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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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June 3, 2026

Stopping Stealth Attacks with Precision: How Núclea Prevented a Breach Without Disruption

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Núclea is a Brazilian data and technology company that supports the country’s financial system by delivering digital services exclusively to banks and financial institutions. Operating in an environment where trust, availability, and data integrity are critical, the company faces a threat landscape that has evolved rapidly—particularly with the rise of AI-driven cyberattacks.

Brazil has experienced a wave of successful cyber incidents targeting financial institutions, many of them enabled by insiders or compromised credentials. The result was a noticeable shift in attacker strategy: instead of focusing on end customers, threat actors began targeting the institutions and platforms that underpin the financial ecosystem itself.

“Attacks became far more directed and contextual,” explains Guilherme, who leads incident response within Núclea’s security platform engineering team. “They weren’t noisy or obviously malicious—they were precise, patient, and designed to blend into normal operations.”

That precision was on full display in January 2026, when Núclea faced one of the most convincing phishing attacks the team had seen.

A real attack, built on trust and context

The attack began with a seemingly routine email.

It was sent from a real Brazilian government institution, using legitimate infrastructure and valid credentials that were later confirmed to have been compromised. Núclea had an established, ongoing relationship with this organization, and the email’s language, tone, and subject matter aligned perfectly with the type of communication the recipient team handled every day.

Attached to the email was a PDF document containing content that looked entirely legitimate.

The problem? A single URL embedded inside that PDF.

“The message itself was correct. The sender was real. The context was familiar. Even the document content made sense,” Guilherme explains. “There was just one small element that didn’t belong.”

That small detail was enough to initiate a full attack chain.

What the attackers were trying to do

If clicked, the URL would have downloaded a malicious payload designed to:

  • Collect information about the user and device
  • Identify where the system was located within the financial ecosystem
  • Install remote access tools to maintain control
  • Deploy an infostealer to extract sensitive data
  • Execute anti-forensic scripts to erase traces of the intrusion

In other words, it was a carefully engineered operation designed for persistence and stealth, not immediate disruption.

The attack also employed urgency—a classic social engineering technique. When the link didn’t open as expected, employees requested assistance from the security team, insisting the document was important and needed to be accessed quickly.

This is precisely the kind of scenario where traditional security tools struggle: almost everything about the interaction is legitimate.

Where Darktrace made the difference

Instead of blocking the entire message or relying on known indicators of compromise, Darktrace focused on behavioral context.

Darktrace recognized:

  • That the sending organization was normally trusted
  • That the communication pattern matched historical behavior
  • That the PDF content itself was not suspicious

But it also identified that the URL embedded within the document deviated from established behavioral patterns.

Rather than disrupting business operations, Darktrace took precise action: it rewrote the URL, preventing the malicious download while leaving the rest of the email untouched.

“When we analyzed it afterward, it became clear how dangerous the attack would have been,” says Guilherme. “But it never progressed—because Darktrace acted at exactly the right point.”

Subsequent forensic analysis confirmed the payload’s malicious intent. The attack never succeeded.

Precision over disruption

For Núclea, this incident reinforced a critical lesson: modern attacks don’t always look malicious—they hide within normal activity.

“What stands out to me is the precision,” Guilherme says. “Darktrace doesn’t rely on big, obvious signals. It’s effective in situations that fall outside the standard patterns we all know.”

Building resilience in a high trust ecosystem

For Núclea, cybersecurity is not just a defensive measure—it’s a business enabler.

Availability failures or successful breaches in the financial ecosystem can have immediate, large-scale consequences, from financial loss to reputational damage. Preventing those outcomes protects not just Núclea, but its partners and customers as well.

“Cyber resilience means keeping the business running—even under attack,” Guilherme explains. “And that requires people, processes, and technology working together.”

As AI continues to accelerate both attacks and defenses, the role of security is evolving. Precision, behavioral understanding, and intelligent automation are no longer optional—they’re essential.

“The easy days were yesterday,” Guilherme says. “The challenges ahead are bigger. We need to be prepared—internally and with partners that help us build resilience.”

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Mariana Pereira
VP, Field CISO

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June 1, 2026

Defend What You Trust: Stories from the Front Lines of Modern Cyber Defense

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Modern attacks don’t always announce themselves, follow obvious patterns, or rely on known malware. Often, they move quietly inside trusted systems, authenticated sessions, and everyday behavior.

They don’t break in. They blend in.

That’s why an AI-powered defense is essential. It turns invisible signals into actionable insights at a scale neither analysts nor traditional tools can achieve alone.

Confidence is creating risk

One of the most dangerous assumptions in cybersecurity today is that strong controls equal strong protection.

Multi-factor authentication (MFA), for example, is widely viewed as a foundational safeguard. But as the CISO for a professional sports organization explains, that confidence can be misplaced. “A lot of organizations assume that once you have MFA, those accounts are safe. That’s not true.”

In one instance, his team identified a sophisticated attack where a threat actor bypassed MFA entirely, not by breaking it, but by going around it. A user’s authenticated session was hijacked and re-used, allowing the attacker to impersonate them without triggering traditional controls.

“Darktrace picked up that a session had been re-injected by the hacker, and we were able to block it right away,” he explains.

Attackers anticipate what we miss

Even well-trained users can become entry points.

“An email bypassed our existing security tools,” shares the VP of IT at a U.S.-based risk management services provider.  “The user missed one signal and entered their credentials into a malicious site. That’s what the bad guys count on.”

The organization responded quickly, but not before damage was done. Crucially, this occurred while Darktrace was in “watch mode,” before autonomous response was fully enabled. “Darktrace would have seen that and shut it down immediately,” he notes.

Mistakes and oversights like misconfigurations, forgotten machines, and missed patches can create serious vulnerabilities.

The CIO of a utility services organization shares an instance when Darktrace detected a breach to a client’s network via their ZTNA VPN due to misconfigured MFA. “Darktrace alerted us and autonomously blocked the scanning, preventing what could have been a ransomware-type incident.”  

The most dangerous threats are already inside

The Head of Security at a global business services provider knows firsthand how blind spots can persist inside environments. His team uncovered evidence of dormant ransomware artifacts sitting unnoticed within a company’s environment ¬¬– long before modern detection was in place.

“During a routine file transfer, Darktrace flagged the suspicious activity, identified the ransomware, and immediately quarantined the server,” he recalls.  While the attack was never executed, the implication was significant: the risk existed long before it was finally detected.

Cyber threats are also successful because they take advantage of normal human behavior, exploiting moments of cognitive overload, urgency, and trust.

The Executive Director of IT and Business Applications at a pharmaceutical lab describes the time Darktrace flagged an employee logging into Microsoft 365 from Singapore, despite him being physically located in the U.S. Darktrace immediately cut off his access and within minutes revealed that the employee’s son was using a VPN to play a video game.

While the threat was benign, it demonstrated the strength of AI to use contextual information to detect threats other tools miss. The information also saved security analysts hours of investigation and minimized downtime for the employee. “That level of precision and speed isn’t just convenient, it’s game changing.”

“Unusual” behavior is the new red flag

Detecting modern threats requires an understanding of what “normal” looks like and recognizing when something subtly deviates.

One security leader  at an AI technology enterprise described a scenario in which an employee connected to a proxy service in China. The service itself was legitimate, and although traditional tools didn’t flag it, the behavior was unusual for that user specifically.

“That’s what Darktrace picked up on. The activity turned out to be benign, but without visibility into behavioral deviations, it could just as easily have been something more serious.”

AI shifts defense from reaction to anticipation

These stories point to a fundamental shift by cyber attackers, both tactically and strategically. Because traditional security tools were built to detect what’s already known, modern attacks are often:

  • Credential-based, not malware-based
  • Behavioral, not signature-based
  • Subtle, not overt

They may operate within the boundaries of what appears normal, exploiting what organizations trust, not what they block:

  • Trusted sessions
  • Legitimate services
  • Human error

This is where AI is changing the equation. Rather than relying on predefined rules or known threat signatures, AI can:

  • Establish a baseline of normal behavior
  • Detect subtle anomalies in real time
  • Act autonomously to contain potential threats

Resilience, not perfection, is the new security standard

As these frontline experiences show, the organizations that lead are those that move beyond reactive defense and embrace AI as a core part of their strategy.

It eliminates the blind spots and uncertainty, says the CISO of a professional sports organization. “If you lack visibility, you’re not managing risk, you’re assuming it. AI gives you the actionable insights needed to turn uncertainty into control.”

And it provides the speed and agility that are vital when seconds matter, says the Executive Director of IT and Business Applications. “When Darktrace alerted us at 3:00 am to a ransomware attack, it had already quarantined the affected systems, blocked the attacker’s access, and provided us with the critical details and time needed to investigate. That action likely saved us hundreds of thousands, if not millions, of dollars.”

The modern SOC has become a cornerstone of enterprise resilience, responsible for protecting data and operational continuity while enabling digital growth and innovation. For today’s security professional, that means success is no longer measured by what they keep out, but by what they protect: revenue, reputation, and trust.

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