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October 1, 2017

Feodo Banking Trojan Threatens Government Network

Learn how AI detected new Feodo banking Trojan on a government network and the resurgence of the Feodo banking trojan on a government network.
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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.
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01
Oct 2017

Famous malware like Zeus, Conficker, and CryptoLocker are still some of the most common threats globally. By repurposing and repackaging known threats like these, attackers can create unknown variants that bypass signature-based security tools.

For instance, an older class of banking Trojans – known as Feodo – recently cropped up again on the network of a local US government. However, this particular strain had a key differentiator.

Darktrace detected the malware when it first was downloaded onto the government’s network. After analysis, the malware was found to be consistent with two well-documented Trojans in the Feodo family: Dridex and Emotet.

Traditionally, Trojans in the Feodo family will infect just a single device, but this attack immediately began propagating on the network, spreading to over 200 devices in a matter of hours.

The incident is part of an emerging trend of similar infections, suggesting that the Feodo family of Trojans is undergoing a resurgence, but this time retooled with ability to rapidly spread across the network.

Darktrace first detected the threat when an internal device made a series of anomalous SSL connections to IPs with self-signed certificates. The abnormal connections were a deviation from what Darktrace’s AI algorithms had learned to be normal, triggering Darktrace to raise the first in a series of alerts.

Time: 2017-04-26 11:38:05 [UTC]
Source: 172.16.14.39
Destination: 76.164.161.46
Destination Port: 995
Protocol: SSL
Version: TLSv12 [Considered HIGH security]
Cipher: TLS_RSA_WI TH_AES_256_ GCM_SHA384 [Considered HIGH security]
UID: CbenK822ViUMxJok00

The identical IP certificate subject and issuer:
Subject: CN=euwtrdjuee.biz,OU=Tslspyqh Dfxdekt Brftapckwr,O=Kaqt Aooscr LLC.,street=132 Vfjteuadivm Fklhnxdmza.,L=Elqazgap Nvax,ST=XI,C=PO
Issuer: CN=euwtrdjuee.biz,OU=Tslspyqh Dfxdekt Brftapckwr,O=Kaqt Aooscr LLC.,street=132 Vfjteuadivm Fklhnxdmza.,L=Elqazgap Nvax,ST=XI,C=PO

The device proceeded to download an anomalous ZIP file from an unusual external server. The email purported to be a notification from FedEx, and the file was disguised as an attachment containing tracking numbers. The download was nearly identical to the malicious files usually seen in Dridex and Emotet infections.

Time: 2017-04-28 16:01:03 [UTC]
Source: 172.16.14.39
Destination: 89.38.128.232
Destination Port: 80/tcp
Protocol: HTTP
Path: hxxp://XX[.]ro/UPS__Ship__Notification__Tracking__Number__2SM099383266006810/Y0894C/FEDEX-TRACK/track-tracknumbers-673639733202/
Filename: fedex-track-tracknumbers-133977976498-language-en.zip
Mime Type: application/zip

After downloading the ZIP, the device wrote an executable file to a second device via SMB. This strongly suggested that the infection was spreading, and quickly.

Time: 2017-04-28 16:52:57 [UTC]
Source: 172.16.14.39
Destination: 172.16.10.41
Destination Port: 445/tcp
Protocol: SMB
Action: write
Filename: tptzfqa.exe
Path: \\PU12881\C$
Write Size: 65536
UID: Cxq64s3tCi1vq4Uo00

The graph shows the internal connectivity of the initial device. The spike in activity, which includes numerous alerts due to unusual behavior, occurs immediately following the SMB write made by the original device.

Devices across the network started to mimic this activity by performing the same type of SMB write, each time with the same amount of data – 65536B – and a random string of characters followed by the .exe filetype.

Meanwhile, the initial device was flagged for making a large number of SMB and Kerberos login attempts. At this point, the infection had spread to over 200 devices, which were all attempting to bruteforce passwords using the same credentials as the original device, in addition to standard usernames like ‘Administrator’ and ‘misadmin’.

Bruteforcing over SMB is consistent with lateral movement seen in recent instances of Emotet, in which the Trojan was seen with new, built-in functionality designed for network propagation.

As the malware continued to spread in the government network, devices began making anomalous SSL connections without SNI (Server Name Indication).

This series of anomalies represented a massive deviation from the network’s normal ‘pattern of life’, causing the Enterprise Immune System to raise three high-priority alerts in real time: one alert for the SMB session bruteforce, another for the Kerberos activity, and another for the anomalous SSL connections without SNI.

The final anomaly occurred when devices made a flurry of unusual DNS requests for DGA-generated domains, often involving rare TLDs such as .biz and .info. The DNS requests illustrate a sophisticated method to disguise communications to the attacker’s command and control centers. Darktrace’s AI algorithms deemed this domain fluxing activity to be highly unusual compared to ordinary behavior, thus raising one final alert before the security team was able to intervene.

A sample of the DNS requests:

15:33:00 hd12530.mi.SALTEDHAZE.org made a successful DNS request for rbqfkjjemttqumeobxb.org to dc1-2012.mi.[REDACTED].org
15:33:10 hd12530.mi.SALTEDHAZE.org made a successful DNS request for tmmiqtsdnkjdcqr.biz to dc1-2012.mi.SALTEDHAZE.org
15:33:20 hd12530.mi.SALTEDHAZE.org made a successful DNS request for mehqdlodsgggehchxdwfsmmoq.biz to dc1-2012.mi.SALTEDHAZE.org

Taken on their own, each of these anomalies could be explained as an isolated incident or perhaps a false-positive. But taken together, they form a broader picture of a widespread and aggressive infection, in which an external hacker had taken control of over 200 devices and was using them to attempt to harvest the users’ banking credentials and transfer funds into their own account.

In accordance with the Feodo family of banking Trojans, the malware was likely attempting to steal banking credentials by intercepting web form submissions. Yet, by adding the ability to spread through the network, the attacker was able to create a completely novel attack type that circumvented the perimeter security controls and infected over 200 devices.

As the threat progressed, the Enterprise Immune System raised real-time alerts and revealed in-depth details on the nature of the compromise. Using this information, the government’s security team was able to remediate the situation before any banking credentials could be stolen.

To learn more about the threats Darktrace finds, check out our Threat Use Cases page which discusses a host of other novel infections that were stopped by the Enterprise Immune System.

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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.
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January 13, 2026

Runtime Is Where Cloud Security Really Counts: The Importance of Detection, Forensics and Real-Time Architecture Awareness

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Introduction: Shifting focus from prevention to runtime

Cloud security has spent the last decade focused on prevention; tightening configurations, scanning for vulnerabilities, and enforcing best practices through Cloud Native Application Protection Platforms (CNAPP). These capabilities remain essential, but they are not where cloud attacks happen.

Attacks happen at runtime: the dynamic, ephemeral, constantly changing execution layer where applications run, permissions are granted, identities act, and workloads communicate. This is also the layer where defenders traditionally have the least visibility and the least time to respond.

Today’s threat landscape demands a fundamental shift. Reducing cloud risk now requires moving beyond static posture and CNAPP only approaches and embracing realtime behavioral detection across workloads and identities, paired with the ability to automatically preserve forensic evidence. Defenders need a continuous, real-time understanding of what “normal” looks like in their cloud environments, and AI capable of processing massive data streams to surface deviations that signal emerging attacker behavior.

Runtime: The layer where attacks happen

Runtime is the cloud in motion — containers starting and stopping, serverless functions being called, IAM roles being assumed, workloads auto scaling, and data flowing across hundreds of services. It’s also where attackers:

  • Weaponize stolen credentials
  • Escalate privileges
  • Pivot programmatically
  • Deploy malicious compute
  • Manipulate or exfiltrate data

The challenge is complex: runtime evidence is ephemeral. Containers vanish; critical process data disappears in seconds. By the time a human analyst begins investigating, the detail required to understand and respond to the alert, often is already gone. This volatility makes runtime the hardest layer to monitor, and the most important one to secure.

What Darktrace / CLOUD Brings to Runtime Defence

Darktrace / CLOUD is purpose-built for the cloud execution layer. It unifies the capabilities required to detect, contain, and understand attacks as they unfold, not hours or days later. Four elements define its value:

1. Behavioral, real-time detection

The platform learns normal activity across cloud services, identities, workloads, and data flows, then surfaces anomalies that signify real attacker behavior, even when no signature exists.

2. Automated forensic level artifact collection

The moment Darktrace detects a threat, it can automatically capture volatile forensic evidence; disk state, memory, logs, and process context, including from ephemeral resources. This preserves the truth of what happened before workloads terminate and evidence disappears.

3. AI-led investigation

Cyber AI Analyst assembles cloud behaviors into a coherent incident story, correlating identity activity, network flows, and Cloud workload behavior. Analysts no longer need to pivot across dashboards or reconstruct timelines manually.

4. Live architectural awareness

Darktrace continuously maps your cloud environment as it operates; including services, identities, connectivity, and data pathways. This real-time visibility makes anomalies clearer and investigations dramatically faster.

Together, these capabilities form a runtime-first security model.

Why CNAPP alone isn’t enough

CNAPP platforms excel at pre deployment checks all the way down to developer workstations, identifying misconfigurations, concerning permission combinations, vulnerable images, and risky infrastructure choices. But CNAPP’s breadth is also its limitation. CNAPP is about posture. Runtime defense is about behavior.

CNAPP tells you what could go wrong; runtime detection highlights what is going wrong right now.

It cannot preserve ephemeral evidence, correlate active behaviors across domains, or contain unfolding attacks with the precision and speed required during a real incident. Prevention remains essential, but prevention alone cannot stop an attacker who is already operating inside your cloud environment.

Real-world AWS Scenario: Why Runtime Monitoring Wins

A recent incident detected by Darktrace / CLOUD highlights how cloud compromises unfold, and why runtime visibility is non-negotiable. Each step below reflects detections that occur only when monitoring behavior in real time.

1. External Credential Use

Detection: Unusual external source for credential use: An attacker logs into a cloud account from a never-before-seen location, the earliest sign of account takeover.

2. AWS CLI Pivot

Detection: Unusual CLI activity: The attacker switches to programmatic access, issuing commands from a suspicious host to gain automation and stealth.

3. Credential Manipulation

Detection: Rare password reset: They reset or assign new passwords to establish persistence and bypass existing security controls.

4. Cloud Reconnaissance

Detection: Burst of resource discovery: The attacker enumerates buckets, roles, and services to map high value assets and plan next steps.

5. Privilege Escalation

Detection: Anomalous IAM update: Unauthorized policy updates or role changes grant the attacker elevated access or a backdoor.

6. Malicious Compute Deployment

Detection: Unusual EC2/Lambda/ECS creation: The attacker deploys compute resources for mining, lateral movement, or staging further tools.

7. Data Access or Tampering

Detection: Unusual S3 modifications: They alter S3 permissions or objects, often a prelude to data exfiltration or corruption.

Only some of these actions would appear in a posture scan, crucially after the fact.
Every one of these runtime detections is visible only through real-time behavioral monitoring while the attack is in progress.

The future of cloud security Is runtime-first

Cloud defense can no longer revolve solely around prevention. Modern attacks unfold in runtime, across a fast-changing mesh of workloads, services, and — critically — identities. To reduce risk, organizations must be able to detect, understand, and contain malicious activity as it happens, before ephemeral evidence disappears and before attacker's pivot across identity layers.

Darktrace / CLOUD delivers this shift by turning runtime, the most volatile and consequential layer in the cloud, into a fully defensible control point through unified visibility across behavior, workloads, and identities. It does this by providing:

  • Real-time behavior detection across workloads and identity activity
  • Autonomous response actions for rapid containment
  • Automated forensic level artifact preservation the moment events occur
  • AI-driven investigation that separates weak signals from true attacker patterns
  • Live cloud environment insight to understand context and impact instantly

Cloud security must evolve from securing what might go wrong to continuously understanding what is happening; in runtime, across identities, and at the speed attackers operate. Unifying runtime and identity visibility is how defenders regain the advantage.

[related-resource]

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About the author
Adam Stevens
Senior Director of Product, Cloud | Darktrace

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January 12, 2026

Maduro Arrest Used as a Lure to Deliver Backdoor

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Introduction

Threat actors frequently exploit ongoing world events to trick users into opening and executing malicious files. Darktrace security researchers recently identified a threat group using reports around the arrest of Venezuelan President Nicolàs Maduro on January 3, 2025, as a lure to deliver backdoor malware.

Technical Analysis

While the exact initial access method is unknown, it is likely that a spear-phishing email was sent to victims, containing a zip archive titled “US now deciding what’s next for Venezuela.zip”. This file included an executable named “Maduro to be taken to New York.exe” and a dynamic-link library (DLL), “kugou.dll”.  

The binary “Maduro to be taken to New York.exe” is a legitimate binary (albeit with an expired signature) related to KuGou, a Chinese streaming platform. Its function is to load the DLL “kugou.dll” via DLL search order. In this instance, the expected DLL has been replaced with a malicious one with the same name to load it.  

DLL called with LoadLibraryW.
Figure 1: DLL called with LoadLibraryW.

Once the DLL is executed, a directory is created C:\ProgramData\Technology360NB with the DLL copied into the directory along with the executable, renamed as “DataTechnology.exe”. A registry key is created for persistence in “HKCU\Software\Microsoft\Windows\CurrentVersion\Run\Lite360” to run DataTechnology.exe --DATA on log on.

 Registry key added for persistence.
Figure 2. Registry key added for persistence.
Folder “Technology360NB” created.
Figure 3: Folder “Technology360NB” created.

During execution, a dialog box appears with the caption “Please restart your computer and try again, or contact the original author.”

Message box prompting user to restart.
Figure 4. Message box prompting user to restart.

Prompting the user to restart triggers the malware to run from the registry key with the command --DATA, and if the user doesn't, a forced restart is triggered. Once the system is reset, the malware begins periodic TLS connections to the command-and-control (C2) server 172.81.60[.]97 on port 443. While the encrypted traffic prevents direct inspection of commands or data, the regular beaconing and response traffic strongly imply that the malware has the ability to poll a remote server for instructions, configuration, or tasking.

Conclusion

Threat groups have long used geopolitical issues and other high-profile events to make malicious content appear more credible or urgent. Since the onset of the war in Ukraine, organizations have been repeatedly targeted with spear-phishing emails using subject lines related to the ongoing conflict, including references to prisoners of war [1]. Similarly, the Chinese threat group Mustang Panda frequently uses this tactic to deploy backdoors, using lures related to the Ukrainian war, conventions on Tibet [2], the South China Sea [3], and Taiwan [4].  

The activity described in this blog shares similarities with previous Mustang Panda campaigns, including the use of a current-events archive, a directory created in ProgramData with a legitimate executable used to load a malicious DLL and run registry keys used for persistence. While there is an overlap of tactics, techniques and procedures (TTPs), there is insufficient information available to confidently attribute this activity to a specific threat group. Users should remain vigilant, especially when opening email attachments.

Credit to Tara Gould (Malware Research Lead)
Edited by Ryan Traill (Analyst Content Lead)

Indicators of Compromise (IoCs)

172.81.60[.]97
8f81ce8ca6cdbc7d7eb10f4da5f470c6 - US now deciding what's next for Venezuela.zip
722bcd4b14aac3395f8a073050b9a578 - Maduro to be taken to New York.exe
aea6f6edbbbb0ab0f22568dcb503d731  - kugou.dll

References

[1] https://cert.gov.ua/article/6280422  

[2] https://www.ibm.com/think/x-force/hive0154-mustang-panda-shifts-focus-tibetan-community-deploy-pubload-backdoor

[3] https://www.ibm.com/think/x-force/hive0154-targeting-us-philippines-pakistan-taiwan

[4] https://www.ibm.com/think/x-force/hive0154-targeting-us-philippines-pakistan-taiwan

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About the author
Tara Gould
Malware Research Lead
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