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January 18, 2024

Containerised Clicks: Malicious Use of 9hits on Vulnerable Docker Hosts

Cado Security Labs uncovered a new campaign targeting vulnerable Docker services. Attackers deploy XMRig miners and the 9hits viewer application to generate credits. This campaign highlights attackers' evolving monetization strategies and the ongoing vulnerability of exposed Docker hosts.
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
Nate Bill
Threat Researcher
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18
Jan 2024

Introduction: Malicious use of 9hits on vulnerable docker hosts

During routine monitoring of our honeypot infrastructure, Cado Security Labs researchers (now part of Darktrace) observed a novel campaign targeting vulnerable Docker services. The campaign deploys two containers to the vulnerable instance - a regular XMRig miner, as well as the 9hits viewer application. This was the first documented case of malware deploying the 9hits application as a payload, based on available open-source intelligence at the time.

9hits [1] describes itself as “A Unique Web Traffic Solution”. It is a platform where members can buy credits, which can then be exchanged for traffic being generated on their website of choice. Members can also run the 9hits viewer app, which runs a headless chrome instance in order to visit websites requested by other members, in exchange for a cut of the credits.

Screenshot from 9hits
Figure 1: Steps for using 9hits platform from viewer app

The viewer app responsible for generating hits and credits is now being deployed by malware, in order to generate credits for the attacker.

Initial access

The containers are deployed on the vulnerable Docker host over the Internet by an attacker-controlled server. Cado Security have been unable to obtain a copy of the spreader, however can speculate that the attacker discovered the honeypot via a service like Shodan. This is because the attacker’s IP does not have any entries in common abuse databases, suggesting it is not actively scanning. It is also possible the attacker is using a separate server for scanning.

After discovery, the spreader uses the Docker API to deploy two containers:

Jan 08 16:44:27 docker.novalocal dockerd[1014]: time="2024-01-08T16:44:27.619512372Z" level=debug msg="Calling POST /v1.43/images/create?fromImage=minerboy%2FXMRig&tag=latest" 
Jan 08 16:44:38 docker.novalocal dockerd[1014]: time="2024-01-08T16:44:38.725291585Z" level=debug msg="Calling POST /v1.43/images/create?fromImage=9hitste%2Fapp&tag=latest" 

This can also be seen reflected in the network capture of the honeypot, originating from IP 27[.]36.82.56 (An IP in Foshan, China). The IP 43[.]163.195.252 (Tencent hosting in Japan) has also been observed in the past.

Network capture
Figure 2: Network capture

Looking closer at the requests, we can observe a user agent of docker client:

User agent of docker client
Figure 3: User agent of docker client

Obviously, it is possible to clone a user agent and make it look like a Docker client. However, the order of API requests in the capture is identical to an actual instance of the Docker CLI. It is likely the attacker is using a script that sets the DOCKER_HOST variable and runs the regular CLI in order to compromise the server.  

The above API calls fetches off-the-shelf images from Dockerhub for the 9hits and XMRig software. This is a common attack vector for campaigns targeting Docker, where instead of fetching a bespoke image for their purposes they pull a generic image off Dockerhub (which will almost always be accessible) and leverage it for their needs.

In Cado’s investigations of campaigns targeting our honeypot, attackers often used a generic Alpine image and attach to it in order to break out of the container and run their malware on the host. In this case, the attacker makes no attempt to exit the container, and instead just runs the container with a predetermined argument.

Payload operation

As mentioned previously, the spreader invokes the Docker container with a custom command to kick start the infection. This command includes configuration and session identifiers.

Using memory forensics, the following processes being run by the 9hits container can be observed:

pid	  ppid	proc	cmd 
2379	2358	nh.sh	/bin/bash /nh.sh --token=c89f8b41d4972209ec497349cce7e840 --system-session --allow-crypto=no 
2406	2379	Xvfb	Xvfb :1 
2407	2379	9hits	/etc/9hitsv3-linux64/9hits --mode=exchange --current-hash=1704770235 --hide-browser=no --token=c89f8b41d4972209ec497349cce7e840 --allow-popups=yes --allow-adult=yes --allow-crypto=no --system-session --cache-del=200 --single-process --no-sandbox --no-zygote --auto-start 
2508	2455	9hbrowser	/etc/9hitsv3-linux64/browser/9hbrowser --nh-param=b2e931191f49d --ssid=<honeypot IP> 

In this case, the entry point for the container is the “ nh.sh ” script, which the attacker has added their session token to. This allows the 9hits app to authenticate with their servers and pull a list of sites to visit from them. Once the app has visited the site, the owner of the session token is awarded with a credit on the 9hits platform.

It appears that 9hits designed the session token system to work in untrusted contexts. It’s impossible to use the token for anything other than running the app to generate credits for the token owner, with the API and authentication tokens being a separate system. This allows the app to be run in illegitimate campaigns without the risk of the attacker's account being compromised.

9hits itself is based on headless Chrome, and as can be seen from the other processes, a browser instance is spawned to visit websites. The no sandbox, single process, and no zygote arguments are frequently passed to Chrome browsers running as root or in containers. There are a few other options that are set for this campaign, such as allowing it to visit adult sites, allowing it to visit sites that show popups, and configuring the cache duration. In addition, the actor behind this campaign has disabled the 9hits app’s ability to visit crypto related sites. The reason for this is unclear.

On the other container deployed by the attacker (XMRig), we can see it executes the following:

<code>1572	1552	XMRig	/app/XMRig -o byw.dscloud.me:3333 --randomx-1gb-pages --donate-level=0</code> 

The -o option specifies a mining pool to use. Most XMRig deployments will use a public pool and tell it the owner's wallet address, which can be frequently combined with the pool’s public data to see how many machines are mining for that address, along with the earnings of the owner. However, in this case it would appear that the mining pool is private, preventing access to statistics related to the campaign.

The dscloud domain is used by synology for dynamic DNS, where the synology server will keep the domain updated with the current IP of the attacker. Performing a lookup for this address at the time of writing, we can see it resolves to 27[.]36.82.56, the same IP that infected the honeypot in the first place.

Conclusion

The main impact of this campaign on compromised hosts is resource exhaustion, as the XMRig miner will use all available CPU resources it can while 9hits will use a large amount of bandwidth, memory, and what little CPU is left. The result of this is that legitimate workloads on infected servers will be unable to perform as expected. In addition, the campaign could be updated to leave a remote shell on the system, potentially causing a more serious breach. This has been seen before with mexals/diicot [2], a Romanian threat actor that maintained access to compromised servers using a malicious SSH key in addition to executing XMRig.

This campaign demonstrates that attackers are always looking for more strategies to make money from compromised hosts. It additionally shows that exposed Docker hosts are still a common entry vector for attackers. As Docker allows users to run arbitrary code, it is critical that it is kept secure to avoid your systems being used for malicious purposes.

IoCs

Docker container name Docker container image

faucet 9hitste/app

xmg minerboy/XMRig

Mining pool

byw.dscloud.me:3333

Session token

c89f8b41d4972209ec497349cce7e840

References:

[1] https://9hits.com/

[2] https://www.darktrace.com/blog/tracking-diicot-an-emerging-romanian-threat-actor

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
Nate Bill
Threat Researcher

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April 1, 2026

AI-powered security for a rapidly growing grocery enterprise

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Protecting a complex, fast-growing retail organization

For this multi-banner grocery holding organization, cybersecurity is considered an essential business enabler, protecting operations, growth, and customer trust. The organization’s lean IT team manages a highly distributed environment spanning corporate offices, 100+ stores, distribution centers and  thousands of endpoints, users, and third-party connections.

Mergers and acquisitions fueled rapid growth, but they also introduced escalating complexity that constrained visibility into users, endpoints, and security risks inherited across acquired environments.

Closing critical visibility gaps with limited resources

Enterprise-wide visibility is a top priority for the organization, says the  Vice President of Information Technology. “We needed insights beyond the perimeter into how users and devices were behaving across the organization.”

A security breach that occurred before the current IT leadership joined the company reinforced the urgency and elevated cybersecurity to an executive-level priority with a focus on protecting customer trust. The goal was to build a multi-layered security model that could deliver autonomous, enterprise-wide protection without adding headcount.

Managing cyber risk in M&A

Mergers and acquisitions are central to the grocery holding company’s growth strategy. But each transaction introduces new cyber risk, including inherited network architectures, inconsistent tooling, excessive privileges, and remnants of prior security incidents that were never fully remediated.

“Our M&A targets range from small chains with a single IT person and limited cyber tools to large chains with more developed IT teams, toolsets and instrumentation,” explains the VP of IT. “We needed a fast, repeatable, and reliable way to assess cyber risk before transactions closed.”

AI-driven security built for scale, speed, and resilience

Rather than layering additional point tools onto an already complex environment, the retailer adopted the Darktrace ActiveAI Security Platform™ in 2020 as part of a broader modernization effort to improve resilience, close visibility gaps, and establish a security foundation that could scale with growth.

“Darktrace’s AI-driven approach provided the ideal solution to these challenges,” shares the VP of IT. “It has empowered our organization to maintain a robust security strategy, ensuring the protection of our network and the smooth operation of our business.”

Enterprise-wide visibility into traffic  

By monitoring both north-south and east-west traffic and applying Self-Learning AI, Darktrace develops a dynamic understanding of how users and devices normally behave across locations, roles, and systems.

“Modeling normal behavior across the environment enables us to quickly spot behavior that doesn’t fit. Even subtle changes that could signal a threat but appear legitimate at first glance,” explains the VP of IT.

Real-time threat containment, 24/7

Adopting autonomous response has created operational breathing room for the security team, says the company’s Cybersecurity  Engineer.

“Early on, we enabled full Darktrace autonomous mode and we continue to do so today,” shares the IT Security Architect. “Allowing the technology to act first gives us the time we need to investigate incidents during business hours without putting the business at risk.”

Unified, actionable view of security ecosystem

The grocery retailer integrated Darktrace with its existing security ecosystem of firewalls, vulnerability management tools, and endpoint detection and response, and the VP of IT described the adoption process as “exceptionally smooth.”

The team can correlate enterprise-wide security data for a unified and actionable picture of all activity and risk. Using this “single pane of glass” approach, the retailer trains Level 1 and Level 2 operations staff to assist with investigations and user follow-ups, effectively extending the reach of the security function without expanding headcount.

From reactive defense to security at scale

With Darktrace delivering continuous visibility, autonomous containment, and integrated security workflows, the organization has strengthened its cybersecurity posture while improving operational efficiency. The result is a security model that not only reduces risk, but also supports growth, resilience, and informed decision-making at the business level.

Faster detection, faster resolution

With autonomous detection and response, the retailer can immediately contain risk while analysts investigate and validate activity. With this approach, the company can maintain continuous protection even outside business hours and reduce the chance of lateral spread across systems or locations.

Enterprise-grade protection with a lean team

From cloud environments to clients to SaaS collaboration tools, Darktrace provides holistic autonomous AI defense, processing petabytes of the organization’s network traffic and investigating millions of individual events that could be indicative of a wider incident.

Today, Darktrace autonomously conducts the majority of all investigations on behalf of the IT team, escalating only a tiny fraction for analyst review. The impact has been profound, freeing analysts from endless alerts and hours of triage so they can focus on more valuable, proactive, and gratifying work.

“From an operational perspective, Darktrace gives us time back,” says the Cybersecurity Engineer. More importantly, says the VP of IT, “it gives us peace of mind that we’re protected even if we’re not actively monitoring every alert.”

A strategic input for M&A decision-making

One of the most strategic outcomes has been the role of cybersecurity on M&A. 90 days prior to closing a transaction, the security team uses Darktrace alongside other tools to perform a cyber risk assessment of the potential acquisition. “Our approach with Darktrace has consistently identified gaps and exposed risks,” says the VP of IT, including:

  • Remnants of previous incidents that were never fully remediated
  • Network configurations with direct internet exposure
  • Excessive administrative privileges in Active Directory or on critical hosts

While security findings may not alter deal timelines, the VP of IT says they can have enormous business implications. “With early visibility into these risks, we can reduce exposure to inherited cyber threats, strengthen our position during negotiations, and establish clear remediation requirements.”

A security strategy built to evolve with the business

As the holding group expands its cloud footprint, it will extend Darktrace protections into Azure, applying the same AI-driven visibility and autonomous response to cloud workloads. The VP of IT says Darktrace's evolving capabilities will be instrumental in addressing the organization’s future cybersecurity needs and ability to adapt to the dynamic nature of cloud security.

“With Darktrace’s AI-driven approach, we have moved beyond reactive defense, establishing a resilient security foundation for confident expansion and modernization.”

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March 31, 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
Isabel Evans
Cyber Analyst
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