s TTPs have changed over time, their key elements still involve ransomware, exfiltration, and extortion. Once they've gained access to an environment, Pistachio Tempest typically utilizes additional tools to complement their use of Cobalt Strike; this includes the use of the SystemBC RAT and the SliverC2 framework, respectively. It has also been reported that Pistacho Tempest has experimented with various RaaS offerings, which recently included Qilin ransomware[4].

Conclusion

Qilin is a RaaS group that has gained notoriety recently due to high-profile attacks perpetrated by its affiliates. Despite this, the group likely includes affiliates and actors who were previously associated with other ransomware groups. These individuals bring their own modus operandi and utilize both known and novel TTPs and IoCs that differ from one attack to another.

Darktrace’s anomaly-based technology is inherently threat-agnostic, treating all RaaS variants equally regardless of the attackers’ tools and infrastructure. Deviations from a device’s ‘learned’ pattern of behavior during an attack enable Darktrace to detect and contain potentially disruptive ransomware attacks.

Credit to: Alexandra Sentenac, Emma Foulger, Justin Torres, Min Kim, Signe Zaharka for their contributions.

References

[1] https://www.sentinelone.com/anthology/agenda-qilin/  

[2] https://www.group-ib.com/blog/qilin-ransomware/

[3] https://www.trendmicro.com/en_us/research/22/h/new-golang-ransomware-agenda-customizes-attacks.html

[4] https://www.microsoft.com/en-us/security/security-insider/pistachio-tempest

[5] https://www.trendmicro.com/en_us/research/22/h/new-golang-ransomware-agenda-customizes-attacks.html

[6] https://www.bleepingcomputer.com/forums/t/790240/agenda-qilin-ransomware-id-random-10-char;-recover-readmetxt-support/

[7] https://github.com/threatlabz/ransomware_notes/tree/main/qilin

Darktrace Model Detections

Internal Reconnaissance

Device / Suspicious SMB Scanning Activity

Device / Network Scan

Device / RDP Scan

Device / ICMP Address Scan

Device / Suspicious Network Scan Activity

Anomalous Connection / SMB Enumeration

Device / New or Uncommon WMI Activity

Device / Attack and Recon Tools

Lateral Movement

Device / SMB Session Brute Force (Admin)

Device / Large Number of Model Breaches from Critical Network Device

Device / Multiple Lateral Movement Model Breaches

Anomalous Connection / Unusual Admin RDP Session

Device / SMB Lateral Movement

Compliance / SMB Drive Write

Anomalous Connection / New or Uncommon Service Control

Anomalous Connection / Anomalous DRSGetNCChanges Operation

Anomalous Server Activity / Domain Controller Initiated to Client

User / New Admin Credentials on Client

C2 Communication

Anomalous Server Activity / Outgoing from Server

Anomalous Connection / Multiple Connections to New External TCP Port

Anomalous Connection / Anomalous SSL without SNI to New External

Anomalous Connection / Rare External SSL Self-Signed

Device / Increased External Connectivity

Unusual Activity / Unusual External Activity

Compromise / New or Repeated to Unusual SSL Port

Anomalous Connection / Multiple Failed Connections to Rare Endpoint

Device / Suspicious Domain

Device / Increased External Connectivity

Compromise / Sustained SSL or HTTP Increase

Compromise / Botnet C2 Behaviour

Anomalous Connection / POST to PHP on New External Host

Anomalous Connection / Multiple HTTP POSTs to Rare Hostname

Anomalous File / EXE from Rare External Location

Exfiltration

Unusual Activity / Enhanced Unusual External Data Transfer

Anomalous Connection / Data Sent to Rare Domain

Unusual Activity / Unusual External Data Transfer

Anomalous Connection / Uncommon 1 GiB Outbound

Unusual Activity / Unusual External Data to New Endpoint

Compliance / FTP / Unusual Outbound FTP

File Encryption

Compromise / Ransomware / Suspicious SMB Activity

Anomalous Connection / Sustained MIME Type Conversion

Anomalous File / Internal / Additional Extension Appended to SMB File

Compromise / Ransomware / Possible Ransom Note Write

Compromise / Ransomware / Possible Ransom Note Read

Anomalous Connection / Suspicious Read Write Ratio

IoC List

IoC – Type – Description + Confidence

93.115.25[.]139 IP C2 Server, likely associated with SystemBC

194.165.16[.]13 IP Probable Exfiltration Server

91.238.181[.]230 IP C2 Server, likely associated with Cobalt Strike

ikea0[.]com Hostname C2 Server, likely associated with Cobalt Strike

lebondogicoin[.]com Hostname C2 Server, likely associated with Cobalt Strike

184.168.123[.]220 IP Possible C2 Infrastructure

184.168.123[.]219 IP Possible C2 Infrastructure

184.168.123[.]236 IP Possible C2 Infrastructure

184.168.123[.]241 IP Possible C2 Infrastructure

184.168.123[.]247 IP Possible C2 Infrastructure

184.168.123[.]251 IP Possible C2 Infrastructure

184.168.123[.]252 IP Possible C2 Infrastructure

184.168.123[.]229 IP Possible C2 Infrastructure

184.168.123[.]246 IP Possible C2 Infrastructure

184.168.123[.]230 IP Possible C2 Infrastructure

gfs440n010.userstorage.me ga.co[.]nz Hostname Possible Exfiltration Server. Not inherently malicious; associated with MEGA file storage.

gfs440n010.userstorage.me ga.co[.]nz Hostname Possible Exfiltration Server. Not inherently malicious; associated with MEGA file storage.

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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Alexandra Sentenac
Cyber Analyst
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March 18, 2025

Survey findings: How is AI Impacting the SOC?

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There’s no question that AI is already impacting the SOC – augmenting, assisting, and filling the gaps left by staff and skills shortages. We surveyed over 1,500 cybersecurity professionals from around the world to uncover their attitudes to AI cybersecurity in 2025. Our findings revealed striking trends in how AI is changing the way security leaders think about hiring and SOC transformation. Download the full report for the big picture, available now.

Download the full report to explore these findings in depth

The AI-human conundrum

Let’s start with some context. As the cybersecurity sector has rapidly evolved to integrate AI into all elements of cyber defense, the pace of technological advancement is outstripping the development of necessary skills. Given the ongoing challenges in security operations, such as employee burnout, high turnover rates, and talent shortages, recruiting personnel to bridge these skills gaps remains an immense challenge in today’s landscape.

But here, our main findings on this topic seem to contradict each other.

There’s no question over the impact of AI-powered threats – nearly three-quarters (74%) agree that AI-powered threats now pose a significant challenge for their organization.  

When we look at how security leaders are defending against AI-powered threats, over 3 out of 5 (62%) see insufficient personnel to manage tools and alerts as the biggest barrier.  

Yet at the same time, increasing cyber security staff is at the bottom of the priority list for survey participants, with only 11% planning to increase cybersecurity staff in 2025 – less than in 2024. What 64% of stakeholders are committed to, however, is adding new AI-powered tools onto their existing security stacks.

The conclusion? Due to pressures around hiring, defensive AI is becoming integral to the SOC as a means of augmenting understaffed teams.

How is AI plugging skills shortages in the SOC?

As explored in our recent white paper, the CISO’s Guide to Navigating the Cybersecurity Skills Shortage, 71% of organizations report unfilled cybersecurity positions, leading to the estimation that less than 10% of alerts are thoroughly vetted. In this scenario, AI has become an essential multiplier to relieve the burden on security teams.

95% of respondents agree that AI-powered solutions can significantly improve the speed and efficiency of their defenses. But how?

The area security leaders expect defensive AI to have the biggest impact is on improving threat detection, followed by autonomous response to threats and identifying exploitable vulnerabilities.

Interestingly, the areas that participants ranked less highly (reducing alert fatigue and running phishing simulation), are the tasks that AI already does well and can therefore be used already to relieve the burden of manual, repetitive work on the SOC.

Different perspectives from different sides of the SOC

CISOs and SecOps teams aren’t necessarily aligned on the AI defense question – while CISOs tend to see it as a strategic game-changer, SecOps teams on the front lines may be more sceptical, wary of its real-world reliability and integration into workflows.  

From the data, we see that while less than a quarter of execs doubt that AI-powered solutions will block and automatically respond to AI threats, about half of SecOps aren’t convinced. And only 17% of CISOs lack confidence in the ability of their teams to implement and use AI-powered solutions, whereas over 40% those in the team doubt their own ability to do so.

This gap feeds into the enthusiasm that executives share about adding AI-driven tools into the stack, while day-to-day users of the tools are more interested in improving security awareness training and improving cybersecurity tool integration.

Levels of AI understanding in the SOC

AI is only as powerful as the people who use it, and levels of AI expertise in the SOC can make or break its real-world impact. If security leaders want to unlock AI’s full potential, they must bridge the knowledge gap—ensuring teams understand not just the different types of AI, but where it can be applied for maximum value.

Only 42% of security professionals are confident that they fully understand all the types of AI in their organization’s security stack.

This data varies between job roles – executives report higher levels of understanding (60% say they know exactly which types of AI are being used) than participants in other roles. Despite having a working knowledge of using the tools day-to-day, SecOps practitioners were more likely to report having a “reasonable understanding” of the types of AI in use in their organization (42%).  

Whether this reflects a general confidence in executives rather than technical proficiency it’s hard to say, but it speaks to the importance of AI-human collaboration – introducing AI tools for cybersecurity to plug the gaps in human teams will only be effective if security professionals are supported with the correct education and training.  

Download the full report to explore these findings in depth

The full report for Darktrace’s State of AI Cybersecurity is out now. Download the paper to dig deeper into these trends, and see how results differ by industry, region, organization size, and job title.  

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March 18, 2025

Darktrace's Detection of State-Linked ShadowPad Malware

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An integral part of cybersecurity is anomaly detection, which involves identifying unusual patterns or behaviors in network traffic that could indicate malicious activity, such as a cyber-based intrusion. However, attribution remains one of the ever present challenges in cybersecurity. Attribution involves the process of accurately identifying and tracing the source to a specific threat actor(s).

Given the complexity of digital networks and the sophistication of attackers who often use proxies or other methods to disguise their origin, pinpointing the exact source of a cyberattack is an arduous task. Threat actors can use proxy servers, botnets, sophisticated techniques, false flags, etc. Darktrace’s strategy is rooted in the belief that identifying behavioral anomalies is crucial for identifying both known and novel threat actor campaigns.

The ShadowPad cluster

Between July 2024 and November 2024, Darktrace observed a cluster of activity threads sharing notable similarities. The threads began with a malicious actor using compromised user credentials to log in to the target organization's Check Point Remote Access virtual private network (VPN) from an attacker-controlled, remote device named 'DESKTOP-O82ILGG'.  In one case, the IP from which the initial login was carried out was observed to be the ExpressVPN IP address, 194.5.83[.]25. After logging in, the actor gained access to service account credentials, likely via exploitation of an information disclosure vulnerability affecting Check Point Security Gateway devices. Recent reporting suggests this could represent exploitation of CVE-2024-24919 [27,28]. The actor then used these compromised service account credentials to move laterally over RDP and SMB, with files related to the modular backdoor, ShadowPad, being delivered to the  ‘C:\PerfLogs\’ directory of targeted internal systems. ShadowPad was seen communicating with its command-and-control (C2) infrastructure, 158.247.199[.]185 (dscriy.chtq[.]net), via both HTTPS traffic and DNS tunneling, with subdomains of the domain ‘cybaq.chtq[.]net’ being used in the compromised devices’ TXT DNS queries.

Darktrace’s Advanced Search data showing the VPN-connected device initiating RDP connections to a domain controller (DC). The device subsequently distributes likely ShadowPad-related payloads and makes DRSGetNCChanges requests to a second DC.
Figure 1: Darktrace’s Advanced Search data showing the VPN-connected device initiating RDP connections to a domain controller (DC). The device subsequently distributes likely ShadowPad-related payloads and makes DRSGetNCChanges requests to a second DC.
Event Log data showing a DC making DNS queries for subdomains of ‘cbaq.chtq[.]net’ to 158.247.199[.]185 after receiving SMB and RDP connections from the VPN-connected device, DESKTOP-O82ILGG.
Figure 2: Event Log data showing a DC making DNS queries for subdomains of ‘cbaq.chtq[.]net’ to 158.247.199[.]185 after receiving SMB and RDP connections from the VPN-connected device, DESKTOP-O82ILGG.

Darktrace observed these ShadowPad activity threads within the networks of European-based customers in the manufacturing and financial sectors.  One of these intrusions was followed a few months later by likely state-sponsored espionage activity, as detailed in the investigation of the year in Darktrace’s Annual Threat Report 2024.

Related ShadowPad activity

Additional cases of ShadowPad were observed across Darktrace’s customer base in 2024. In some cases, common C2 infrastructure with the cluster discussed above was observed, with dscriy.chtq[.]net and cybaq.chtq[.]net both involved; however, no other common features were identified. These ShadowPad infections were observed between April and November 2024, with customers across multiple regions and sectors affected.  Darktrace’s observations align with multiple other public reports that fit the timeframe of this campaign.

Darktrace has also observed other cases of ShadowPad without common infrastructure since September 2024, suggesting the use of this tool by additional threat actors.

The data theft thread

One of the Darktrace customers impacted by the ShadowPad cluster highlighted above was a European manufacturer. A distinct thread of activity occurred within this organization’s network several months after the ShadowPad intrusion, in October 2024.

The thread involved the internal distribution of highly masqueraded executable files via Sever Message Block (SMB) and WMI (Windows Management Instrumentation), the targeted collection of sensitive information from an internal server, and the exfiltration of collected information to a web of likely compromised sites. This observed thread of activity, therefore, consisted of three phrases: lateral movement, collection, and exfiltration.

The lateral movement phase began when an internal user device used an administrative credential to distribute files named ‘ProgramData\Oracle\java.log’ and 'ProgramData\Oracle\duxwfnfo' to the c$ share on another internal system.  

Darktrace model alert highlighting an SMB write of a file named ‘ProgramData\Oracle\java.log’ to the c$ share on another device.
Figure 3: Darktrace model alert highlighting an SMB write of a file named ‘ProgramData\Oracle\java.log’ to the c$ share on another device.

Over the next few days, Darktrace detected several other internal systems using administrative credentials to upload files with the following names to the c$ share on internal systems:

ProgramData\Adobe\ARM\webservices.dll

ProgramData\Adobe\ARM\wksprt.exe

ProgramData\Oracle\Java\wksprt.exe

ProgramData\Oracle\Java\webservices.dll

ProgramData\Microsoft\DRM\wksprt.exe

ProgramData\Microsoft\DRM\webservices.dll

ProgramData\Abletech\Client\webservices.dll

ProgramData\Abletech\Client\client.exe

ProgramData\Adobe\ARM\rzrmxrwfvp

ProgramData\3Dconnexion\3DxWare\3DxWare.exe

ProgramData\3Dconnexion\3DxWare\webservices.dll

ProgramData\IDMComp\UltraCompare\updater.exe

ProgramData\IDMComp\UltraCompare\webservices.dll

ProgramData\IDMComp\UltraCompare\imtrqjsaqmm

Cyber AI Analyst highlighting an SMB write of a file named ‘ProgramData\Adobe\ARM\webservices.dll’ to the c$ share on an internal system.
Figure 4: Cyber AI Analyst highlighting an SMB write of a file named ‘ProgramData\Adobe\ARM\webservices.dll’ to the c$ share on an internal system.

The threat actor appears to have abused the Microsoft RPC (MS-RPC) service, WMI, to execute distributed payloads, as evidenced by the ExecMethod requests to the IWbemServices RPC interface which immediately followed devices’ SMB uploads.  

Cyber AI Analyst data highlighting a thread of activity starting with an SMB data upload followed by ExecMethod requests.
Figure 5: Cyber AI Analyst data highlighting a thread of activity starting with an SMB data upload followed by ExecMethod requests.

Several of the devices involved in these lateral movement activities, both on the source and destination side, were subsequently seen using administrative credentials to download tens of GBs of sensitive data over SMB from a specially selected server.  The data gathering stage of the threat sequence indicates that the threat actor had a comprehensive understanding of the organization’s system architecture and had precise objectives for the information they sought to extract.

Immediately after collecting data from the targeted server, devices went on to exfiltrate stolen data to multiple sites. Several other likely compromised sites appear to have been used as general C2 infrastructure for this intrusion activity. The sites used by the threat actor for C2 and data exfiltration purport to be sites for companies offering a variety of service, ranging from consultancy to web design.

Screenshot of one of the likely compromised sites used in the intrusion. 
Figure 6: Screenshot of one of the likely compromised sites used in the intrusion.

At least 16 sites were identified as being likely data exfiltration or C2 sites used by this threat actor in their operation against this organization. The fact that the actor had such a wide web of compromised sites at their disposal suggests that they were well-resourced and highly prepared.  

Darktrace model alert highlighting an internal device slowly exfiltrating data to the external endpoint, yasuconsulting[.]com.
Figure 7: Darktrace model alert highlighting an internal device slowly exfiltrating data to the external endpoint, yasuconsulting[.]com.
Darktrace model alert highlighting an internal device downloading nearly 1 GB of data from an internal system just before uploading a similar volume of data to another suspicious endpoint, www.tunemmuhendislik[.]com    
Figure 8: Darktrace model alert highlighting an internal device downloading nearly 1 GB of data from an internal system just before uploading a similar volume of data to another suspicious endpoint, www.tunemmuhendislik[.]com  

Cyber AI Analyst spotlight

Cyber AI Analyst identifying and piecing together the various steps of a ShadowPad intrusion.
Figure 9: Cyber AI Analyst identifying and piecing together the various steps of a ShadowPad intrusion.  
Cyber AI Analyst Incident identifying and piecing together the various steps of the data theft activity.
Figure 10: Cyber AI Analyst Incident identifying and piecing together the various steps of the data theft activity.

As shown in the above figures, Cyber AI Analyst’s ability to thread together the different steps of these attack chains are worth highlighting.

In the ShadowPad attack chains, Cyber AI Analyst was able to identify SMB writes from the VPN subnet to the DC, and the C2 connections from the DC. It was also able to weave together this activity into a single thread representing the attacker’s progression.

Similarly, in the data exfiltration attack chain, Cyber AI Analyst identified and connected multiple types of lateral movement over SMB and WMI and external C2 communication to various external endpoints, linking them in a single, connected incident.

These Cyber AI Analyst actions enabled a quicker understanding of the threat actor sequence of events and, in some cases, faster containment.

Attribution puzzle

Publicly shared research into ShadowPad indicates that it is predominantly used as a backdoor in People’s Republic of China (PRC)-sponsored espionage operations [5][6][7][8][9][10]. Most publicly reported intrusions involving ShadowPad  are attributed to the China-based threat actor, APT41 [11][12]. Furthermore, Google Threat Intelligence Group (GTIG) recently shared their assessment that ShadowPad usage is restricted to clusters associated with APT41 [13]. Interestingly, however, there have also been public reports of ShadowPad usage in unattributed intrusions [5].

The data theft activity that later occurred in the same Darktrace customer network as one of these ShadowPad compromises appeared to be the targeted collection and exfiltration of sensitive data. Such an objective indicates the activity may have been part of a state-sponsored operation. The tactics, techniques, and procedures (TTPs), artifacts, and C2 infrastructure observed in the data theft thread appear to resemble activity seen in previous Democratic People’s Republic of Korea (DPRK)-linked intrusion activities [15] [16] [17] [18] [19].

The distribution of payloads to the following directory locations appears to be a relatively common behavior in DPRK-sponsored intrusions.

Observed examples:

C:\ProgramData\Oracle\Java\  

C:\ProgramData\Adobe\ARM\  

C:\ProgramData\Microsoft\DRM\  

C:\ProgramData\Abletech\Client\  

C:\ProgramData\IDMComp\UltraCompare\  

C:\ProgramData\3Dconnexion\3DxWare\

Additionally, the likely compromised websites observed in the data theft thread, along with some of the target URI patterns seen in the C2 communications to these sites, resemble those seen in previously reported DPRK-linked intrusion activities.

No clear evidence was found to link the ShadowPad compromise to the subsequent data theft activity that was observed on the network of the manufacturing customer. It should be noted, however, that no clear signs of initial access were found for the data theft thread – this could suggest the ShadowPad intrusion itself represents the initial point of entry that ultimately led to data exfiltration.

Motivation-wise, it seems plausible for the data theft thread to have been part of a DPRK-sponsored operation. DPRK is known to pursue targets that could potentially fulfil its national security goals and had been publicly reported as being active in months prior to this intrusion [21]. Furthermore, the timing of the data theft aligns with the ratification of the mutual defense treaty between DPRK and Russia and the subsequent accused activities [20].

Darktrace assesses with medium confidence that a nation-state, likely DPRK, was responsible, based on our investigation, the threat actor applied resources, patience, obfuscation, and evasiveness combined with external reporting, collaboration with the cyber community, assessing the attacker’s motivation and world geopolitical timeline, and undisclosed intelligence.

Conclusion

When state-linked cyber activity occurs within an organization’s environment, previously unseen C2 infrastructure and advanced evasion techniques will likely be used. State-linked cyber actors, through their resources and patience, are able to bypass most detection methods, leaving anomaly-based methods as a last line of defense.

Two threads of activity were observed within Darktrace’s customer base over the last year: The first operation involved the abuse of Check Point VPN credentials to log in remotely to organizations’ networks, followed by the distribution of ShadowPad to an internal domain controller. The second operation involved highly targeted data exfiltration from the network of one of the customers impacted by the previously mentioned ShadowPad activity.

Despite definitive attribution remaining unresolved, both the ShadowPad and data exfiltration activities were detected by Darktrace’s Self-Learning AI, with Cyber AI Analyst playing a significant role in identifying and piecing together the various steps of the intrusion activities.  

Credit to Sam Lister (R&D Detection Analyst), Emma Foulger (Principal Cyber Analyst), Nathaniel Jones (VP), and the Darktrace Threat Research team.

Appendices

Darktrace / NETWORK model alerts

User / New Admin Credentials on Client

Anomalous Connection / Unusual Admin SMB Session

Compliance / SMB Drive Write  

Device / Anomalous SMB Followed By Multiple Model Breaches

Anomalous File / Internal / Unusual SMB Script Write

User / New Admin Credentials on Client  

Anomalous Connection / Unusual Admin SMB Session

Compliance / SMB Drive Write

Device / Anomalous SMB Followed By Multiple Model Breaches

Anomalous File / Internal / Unusual SMB Script Write

Device / New or Uncommon WMI Activity

Unusual Activity / Internal Data Transfer

Anomalous Connection / Download and Upload

Anomalous Server Activity / Rare External from Server

Compromise / Beacon to Young Endpoint

Compromise / Agent Beacon (Short Period)

Anomalous Server Activity / Anomalous External Activity from Critical Network Device

Anomalous Connection / POST to PHP on New External Host

Compromise / Sustained SSL or HTTP Increase

Compromise / Sustained TCP Beaconing Activity To Rare Endpoint

Anomalous Connection / Multiple Failed Connections to Rare Endpoint

Device / Multiple C2 Model Alerts

Anomalous Connection / Data Sent to Rare Domain

Anomalous Connection / Download and Upload

Unusual Activity / Unusual External Data Transfer

Anomalous Connection / Low and Slow Exfiltration

Anomalous Connection / Uncommon 1 GiB Outbound  

MITRE ATT&CK mapping

(Technique name – Tactic ID)

ShadowPad malware threads

Initial Access - Valid Accounts: Domain Accounts (T1078.002)

Initial Access - External Remote Services (T1133)

Privilege Escalation - Exploitation for Privilege Escalation (T1068)

Privilege Escalation - Valid Accounts: Default Accounts (T1078.001)

Defense Evasion - Masquerading: Match Legitimate Name or Location (T1036.005)

Lateral Movement - Remote Services: Remote Desktop Protocol (T1021.001)

Lateral Movement - Remote Services: SMB/Windows Admin Shares (T1021.002)

Command and Control - Proxy: Internal Proxy (T1090.001)

Command and Control - Application Layer Protocol: Web Protocols (T1071.001)

Command and Control - Encrypted Channel: Asymmetric Cryptography (T1573.002)

Command and Control - Application Layer Protocol: DNS (T1071.004)

Data theft thread

Resource Development - Compromise Infrastructure: Domains (T1584.001)

Privilege Escalation - Valid Accounts: Default Accounts (T1078.001)

Privilege Escalation - Valid Accounts: Domain Accounts (T1078.002)

Execution - Windows Management Instrumentation (T1047)

Defense Evasion - Masquerading: Match Legitimate Name or Location (T1036.005)

Defense Evasion - Obfuscated Files or Information (T1027)

Lateral Movement - Remote Services: SMB/Windows Admin Shares (T1021.002)

Collection - Data from Network Shared Drive (T1039)

Command and Control - Application Layer Protocol: Web Protocols (T1071.001)

Command and Control - Encrypted Channel: Asymmetric Cryptography (T1573.002)

Command and Control - Proxy: External Proxy (T1090.002)

Exfiltration - Exfiltration Over C2 Channel (T1041)

Exfiltration - Data Transfer Size Limits (T1030)

List of indicators of compromise (IoCs)

IP addresses and/or domain names (Mid-high confidence):

ShadowPad thread

- dscriy.chtq[.]net • 158.247.199[.]185 (endpoint of C2 comms)

- cybaq.chtq[.]net (domain name used for DNS tunneling)  

Data theft thread

- yasuconsulting[.]com (45.158.12[.]7)

- hobivan[.]net (94.73.151[.]72)

- mediostresbarbas.com[.]ar (75.102.23[.]3)

- mnmathleague[.]org (185.148.129[.]24)

- goldenborek[.]com (94.138.200[.]40)

- tunemmuhendislik[.]com (94.199.206[.]45)

- anvil.org[.]ph (67.209.121[.]137)

- partnerls[.]pl (5.187.53[.]50)

- angoramedikal[.]com (89.19.29[.]128)

- awork-designs[.]dk (78.46.20[.]225)

- digitweco[.]com (38.54.95[.]190)

- duepunti-studio[.]it (89.46.106[.]61)

- scgestor.com[.]br (108.181.92[.]71)

- lacapannadelsilenzio[.]it (86.107.36[.]15)

- lovetamagotchith[.]com (203.170.190[.]137)

- lieta[.]it (78.46.146[.]147)

File names (Mid-high confidence):

ShadowPad thread:

- perflogs\1.txt

- perflogs\AppLaunch.exe

- perflogs\F4A3E8BE.tmp

- perflogs\mscoree.dll

Data theft thread

- ProgramData\Oracle\java.log

- ProgramData\Oracle\duxwfnfo

- ProgramData\Adobe\ARM\webservices.dll

- ProgramData\Adobe\ARM\wksprt.exe

- ProgramData\Oracle\Java\wksprt.exe

- ProgramData\Oracle\Java\webservices.dll

- ProgramData\Microsoft\DRM\wksprt.exe

- ProgramData\Microsoft\DRM\webservices.dll

- ProgramData\Abletech\Client\webservices.dll

- ProgramData\Abletech\Client\client.exe

- ProgramData\Adobe\ARM\rzrmxrwfvp

- ProgramData\3Dconnexion\3DxWare\3DxWare.exe

- ProgramData\3Dconnexion\3DxWare\webservices.dll

- ProgramData\IDMComp\UltraCompare\updater.exe

- ProgramData\IDMComp\UltraCompare\webservices.dll

- ProgramData\IDMComp\UltraCompare\imtrqjsaqmm

- temp\HousecallLauncher64.exe

Attacker-controlled device hostname (Mid-high confidence)

- DESKTOP-O82ILGG

References  

[1] https://www.kaspersky.com/about/press-releases/shadowpad-how-attackers-hide-backdoor-in-software-used-by-hundreds-of-large-companies-around-the-world  

[2] https://media.kasperskycontenthub.com/wp-content/uploads/sites/43/2017/08/07172148/ShadowPad_technical_description_PDF.pdf

[3] https://blog.avast.com/new-investigations-in-ccleaner-incident-point-to-a-possible-third-stage-that-had-keylogger-capacities

[4] https://securelist.com/operation-shadowhammer-a-high-profile-supply-chain-attack/90380/

[5] https://assets.sentinelone.com/c/Shadowpad?x=P42eqA

[6] https://www.cyfirma.com/research/the-origins-of-apt-41-and-shadowpad-lineage/

[7] https://www.csoonline.com/article/572061/shadowpad-has-become-the-rat-of-choice-for-several-state-sponsored-chinese-apts.html

[8] https://global.ptsecurity.com/analytics/pt-esc-threat-intelligence/shadowpad-new-activity-from-the-winnti-group

[9] https://cymulate.com/threats/shadowpad-privately-sold-malware-espionage-tool/

[10] https://www.secureworks.com/research/shadowpad-malware-analysis

[11] https://blog.talosintelligence.com/chinese-hacking-group-apt41-compromised-taiwanese-government-affiliated-research-institute-with-shadowpad-and-cobaltstrike-2/

[12] https://hackerseye.net/all-blog-items/tails-from-the-shadow-apt-41-injecting-shadowpad-with-sideloading/

[13] https://cloud.google.com/blog/topics/threat-intelligence/scatterbrain-unmasking-poisonplug-obfuscator

[14] https://www.domaintools.com/wp-content/uploads/conceptualizing-a-continuum-of-cyber-threat-attribution.pdf

[15] https://www.nccgroup.com/es/research-blog/north-korea-s-lazarus-their-initial-access-trade-craft-using-social-media-and-social-engineering/  

[16] https://www.microsoft.com/en-us/security/blog/2021/01/28/zinc-attacks-against-security-researchers/

[17] https://www.microsoft.com/en-us/security/blog/2022/09/29/zinc-weaponizing-open-source-software/  

[18] https://www.welivesecurity.com/en/eset-research/lazarus-luring-employees-trojanized-coding-challenges-case-spanish-aerospace-company/  

[19] https://blogs.jpcert.or.jp/en/2021/01/Lazarus_malware2.html  

[20] https://usun.usmission.gov/joint-statement-on-the-unlawful-arms-transfer-by-the-democratic-peoples-republic-of-korea-to-russia/

[21] https://media.defense.gov/2024/Jul/25/2003510137/-1/-1/1/Joint-CSA-North-Korea-Cyber-Espionage-Advance-Military-Nuclear-Programs.PDF  

[22] https://kyivindependent.com/first-north-korean-troops-deployed-to-front-line-in-kursk-oblast-ukraines-military-intelligence-says/

[23] https://www.microsoft.com/en-us/security/blog/2024/12/04/frequent-freeloader-part-i-secret-blizzard-compromising-storm-0156-infrastructure-for-espionage/  

[24] https://www.microsoft.com/en-us/security/blog/2024/12/11/frequent-freeloader-part-ii-russian-actor-secret-blizzard-using-tools-of-other-groups-to-attack-ukraine/  

[25] https://www.sentinelone.com/labs/chamelgang-attacking-critical-infrastructure-with-ransomware/    

[26] https://thehackernews.com/2022/06/state-backed-hackers-using-ransomware.html/  

[27] https://blog.checkpoint.com/security/check-point-research-explains-shadow-pad-nailaolocker-and-its-protection/

[28] https://www.orangecyberdefense.com/global/blog/cert-news/meet-nailaolocker-a-ransomware-distributed-in-europe-by-shadowpad-and-plugx-backdoors

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About the author
Sam Lister
SOC Analyst
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