Blog
/
Network
/
May 25, 2022

Uncovering the Sysrv-Hello Crypto-Jacking Bonet

Discover the cyber kill chain of a Sysrv-hello botnet infection in France and gain insights into the latest TTPs of the botnet in March and April 2022.
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
Shuh Chin Goh
Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
25
May 2022

In recent years, the prevalence of crypto-jacking botnets has risen in tandem with the popularity and value of cryptocurrencies. Increasingly crypto-mining malware programs are distributed by botnets as they allow threat actors to harness the cumulative processing power of a large number of machines (discussed in our other Darktrace blogs.1 2 One of these botnets is Sysrv-hello, which in addition to crypto-mining, propagates aggressively across the Internet in a worm-like manner by trolling for Remote Code Execution (RCE) vulnerabilities and SSH worming from the compromised victim devices. This all has the purpose of expanding the botnet.

First identified in December 2020, Sysrv-hello’s operators constantly update and change the bots’ behavior to evolve and stay ahead of security researchers and law enforcement. As such, infected systems can easily go unnoticed by both users and organizations. This blog examines the cyber kill chain sequence of a Sysrv-hello botnet infection detected at the network level by Darktrace DETECT/Network, as well as the botnet’s tactics, techniques, and procedures (TTPs) in March and April 2022.

Figure 1: Timeline of the attack

Delivery and exploitation

The organization, which was trialing Darktrace, had deployed the technology on March 2, 2022. On the very same day, the initial host infection was seen through the download of a first-stage PowerShell loader script from a rare external endpoint by a device in the internal network. Although initial exploitation of the device happened prior to the installation and was not observed, this botnet is known to target RCE vulnerabilities in various applications such as MySQL, Tomcat, PHPUnit, Apache Solar, Confluence, Laravel, JBoss, Jira, Sonatype, Oracle WebLogic and Apache Struts to gain initial access to internal systems.3 Recent iterations have also been reported to have been deployed via drive-by-downloads from an empty HTML iframe pointing to a malicious executable that downloads to the device from a user visiting a compromised website.4

Initial intrusion

The Sysrv-hello botnet is distributed for both Linux and Windows environments, with the corresponding compatible script pulled based on the architecture of the system. In this incident, the Windows version was observed.

On March 2, 2022 at 15:15:28 UTC, the device made a successful HTTP GET request to a malicious IP address5 that had a rarity score of 100% in the network. It subsequently downloaded a malicious PowerShell script named ‘ldr.ps1'6 onto the system. The associated IP address ‘194.145.227[.]21’ belongs to ‘ASN AS48693 Rices Privately owned enterprise’ and had been identified as a Sysrv-hello botnet command and control (C2) server in April the previous year. 3

Looking at the URI ‘/ldr.ps1?b0f895_admin:admin_81.255.222.82:8443_https’, it appears some form of query was being executed onto the object. The question mark ‘?’ in this URI is used to delimit the boundary between the URI of the queryable object and the set of strings used to express a query onto that object. Conventionally, we see the set of strings contains a list of key/value pairs with equal signs ‘=’, which are separated by the ampersand symbol ‘&’ between each of those parameters (e.g. www.youtube[.]com/watch?v=RdcCjDS0s6s&ab_channel=SANSCyberDefense), though the exact structure of the query string is not standardized and different servers may parse it differently. Instead, this case saw a set of strings with the hexadecimal color code #b0f895 (a light shade of green), admin username and password login credentials, and the IP address ‘81.255.222[.]82’ being applied during the object query (via HTTPS protocol on port 8443). In recent months this French IP has also had reports of abuse from the OSINT community.7

On March 2, 2022 at 15:15:33 UTC, the PowerShell loader script further downloaded second-stage executables named ‘sys.exe’ and ‘xmrig.2 sver.8 9 These have been identified as the worm and cryptocurrency miner payloads respectively.

Establish foothold

On March 2, 2022 at 17:46:55 UTC, after the downloads of the worm and cryptocurrency miner payloads, the device initiated multiple SSL connections in a regular, automated manner to Pastebin – a text storage website. This technique was used as a vector to download/upload data and drop further malicious scripts onto the host. OSINT sources suggest the JA3 client SSL fingerprint (05af1f5ca1b87cc9cc9b25185115607d) is associated with PowerShell usage, corroborating with the observation that further tooling was initiated by the PowerShell script ‘ldr.ps1’.

Continual Pastebin C2 connections were still being made by the device almost two months since the initiation of such connections. These Pastebin C2 connections point to new tactics and techniques employed by Sysrv-hello — reports earlier than May do not appear to mention any usage of the file storage site. These new TTPs serve two purposes: defense evasion using a web service/protocol and persistence. Persistence was likely achieved through scheduling daemons downloaded from this web service and shellcode executions at set intervals to kill off other malware processes, as similarly seen in other botnets.10 Recent reports have seen other malware programs also switch to Pastebin C2 tunnels to deliver subsequent payloads, scrapping the need for traditional C2 servers and evading detection.11

Figure 2: A section of the constant SSL connections that the device was still making to ‘pastebin[.]com’ even in the month of April, which resembles beaconing scheduled activity

Throughout the months of March and April, suspicious SSL connections were made from a second potentially compromised device in the internal network to the infected breach device. The suspicious French IP address ‘81.255.222[.]82’ previously seen in the URI object query was revealed as the value of the Server Name Indicator (SNI) in these SSL connections where, typically, a hostname or domain name is indicated.

After an initial compromise, attackers usually aim to gain long-term remote shell access to continue the attack. As the breach device does not have a public IP address and is most certainly behind a firewall, for it to be directly accessible from the Internet a reverse shell would need to be established. Outgoing connections often succeed because firewalls generally filter only incoming traffic. Darktrace observed the device making continuous outgoing connections to an external host listening on an unusual port, 8443, indicating the presence of a reverse shell for pivoting and remote administration.

Figure 3: SSL connections to server name ‘81.255.222[.]8’ at end of March and start of April

Accomplish mission

On March 4, 2022 at 15:07:04 UTC, the device made a total of 16,029 failed connections to a large volume of external endpoints on the same port (8080). This behavior is consistent with address scanning. From the country codes, it appears that public IP addresses for various countries around the world were contacted (at least 99 unique addresses), with the US being the most targeted.

From 19:44:36 UTC onwards, the device performed cryptocurrency mining using the Minergate mining pool protocol to generate profits for the attacker. A login credential called ‘x’ was observed in the Minergate connections to ‘194.145.227[.]21’ via port 5443. JSON-RPC methods of ‘login’ and ‘submit’ were seen from the connection originator (the infected breach device) and ‘job’ was seen from the connection responder (the C2 server). A high volume of connections using the JSON-RPC application protocol to ‘pool-fr.supportxmr[.]com’ were also made on port 80.

When the botnet was first discovered in December 2020, mining pools MineXMR and F2Pool were used. In February 2021, MineXMR was removed and in March 2021, Nanopool mining pool was added,12 before switching to the present SupportXMR and Minergate mining pools. Threat actors utilize such proxy pools to help hide the actual crypto wallet address where the contributions are made by the crypto-mining activity. From April onwards, the device appears to download the ‘xmrig.exe’ executable from a rare IP address ‘61.103.177[.]229’ in Korea every few days – likely in an attempt to establish persistency and ensure the cryptocurrency mining payload continues to exist on the compromised system for continued mining.

On March 9, 2022 from 18:16:20 UTC onwards, trolling for various RCE vulnerabilities (including but not limited to these four) was observed over HTTP connections to public IP addresses:

  1. Through March, the device made around 5,417 HTTP POSTs with the URI ‘/vendor/phpunit/phpunit/src/Util/PHP/eval-stdin.php’ to at least 99 unique public IPs. This appears to be related to CVE-2017-9841, which in PHPUnit allows remote attackers to execute arbitrary PHP code via HTTP POST data beginning with a ‘13 PHPUnit is a common testing framework for PHP, used for performing unit tests during application development. It is used by a variety of popular Content Management Systems (CMS) such as WordPress, Drupal and Prestashop. This CVE has been called “one of the most exploitable CVEs of 2019,” with around seven million attack attempts being observed that year.14 This framework is not designed to be exposed on the critical paths serving web pages and should not be reachable by external HTTP requests. Looking at the status messages of the HTTP POSTs in this incident, some ‘Found’ and ‘OK’ messages were seen, suggesting the vulnerable path could be accessible on some of those endpoints.

Figure 4: PCAP of CVE-2017-9841 vulnerability trolling

Figure 5: The CVE-2017-9841 vulnerable path appears to be reachable on some endpoints

  1. Through March, the device also made around 5,500 HTTP POSTs with the URI ‘/_ignition/execute-solution’ to at least 99 unique public IPs. This appears related to CVE-2021-3129, which allows unauthenticated remote attackers to execute arbitrary code using debug mode with Laravel, a PHP web application framework in versions prior to 8.4.2.15 The POST request below makes the variable ‘username’ optional, and the ‘viewFile’ parameter is empty, as a test to see if the endpoint is vulnerable.16

Figure 6: PCAP of CVE-2021-3129 vulnerability trolling

  1. The device made approximately a further 252 HTTP GETs with URIs containing ‘invokefunction&function’ to another minimum of 99 unique public IPs. This appears related to a RCE vulnerability in ThinkPHP, an open-source web framework.17

Figure 7: Some of the URIs associated with ThinkPHP RCE vulnerability

  1. A HTTP header related to a RCE vulnerability for the Jakarta Multipart parser used by Apache struts2 in CVE-2017-563818 was also seen during the connection attempts. In this case the payload used a custom Content-Type header.

Figure 8: PCAP of CVE-2017-5638 vulnerability trolling

Two widely used methods of SSH authentication are public key authentication and password authentication. After gaining a foothold in the network, previous reports3 19 have mentioned that Sysrv-hello harvests private SSH keys from the compromised device, along with identifying known devices. Being a known device means the system can communicate with the other system without any further authentication checks after the initial key exchange. This technique was likely performed in conjunction with password brute-force attacks against the known devices. Starting from March 9, 2022 at 20:31:25 UTC, Darktrace observed the device making a large number of SSH connections and login failures to public IP ranges. For example, between 00:05:41 UTC on March 26 and 05:00:02 UTC on April 14, around 83,389 SSH connection attempts were made to 31 unique public IPs.

Figure 9: Darktrace’s Threat Visualizer shows large spikes in SSH connections by the breach device

Figure 10: Beaconing SSH connections to a single external endpoint, indicating a potential brute-force attack

Darktrace coverage

Cyber AI Analyst was able to connect the events and present them in a digestible, chronological order for the organization. In the aftermath of any security incidents, this is a convenient way for security users to conduct assisted investigations and reduce the workload on human analysts. However, it is good to note that this activity was also easily observed in real time from the model section on the Threat Visualizer due to the large number of escalating model breaches.

Figure 11: Cyber AI Analyst consolidating the events in the month of March into a summary

Figure 12: Cyber AI Analyst shows the progression of the attack through the month of March

As this incident occurred during a trial, Darktrace RESPOND was enabled in passive mode – with a valid license to display the actions that it would have taken, but with no active control performed. In this instance, no Antigena models breached for the initial compromised device as it was not tagged to be eligible for Antigena actions. Nonetheless, Darktrace was able to provide visibility into these anomalous connections.

Had Antigena been deployed in active mode, and the breach device appropriately tagged with Antigena All or Antigena External Threat, Darktrace would have been able to respond and neutralize different stages of the attack through network inhibitors Block Matching Connections and Enforce Group Pattern of Life, and relevant Antigena models such as Antigena Suspicious File Block, Antigena Suspicious File Pattern of Life Block, Antigena Pastebin Block and Antigena Crypto Currency Mining Block. The first of these inhibitors, Block Matching Connections, will block the specific connection and all future connections that matches the same criteria (e.g. all future outbound HTTP connections from the breach device to destination port 80) for a set period of time. Enforce Group Pattern of Life allows a device to only make connections and data transfers that it or any of its peer group typically make.

Conclusion

Resource hijacking results in unauthorized consumption of system resources and monetary loss for affected organizations. Compromised devices can potentially be rented out to other threat actors and botnet operators could switch from conducting crypto-mining to other more destructive illicit activities (e.g. DDoS or dropping of ransomware) whilst changing their TTPs in the future. Defenders are constantly playing catch-up to this continual evolution, and retrospective rules and signatures solutions or threat intelligence that relies on humans to spot future threats will not be able to keep up.

In this case, it appears the botnet operator has added an object query in the URL of the initial PowerShell loader script download, added Pastebin C2 for evasion and persistence, and utilized new cryptocurrency mining pools. Despite this, Darktrace’s Self-Learning AI was able to identify the threats the moment attackers changed their approach, detecting every step of the attack in the network without relying on known indicators of threat.

Appendix

Darktrace model detections

  • Anomalous File / Script from Rare Location
  • Anomalous File / EXE from Rare External Location
  • Compromise / Agent Beacon (Medium Period)
  • Compromise / Slow Beaconing Activity To External Rare
  • Compromise / Beaconing Activity To External Rare
  • Device / External Address Scan
  • Compromise / Crypto Currency Mining Activity
  • Compromise / High Priority Crypto Currency Mining
  • Compromise / High Volume of Connections with Beacon Score
  • Compromise / SSL Beaconing to Rare Destination
  • Anomalous Connection / Multiple HTTP POSTs to Rare Hostname
  • Device / Large Number of Model Breaches
  • Anomalous Connection / Multiple Failed Connections to Rare Endpoint
  • Anomalous Connection / SSH Brute Force
  • Compromise / SSH Beacon
  • Compliance / SSH to Rare External AWS
  • Compromise / High Frequency SSH Beacon
  • Compliance / SSH to Rare External Destination
  • Device / Multiple C2 Model Breaches
  • Anomalous Connection / POST to PHP on New External Host

MITRE ATT&CK techniques observed:

IoCs

Thanks to Victoria Baldie and Yung Ju Chua for their contributions.

Footnotes

1. https://www.darktrace.com/en/blog/crypto-botnets-moving-laterally

2. https://www.darktrace.com/en/blog/how-ai-uncovered-outlaws-secret-crypto-mining-operation

3. https://www.lacework.com/blog/sysrv-hello-expands-infrastructure

4. https://www.riskiq.com/blog/external-threat-management/sysrv-hello-cryptojacking-botnet

5. https://www.virustotal.com/gui/ip-address/194.145.227.21

6. https://www.virustotal.com/gui/url/c586845daa2aec275453659f287dcb302921321e04cb476b0d98d731d57c4e83?nocache=1

7. https://www.abuseipdb.com/check/81.255.222.82

8. https://www.virustotal.com/gui/file/586e271b5095068484446ee222a4bb0f885987a0b77e59eb24511f6d4a774c30

9. https://www.virustotal.com/gui/file/f5bef6ace91110289a2977cfc9f4dbec1e32fecdbe77326e8efe7b353c58e639

10. https://www.ironnet.com/blog/continued-exploitation-of-cve-2021-26084

11. https://www.zdnet.com/article/njrat-trojan-operators-are-now-using-pastebin-as-alternative-to-central-command-server

12. https://blogs.juniper.net/en-us/threat-research/sysrv-botnet-expands-and-gains-persistence

13. https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2017-9841

14. https://www.imperva.com/blog/the-resurrection-of-phpunit-rce-vulnerability

15. https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-3129

16. https://isc.sans.edu/forums/diary/Laravel+v842+exploit+attempts+for+CVE20213129+debug+mode+Remote+code+execution/27758

17. https://securitynews.sonicwall.com/xmlpost/thinkphp-remote-code-execution-rce-bug-is-actively-being-exploited

18. https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2017-5638

19. https://sysdig.com/blog/crypto-sysrv-hello-wordpress

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
Shuh Chin Goh

More in this series

No items found.

Blog

/

Email

/

September 30, 2025

Out of Character: Detecting Vendor Compromise and Trusted Relationship Abuse with Darktrace

Default blog imageDefault blog image

What is Vendor Email Compromise?

Vendor Email Compromise (VEC) refers to an attack where actors breach a third-party provider to exploit their access, relationships, or systems for malicious purposes. The initially compromised entities are often the target’s existing partners, though this can extend to any organization or individual the target is likely to trust.

It sits at the intersection of supply chain attacks and business email compromise (BEC), blending technical exploitation with trust-based deception. Attackers often infiltrate existing conversations, leveraging AI to mimic tone and avoid common spelling and grammar pitfalls. Malicious content is typically hosted on otherwise reputable file sharing platforms, meaning any shared links initially seem harmless.

While techniques to achieve initial access may have evolved, the goals remain familiar. Threat actors harvest credentials, launch subsequent phishing campaigns, attempt to redirect invoice payments for financial gain, and exfiltrate sensitive corporate data.

Why traditional defenses fall short

These subtle and sophisticated email attacks pose unique challenges for defenders. Few busy people would treat an ongoing conversation with a trusted contact with the same level of suspicion as an email from the CEO requesting ‘URGENT ASSISTANCE!’ Unfortunately, many traditional secure email gateways (SEGs) struggle with this too. Detecting an out-of-character email, when it does not obviously appear out of character, is a complex challenge. It’s hardly surprising, then, that 83% of organizations have experienced a security incident involving third-party vendors [1].  

This article explores how Darktrace detected four different vendor compromise campaigns for a single customer, within a two-week period in 2025.  Darktrace / EMAIL successfully identified the subtle indicators that these seemingly benign emails from trusted senders were, in fact, malicious. Due to the configuration of Darktrace / EMAIL in this customer’s environment, it was unable to take action against the malicious emails. However, if fully enabled to take Autonomous Response, it would have held all offending emails identified.

How does Darktrace detect vendor compromise?

The answer lies at the core of how Darktrace operates: anomaly detection. Rather than relying on known malicious rules or signatures, Darktrace learns what ‘normal’ looks like for an environment, then looks for anomalies across a wide range of metrics. Despite the resourcefulness of the threat actors involved in this case, Darktrace identified many anomalies across these campaigns.

Different campaigns, common traits

A wide variety of approaches was observed. Individuals, shared mailboxes and external contractors were all targeted. Two emails originated from compromised current vendors, while two came from unknown compromised organizations - one in an associated industry. The sender organizations were either familiar or, at the very least, professional in appearance, with no unusual alphanumeric strings or suspicious top-level domains (TLDs). Subject line, such as “New Approved Statement From [REDACTED]” and “[REDACTED] - Proposal Document” appeared unremarkable and were not designed to provoke heightened emotions like typical social engineering or BEC attempts.

All emails had been given a Microsoft Spam Confidence Level of 1, indicating Microsoft did not consider them to be spam or malicious [2]. They also passed authentication checks (including SPF, and in some cases DKIM and DMARC), meaning they appeared to originate from an authentic source for the sender domain and had not been tampered with in transit.  

All observed phishing emails contained a link hosted on a legitimate and commonly used file-sharing site. These sites were often convincingly themed, frequently featuring the name of a trusted vendor either on the page or within the URL, to appear authentic and avoid raising suspicion. However, these links served only as the initial step in a more complex, multi-stage phishing process.

A legitimate file sharing site used in phishing emails to host a secondary malicious link.
Figure 1: A legitimate file sharing site used in phishing emails to host a secondary malicious link.
Another example of a legitimate file sharing endpoint sent in a phishing email and used to host a malicious link.
Figure 2: Another example of a legitimate file sharing endpoint sent in a phishing email and used to host a malicious link.

If followed, the recipient would be redirected, sometimes via CAPTCHA, to fake Microsoft login pages designed to capturing credentials, namely http://pub-ac94c05b39aa4f75ad1df88d384932b8.r2[.]dev/offline[.]html and https://s3.us-east-1.amazonaws[.]com/s3cure0line-0365cql0.19db86c3-b2b9-44cc-b339-36da233a3be2ml0qin/s3cccql0.19db86c3-b2b9-44cc-b339-36da233a3be2%26l0qn[.]html#.

The latter made use of homoglyphs to deceive the user, with a link referencing ‘s3cure0line’, rather than ‘secureonline’. Post-incident investigation using open-source intelligence (OSINT) confirmed that the domains were linked to malicious phishing endpoints [3] [4].

Fake Microsoft login page designed to harvest credentials.
Figure 3: Fake Microsoft login page designed to harvest credentials.
Phishing kit with likely AI-generated image, designed to harvest user credentials. The URL uses ‘s3cure0line’ instead of ‘secureonline’, a subtle misspelling intended to deceive users.
Figure 4: Phishing kit with likely AI-generated image, designed to harvest user credentials. The URL uses ‘s3cure0line’ instead of ‘secureonline’, a subtle misspelling intended to deceive users.

Darktrace Anomaly Detection

Some senders were unknown to the network, with no previous outbound or inbound emails. Some had sent the email to multiple undisclosed recipients using BCC, an unusual behavior for a new sender.  

Where the sender organization was an existing vendor, Darktrace recognized out-of-character behavior, in this case it was the first time a link to a particular file-sharing site had been shared. Often the links themselves exhibited anomalies, either being unusually prominent or hidden altogether - masked by text or a clickable image.

Crucially, Darktrace / EMAIL is able to identify malicious links at the time of processing the emails, without needing to visit the URLs or analyze the destination endpoints, meaning even the most convincing phishing pages cannot evade detection – meaning even the most convincing phishing emails cannot evade detection. This sets it apart from many competitors who rely on crawling the endpoints present in emails. This, among other things, risks disruption to user experience, such as unsubscribing them from emails, for instance.

Darktrace was also able to determine that the malicious emails originated from a compromised mailbox, using a series of behavioral and contextual metrics to make the identification. Upon analysis of the emails, Darktrace autonomously assigned several contextual tags to highlight their concerning elements, indicating that the messages contained phishing links, were likely sent from a compromised account, and originated from a known correspondent exhibiting out-of-character behavior.

A summary of the anomalous email, confirming that it contained a highly suspicious link.
Figure 5: Tags assigned to offending emails by Darktrace / EMAIL.

Figure 6: A summary of the anomalous email, confirming that it contained a highly suspicious link.

Out-of-character behavior caught in real-time

In another customer environment around the same time Darktrace / EMAIL detected multiple emails with carefully crafted, contextually appropriate subject lines sent from an established correspondent being sent to 30 different recipients. In many cases, the attacker hijacked existing threads and inserted their malicious emails into an ongoing conversation in an effort to blend in and avoid detection. As in the previous, the attacker leveraged a well-known service, this time ClickFunnels, to host a document containing another malicious link. Once again, they were assigned a Microsoft Spam Confidence Level of 1, indicating that they were not considered malicious.

The legitimate ClickFunnels page used to host a malicious phishing link.
Figure 7: The legitimate ClickFunnels page used to host a malicious phishing link.

This time, however, the customer had Darktrace / EMAIL fully enabled to take Autonomous Response against suspicious emails. As a result, when Darktrace detected the out-of-character behavior, specifically, the sharing of a link to a previously unused file-sharing domain, and identified the likely malicious intent of the message, it held the email, preventing it from reaching recipients’ inboxes and effectively shutting down the attack.

Figure 8: Darktrace / EMAIL’s detection of malicious emails inserted into an existing thread.*

*To preserve anonymity, all real customer names, email addresses, and other identifying details have been redacted and replaced with fictitious placeholders.

Legitimate messages in the conversation were assigned an Anomaly Score of 0, while the newly inserted malicious emails identified and were flagged with the maximum score of 100.

Key takeaways for defenders

Phishing remains big business, and as the landscape evolves, today’s campaigns often look very different from earlier versions. As with network-based attacks, threat actors are increasingly leveraging legitimate tools and exploiting trusted relationships to carry out their malicious goals, often staying under the radar of security teams and traditional email defenses.

As attackers continue to exploit trusted relationships between organizations and their third-party associates, security teams must remain vigilant to unexpected or suspicious email activity. Protecting the digital estate requires an email solution capable of identifying malicious characteristics, even when they originate from otherwise trusted senders.

Credit to Jennifer Beckett (Cyber Analyst), Patrick Anjos (Senior Cyber Analyst), Ryan Traill (Analyst Content Lead), Kiri Addison (Director of Product)

Appendices

IoC - Type - Description + Confidence  

- http://pub-ac94c05b39aa4f75ad1df88d384932b8.r2[.]dev/offline[.]html#p – fake Microsoft login page

- https://s3.us-east-1.amazonaws[.]com/s3cure0line-0365cql0.19db86c3-b2b9-44cc-b339-36da233a3be2ml0qin/s3cccql0.19db86c3-b2b9-44cc-b339-36da233a3be2%26l0qn[.]html# - link to domain used in homoglyph attack

MITRE ATT&CK Mapping  

Tactic – Technique – Sub-Technique  

Initial Access - Phishing – (T1566)  

References

1.     https://gitnux.org/third-party-risk-statistics/

2.     https://learn.microsoft.com/en-us/defender-office-365/anti-spam-spam-confidence-level-scl-about

3.     https://www.virustotal.com/gui/url/5df9aae8f78445a590f674d7b64c69630c1473c294ce5337d73732c03ab7fca2/detection

4.     https://www.virustotal.com/gui/url/695d0d173d1bd4755eb79952704e3f2f2b87d1a08e2ec660b98a4cc65f6b2577/details

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

Continue reading
About the author

Blog

/

OT

/

October 1, 2025

Announcing Unified OT Security with Dedicated OT Workflows, Segmentation-Aware Risk Insights, and Next-Gen Endpoint Visibility for Industrial Teams

Default blog imageDefault blog image

The challenge of convergence without clarity

Convergence is no longer a roadmap idea, it is the daily reality for industrial security teams. As Information Technology (IT) and Operational Technology (OT) environments merge, the line between a cyber incident and an operational disruption grows increasingly hard to define. A misconfigured firewall rule can lead to downtime. A protocol misuse might look like a glitch. And when a pump stalls but nothing appears in the Security Operations Center (SOC) dashboard, teams are left asking: is this operational or is this a threat?

The lack of shared context slows down response, creates friction between SOC analysts and plant engineers, and leaves organizations vulnerable at exactly the points where IT and OT converge. Defenders need more than alerts, they need clarity that both sides can trust.

The breakthrough with Darktrace / OT

This latest Darktrace / OT release was built to deliver exactly that. It introduces shared context between Security, IT, and OT operations, helping reduce friction and close the security gaps at the intersection of these domains.

With a dedicated dashboard built for operations teams, extended visibility into endpoints for new forms of detection and CVE collection, expanded protocol coverage, and smarter risk modeling aligned to segmentation policies, teams can now operate from a shared source of truth. These enhancements are not just incremental upgrades, they are foundational improvements designed to bring clarity, efficiency, and trust to converged environments.

A dashboard built for OT engineers

The new Operational Overview provides OT engineers with a workspace designed for them, not for SOC analysts. It brings asset management, risk insights and operational alerts into one place. Engineers can now see activity like firmware changes, controller reprograms or the sudden appearance of a new workstation on the network, providing a tailored view for critical insights and productivity gains without navigating IT-centric workflows. Each device view is now enriched with cross-linked intelligence, make, model, firmware version and the roles inferred by Self-Learning AI, making it easier to understand how each asset behaves, what function it serves, and where it fits within the broader industrial process. By suppressing IT-centric noise, the dashboard highlights only the anomalies that matter to operations, accelerating triage, enabling smoother IT/OT collaboration, and reducing time to root cause without jumping between tools.

This is usability with purpose, a view that matches OT workflows and accelerates response.

Figure 1: The Operational Overview provides an intuitive dashboard summarizing all OT Assets, Alerts, and Risk.

Full-spectrum coverage across endpoints, sensors and protocols

The release also extends visibility into areas that have traditionally been blind spots. Engineering workstations, Human-Machine Interfaces (HMIs), contractor laptops and field devices are often the entry points for attackers, yet the hardest to monitor.

Darktrace introduces Network Endpoint eXtended Telemetry (NEXT) for OT, a lightweight collector built for segmented and resource-constrained environments. NEXT for OT uses Endpoint sensors to capture localized network, and now process-level telemetry, placing it in context alongside other network and asset data to:

  1. Identify vulnerabilities and OS data, which is leveraged by OT Risk Management for risk scoring and patching prioritization, removing the need for third-party CVE collection.
  1. Surface novel threats using Self-Learning AI that standalone Endpoint Detection and Response (EDR) would miss.
  1. Extend Cyber AI Analyst investigations through to the endpoint root cause.

NEXT is part of our existing cSensor endpoint agent, can be deployed standalone or alongside existing EDR tools, and allows capabilities to be enabled or disabled depending on factors such as security or OT team objectives and resource utilization.

Figure 2: Darktrace / OT delivers CVE patch priority insights by combining threat intelligence with extended network and endpoint telemetry

The family of Darktrace Endpoint sensors also receive a boost in deployment flexibility, with on-prem server-based setups, as well as a Windows driver tailored for zero-trust and high-security environments.

Protocol coverage has been extended where it matters most. Darktrace now performs protocol analysis of a wider range of GE and Mitsubishi protocols, giving operators real-time visibility into commands and state changes on Programmable Logic Controllers (PLCs), robots and controllers. Backed by Self-Learning AI, this inspection does more than parse traffic, it understands what normal looks like and flags deviations that signal risk.

Integrated risk and governance workflows

Security data is only valuable when it drives action. Darktrace / OT delivers risk insights that go beyond patching, helping teams take meaningful steps even when remediation isn't possible. Risk is assessed not just by CVE presence, but by how network segmentation, firewall policies, and attack path logic neutralize or contain real-world exposure. This approach empowers defenders to deprioritize low-impact vulnerabilities and focus effort where risk truly exists. Building on the foundation introduced in release 6.3, such as KEV enrichment, endpoint OS data, and exploit mapping, this release introduces new integrations that bring Darktrace / OT intelligence directly into governance workflows.

Fortinet FortiGate firewall ingestion feeds segmentation rules into attack path modeling, revealing real exposure when policies fail and closing feeds into patching prioritization based on a policy to CVE exposure assessment.

  • ServiceNow Configuration Management Database (CMDB) sync ensures asset intelligence stays current across governance platforms, eliminating manual inventory work.

Risk modeling has also been made more operationally relevant. Scores are now contextualized by exploitability, asset criticality, firewall policy, and segmentation posture. Patch recommendations are modeled in terms of safety, uptime and compliance rather than just Common Vulnerability Scoring System (CVSS) numbers. And importantly, risk is prioritized across the Purdue Model, giving defenders visibility into whether vulnerabilities remain isolated to IT or extend into OT-critical layers.

Figure 3: Attack Path Modeling based on NetFlow and network topology reveals high risk points of IT/OT convergence.

The real-world impact for defenders

In today’s environments, attackers move fluidly between IT and OT. Without unified visibility and shared context, incidents cascade faster than teams can respond.

With this release, Darktrace / OT changes that reality. The Operational Overview gives Engineers a dashboard they can use daily, tailored to their workflows. SOC analysts can seamlessly investigate telemetry across endpoints, sensors and protocols that were once blind spots. Operators gain transparency into PLCs and controllers. Governance teams benefit from automated integrations with platforms like Fortinet and ServiceNow. And all stakeholders work from risk models that reflect what truly matters: safety, uptime and compliance.

This release is not about creating more alerts. It is about providing more clarity. By unifying context across IT and OT, Darktrace / OT enables defenders to see more, understand more and act faster.

Because in environments where safety and uptime are non-negotiable, clarity is what matters most.

Join us for our live event where we will discuss these product innovations in greater detail

Continue reading
About the author
Pallavi Singh
Product Marketing Manager, OT Security & Compliance
Your data. Our AI.
Elevate your network security with Darktrace AI