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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 2, 2026

How Chinese-Nexus Cyber Operations Have Evolved – And What It Means For Cyber Risk and Resilience 

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Cybersecurity has traditionally organized risk around incidents, breaches, campaigns, and threat groups. Those elements still matter—but if we fixate on individual incidents, we risk missing the shaping of the entire ecosystem. Nation‑state–aligned operators are increasingly using cyber operations to establish long-term strategic leverage, not just to execute isolated attacks or short‑term objectives.  

Our latest research, Crimson Echo, shifts the lens accordingly. Instead of dissecting campaigns, malware families, or actor labels as discrete events, the threat research team analyzed Chinese‑nexus activity as a continuum of behaviors over time. That broader view reveals how these operators position themselves within environments: quietly, patiently, and persistently—often preparing the ground long before any recognizable “incident” occurs.  

How Chinese-nexus cyber threats have changed over time

Chinese-nexus cyber activity has evolved in four phases over the past two decades. This ranges from early, high-volume operations in the 1990s and early 2000s to more structured, strategically-aligned activity in the 2010s, and now toward highly adaptive, identity-centric intrusions.  

Today’s phase is defined by scale, operational restraint, and persistence. Attackers are establishing access, evaluating its strategic value, and maintaining it over time. This reflects a broader shift: cyber operations are increasingly integrated into long-term economic and geopolitical strategies. Access to digital environments, specifically those tied to critical national infrastructure, supply chains, and advanced technology, has become a form of strategic leverage for the long-term.  

How Darktrace analysts took a behavioral approach to a complex problem

One of the challenges in analyzing nation-state cyber activity is attribution. Traditional approaches often rely on tracking specific threat groups, malware families, or infrastructure. But these change constantly, and in the case of Chinese-nexus operations, they often overlap.

Crimson Echo is the result of a retrospective analysis of three years of anomalous activity observed across the Darktrace fleet between July 2022 and September 2025. Using behavioral detection, threat hunting, open-source intelligence, and a structured attribution framework (the Darktrace Cybersecurity Attribution Framework), the team identified dozens of medium- to high-confidence cases and analyzed them for recurring operational patterns.  

This long-horizon, behavior-centric approach allows Darktrace to identify consistent patterns in how intrusions unfold, reinforcing that behavioral patterns that matter.  

What the data shows

Several clear trends emerged from the analysis:

  • Targeting is concentrated in strategically important sectors. Across the dataset, 88% of intrusions occurred in organizations classified as critical infrastructure, including transportation, critical manufacturing, telecommunications, government, healthcare, and Information Technology (IT) services.  
  • Strategically important Western economies are a primary focus. The US alone accounted for 22.5% of observed cases, and when combined with major European economies including Germany, Italy, Spain and the UK, over half of all intrusions (55%) were concentrated in these regions.  
  • Nearly 63% of intrusions of intrusions began with the exploitation of internet-facing systems, reinforcing the continued risk posed by externally exposed infrastructure.  

Two models of cyber operations

Across the dataset, Chinese-nexus activity followed two operational models.  

The first is best described as “smash and grab.” These are short-horizon intrusions optimized for speed. Attackers move quickly – often exfiltrating data within 48 hours – and prioritize scale over stealth. The median duration of these compromises is around 10 days. It’s clear they are willing to risk detection for short-term gain.  

The second is “low and slow.” These operations were less prevalent in the dataset, but potentially more consequential. Here, attackers prioritize persistence, establishing durable access through identity systems and legitimate administrative tools, so they can maintain access undetected for months or even years. In one notable case, the actor had fully compromised the environment and established persistence, only to resurface in the environment more than 600 days after. The operational pause underscores both the depth of the intrusion and the actor’s long‑term strategic intent. This suggests that cyber access is a strategic asset to preserve and leverage over time, and we observed these attacks most often inin sectors of the high strategic importance.  

It’s important to note that the same operational ecosystem can employ both models concurrently, selecting the appropriate model based on target value, urgency, intended access. The observation of a “smash and grab” model should not be solely interpreted as a failure of tradecraft, but instead an operational choice likely aligned with objectives. Where “low and slow” operations are optimized for patience, smash and grab is optimized for speed; both seemingly are deliberate operational choices, not necessarily indicators of capability.  

Rethinking cyber risk

For many organizations, cyber risk is still framed as a series of discrete events. Something happens, it is detected and contained, and the organization moves on. But persistent access, particularly in deeply interconnected environments that span cloud, identity-based SaaS and agentic systems, and complex supply chain networks, creates a major ongoing exposure risk. Even in the absence of disruption or data theft, that access can provide insight into operations, dependencies, and strategic decision-making. Cyber risk increasingly resembles long-term competitive intelligence.  

This has impact beyond the Security Operations Center. Organizations need to shift how they think about governance, visibility, and resilience, and treat cyber exposure as a structural business risk instead of an incident response challenge.  

What comes next

The goal of this research is to provide a clearer understanding of how these operations work, so defenders can recognize them earlier and respond more effectively. That includes shifting from tracking indicators to understanding behaviors, treating identity providers as critical infrastructure risks, expanding supplier oversight, investing in rapid containment capabilities, and more.  

Learn more about the findings of Darktrace’s latest research, Crimson Echo: Understanding Chinese-nexus Cyber Operations Through Behavioral Analysis, by downloading the full report and summaries for business leaders, CISOs, and SOC analysts here.  

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Nathaniel Jones
VP, Security & AI Strategy, Field CISO

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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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