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August 29, 2023

Analyzing Post-Exploitation on Papercut Servers

Dive into our analysis covering post-exploitation activity on PaperCut servers. Learn the details and impact of this attack and how to keep yourself safe!
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
Sam Lister
Specialist Security Researcher
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29
Aug 2023

Introduction

Malicious cyber actors are known to exploit vulnerabilities in Internet-facing systems and services to gain entry to organizations’ digital environments. Keeping track of the vulnerabilities which malicious actors are exploiting is seemingly futile, with malicious actors continually finding new avenues of exploitation.  

In mid-April 2023, Darktrace, along with the wider security community, observed malicious cyber actors gaining entry to networks through exploitation of a critical vulnerability in the print management system, PaperCut. Darktrace observed two types of attack chain within its customer base, one involving the deployment of payloads to facilitate crypto-mining, and the other involving the deployment of a payload to facilitate Tor-based command-and-control (C2) communication.

Walking Through the Front Door

One of the most widely abused Initial Access methods attackers use to gain entry to an organization’s digital environment is the exploitation of vulnerabilities in Internet-facing systems and services [1]. The public disclosure of a critical vulnerability in a widely used, Internet-facing service, along with a proof of concept (POC) exploit for such vulnerability, provides malicious cyber actors with a key to the front door of countless organizations. Once malicious actors are in possession of such a key, security teams are in a race against time to patch all their vulnerable systems and services. But until organizations accomplish this, the doors are left open.

This year, the security community has seen malicious actors gaining entry to networks through the exploitation of vulnerabilities in a range of services. These services include familiar suspects, such as Microsoft Exchange and ManageEngine, along with less familiar suspects, such as PaperCut. PaperCut is a system for managing and tracking printing, copying, and scanning activity within organizations. In 2021, PaperCut was used in more than 50,000 sites across over 100 countries [2], making PaperCut a widely used print management system.

In January 2023, Trend Micro’s Zero Day Initiative (ZDI) notified PaperCut of a critical RCE vulnerability, namely CVE-2023–27350, in certain versions of PaperCut NG (PaperCut’s ‘print only’ variant) and PaperCut MF (PaperCut’s ‘extended feature’ variant) [3,4]. In March 2023, PaperCut released versions of PaperCut NG and PaperCut MF containing a fix for CVE-2023–27350 [4]. Despite this, security teams observed a surge in cases of malicious actors exploiting CVE-2023–27350 to compromise PaperCut servers in April 2023 [4-10]. This trend was mirrored in Darktrace’s customer base, where a surge in compromises of PaperCut servers was observed in April 2023.

Observed Attack Chains

In mid-April 2023, Darktrace identified two related clusters of attack chains. The attack chains within the first of these clusters involved Internet-facing PaperCut servers downloading payloads with crypto-mining capabilities from the external location, 50.19.48[.]59. While the attack chains within the second of the clusters involved Internet-facing PaperCut servers downloading payloads with Tor-based C2 capabilities from 192.184.35[.]216. The attack chains within the first cluster, which were observed on April 22, 2023, will be referred to as ‘50.19.48[.]59 chains’ and the attack chains in the second cluster, observed on April 24, 2023, will be called ‘192.184.35[.]216 chains’.

Both attack chains started with highly unusual external endpoints contacting the '/SetupCompleted' endpoint of an Internet-facing PaperCut server. These requests to the ‘/SetupCompleted’ endpoint likely represented attempts to exploit CVE-2023–27350 [10].  50.19.48[.]59 chains started with exploit connections from the external endpoint, 85.106.112[.]60, whereas 192.184.35[.]216 chains started with exploit connections from Tor nodes, such as 185.34.33[.]2.

Figure 1: Darktrace’s Advanced Search data showing likely CVE-2023-27350 exploitation activity from the suspicious, external endpoint, 85.106.112[.]60.

After the exploitation step, the two attack chains took different paths. In the 50.19.48[.]59 chains, the exploitation step was followed by the affected PaperCut server making HTTP GET requests over port 82 to the rare external endpoint, 50.19.48[.]59. In the 192.184.35[.]216 chains, the exploitation step was followed by the affected PaperCut server making an HTTP GET request over port 443 to 192.184.35[.]216.

The HTTP GET requests to 50.19.48[.]59 had Target URIs such as ‘/me1.bat’, ‘/me2.bat’, ‘/dom.zip’, ‘/mazar.bat’, and ‘/mazar.zip’, whilst the HTTP GET requests to 192.184.35[.]216 had the Target URI ‘/4591187629.exe’. The User-Agent header of the GET requests to 192.184.35[.]216 indicated that that the malicious file transfers were initiated through Microsoft’s pre-installed Background Intelligent Transfer Service (BITS).

Figure 2: Darktrace’s Advanced Search data showing a PaperCut server downloading Batch and ZIP files from 50.19.48[.]59 straight after receiving likely exploit connections from 85.106.112[.]60.
Figure 3: Darktrace’s Event Log data showing a PaperCut server downloading an executable file from 192.184.35[.]216 immediately after receiving a likely exploit connection from the Tor node, 185.34.33[.]2.

Downloads from 50.19.48[.]59 were followed by cURL GET requests to 138.68.61[.]82 and then connections to external endpoints associated with the cryptocurrency miner, Mimu (as seen in Fig 4). Downloads from 192.184.35[.]216 were followed by Python-urllib GET requests to api.ipify[.]org and long connections to Tor nodes (as seen in Fig 5).  

These facts suggest that the actor behind the 50.19.48[.]59 chains were seeking to drop cryptocurrency miners on PaperCut servers, with the intention of abusing the customer’s network to carry out resource intensive and costly cryptocurrency mining activity. Meanwhile, the actors behind the 192.184.35[.]216 chains were likely attempting to establish a Tor-based C2 channel with PaperCut servers to allow actors to further communicate with compromised devices.

Figure 4: Darktrace's Event Log data showing a PaperCut contacting 50.19.48[.]59 to download payloads, and then making a cURL request to 138.68.61[.]82 before contacting a Mimu crypto-mining endpoint.
Figure 5: Darktrace’s Event Log data showing a PaperCut server contacting 192.184.35[.]216 to download a payload, and then making connections to api.ipify[.]org and several Tor nodes.

The activities ensuing from both attack chains were varied, making it difficult to ascertain whether the activities were steps of separate attack chains, or steps of the existing 50.19.48[.]59 and 192.184.35[.]216 chains. A wide variety of activities ensued from observed 50.19.48[.]59 and 192.184.35[.]216 chains, including the abuse of pre-installed tools, such as cURL, CertUtil, and PowerShell to transfer further payloads to PaperCut servers, Cobalt Strike C2 communication, Ngrok usage, Mimikatz usage, AnyDesk usage, and in one case, detonation of the LockBit ransomware strain.

Figure 6: Diagram representing the steps of observed 50.19.48[.]59 chains.
Figure 7: Diagram representing the steps of observed 192.184.35[.]215 chains.

As the PaperCut servers that were targeted by malicious actors are Internet-facing, they regularly receive connections from unusual external endpoints. The exploit connections in the 50.19.48[.]59 and 192.184.35[.]216 chains, which originated from unusual external endpoints, were therefore not detected by Darktrace DETECT™, which relies on anomaly-based methods to detect network-based steps of an intrusion.

On the other hand, the post-exploitation steps of the 50.19.48[.]59 and 192.184.35[.]216 chains yielded ample anomaly-based detections, given that they consisted of PaperCut servers displaying highly unusual behaviors. As such Darktrace DETECT was able to successfully identify multiple chains of suspicious activity, including unusual file downloads from external endpoints and beaconing activity to rare external locations.

The file downloads from 50.19.48[.]59 observed in the 50.19.48[.]59 chains caused the following Darktrace DETECT models to breach:

- Anomalous Connection / Application Protocol on Uncommon Port

- Anomalous File / Internet Facing System File Download

- Anomalous File / Script from Rare External Location

- Anomalous File / Zip or Gzip from Rare External Location

- Device / Internet Facing Device with High Priority Alert

Figure 8: Darktrace’s Event Log data showing a PaperCut server breaching several models immediately after contacting 50.19.48[.]59.

The file downloads from 192.184.35[.]216 observed in the 192.184.35[.]216 chains caused the following Darktrace DETECT models to breach:

- Anomalous File / EXE from Rare External Location

- Anomalous File / Numeric File Download

- Device / Internet Facing Device with High Priority Alert

Figure 9: Darktrace’s Event Log data showing a PaperCut server breaching several models immediately after contacting 192.184.35[.]216.

Subsequent C2, beaconing, and crypto-mining connections in the 50.19.48[.]59 chains caused the following Darktrace DETECT models to breach:

- Anomalous Connection / New User Agent to IP Without Hostname

- Anomalous Server Activity / New User Agent from Internet Facing System

- Anomalous Server Activity / Rare External from Server

- Compromise / Crypto Currency Mining Activity

- Compromise / High Priority Crypto Currency Mining

- Compromise / High Volume of Connections with Beacon Score

- Compromise / Large Number of Suspicious Failed Connections

- Compromise / SSL Beaconing to Rare Destination

- Device / Initial Breach Chain Compromise

- Device / Large Number of Model Breaches

Figure 10: Darktrace’s Event Log data showing a PaperCut server breaching models as a result of its connections to a Mimu crypto-mining endpoint.

Subsequent C2, beaconing, and Tor connections in the 192.184.35[.]216 chains caused the following Darktrace DETECT models to breach:

- Anomalous Connection / Application Protocol on Uncommon Port

- Compromise / Anomalous File then Tor

- Compromise / Beaconing Activity To External Rare

- Compromise / Possible Tor Usage

- Compromise / Slow Beaconing Activity To External Rare

- Compromise / Uncommon Tor Usage

- Device / Initial Breach Chain Compromise

Figure 11: Darktrace’s Event Log data showing a PaperCut server breaching several models as a result of its connections to Tor nodes.

Darktrace RESPOND

Darktrace RESPOND™ was not active in any of the networks affected by 192.184.35[.]216 activity, however, RESPOND was active in some of the networks affected by 50.19.48[.]59 activity.  In those environments where RESPOND was enabled in autonomous mode, observed malicious activities resulted in intervention from RESPOND, including autonomous actions like blocking connections to specific external endpoints, blocking all outgoing traffic, and restricting affected devices to a pre-established pattern of behavior.

Figure 12: Darktrace’s Event Log data showing Darktrace RESPOND automatically performing inhibitive actions on a device in response to the device’s connection to 50.19.48[.]59.
Figure 13: Darktrace’s Event Log data showing Darktrace RESPOND automatically performing inhibitive actions on a device in response to the device’s connections to a Mimu crypto-mining endpoint.

Darktrace Cyber AI Analyst

Cyber AI Analyst autonomously investigated model breaches caused by events within these 50.19.48[.]59 and 192.184.35[.]216 chains. Cyber AI Analyst created user-friendly and detailed descriptions of these events, and then linked together these descriptions into threads representing the attack chains. Darktrace DETECT thus uncovered the individual steps of the attack chains, while Cyber AI Analyst was able to piece together the individual steps and uncover the attack chains themselves.  

Figure 14: An AI Analyst Incident entry showing the first event in a 50.19.48[.]59 chain uncovered by Cyber AI Analyst.
Figure 15: An AI Analyst Incident entry showing the second event in a 50.19.48[.]59 chain uncovered by Cyber AI Analyst.
Figure 16: An AI Analyst Incident entry showing the third event in a 50.19.48[.]59 chain uncovered by Cyber AI Analyst.
Figure 17: An AI Analyst Incident entry showing the first event in a 192.184.35[.]216 chain uncovered by Cyber AI Analyst.
Figure 18: An AI Analyst Incident entry showing the second event in a 192.184.35[.]216 chain uncovered by Cyber AI Analyst.

Conclusion

The existence of critical vulnerabilities in third-party software leaves organizations at constant risk of malicious actors breaching the perimeters of their networks. This risk can be mitigated through attack surface management and regular patching. However, this does not eliminate cyber risk entirely, meaning that organizations must be prepared for the eventuality of malicious actors getting inside their digital estate.

In April 2023, Darktrace observed malicious actors breaching the perimeters of several customer networks through exploitation of a critical vulnerability in PaperCut. Darktrace DETECT observed actors exploiting PaperCut servers to conduct a wide variety of post-exploitation activities, including downloading malicious payloads associated with cryptocurrency mining or payloads with Tor-based C2 capabilities. Darktrace DETECT created numerous model breaches based on this activity which alerted then customer’s security teams early in their development, providing them with ample time to take mitigative steps.

The successful detection of this payload delivery activity, along with the crypto-mining, beaconing, and Tor C2 activities which followed, elicited Darktrace RESPOND to take autonomous inhibitive action against the ongoing activity in those environments where it was operating in autonomous response mode.

If left to unfold, these intrusions developed in a variety of ways, in some cases leading to Cobalt Strike and ransomware activity. The detection of these intrusions in their early stages thus played a vital role in preventing malicious cyber actors from causing significant disruption.

Credit to: Sam Lister, Senior SOC Analyst, Zoe Tilsiter, Senior Cyber Analyst.

Appendices

MITRE ATT&CK Mapping

Initial Access techniques:

- Exploit Public-Facing Application (T1190)

Execution techniques:

- Command and Scripting Interpreter: PowerShell (T1059.001)

Discovery techniques:

- System Network Configuration Discovery (T1016)

Command and Control techniques

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

- Encrypted Channel: Asymmetric Cryptography (T1573.002)

- Ingress Tool Transfer (T1105)

- Non-Standard Port (T1571)

- Protocol Tunneling (T1572)

- Proxy: Multi-hop Proxy (T1090.003)

- Remote Access Software (T1219)

Defense Evasion techniques:

- BITS Jobs (T1197)

Impact techniques:

- Data Encrypted for Impact (T1486)

List of Indicators of Compromise (IoCs)

IoCs from 50.19.48[.]59 attack chains:

- 85.106.112[.]60

- http://50.19.48[.]59:82/me1.bat

- http://50.19.48[.]59:82/me2.bat

- http://50.19.48[.]59:82/dom.zip

- 138.68.61[.]82

- update.mimu-me[.]cyou • 102.130.112[.]157

- 34.195.77[.]216

- http://50.19.48[.]59:82/mazar.bat

- http://50.19.48[.]59:82/mazar.zip

- http://50.19.48[.]59:82/prx.bat

- http://50.19.48[.]59:82/lol.exe  

- http://77.91.85[.]117/122.exe

- windows.n1tro[.]cyou • 176.28.51[.]151

- 77.91.85[.]117

- 91.149.237[.]76

- kernel-mlclosoft[.]site • 104.21.29[.]206

- tunnel.us.ngrok[.]com • 3.134.73[.]173

- 212.113.116[.]105

- c34a54599a1fbaf1786aa6d633545a60 (JA3 client fingerprint of crypto-mining client)

IoCs from 192.184.35[.]216 attack chains:

- 185.56.83[.]83

- 185.34.33[.]2

- http://192.184.35[.]216:443/4591187629.exe

- api.ipify[.]org • 104.237.62[.]211

- www.67m4ipctvrus4cv4qp[.]com • 192.99.43[.]171

- www.ynbznxjq2sckwq3i[.]com • 51.89.106[.]29

- www.kuo2izmlm2silhc[.]com • 51.89.106[.]29

- 148.251.136[.]16

- 51.158.231[.]208

- 51.75.153[.]22

- 82.66.61[.]19

- backmainstream-ltd[.]com • 77.91.72[.]149

- 159.65.42[.]223

- 185.254.37[.]236

- http://137.184.56[.]77:443/for.ps1

- http://137.184.56[.]77:443/c.bat

- 45.88.66[.]59

- http://5.8.18[.]237/download/Load64.exe

- http://5.8.18[.]237/download/sdb64.dll

- 140e0f0cad708278ade0984528fe8493 (JA3 client fingerprint of Tor-based client)

References

[1] https://www.cisa.gov/news-events/cybersecurity-advisories/aa22-137a

[2] https://www.papercut.com/kb/Main/PaperCutMFSolutionBrief/

[3] https://www.zerodayinitiative.com/advisories/ZDI-23-233/

[4] https://www.papercut.com/kb/Main/PO-1216-and-PO-1219

[5] https://www.trendmicro.com/en_us/research/23/d/update-now-papercut-vulnerability-cve-2023-27350-under-active-ex.html

[6] https://www.huntress.com/blog/critical-vulnerabilities-in-papercut-print-management-software

[7] https://news.sophos.com/en-us/2023/04/27/increased-exploitation-of-papercut-drawing-blood-around-the-internet/

[8] https://twitter.com/MsftSecIntel/status/1651346653901725696

[9] https://twitter.com/MsftSecIntel/status/1654610012457648129

[10] https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-131a

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
Sam Lister
Specialist Security Researcher

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January 13, 2026

Runtime Is Where Cloud Security Really Counts: The Importance of Detection, Forensics and Real-Time Architecture Awareness

runtime, cloud security, cnaapDefault blog imageDefault blog image

Introduction: Shifting focus from prevention to runtime

Cloud security has spent the last decade focused on prevention; tightening configurations, scanning for vulnerabilities, and enforcing best practices through Cloud Native Application Protection Platforms (CNAPP). These capabilities remain essential, but they are not where cloud attacks happen.

Attacks happen at runtime: the dynamic, ephemeral, constantly changing execution layer where applications run, permissions are granted, identities act, and workloads communicate. This is also the layer where defenders traditionally have the least visibility and the least time to respond.

Today’s threat landscape demands a fundamental shift. Reducing cloud risk now requires moving beyond static posture and CNAPP only approaches and embracing realtime behavioral detection across workloads and identities, paired with the ability to automatically preserve forensic evidence. Defenders need a continuous, real-time understanding of what “normal” looks like in their cloud environments, and AI capable of processing massive data streams to surface deviations that signal emerging attacker behavior.

Runtime: The layer where attacks happen

Runtime is the cloud in motion — containers starting and stopping, serverless functions being called, IAM roles being assumed, workloads auto scaling, and data flowing across hundreds of services. It’s also where attackers:

  • Weaponize stolen credentials
  • Escalate privileges
  • Pivot programmatically
  • Deploy malicious compute
  • Manipulate or exfiltrate data

The challenge is complex: runtime evidence is ephemeral. Containers vanish; critical process data disappears in seconds. By the time a human analyst begins investigating, the detail required to understand and respond to the alert, often is already gone. This volatility makes runtime the hardest layer to monitor, and the most important one to secure.

What Darktrace / CLOUD Brings to Runtime Defence

Darktrace / CLOUD is purpose-built for the cloud execution layer. It unifies the capabilities required to detect, contain, and understand attacks as they unfold, not hours or days later. Four elements define its value:

1. Behavioral, real-time detection

The platform learns normal activity across cloud services, identities, workloads, and data flows, then surfaces anomalies that signify real attacker behavior, even when no signature exists.

2. Automated forensic level artifact collection

The moment Darktrace detects a threat, it can automatically capture volatile forensic evidence; disk state, memory, logs, and process context, including from ephemeral resources. This preserves the truth of what happened before workloads terminate and evidence disappears.

3. AI-led investigation

Cyber AI Analyst assembles cloud behaviors into a coherent incident story, correlating identity activity, network flows, and Cloud workload behavior. Analysts no longer need to pivot across dashboards or reconstruct timelines manually.

4. Live architectural awareness

Darktrace continuously maps your cloud environment as it operates; including services, identities, connectivity, and data pathways. This real-time visibility makes anomalies clearer and investigations dramatically faster.

Together, these capabilities form a runtime-first security model.

Why CNAPP alone isn’t enough

CNAPP platforms excel at pre deployment checks all the way down to developer workstations, identifying misconfigurations, concerning permission combinations, vulnerable images, and risky infrastructure choices. But CNAPP’s breadth is also its limitation. CNAPP is about posture. Runtime defense is about behavior.

CNAPP tells you what could go wrong; runtime detection highlights what is going wrong right now.

It cannot preserve ephemeral evidence, correlate active behaviors across domains, or contain unfolding attacks with the precision and speed required during a real incident. Prevention remains essential, but prevention alone cannot stop an attacker who is already operating inside your cloud environment.

Real-world AWS Scenario: Why Runtime Monitoring Wins

A recent incident detected by Darktrace / CLOUD highlights how cloud compromises unfold, and why runtime visibility is non-negotiable. Each step below reflects detections that occur only when monitoring behavior in real time.

1. External Credential Use

Detection: Unusual external source for credential use: An attacker logs into a cloud account from a never-before-seen location, the earliest sign of account takeover.

2. AWS CLI Pivot

Detection: Unusual CLI activity: The attacker switches to programmatic access, issuing commands from a suspicious host to gain automation and stealth.

3. Credential Manipulation

Detection: Rare password reset: They reset or assign new passwords to establish persistence and bypass existing security controls.

4. Cloud Reconnaissance

Detection: Burst of resource discovery: The attacker enumerates buckets, roles, and services to map high value assets and plan next steps.

5. Privilege Escalation

Detection: Anomalous IAM update: Unauthorized policy updates or role changes grant the attacker elevated access or a backdoor.

6. Malicious Compute Deployment

Detection: Unusual EC2/Lambda/ECS creation: The attacker deploys compute resources for mining, lateral movement, or staging further tools.

7. Data Access or Tampering

Detection: Unusual S3 modifications: They alter S3 permissions or objects, often a prelude to data exfiltration or corruption.

Only some of these actions would appear in a posture scan, crucially after the fact.
Every one of these runtime detections is visible only through real-time behavioral monitoring while the attack is in progress.

The future of cloud security Is runtime-first

Cloud defense can no longer revolve solely around prevention. Modern attacks unfold in runtime, across a fast-changing mesh of workloads, services, and — critically — identities. To reduce risk, organizations must be able to detect, understand, and contain malicious activity as it happens, before ephemeral evidence disappears and before attacker's pivot across identity layers.

Darktrace / CLOUD delivers this shift by turning runtime, the most volatile and consequential layer in the cloud, into a fully defensible control point through unified visibility across behavior, workloads, and identities. It does this by providing:

  • Real-time behavior detection across workloads and identity activity
  • Autonomous response actions for rapid containment
  • Automated forensic level artifact preservation the moment events occur
  • AI-driven investigation that separates weak signals from true attacker patterns
  • Live cloud environment insight to understand context and impact instantly

Cloud security must evolve from securing what might go wrong to continuously understanding what is happening; in runtime, across identities, and at the speed attackers operate. Unifying runtime and identity visibility is how defenders regain the advantage.

[related-resource]

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About the author
Adam Stevens
Senior Director of Product, Cloud | Darktrace

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January 12, 2026

Maduro Arrest Used as a Lure to Deliver Backdoor

maduro arrest used as lure to deliver backdoorDefault blog imageDefault blog image

Introduction

Threat actors frequently exploit ongoing world events to trick users into opening and executing malicious files. Darktrace security researchers recently identified a threat group using reports around the arrest of Venezuelan President Nicolàs Maduro on January 3, 2025, as a lure to deliver backdoor malware.

Technical Analysis

While the exact initial access method is unknown, it is likely that a spear-phishing email was sent to victims, containing a zip archive titled “US now deciding what’s next for Venezuela.zip”. This file included an executable named “Maduro to be taken to New York.exe” and a dynamic-link library (DLL), “kugou.dll”.  

The binary “Maduro to be taken to New York.exe” is a legitimate binary (albeit with an expired signature) related to KuGou, a Chinese streaming platform. Its function is to load the DLL “kugou.dll” via DLL search order. In this instance, the expected DLL has been replaced with a malicious one with the same name to load it.  

DLL called with LoadLibraryW.
Figure 1: DLL called with LoadLibraryW.

Once the DLL is executed, a directory is created C:\ProgramData\Technology360NB with the DLL copied into the directory along with the executable, renamed as “DataTechnology.exe”. A registry key is created for persistence in “HKCU\Software\Microsoft\Windows\CurrentVersion\Run\Lite360” to run DataTechnology.exe --DATA on log on.

 Registry key added for persistence.
Figure 2. Registry key added for persistence.
Folder “Technology360NB” created.
Figure 3: Folder “Technology360NB” created.

During execution, a dialog box appears with the caption “Please restart your computer and try again, or contact the original author.”

Message box prompting user to restart.
Figure 4. Message box prompting user to restart.

Prompting the user to restart triggers the malware to run from the registry key with the command --DATA, and if the user doesn't, a forced restart is triggered. Once the system is reset, the malware begins periodic TLS connections to the command-and-control (C2) server 172.81.60[.]97 on port 443. While the encrypted traffic prevents direct inspection of commands or data, the regular beaconing and response traffic strongly imply that the malware has the ability to poll a remote server for instructions, configuration, or tasking.

Conclusion

Threat groups have long used geopolitical issues and other high-profile events to make malicious content appear more credible or urgent. Since the onset of the war in Ukraine, organizations have been repeatedly targeted with spear-phishing emails using subject lines related to the ongoing conflict, including references to prisoners of war [1]. Similarly, the Chinese threat group Mustang Panda frequently uses this tactic to deploy backdoors, using lures related to the Ukrainian war, conventions on Tibet [2], the South China Sea [3], and Taiwan [4].  

The activity described in this blog shares similarities with previous Mustang Panda campaigns, including the use of a current-events archive, a directory created in ProgramData with a legitimate executable used to load a malicious DLL and run registry keys used for persistence. While there is an overlap of tactics, techniques and procedures (TTPs), there is insufficient information available to confidently attribute this activity to a specific threat group. Users should remain vigilant, especially when opening email attachments.

Credit to Tara Gould (Malware Research Lead)
Edited by Ryan Traill (Analyst Content Lead)

Indicators of Compromise (IoCs)

172.81.60[.]97
8f81ce8ca6cdbc7d7eb10f4da5f470c6 - US now deciding what's next for Venezuela.zip
722bcd4b14aac3395f8a073050b9a578 - Maduro to be taken to New York.exe
aea6f6edbbbb0ab0f22568dcb503d731  - kugou.dll

References

[1] https://cert.gov.ua/article/6280422  

[2] https://www.ibm.com/think/x-force/hive0154-mustang-panda-shifts-focus-tibetan-community-deploy-pubload-backdoor

[3] https://www.ibm.com/think/x-force/hive0154-targeting-us-philippines-pakistan-taiwan

[4] https://www.ibm.com/think/x-force/hive0154-targeting-us-philippines-pakistan-taiwan

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About the author
Tara Gould
Malware Research Lead
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