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October 11, 2017

Stealth Attacks: The ‘Matrix Banker’ Reloaded

Over the last few weeks, Darktrace has confidently identified traces of the resurgence of a stealthy attack targeting Latin American companies. Learn more!
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
Max Heinemeyer
Global Field CISO
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11
Oct 2017

Overview

Over the last few weeks, Darktrace has confidently identified traces of the resurgence of a stealthy attack targeting Latin American companies. This targeted campaign was first observed between March and June this year. Arbor Networks initially labelled the malware used in the campaign ‘Matrix Banker’. The name used by Proofpoint is ‘Win32/RediModiUpd’. The malware used by the attackers appeared to be still under development when the last report came out in June 2017.

Darktrace has observed an attack wave targeting Mexican companies in August and September 2017. Some of the TTPs (tools, techniques, procedures) observed bear close resemblance to those seen in the ‘Matrix Banker’ attacks earlier this year. The campaign is crafted to be particularly stealthy and to blend into certain networks in Latin America, confirming the suspicion of its targeted nature. Darktrace’s machine learning and AI algorithms were able to identify the infected devices almost instantaneously, despite apparent efforts by the malware author to be covert and stealthy.

Between August and October 2017, Darktrace detected highly anomalous behavior on five seemingly unrelated networks in Mexico. Unlike the original strain of this attack, which was believed to target financial institutions almost exclusively, this latest variant affected customers across a number of industry verticals, suggesting that the threat actors are diversifying their targets. Darktrace has seen the attack hit companies in the healthcare, telecommunications, food and retail sectors.

Infection process

The initial infection vector appears to be phishing emails. The users downloaded the initial piece of malware from compromised Mexican websites. The infected files were Windows executables masqueraded as .mp3 and .gif files. Example downloads are listed below. Darktrace instantly detected the highly anomalous behavior of these downloads, which occurred from 100% rare external domains for the networks, and alerted the respective security teams.

hxxp://gorrasbaratas.com[.]mx/images/sss/sound.mp3 [1]
hxxp://inseltech.com[.]mx/inicio/wp-includes/kk/sound.mp3 [2]

The actual file names of the downloads are ‘logo.gif’.

The ‘Matrix Bankers’ attack tried to conceal malware downloads using masqueraded files in previous attacks. What is interesting about the hacked websites serving the malware is that they are using the .mx top level domain. This localised and targeted technique is used to conceal the traffic and make it blend in with normal network traffic on networks in Mexico.

Following the initial infection, in some cases a second stage malware was downloaded. Darktrace detected this as more anomalous activity since the downloads took place from more 100% rare external destinations:

hxxp://dackdack[.]club/APIv3/modules/nn_grabber_x64.dll [3]
hxxp://dackdack[.]club/APIv3/modules/nn_grabber_x32.dll [4]

Successful second stage downloads were seen to be followed by suspicious HTTP POST beaconing behavior, resembling command and control communication to various domains:

hxxp://kuxkux[.]bit/APIv3/api.php
hxxp://drdrfdd[.]cat/forum/logout.php
hxxp://eaxsess[.]cat/forum/logout.php

Not all targeted companies were seen to receive a second-stage malware download. This might indicate a sophisticated attack plan where the initial generic, covert backdoor is followed by a targeted second-stage payload that is chosen based on the victim and its potential value to the cyber criminals (long term data exfiltration, ransomware, banking Trojan…). Customers reported that infected devices had their anti-virus disabled, or removed by the malware. This showcases that companies cannot solely rely on signature based systems to catch novel, evolving threats.

The beaconing behavior to these 100% unusual external domains was immediately detected as it represented a strong deviation from the devices’ normal ‘pattern of life’. The use of domains hosted on .cat (top level domain used for the Catalan culture and language) indicates that the attackers are highly aware of the cultural context of their target victims and try to make the malware communication blend in with network traffic.

Compromised machines made further repeated DNS requests to the domains below:

dackdack[.]tech
dackdack[.]online
kuykuy[.]bit

At the time of our investigation, the domains below resolved to the following IP address:

142.44.188[.]42
dackdack[.]club
eaxsess[.]cat
kuxkux[.]bit
drdrfdd[.]cat

Closing thoughts

Although final attribution is impossible, the evidence strongly suggests that the campaign described here is similar to the ‘Matrix Banker’ campaign observed in March and June 2017 and might be a continuation of it.

The initial malware was concealing its file types by using different file extensions than their MIME type. More precisely, the use of ‘logo.gif’ has been seen in previous ‘Matrix Banker’ attacks.

There are 3,000 deployments of Darktrace’s AI technology across 70 countries, but all identified instances of this type of compromise are in Latin American organizations.

The ‘Matrix Bankers’ have used Catalan top-level domains in past attacks. In fact, some of the domains used previously are very similar to domains observed here. One domain seen in September was the exact same domain as seen in an earlier attack – just with an additional ‘s’ appended:

Example domains from March/June 2017

trtr44[.]cat
lalax[.]cat
eaxses[.]cat

Example domains from August/October 2017

drdrfdd[.]cat
kuxkux[.]bit
eaxsess[.]cat
kuykuy[.]bit
dackdack[.]tech

Although the domains appear to be randomly generated, a closer look reveals that the ‘Matrix Bankers’ seem to favor generating domain names by using keys that are physically close together on a keyboard, or by repeating phrases one might type in a hurry, when lacking creativity for naming a temporary download (e.g. asdasd.jpeg). We saw this pattern for domain name generation in the March - June ‘Matrix Bankers’ campaign as well as here.

Darktrace’s AI technology was able to detect these stealthy and sophisticated attacks because the way in which they manifest themselves represents a sharp deviation from the normal ‘pattern of life’ within an organization. The threat actors applied a number of techniques to blend into the normal noise of networks, but the self-learning algorithms were quick in detecting the anomalous behavior automatically and in real time.

Footnotes

List of IoCs

dackdack[.]club
dackdack[.]tech
dackdack[.]online
eaxsess[.]cat
kuxkux[.]bit
kuykuy[.]bit
drdrfdd[.]cat
inseltech.com[.]mx
gorrasbaratas.com[.]mx
142.44.188[.]42

[1] VirusTotal analysis of this file
[2] SHA-1: 88f3bdc84908c1fb844b337c535eef2d2b31e1dc
[3] VirusTotal analysis of this file
[4] VirusTotal analysis of this file

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
Max Heinemeyer
Global Field CISO

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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

maduro arrest used as lure to deliver backdoorDefault blog imageDefault blog image

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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