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January 17, 2024

Detecting Trusted Network Relationship Abuse

Discover how Darktrace DETECT and the SOC team responded to a network compromise via a trusted partner relationship with this case study.
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
Adam Potter
Senior Cyber Analyst
Written by
Taylor Breland
Analyst Team Lead, San Francisco
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17
Jan 2024

Trusted relationships between organizations and third parties have become an increasingly popular target for cyber threat actors to gain access to sensitive networks. These relationships are typically granted by organizations to external or adjacent entities and allow for the access of internal resources for business purposes.1 Trusted network relations can exist between constituent elements of an overarching corporation, IT-service providers and their customers, and even implicitly between IT product vendors and their customers.

Several high-profile compromises have occurred due to the leveraging of privileged network access by such third parties. One prominent example is the 2016 DNC network attack, in which the trust between the Democratic Congressional Campaign Committee (DCCC) and the Democratic National Committee (DNC) was exploited. Supply chain attacks, which also leverage the implicit trust between IT vendors and customers, are also on the rise with some estimates projecting that by 2025, almost half of all organizations will be impact by supply chain compromises.2 These trends may also be attributed to the prevalence of remote work as well as the growth in IT-managed service providers.3

Given the nature of such network relationships and threat techniques, signatures-based detection is heavily disadvantaged in the identification and mitigation of such trust abuses; network administrators cannot as easily use firewalls to block IPs that need access to networks. However, Darktrace DETECT™, and its Self-Learning AI, has proven successful in the identification and mitigation of these compromises. In September 2023, Darktrace observed an incident involving the abuse of such a trusted relationship on the network of a healthcare provider.

Attack Overview

In early September 2023, a Darktrace customer contacted the Darktrace Security Operations Center (SOC) through the Ask the Expert™ (ATE) service requesting assistance with suspicious activity detected on their network. Darktrace had alerted the customer’s security team to an unknown device that had appeared on their network and proceeded to perform a series of unexpected activities, including reconnaissance, lateral movement, and attempted data exfiltration.

Unfortunately for this customer, Darktrace RESPOND™ was not enabled in autonomous response mode at the time of this compromise, meaning any preventative actions suggested by RESPOND had to be applied manually by the customer’s security team after the fact.  Nevertheless, Darktrace’s prompt identification of the suspicious activity and the SOC’s investigation helped to disrupt the intrusion in its early stages, preventing it from developing into a more disruptive compromise.

Initial Access

Darktrace initially observed a new device that appeared within the customers internal network with a Network Address Translated (NAT) IP address that suggested remote access from a former partner organization’s network. Further investigation carried out by the customer revealed that poor credential policies within the partner’s organization had likely been exploited by attackers to gain access to a virtual desktop interface (VDI) machine.

Using the VDI appliance of a trusted associate, the threat actor was then able to gain access to the customer’s environment by utilizing NAT remote access infrastructure. Devices within the customer’s network had previously been utilized for remote access from the partner network when such activity was permitted and expected. Since then, access to this network was thought to have been removed for all parties. However, it became apparent that the remote access functionality remained operational. While the customer also had firewalls within the environment, a misconfiguration at the time of the attack allowed inbound port access to the remote environment resulting in the suspicious device joining the network on August 29, 2023.

Internal Reconnaissance

Shortly after the device joined the network, Darktrace observed it carrying out a string of internal reconnaissance activity. This activity was initiated with internal ICMP address connectivity, followed by internal TCP connection attempts to a range of ports associated with critical services like SMB, RDP, HTTP, RPC, and SSL. The device was also detected attempting to utilize privileged credentials, which were later identified as relating to a generic multi-purpose administrative account. The threat actor proceeded to conduct further internal reconnaissance, including reverse DNS sweeps, while also attempting to use six additional user credentials.

In addition to the widespread internal connectivity, Darktrace observed persistent connection attempts focused on the RDP and SMB protocols. Darktrace also detected additional SMB enumeration during this phase of the attacker’s reconnaissance. This reconnaissance activity largely attempted to access a wide variety of SMB shares, previously unseen by the host to identify available share types and information available for aggregation. As such, the breach host conducted a large spike in SMB writes to the server service (srvsvc) endpoint on a range of internal hosts using the credential: extramedwb. SMB writes to this endpoint traditionally indicate binding attempts.

Beginning on August 31, Darktrace identified a new host associated with the aforementioned NAT IP address. This new host appeared to have taken over as the primary host conducting the reconnaissance and lateral movement on the network taking advantage of the VDI infrastructure. Like the previous host, this one was observed sustaining reconnaissance activity on August 31, featuring elevated SMB enumeration, SMB access failures, RDP connection attempts, and reverse DNS sweeps.  The attackers utilized several credentials to execute their reconnaissance, including generic and possibly default administrative credentials, including “auditor” and “administrator”.

Figure 1: Advanced Search query highlighting anomalous activity from the second observed remote access host over the course of one week surrounding the time of the breach.

Following these initial detections by Darktrace DETECT, Darktrace’s Cyber AI Analyst™ launched an autonomous investigation into the scanning and privileged internal connectivity and linked these seemingly separate events together into one wider internal reconnaissance incident.

Figure 2: Timeline of an AI Analyst investigation carried out between August 29 and August 31, 2023, during which it detected an increased volume of scanning and unusual privileged internal connectivity.

Lateral Movement

Following the reconnaissance activity performed by the new host observed exploiting the remote access infrastructure, Darktrace detected an increase in attempts to move laterally within the customer’s network, particularly via RPC commands and SMB file writes.

Specifically, the threat actor was observed attempting RPC binds to several destination devices, which can be used in the calling of commands and/or the creation of services on destination devices. This activity was highlighted in repeated failed attempts to bind to the ntsvcs named pipe on several destination devices within the network. However, given the large number of connection attempts, Darktrace did also detect a number of successful RPC connections.

Darktrace also detected a spike in uncommon service control (SVCCTL) ExecMethod, Create, and Start service operations from the breach device.

Figure 3: Model breach details noting the affected device performing unsuccessful RPC binds to endpoints not supported on the destination device.

Additional lateral movement activity was performed using the SMB/NTLM protocols. The affected device also conducted a series of anonymous NTLM logins, whereby NTLM authentication attempts occurred without a named client principal, to a range of internal hosts. Such activity is highly indicative of malicious or unauthorized activity on the network. The host also employed the outdated SMB version 1 (SMBv1) protocol during this phase of the kill chain. The use of SMBv1 often represents a compliance issue for most networks due to the high number of exploitable vulnerabilities associated with this version of the protocol.

Lastly, Darktrace identified the internal transfer of uncommon executables, such as ‘TRMtZSqo.exe’, via SMB write. The breach device was observed writing this file to the hidden administrative share (ADMIN$) on a destination server. Darktrace recognized that this activity was highly unusual for the device and may have represented the threat actor transferring a malicious payload to the destination server for further persistence, data aggregation, and/or command and control (C2) operations. Further SMB writes of executable files, and the subsequent delete of these binaries, were observed from the device at this time. For example, the additional executable ‘JAqfhBEB.exe’ was seen being deleted by the breach device. This deletion, paired with the spike in SVCCTL Create and Start operations occurring, suggests the transfer, execution, and removal of persistence and data harvesting binaries within the network.

Figure 4: AI Analyst details highlighting the SMB file writes of the unusual executable from the remote access device during the compromise.

Conclusion

Ultimately, Darktrace was able to successfully identify and alert for suspicious activity being performed by a threat actor who had gained unauthorized access to the customer’s network by abusing one of their trusted relationships.

The identification of scanning, RPC commands and SMB sessions directly assisted the customer in their response to contain and mitigate this intrusion. The investigation carried out by the Darktrace SOC enabled the customer to promptly triage and remediate the attack, mitigating the potential damage and preventing the compromise from escalating further. Had Darktrace RESPOND been enabled in autonomous response mode at the time of the attack, it would have been able to take swift action to inhibit the scanning, share enumerations and file write activity, thereby thwarting the attacker’s network reconnaissance and lateral movement attempts.

By exploiting trusted relationships between organizations, threat actors are often able to bypass traditional signatured-based security methods that have previously been reconfigured to allow and trust connections from and to specific endpoints. Rather than relying on the configurations of specific rules and permitted IP addresses, ports, and devices, Darktrace DETECT’s anomaly-based approach to threat detection meant it was able to identify suspicious network activity at the earliest stage, irrespective of the offending device and whether the domain or relationship was trusted.

Credit to Adam Potter, Cyber Security Analyst, Taylor Breland, Analyst Team Lead, San Francisco.

Darktrace DETECT Model Breach Coverage:

  • Device / ICMP Address Scan
  • Device / Network Scan
  • Device / Suspicious SMB Scanning Activity
  • Device / RDP Scan
  • Device / Possible SMB/NTLM Reconnaissance
  • Device / Reverse DNS Sweep
  • Anomalous Connection / SMB Enumeration
  • Device / Large Number of Model Breaches
  • Anomalous Connection / Suspicious Activity On High Risk Device
  • Unusual Activity / Possible RPC Recon Activity
  • Device / Anonymous NTLM Logins
  • Anomalous Connection / Unusual SMB Version 1 Connectivity
  • Device / Repeated Unknown RPC Service Bind Errors
  • Anomalous Connection / New or Uncommon Service Control
  • Compliance / SMB Drive Write
  • Anomalous File / Internal / Unusual Internal EXE File Transfer
  • Device / Multiple Lateral Movement Model Breaches

AI Analyst Incidents:

  • Scanning of Multiple Devices
  • Extensive Unusual RDPConnections
  • SMB Write of Suspicious File
  • Suspicious DCE-RPC Activity

MITRE ATT&CK Mapping

  • Tactic: Initial Access
  • Technique: T1199 - Trusted Relationship
  • Tactic: Discovery
  • Technique:
  • T1018 - Remote System Discovery
  • T1046 - Network Service Discovery
  • T1135 - Network Share Discovery
  • T1083 - File and Directory Discovery
  • Tactic: Lateral Movement
  • Technique:
  • T1570 - Lateral Tool Transfer
  • T1021 - Remote Services
  • T1021.002 - SMB/Windows Admin Shares
  • T1021.003 - Distributed Component Object Model
  • T1550 - Use Alternate Authentication Material

References

1https://attack.mitre.org/techniques/T1199/

2https://www.cloudflare.com/learning/insights-supply-chain-attacks/

3https://newsroom.cisco.com/c/r/newsroom/en/us/a/y2023/m09/companies-reliance-on-it-managed-services-increases-in-2023-sector-valued-at-us-472-billion-globally.html#:~:text=IT%20channel%20partners%20selling%20managed,US%24419%20billion%20in%202022.

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
Adam Potter
Senior Cyber Analyst
Written by
Taylor Breland
Analyst Team Lead, San Francisco

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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.

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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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