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May 15, 2024

Lost in Translation: Darktrace Blocks Non-English Phishing Campaign Concealing Hidden Payloads

This blog explores how Darktrace/Email was able to successfully identify a wave of phishing emails sent from addresses belonging to a major fast-food chain which were leveraged in a coordinated attack. Despite the use of non-English language emails and payloads hidden behind QR codes, Darktrace was able to detect the attack and block the phishing emails in the first instance.
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
Rajendra Rushanth
Cyber Analyst
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15
May 2024

Email – the vector of choice for threat actors

In times of unprecedented globalization and internationalization, the enormous number of emails sent and received by organizations every day has opened the door for threat actors looking to gain unauthorized access to target networks.

Now, increasingly global organizations not only need to safeguard their email environments against phishing campaigns targeting their employees in their own language, but they also need to be able to detect malicious emails sent in foreign languages too [1].

Why are non-English language phishing emails more popular?

Many traditional email security vendors rely on pre-trained English language models which, while function adequately against malicious emails composed in English, would struggle in the face of emails composed in other languages. It should, therefore, come as no surprise that this limitation is becoming increasingly taken advantage of by attackers.  

Darktrace/Email™, on the other hand, focuses on behavioral analysis and its Self-Learning AI understands what is considered ‘normal’ for every user within an organization’s email environment, bypassing any limitations that would come from relying on language-trained models [1].

In March 2024, Darktrace observed anomalous emails on a customer’s network that were sent from email addresses belonging to an international fast-food chain. Despite this seeming legitimacy, Darktrace promptly identified them as phishing emails that contained malicious payloads, preventing a potentially disruptive network compromise.

Attack Overview and Darktrace Coverage

On March 3, 2024, Darktrace observed one of the customer’s employees receiving an email which would turn out to be the first of more than 50 malicious emails sent by attackers over the course of three days.

The Sender

Darktrace/Email immediately understood that the sender never had any previous correspondence with the organization or its employees, and therefore treated the emails with caution from the onset. Not only was Darktrace able to detect this new sender, but it also identified that the emails had been sent from a domain located in China and contained an attachment with a Chinese file name.

The phishing emails detected by Darktrace sent from a domain in China and containing an attachment with a Chinese file name.
Figure 1: The phishing emails detected by Darktrace sent from a domain in China and containing an attachment with a Chinese file name.

Darktrace further detected that the phishing emails had been sent in a synchronized fashion between March 3 and March 5. Eight unique senders were observed sending a total of 55 emails to 55 separate recipients within the customer’s email environment. The format of the addresses used to send these suspicious emails was “12345@fastflavor-shack[.]cn”*. The domain “fastflavor-shack[.]cn” is the legitimate domain of the Chinese division of an international fast-food company, and the numerical username contained five numbers, with the final three digits changing which likely represented different stores.

*(To maintain anonymity, the pseudonym “Fast Flavor Shack” and its fictitious domain, “fastflavor-shack[.]cn”, have been used in this blog to represent the actual fast-food company and the domains identified by Darktrace throughout this incident.)

The use of legitimate domains for malicious activities become commonplace in recent years, with attackers attempting to leverage the trust endpoint users have for reputable organizations or services, in order to achieve their nefarious goals. One similar example was observed when Darktrace detected an attacker attempting to carry out a phishing attack using the cloud storage service Dropbox.

As these emails were sent from a legitimate domain associated with a trusted organization and seemed to be coming from the correct connection source, they were verified by Sender Policy Framework (SPF) and were able to evade the customer’s native email security measures. Darktrace/Email; however, recognized that these emails were actually sent from a user located in Singapore, not China.

Darktrace/Email identified that the email had been sent by a user who had logged in from Singapore, despite the connection source being in China.
Figure 2: Darktrace/Email identified that the email had been sent by a user who had logged in from Singapore, despite the connection source being in China.

The Emails

Darktrace/Email autonomously analyzed the suspicious emails and identified that they were likely phishing emails containing a malicious multistage payload.

Darktrace/Email identifying the presence of a malicious phishing link and a multistage payload.
Figure 3: Darktrace/Email identifying the presence of a malicious phishing link and a multistage payload.

There has been a significant increase in multistage payload attacks in recent years, whereby a malicious email attempts to elicit recipients to follow a series of steps, such as clicking a link or scanning a QR code, before delivering a malicious payload or attempting to harvest credentials [2].

In this case, the malicious actor had embedded a suspicious link into a QR code inside a Microsoft Word document which was then attached to the email in order to direct targets to a malicious domain. While this attempt to utilize a malicious QR code may have bypassed traditional email security tools that do not scan for QR codes, Darktrace was able to identify the presence of the QR code and scan its destination, revealing it to be a suspicious domain that had never previously been seen on the network, “sssafjeuihiolsw[.]bond”.

Suspicious link embedded in QR Code, which was detected and extracted by Darktrace.
Figure 4: Suspicious link embedded in QR Code, which was detected and extracted by Darktrace.

At the time of the attack, there was no open-source intelligence (OSINT) on the domain in question as it had only been registered earlier the same day. This is significant as newly registered domains are typically much more likely to bypass gateways until traditional security tools have enough intelligence to determine that these domains are malicious, by which point a malicious actor may likely have already gained access to internal systems [4]. Despite this, Darktrace’s Self-Learning AI enabled it to recognize the activity surrounding these unusual emails as suspicious and indicative of a malicious phishing campaign, without needing to rely on existing threat intelligence.

The most commonly used sender name line for the observed phishing emails was “财务部”, meaning “finance department”, and Darktrace observed subject lines including “The document has been delivered”, “Income Tax Return Notice” and “The file has been released”, all written in Chinese.  The emails also contained an attachment named “通知文件.docx” (“Notification document”), further indicating that they had been crafted to pass for emails related to financial transaction documents.

 Darktrace/Email took autonomous mitigative action against the suspicious emails by holding the message from recipient inboxes.
Figure 5: Darktrace/Email took autonomous mitigative action against the suspicious emails by holding the message from recipient inboxes.

Conclusion

Although this phishing attack was ultimately thwarted by Darktrace/Email, it serves to demonstrate the potential risks of relying on solely language-trained models to detect suspicious email activity. Darktrace’s behavioral and contextual learning-based detection ensures that any deviations in expected email activity, be that a new sender, unusual locations or unexpected attachments or link, are promptly identified and actioned to disrupt the attacks at the earliest opportunity.

In this example, attackers attempted to use non-English language phishing emails containing a multistage payload hidden behind a QR code. As traditional email security measures typically rely on pre-trained language models or the signature-based detection of blacklisted senders or known malicious endpoints, this multistage approach would likely bypass native protection.  

Darktrace/Email, meanwhile, is able to autonomously scan attachments and detect QR codes within them, whilst also identifying the embedded links. This ensured that the customer’s email environment was protected against this phishing threat, preventing potential financial and reputation damage.

Credit to: Rajendra Rushanth, Cyber Analyst, Steven Haworth, Head of Threat Modelling, Email

Appendices  

List of Indicators of Compromise (IoCs)  

IoC – Type – Description

sssafjeuihiolsw[.]bond – Domain Name – Suspicious Link Domain

通知文件.docx – File - Payload  

References

[1] https://darktrace.com/blog/stopping-phishing-attacks-in-enter-language  

[2] https://darktrace.com/blog/attacks-are-getting-personal

[3] https://darktrace.com/blog/phishing-with-qr-codes-how-darktrace-detected-and-blocked-the-bait

[4] https://darktrace.com/blog/the-domain-game-how-email-attackers-are-buying-their-way-into-inboxes

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
Rajendra Rushanth
Cyber Analyst

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May 16, 2025

Catching a RAT: How Darktrace neutralized AsyncRAT

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What is a RAT?

As the proliferation of new and more advanced cyber threats continues, the Remote Access Trojan (RAT) remains a classic tool in a threat actor's arsenal. RATs, whether standardized or custom-built, enable attackers to remotely control compromised devices, facilitating a range of malicious activities.

What is AsyncRAT?

Since its first appearance in 2019, AsyncRAT has become increasingly popular among a wide range of threat actors, including cybercriminals and advanced persistent threat (APT) groups.

Originally available on GitHub as a legitimate tool, its open-source nature has led to widespread exploitation. AsyncRAT has been used in numerous campaigns, including prolonged attacks on essential US infrastructure, and has even reportedly penetrated the Chinese cybercriminal underground market [1] [2].

How does AsyncRAT work?

Original source code analysis of AsyncRAT demonstrates that once installed, it establishes persistence via techniques such as creating scheduled tasks or registry keys and uses SeDebugPrivilege to gain elevated privileges [3].

Its key features include:

  • Keylogging
  • File search
  • Remote audio and camera access
  • Exfiltration techniques
  • Staging for final payload delivery

These are generally typical functions found in traditional RATs. However, it also boasts interesting anti-detection capabilities. Due to the popularity of Virtual Machines (VM) and sandboxes for dynamic analysis, this RAT checks for the manufacturer via the WMI query 'Select * from Win32_ComputerSystem' and looks for strings containing 'VMware' and 'VirtualBox' [4].

Darktrace’s coverage of AsyncRAT

In late 2024 and early 2025, Darktrace observed a spike in AsyncRAT activity across various customer environments. Multiple indicators of post-compromise were detected, including devices attempting or successfully connecting to endpoints associated with AsyncRAT.

On several occasions, Darktrace identified a clear association with AsyncRAT through the digital certificates of the highlighted SSL endpoints. Darktrace’s Real-time Detection effectively identified and alerted on suspicious activities related to AsyncRAT. In one notable incident, Darktrace’s Autonomous Response promptly took action to contain the emerging threat posed by AsyncRAT.

AsyncRAT attack overview

On December 20, 2024, Darktrace first identified the use of AsyncRAT, noting a device successfully establishing SSL connections to the uncommon external IP 185.49.126[.]50 (AS199654 Oxide Group Limited) via port 6606. The IP address appears to be associated with AsyncRAT as flagged by open-source intelligence (OSINT) sources [5]. This activity triggered the device to alert the ‘Anomalous Connection / Rare External SSL Self-Signed' model.

Model alert in Darktrace / NETWORK showing the repeated SSL connections to a rare external Self-Signed endpoint, 185.49.126[.]50.
Figure 1: Model alert in Darktrace / NETWORK showing the repeated SSL connections to a rare external Self-Signed endpoint, 185.49.126[.]50.

Following these initial connections, the device was observed making a significantly higher number of connections to the same endpoint 185.49.126[.]50 via port 6606 over an extended period. This pattern suggested beaconing activity and triggered the 'Compromise/Beaconing Activity to External Rare' model alert.

Further analysis of the original source code, available publicly, outlines the default ports used by AsyncRAT clients for command-and-control (C2) communications [6]. It reveals that port 6606 is the default port for creating a new AsyncRAT client. Darktrace identified both the Certificate Issuer and the Certificate Subject as "CN=AsyncRAT Server". This SSL certificate encrypts the packets between the compromised system and the server. These indicators of compromise (IoCs) detected by Darktrace further suggest that the device was successfully connecting to a server associated with AsyncRAT.

Model alert in Darktrace / NETWORK displaying the Digital Certificate attributes, IP address and port number associated with AsyncRAT.
Figure 2: Model alert in Darktrace / NETWORK displaying the Digital Certificate attributes, IP address and port number associated with AsyncRAT.
Darktrace’s detection of repeated connections to the suspicious IP address 185.49.126[.]50 over port 6606, indicative of beaconing behavior.
Figure 3: Darktrace’s detection of repeated connections to the suspicious IP address 185.49.126[.]50 over port 6606, indicative of beaconing behavior.
Darktrace's Autonomous Response actions blocking the suspicious IP address,185.49.126[.]50.
Figure 4: Darktrace's Autonomous Response actions blocking the suspicious IP address,185.49.126[.]50.

A few days later, the same device was detected making numerous connections to a different IP address, 195.26.255[.]81 (AS40021 NL-811-40021), via various ports including 2106, 6606, 7707, and 8808. Notably, ports 7707 and 8808 are also default ports specified in the original AsyncRAT source code [6].

Darktrace’s detection of connections to the suspicious endpoint 195.26.255[.]81, where the default ports (6606, 7707, and 8808) for AsyncRAT were observed.
Figure 5: Darktrace’s detection of connections to the suspicious endpoint 195.26.255[.]81, where the default ports (6606, 7707, and 8808) for AsyncRAT were observed.

Similar to the activity observed with the first endpoint, 185.49.126[.]50, the Certificate Issuer for the connections to 195.26.255[.]81 was identified as "CN=AsyncRAT Server". Further OSINT investigation confirmed associations between the IP address 195.26.255[.]81 and AsyncRAT [7].

Darktrace's detection of a connection to the suspicious IP address 195.26.255[.]81 and the domain name identified under the common name (CN) of a certificate as AsyncRAT Server
Figure 6: Darktrace's detection of a connection to the suspicious IP address 195.26.255[.]81 and the domain name identified under the common name (CN) of a certificate as AsyncRAT Server.

Once again, Darktrace's Autonomous Response acted swiftly, blocking the connections to 195.26.255[.]81 throughout the observed AsyncRAT activity.

Figure 7: Darktrace's Autonomous Response actions were applied against the suspicious IP address 195.26.255[.]81.

A day later, Darktrace again alerted to further suspicious activity from the device. This time, connections to the suspicious endpoint 'kashuub[.]com' and IP address 191.96.207[.]246 via port 8041 were observed. Further analysis of port 8041 suggests it is commonly associated with ScreenConnect or Xcorpeon ASIC Carrier Ethernet Transport [8]. ScreenConnect has been observed in recent campaign’s where AsyncRAT has been utilized [9]. Additionally, one of the ASN’s observed, namely ‘ASN Oxide Group Limited’, was seen in both connections to kashuub[.]com and 185.49.126[.]50.

This could suggest a parallel between the two endpoints, indicating they might be hosting AsyncRAT C2 servers, as inferred from our previous analysis of the endpoint 185.49.126[.]50 and its association with AsyncRAT [5]. OSINT reporting suggests that the “kashuub[.]com” endpoint may be associated with ScreenConnect scam domains, further supporting the assumption that the endpoint could be a C2 server.

Darktrace’s Autonomous Response technology was once again able to support the customer here, blocking connections to “kashuub[.]com”. Ultimately, this intervention halted the compromise and prevented the attack from escalating or any sensitive data from being exfiltrated from the customer’s network into the hands of the threat actors.

Darktrace’s Autonomous Response applied a total of nine actions against the IP address 191.96.207[.]246 and the domain 'kashuub[.]com', successfully blocking the connections.
Figure 8: Darktrace’s Autonomous Response applied a total of nine actions against the IP address 191.96.207[.]246 and the domain 'kashuub[.]com', successfully blocking the connections.

Due to the popularity of this RAT, it is difficult to determine the motive behind the attack; however, from existing knowledge of what the RAT does, we can assume accessing and exfiltrating sensitive customer data may have been a factor.

Conclusion

While some cybercriminals seek stability and simplicity, openly available RATs like AsyncRAT provide the infrastructure and open the door for even the most amateur threat actors to compromise sensitive networks. As the cyber landscape continually shifts, RATs are now being used in all types of attacks.

Darktrace’s suite of AI-driven tools provides organizations with the infrastructure to achieve complete visibility and control over emerging threats within their network environment. Although AsyncRAT’s lack of concealment allowed Darktrace to quickly detect the developing threat and alert on unusual behaviors, it was ultimately Darktrace Autonomous Response's consistent blocking of suspicious connections that prevented a more disruptive attack.

Credit to Isabel Evans (Cyber Analyst), Priya Thapa (Cyber Analyst) and Ryan Traill (Analyst Content Lead)

Appendices

  • Real-time Detection Models
       
    • Compromise / Suspicious SSL Activity
    •  
    • Compromise / Beaconing Activity To      External Rare
    •  
    • Compromise / High Volume of      Connections with Beacon Score
    •  
    • Anomalous Connection / Suspicious      Self-Signed SSL
    •  
    • Compromise / Sustained SSL or HTTP      Increase
    •  
    • Compromise / SSL Beaconing to Rare      Destination
    •  
    • Compromise / Suspicious Beaconing      Behaviour
    •  
    • Compromise / Large Number of      Suspicious Failed Connections
  •  
  • Autonomous     Response Models
       
    • Antigena / Network / Significant      Anomaly / Antigena Controlled and Model Alert
    •  
    • Antigena / Network / Significant      Anomaly / Antigena Enhanced Monitoring from Client Block

List of IoCs

·     185.49.126[.]50 - IP – AsyncRAT C2 Endpoint

·     195.26.255[.]81 – IP - AsyncRAT C2 Endpoint

·      191.96.207[.]246 – IP – Likely AsyncRAT C2 Endpoint

·     CN=AsyncRAT Server - SSL certificate - AsyncRATC2 Infrastructure

·      Kashuub[.]com– Hostname – Likely AsyncRAT C2 Endpoint

MITRE ATT&CK Mapping:

Tactic –Technique – Sub-Technique  

 

Execution– T1053 - Scheduled Task/Job: Scheduled Task

DefenceEvasion – T1497 - Virtualization/Sandbox Evasion: System Checks

Discovery– T1057 – Process Discovery

Discovery– T1082 – System Information Discovery

LateralMovement - T1021.001 - Remote Services: Remote Desktop Protocol

Collection/ Credential Access – T1056 – Input Capture: Keylogging

Collection– T1125 – Video Capture

Commandand Control – T1105 - Ingress Tool Transfer

Commandand Control – T1219 - Remote Access Software

Exfiltration– T1041 - Exfiltration Over C2 Channel

 

References

[1]  https://blog.talosintelligence.com/operation-layover-how-we-tracked-attack/

[2] https://intel471.com/blog/china-cybercrime-undergrond-deepmix-tea-horse-road-great-firewall

[3] https://www.attackiq.com/2024/08/01/emulate-asyncrat/

[4] https://www.fortinet.com/blog/threat-research/spear-phishing-campaign-with-new-techniques-aimed-at-aviation-companies

[5] https://www.virustotal.com/gui/ip-address/185.49.126[.]50/community

[6] https://dfir.ch/posts/asyncrat_quasarrat/

[7] https://www.virustotal.com/gui/ip-address/195.26.255[.]81

[8] https://www.speedguide.net/port.php?port=8041

[9] https://www.esentire.com/blog/exploring-the-infection-chain-screenconnects-link-to-asyncrat-deployment

[10] https://scammer.info/t/taking-out-connectwise-sites/153479/518?page=26

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About the author
Isabel Evans
Cyber Analyst

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May 13, 2025

Revolutionizing OT Risk Prioritization with Darktrace 6.3

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Powering smarter protection for industrial systems

In industrial environments, security challenges are deeply operational. Whether you’re running a manufacturing line, a power grid, or a semiconductor fabrication facility (fab), you need to know: What risks can truly disrupt my operations, and what should I focus on first?

Teams need the right tools to shift from reactive defense, constantly putting out fires, to proactively thinking about their security posture. However, most OT teams are stuck using IT-centric tools that don’t speak the language of industrial systems, are consistently overwhelmed with static CVE lists, and offer no understanding of OT-specific protocols. The result? Compliance gaps, siloed insights, and risk models that don’t reflect real-world exposure, making risk prioritization seem like a luxury.

Darktrace / OT 6.3 was built in direct response to these challenges. Developed in close collaboration with OT operators and engineers, this release introduces powerful upgrades that deliver the context, visibility, and automation security teams need, without adding complexity. It’s everything OT defenders need to protect critical operations in one platform that understands the language of industrial systems.

additions to darktrace / ot 6/3

Contextual risk modeling with smarter Risk Scoring

Darktrace / OT 6.3 introduces major upgrades to OT Risk Management, helping teams move beyond generic CVE lists with AI-driven risk scoring and attack path modeling.

By factoring in real-world exploitability, asset criticality, and operational context, this release delivers a more accurate view of what truly puts critical systems at risk.

The platform now integrates:

  • CISA’s Known Exploited Vulnerabilities (KEV) database
  • End-of-life status for legacy OT devices
  • Firewall misconfiguration analysis
  • Incident response plan alignment

Most OT environments are flooded with vulnerability data that lacks context. CVE scores often misrepresent risk by ignoring how threats move through the environment or whether assets are even reachable. Firewalls are frequently misconfigured or undocumented, and EOL (End of Life) devices, some of the most vulnerable, often go untracked.

Legacy tools treat these inputs in isolation. Darktrace unifies them, showing teams exactly which attack paths adversaries could exploit, mapped to the MITRE ATT&CK framework, with visibility into where legacy tech increases exposure.

The result: teams can finally focus on the risks that matter most to uptime, safety, and resilience without wasting resources on noise.

Automating compliance with dynamic IEC-62443 reporting

Darktrace / OT now includes a purpose-built IEC-62443-3-3 compliance module, giving industrial teams real-time visibility into their alignment with regulatory standards. No spreadsheets required!

Industrial environments are among the most heavily regulated. However, for many OT teams, staying compliant is still a manual, time-consuming process.

Darktrace / OT introduces a dedicated IEC-62443-3-3 module designed specifically for industrial environments. Security and operations teams can now map their security posture to IEC standards in real time, directly within the platform. The module automatically gathers evidence across all four security levels, flags non-compliance, and generates structured reports to support audit preparation, all in just a few clicks.Most organizations rely on spreadsheets or static tools to track compliance, without clear visibility into which controls meet standards like IEC-62443. The result is hidden gaps, resource-heavy audits, and slow remediation cycles.

Even dedicated compliance tools are often built for IT, require complex setup, and overlook the unique devices found in OT environments. This leaves teams stuck with fragmented reporting and limited assurance that their controls are actually aligned with regulatory expectations.

By automating compliance tracking, surfacing what matters most, and being purpose built for industrial environments, Darktrace / OT empowers organizations to reduce audit fatigue, eliminate blind spots, and focus resources where they’re needed most.

Expanding protocol visibility with deep insights for specialized OT operations

Darktrace has expanded its Deep Packet Inspection (DPI) capabilities to support five industry-specific protocols, across healthcare, semiconductor manufacturing, and ABB control systems.

The new protocols build on existing capabilities across all OT industry verticals and protocol types to ensure the Darktrace Self-Learning AI TM can learn intelligently about even more assets in complex industrial environments. By enabling native, AI-driven inspection of these protocols, Darktrace can identify both security threats and operational issues without relying on additional appliances or complex integrations.

Most security platforms lack native support for industry-specific protocols, creating critical visibility gaps in customer environments like healthcare, semiconductor manufacturing, and ABB-heavy industrial automation. Without deep protocol awareness, organizations struggle to accurately identify specialized OT and IoT assets, detect malicious activity concealed within proprietary protocol traffic, and generate reliable device risk profiles due to insufficient telemetry.

These blind spots result in incomplete asset inventories, and ultimately, flawed risk posture assessments which over-index for CVE patching and legacy equipment.

By combining protocol-aware detection with full-stack visibility across IT, OT, and IoT, Darktrace’s AI can correlate anomalies across domains. For example, connecting an anomaly from a Medical IoT (MIoT) device with suspicious behavior in IT systems, providing actionable, contextual insights other solutions often miss.

Conclusion

Together, these capabilities take OT security beyond alert noise and basic CVE matching, delivering continuous compliance, protocol-aware visibility, and actionable, prioritized risk insights, all inside a single, unified platform built for the realities of industrial environments.

[related-resource]

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About the author
Pallavi Singh
Product Marketing Manager, OT Security & Compliance
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