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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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March 26, 2026

Phantom Footprints: Tracking GhostSocks Malware

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Why are attackers using residential proxies?

In today's threat landscape, blending in to normal activity is the key to success for attackers and the growing reliance on residential proxies shows a significant shift in how threat actors are attempting to bypass IP detection tools.

The increasing dependency on residential proxies has exposed how prevalent proxy services are and how reliant a diverse range of threat actors are on them. From cybercriminal groups to state‑sponsored actors, the need to bypass IP detection tools is fundamental to the success of these groups. One malware that has quietly become notorious for its ability to avoid anomaly detection is GhostSocks, a malware that turns compromised devices into residential proxies.

What is GhostSocks?

Originally marketed on the Russian underground forum xss[.]is as a Malware‑as‑a‑Service (MaaS), GhostSocks enables threat actors to turn compromised devices into residential proxies, leveraging the victim's internet bandwidth to route malicious traffic through it.

How does Ghostsocks malware work? 

The malware offers the threat actor a “clean” IP address, making it look like it is coming from a household user. This enables the bypassing of geographic restrictions and IP detection tools, a perfect tool for avoiding anomaly detection. It wasn’t until 2024, when a partnership was announced with the infamous information stealer Lumma Stealer, that GhostSocks surged into widespread adoption and alluded to who may be the author of the proxy malware.

Written in GoLang, GhostSocks utilizes the SOCKS5 proxy protocol, creating a SOCKS5 connection on infected devices. It uses a relay‑based C2 implementation, where an intermediary server sits in between the real command-and-control (C2) server and the infected device.

How does Ghostsocks malware evade detection?

To further increase evasion, the Ghostsocks malware wraps its SOCKS5 tunnels in TLS encryption, allowing its malicious traffic to blend into normal network traffic.

Early variants of GhostSocks do not implement a persistence mechanism; however, later versions achieve persistence via registry run keys, ensuring sustained proxy operational time [1].

While proxying is its primary purpose, GhostSocks also incorporates backdoor functionality, enabling malicious actors to run arbitrary commands and download and deploy additional malicious payloads. This was evident with the well‑known ransomware group Black Basta, which reportedly used GhostSocks as a way of maintaining long‑term access to victims’ networks [1].

Darktrace’s detection of GhostSocks Malware

Darktrace observed a steady increase in GhostSocks activity across its customer base from late 2025, with its Threat Research team identifying multiple incidents involving the malware. In one notable case from December 2025, Darktrace detected GhostSocks operating alongside Lumma Stealer, reinforcing that the partnership between Lumma and GhostSocks remains active despite recent attempts to disrupt Lumma’s infrastructure.

Darktrace’s first detection of GhostSocks‑related activity came when a device on the network of a customer in the education sector began making connections to an endpoint with a suspicious self‑signed certificate that had never been seen on the network before.

The endpoint in question, 159.89.46[.]92 with the hostname retreaw[.]click, has been flagged by multiple open‑source intelligence (OSINT) sources as being associated with Lumma Stealer’s C2 infrastructure [2], indicating its likely role in the delivery of malicious payloads.

Darktrace’s detection of suspicious SSL connections to retreaw[.]click, indicating an attempted link to Lumma C2 infrastructure.
Figure 1: Darktrace’s detection of suspicious SSL connections to retreaw[.]click, indicating an attempted link to Lumma C2 infrastructure.

Less than two minutes later, Darktrace observed the same device downloading the executable (.exe) file “Renewable.exe” from the IP 86.54.24[.]29, which Darktrace recognized as 100% rare for this network.

Darktrace’s detection of a device downloading the unusual executable file “Renewable.exe”.
Figure 2: Darktrace’s detection of a device downloading the unusual executable file “Renewable.exe”.

Both the file MD5 hash and the executable itself have been identified by multiple OSINT vendors as being associated with the GhostSocks malware [3], with the executable likely the backdoor component of the GhostSocks malware, facilitating the distribution of additional malicious payloads [4].

Following this detection, Darktrace’s Autonomous Response capability recommended a blocking action for the device in an early attempt to stop the malicious file download. In this instance, Darktrace was configured in Human Confirmation Mode, meaning the customer’s security team was required to manually apply any mitigative response actions. Had Autonomous Response been fully enabled at the time of the attack, the connections to 86.54.24[.]29 would have been blocked, rendering the malware ineffective at reaching its C2 infrastructure and halting any further malicious communication.

 Darktrace’s Autonomous Response capability suggesting blocking the suspicious connections to the unusual endpoint from which the malicious executable was downloaded.
Figure 3: Darktrace’s Autonomous Response capability suggesting blocking the suspicious connections to the unusual endpoint from which the malicious executable was downloaded.

As the attack was able to progress, two days later the device was detected downloading additional payloads from the endpoint www.lbfs[.]site (23.106.58[.]48), including “Setup.exe”, “,.exe”, and “/vp6c63yoz.exe”.

Darktrace’s detection of a malicious payload being downloaded from the endpoint www.lbfs[.]site.
Figure 4: Darktrace’s detection of a malicious payload being downloaded from the endpoint www.lbfs[.]site.

Once again, Darktrace recognized the anomalous nature of these downloads and suggested that a “group pattern of life” be enforced on the offending device in an attempt to contain the activity. By enforcing a pattern of life on a device, Darktrace restricts its activity to connections and behaviors similar to those performed by peer devices within the same group, while still allowing it to carry out its expected activity, effectively preventing deviations indicative of compromise while minimizing disruption. As mentioned earlier, these mitigative actions required manual implementation, so the activity was able to continue. Darktrace proceeded to suggest further actions to contain subsequent malicious downloads, including an attempt to block all outbound traffic to stop the attack from progressing.

An overview of download activity and the Autonomous Response actions recommended by Darktrace to block the downloads.
Figure 5: An overview of download activity and the Autonomous Response actions recommended by Darktrace to block the downloads.

Around the same time, a third executable download was detected, this time from the hostname hxxp[://]d2ihv8ymzp14lr.cloudfront.net/2021-08-19/udppump[.]exe, along with the file “udppump.exe”.While GhostSocks may have been present only to facilitate the delivery of additional payloads, there is no indication that these CloudFront endpoints or files are functionally linked to GhostSocks. Rather, the evidence points to broader malicious file‑download activity.

Shortly after the multiple executable files had been downloaded, Darktrace observed the device initiating a series of repeated successful connections to several rare external endpoints, behavior consistent with early-stage C2 beaconing activity.

Cyber AI Analyst’s investigation

Darktrace’s detection of additional malicious file downloads from malicious CloudFront endpoints.
Figure 7: Darktrace’s detection of additional malicious file downloads from malicious CloudFront endpoints.

Throughout the course of this attack, Darktrace’s Cyber AI Analyst carried out its own autonomous investigation, piecing together seemingly separate events into one wider incident encompassing the first suspicious downloads beginning on December 4, the unusual connectivity to many suspicious IPs that followed, and the successful beaconing activity observed two days later. By analyzing these events in real-time and viewing them as part of the bigger picture, Cyber AI Analyst was able to construct an in‑depth breakdown of the attack to aid the customer’s investigation and remediation efforts.

Cyber AI Analyst investigation detailing the sequence of events on the compromised device, highlighting its extensive connectivity to rare endpoints, the related malicious file‑download activity, and finally the emergence of C2 beaconing behavior.
Figure 8: Cyber AI Analyst investigation detailing the sequence of events on the compromised device, highlighting its extensive connectivity to rare endpoints, the related malicious file‑download activity, and finally the emergence of C2 beaconing behavior.

Conclusion

The versatility offered by GhostSocks is far from new, but its ability to convert compromised devices into residential proxy nodes, while enabling long‑term, covert network access—illustrates how threat actors continue to maximise the value of their victims’ infrastructure. Its growing popularity, coupled with its ongoing partnership with Lumma, demonstrates that infrastructure takedowns alone are insufficient; as long as threat actors remain committed to maintaining anonymity and can rapidly rebuild their ecosystems, related malware activity is likely to persist in some form.

Credit to Isabel Evans (Cyber Analyst), Gernice Lee (Associate Principal Analyst & Regional Consultancy Lead – APJ)
Edited by Ryan Traill (Content Manager)

Appendices

References

1.    https://bloo.io/research/malware/ghostsocks

2.    https://www.virustotal.com/gui/domain/retreaw.click/community

3.    https://synthient.com/blog/ghostsocks-from-initial-access-to-residential-proxy

4.    https://www.joesandbox.com/analysis/1810568/0/html

5. https://www.virustotal.com/gui/url/fab6525bf6e77249b74736cb74501a9491109dc7950688b3ae898354eb920413

Darktrace Model Detections

Real-time Detection Models

Anomalous Connection / Suspicious Self-Signed SSL

Anomalous Connection / Rare External SSL Self-Signed

Anomalous File / EXE from Rare External Location

Anomalous File / Multiple EXE from Rare External Locations

Compromise / Possible Fast Flux C2 Activity

Compromise / Large Number of Suspicious Successful Connections

Compromise / Large Number of Suspicious Failed Connections

Compromise / Sustained SSL or HTTP Increase

Autonomous Response Models

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

Antigena / Network / External Threat / Antigena Suspicious File Block

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

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

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

Antigena / Network / External Threat / Antigena Suspicious Activity Block

MITRE ATT&CK Mapping

Tactic – Technique – Sub-Technique

Resource Development – T1588 - Malware

Initial Access - T1189 - Drive-by Compromise

Persistence – T1112 – Modify Registry

Command and Control – T1071 – Application Layer Protocol

Command and Control – T1095 – Non-application Layer Protocol

Command and Control – T1071 – Web Protocols

Command and Control – T1571 – Non-Standard Port

Command and Control – T1102 – One-Way Communication

List of Indicators of Compromise (IoCs)

86.54.24[.]29 - IP - Likely GhostSocks C2

http[://]86.54.24[.]29/Renewable[.]exe - Hostname - GhostSocks Distribution Endpoint

http[://]d2ihv8ymzp14lr.cloudfront[.]net/2021-08-19/udppump[.]exe - CDN - Payload Distribution Endpoint

www.lbfs[.]site - Hostname - Likely C2 Endpoint

retreaw[.]click - Hostname - Lumma C2 Endpoint

alltipi[.]com - Hostname - Possible C2 Endpoint

w2.bruggebogeyed[.]site - Hostname - Possible C2 Endpoint

9b90c62299d4bed2e0752e2e1fc777ac50308534 - SHA1 file hash – Likely GhostSocks payload

3d9d7a7905e46a3e39a45405cb010c1baa735f9e - SHA1 file hash - Likely follow-up payload

10f928e00a1ed0181992a1e4771673566a02f4e3 - SHA1 file hash - Likely follow-up payload

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About the author
Gernice Lee
Associate Principal Analyst & Regional Consultancy Lead

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March 24, 2026

Darktrace Unites Human Behavior and Threat Detection Across Email, Slack, Teams, and Zoom

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The communication attack surface is expanding

Modern attackers no longer focus solely on inboxes, they target people and the productivity systems where work actually happens. Meanwhile, the boundary between internal and external usage of tools is becoming blurrier everyday – turning the entire workplace into the attack surface. In 2025, identity compromise emerged as the single most consistent threat across the global threat landscape, as observed by Darktrace research across our entire customer base. Over 70% of incidents in the US involved SaaS/M365 account compromise and phishing or email-based social engineering, making credential abuse the single most effective initial access vector.

Despite this upward trend, investment in existing security awareness training (SAT) isn’t moving the needle on reducing risk. 84% of organizations still measure success through completion rates1, even though completion of standard training correlates with less than 2% real improvement in risky behavior.2 By prioritizing completion, organizations reward time spent rather than meaningful engagement, yet time in training doesn’t translate to retention or real-world decision-making. This compliance-first approach has left the workforce unprepared for the threats they actually face.

At the same time, attacks have evolved. Highly personalized, AI-generated campaigns now move fluidly across email, Slack, Teams, Zoom, and beyond, blending channels and even targeting systems directly through techniques like prompt injection. This new reality demands a different approach: one that treats people and the tools they use as a single ecosystem, where behavior and detection continuously inform and strengthen each other.

Only an adaptive communication security system can keep pace with the speed, creativity, and cross channel nature of today’s threats. 

Ushering in the adaptive era of workplace security

With this release, Darktrace brings together our new behavior-driven training solution with email detection, cross-channel visibility, and platform-level insights. Powered by Self-Learning AI, it delivers protection across both people and the communication tools they rely on every day, including email, Slack, Teams, and Zoom.

Each component learns from the others – training adapts to real user behavior, detection evolves across channels, and response is continuously refined – creating a powerful feedback loop that strengthens resilience and improves accuracy against today’s AI-driven threats.

Introducing: Unified training and email security for a self-improving email defense

Our brand new product, Darktrace / Adaptive Human Defense, closes the gap between human behavior and email security to continuously strengthen both people and defenses. Each user receives personalized training that adapts to their own inbox activity and skill level, with learning delivered directly within the flow of their day-to-day email interactions.

By learning from each user’s interactions with security training, it adapts security responses, creating a closed-loop system where training reinforces detection and detection informs training. Let’s look at some of the benefits.

  • Reduce successful phishing at the source with contextual Just in Time coaching: Contextual coaching appears directly in real email threads the moment risky behavior is detected, so habits change where mistakes actually happen. Configurable triggers and group policies target the right users, reducing repeated errors and administrative overhead.
  • Adaptive phishing simulations that progress automatically with each user: Embedded simulations vary in their degree of realism, from generic phishing to generative AI-enabled spear phishing. Users progress through the difficulty levels based on their performance to give an accurate picture of their phishing preparedness.  
  • Native email security integration turns human behavior into quantified risk: The native email security integration allows engagement, links clicked, and question success signals to flow back into / EMAIL recipes and models, so detection and response adapt automatically as users learn.  
  • Actionable risk and trend analytics beyond completion rates: Analytics that surface repeat offenders, high-value targets, and measurable exposure, moving beyond completion metrics to give leaders actionable insights tied to real behavior.

Learn more about / Adaptive Human Defense in the product solution brief.

Industry-first cross-channel full-message analysis for email, Slack, Teams, and Zoom

Darktrace now brings full-message analysis to Email, Slack, Teams, Zoom, and even generative AI prompts. The same leading behavioral analysis from EMAIL extends to every message, tracing intent, tone, relationships, and conversation flow across all communication activity for a complete understanding of every user interaction.

By correlating messaging and collaboration activity with email and account environments, cross-channel analysis reveals multi-domain attack paths and follows both users and threats as a single, continuous narrative – delivering better context to improve detection across the entire organization.

  • Eliminate cross-channel blind spots: Detect phishing, malware, account takeovers, and conversational manipulation across email and collaboration platforms, so attackers can’t exploit Slack, Teams, or Zoom as a new entry point. Unified behavioral analysis gives security teams a coherent, single view, for no more fragmented, channel-specific gaps.
  • Spot generative AI prompt injection attacks before they manipulate assistants: Dedicated models surface threats targeting corporate AI assistants – like ShadowLeak and Hashjack – before they can silently manipulate workflows, reducing risk before static filters catch up.

Learn more about Darktrace’s messaging security offering in the product solution brief.

Industry-first DMARC with bi-directional ASM and email security integration

Darktrace transforms domain protection by linking DMARC, attack surface intelligence, and email security into a single, continuously evolving workflow. Instead of treating domain authentication and exposure as separate tasks, this unified approach shows not just where domains are vulnerable, but how attackers are actively exploiting them.

  • Fix authentication weaknesses faster: SPF, DKIM, DMARC configurations, and external exposure data are analyzed together, giving teams clear guidance to correct weaknesses before they can be abused. Deep bidirectional integration with attack surface intelligence reduces impersonation risk at the source.
  • Accelerate email investigations: DMARC context is embedded directly into email workflows, enriching triage with authentication posture, internal/external sender lists, and seamless pivots between email and domain intelligence for faster, more accurate investigations.

Committed to innovation

These updates are part of a broader Darktrace release, which also includes:

Join our Live Launch Event on April 14, 2026.

Join us for an exclusive announcement event where Darktrace, the leader in AI-native cybersecurity, will be announcing our latest innovations, including  a demo of our new product / Adaptive Human Defense, an exclusive conversation with a Darktrace customer, and a deep dive into the Darktrace ActiveAI Security Portal.  

Register here.

References

[1] 84% of organizations still measure security awareness training success through completion rates, a vanity metric with no correlation to behavior change. (Source:  NIST Awareness Effectiveness Study, Forrester 2025)

[2] 'Limited benefit from embedded phishing training. Using randomized controlled trials and statistical modeling, embedded training provides a statistically-significant reduction in average failure rate, but of only 2%.' Ho, G., Mirian, A., Luo, E., Tong, K., Lee, E., Liu, L., Longhurst, C. A., Dameff, C., Savage, S., & Voelker, G. M. (2025). Understanding the Efficacy of Phishing Training in Practice. Proceedings of the 2025 IEEE Symposium on Security and Privacy.

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About the author
Carlos Gray
Senior Product Marketing Manager, Email
Your data. Our AI.
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