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November 6, 2023

How PlugX Malware Has Evolved & Adapted

Discover how Darktrace effectively detected and thwarted the PlugX remote access trojan in 2023 despite its highly evasive and adaptive nature.
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
Nahisha Nobregas
SOC Analyst
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06
Nov 2023

What is PlugX Remote Access Trojan?

Understanding remote access trojans (RATs)

As malicious actors across the threat landscape continue to pursue more efficient and effective ways of compromising target networks, all while remaining undetected by security measures, it is unsurprising to see an increase in the use of remote access trojans (RATs) in recent years. RATs typically operate stealthily, evading security tools while offering threat actors remote control over infected devices, allowing attackers to execute a wide range of malicious activities like data theft or installing additional malware.

Definition and general functionality of RATs: A Remote Access Trojan (RAT) is a type of malware that enables unauthorized remote control of an infected computer. Once installed, RATs allow attackers to monitor user activities, steal sensitive information, manipulate files, and execute commands. RATs are typically distributed via phishing emails, malicious attachments, drive-by downloads, or exploiting software vulnerabilities. Due to their ability to provide comprehensive control over a compromised system, RATs pose a significant security threat to individuals and organizations.

Historical overview of PlugX

PlugX is one such example of a RAT that has attributed to Chinese threat actors such as Mustang Panda, since it first appeared in the wild back in 2008. It is known for its use in espionage, a modular and plug-in style approach to malware development. It has the ability to evolve with the latest tactics, techniques, and procedures (TTPs) that allow it to avoid the detection of traditional security tools as it implants itself target devices.

How does PlugX work?

The ultimate goal of any RAT is to remotely control affected devices with a wide range of capabilities, which in PlugX’s case has typically included rebooting systems, keylogging, managing critical system processes, and file upload/downloads. One technique PlugX heavily relies on is dynamic-link library (DLL) sideloading to infiltrate devices. This technique involves executing a malicious payload that is embedded within a benign executable found in a data link library (DLL) [1]. The embedded payload within the DLL is often encrypted or obfuscated to prevent detection.

What’s more, a new variant of PlugX was observed in the wild across Papua New Guinea, Ghana, Mongolia, Zimbabwe, and Nigeria in August 2022, that added several new capabilities to its toolbox.

Key capabilities of PlugX

The new variation is reported to continuously monitor affected environments for new USB devices to infect, allowing it to spread further through compromised networks [2]. It is then able to hide malicious files within a USB device by using a novel technique that prevents them from being viewed on Windows operating systems (OS). These hidden files can only be viewed on a Unix-like (.nix) OS, or by analyzing an affected USB devices with a forensic tool [2]. The new PlugX variant also has the ability to create a hidden directory, “RECYCLER.BIN”, containing a collection of stolen documents, likely in preparation for exfiltration via its command and control (C2) channels. [3]

Since December 2022, PlugX has been observed targeting networks in Europe through malware delivery via HTML smuggling campaigns, a technique that has been dubbed SmugX [4].

This evasive tactic allows threat actors to prepare and deploy malware via phishing campaigns by exploiting legitimate HTML5 and JavaScript features [5].

Darktrace Coverage of PlugX

Between January and March 2023, Darktrace observed activity relating to the PlugX RAT on multiple customers across the fleet. While PlugX’s TTPs may have bypassed traditional security tools, the anomaly-based detection capabilities of Darktrace allowed it to identify and alert the subtle deviations in the behavior of affected devices, while Darktrace was able to take immediate mitigative action against such anomalous activity and stop attackers in their tracks.  

C2 Communication

Between January and March 2023, Darktrace detected multiple suspicious connections related to the PlugX RAT within customer environments. When a device has been infected, it will typically communicate through C2 infrastructure established for the PlugX RAT. In most cases observed by Darktrace, affected devices exhibited suspicious C2 connections to rare endpoints that were assessed with moderate to high confidence to be linked to PlugX.

On the network of one Darktrace customer the observed communication was a mix of successful and unsuccessful connections at a high volume to rare endpoints on ports such as 110, 443, 5938, and 80. These ports are commonly associated with POP3, HTTPS, TeamViewer RDP / DynGate, and HTTP, respectively.  Figure 1 below showcases this pattern of activity.

Figure 1: Model Breach Event Log demonstrating various successful and unsuccessful connections to the PlugX C2 endpoint 103.56.53[.]46 via various destination ports.

On another customer’s network, Darktrace observed C2 communication involving multiple failed connection attempts to another rare external endpoint associated with PlugX. The device in this case was detected attempting connections to the endpoint, 45.142.166[.]112 on ports 110, 80, and 443 which caused the DETECT model ‘Anomalous Connection / Multiple Failed Connections to Rare Endpoint’ to breach. This model examines devices attempting connections to a rare external endpoint over a short period of time, and it breached in response to almost all PlugX C2 related activity detected by Darktrace. This highlights Darktrace DETECT’s unique ability to identify anomalous activity which appears benign or uncertain, rather than relying on traditional signature-based detections.

Figure 2: Device Event Log demonstrating various successful and unsuccessful connections to the PlugX C2 endpoint 45.142.166[.]112 via various destination on January 27, 2023.

New User Agent

Darktrace's Self-Learning AI approach to threat detection also allowed it to recognize connections to PlugX associated endpoints that utilized a new user agent. In almost all connections to PlugX endpoints detected by Darktrace, the same user agent, Mozilla/5.0 (Windows NT 10.0;Win64;x64)AppleWebKit/537.36, was observed, illustrating a clear pattern in PlugX-related activity

In one example from February 2023, an affected device successfully connected to an endpoint associated with PlugX, 45.142.166[.]112, while using the aforementioned new user agent, as depicted in Figure 3.

Figure 3: The Device Event log above showcases a successful connection to the PlugX associated IP address, 45.142.166[.]112 using the new user agent ‘Mozilla/5.0 (Windows NT 10.0;Win64;x64)AppleWebKit/537.36’.

On March 21, 2023, Darktrace observed similar activity on a separate customer’s network affected by connections to PlugX. This activity included connections to the same endpoint, 45.142.166[.]112. The connection was an HTTP POST request made via proxy with the same new user agent, ‘Mozilla/5.0 (Windows NT 10.0;Win64;x64)AppleWebKit/537.36’. When investigated further this user agent actually reveals very little about itself and appears to be missing a couple of common features that are typically contained in a user agent string, such as a web browser and its version or the mention of Safari before its build ID (‘537.36’).

Additionally, for this connection the URI observed consisted of a random string of 8 hexadecimal characters, namely ‘d819f07a’. This is a technique often used by malware to communicate with its C2 servers, while evading the detection of signature-based detection tools. Darktrace, however, recognized that this external connection to an endpoint with no hostname constituted anomalous behavior, and could have been indicative of a threat actor communicating with malicious infrastructure, thus the ‘Anomalous Connection / Possible Callback URI’ model was breached.

Figure 4: An affected device was detected using the new user agent, ‘Mozilla/5.0 (Windows NT 10.0;Win64;x64)AppleWebKit/537.36’ while connecting to the rare external endpoint 45.142.166[.]112 via proxy.

Numeric File Download

Darktrace’s detection of PlugX activity on another customer’s network, in February 2023, helped to demonstrate related patterns of activity within the C2 communication and tooling attack phases. Observed PlugX activity on this network followed the subsequent pattern; a connection to a PlugX endpoints is made, followed by a HTTP POST request to a numeric URI with a random string of 8 hexadecimal characters, as previously highlighted. Darktrace identified that this activity represented unusual ‘New Activity’ for this device, and thus treated it with suspicion.

Figure 5: New activity was identified by Darktrace in the Device Event Log shown above for connections to the endpoint 45.142.166[.]112 followed by HTTP POSTs to URIs “/8891431c” and “/ba12b866” on February 15, 2023.

The device in question continued to connect to the endpoint and make HTTP POST connections to various URIs relating to PlugX. Additionally, the user agent `Mozilla/5.0 (Windows NT 10.0;Win64;x64)AppleWebKit/537.36` was again detected for these connections. Figure 6 details the activity captured by Darktrace’s Cyber AI Analyst.

Figure 6: The image above showcases activity captured by Darktrace’s AI Analyst for PlugX connections made on February 15, 2023.

Darktrace detected that during these connections, the device in question attempted to download a suspicious file named only with numbers. The use of numeric file names is a technique often used by threat actors to obfuscate the download of malicious files or programs and bypass traditional security tools. Darktrace understood that the download of a numeric file, coupled with the use of an anomalous new user agent, mean the incident should be treated with suspicion. Fortunately, Darktrace RESPOND was enabled in autonomous response mode during this attack, meaning it was able to automatically block the device from downloading the file, or any other files, from the suspicious external location for a two-hour period, potentially preventing the download of PlugX’s malicious tooling.

Conclusion

Amid the continued evolution of PlugX from an espionage tool to a more widely available malware, it is essential that threat detection does not rely on a set of characteristics or indicators, but rather is focused on anomalies. Throughout these cases, Darktrace demonstrated the efficacy of its detection and alerting on emerging activity pertaining to a particularly stealthy and versatile RAT. Over the years, PlugX has continually looked to evolve and survive in the ever-changing threat landscape by adapting new capabilities and TTPs through which it can infect a system and spread to new devices without being noticed by security teams and their tools.

However, Darktrace’s Self-Learning AI allows it to gain a strong understanding of customer networks, learning what constitutes expected network behavior which in turn allows it to recognize the subtle deviations indicative of an ongoing compromise.

Darktrace’s ability to identify emerging threats through anomaly-based detection, rather than relying on established threat intelligence, uniquely positions it to detect and respond to highly adaptable and dynamic threats, like the PlugX malware, regardless of how it may evolve in the future.

Credit to: Nahisha Nobregas, SOC Analyst & Dylan Hinz, Cyber Analyst

Appendices

MITRE ATT&CK Framework

Execution

  • T1059.003 Command and Scripting Interpreter: Windows Command Shell

Persistence and Privilege Escalation

  • T1547.001 Boot or Logon AutoStart Execution: Registry Run Keys / Startup Folder
  • T1574.001 Hijack Execution Flow: DLL Search Order Hijacking
  • T1574.002 Hijack Execution Flow: DLL Side-Loading
  • T1543.003 Create or Modify System Process: Windows Service
  • T1140 Deobfuscate / Decode Files or Information
  • T1083 File and Directory Discovery

Defense Evasion

  • T1564.001 Hide Artifacts: Hidden Files and Directories
  • T1036.004 Masquerading: Task or Service
  • T1036.005 Masquerading: Match Legitimate Name or Location
  • T1027.006 Obfuscated Files or Information: HTML Smuggling

Credential Access

  • T1056.001 Input Capture: Keylogging

Collection

  • T1105 Ingress Tool Transfer

Command and Control

  • T1573.001 Encrypted Channel: Symmetric Cryptography
  • T1070.003 Mail Protocols
  • T1071.001 Web Protocol

DETECT Model Breaches

  • Anomalous Connection / Multiple Failed Connections to Rare Endpoint
  • Anomalous Connection / New User Agent to IP Without Hostname
  • Anomalous File / New User Agent Followed By Numeric File Download
  • Anomalous Connection / Possible Callback URL

Indicators of Compromise (IoCs)

IoC - Type - Description + Confidence

45.142.166[.]112 - IP - PlugX C2 Endpoint / moderate - high

103.56.53[.]46 - IP - PlugX C2 Endpoint / moderate - high

Mozilla/5.0 (Windows NT 10.0;Win64;x64)AppleWebKit/537.36 - User Agent - PlugX User Agent / moderate – high

/8891431c - URI - PlugX URI / moderate-high

/ba12b866 - URI - PlugX URI / moderate -high

References

1. https://www.crowdstrike.com/blog/dll-side-loading-how-to-combat-threat-actor-evasion-techniques/

2. https://unit42.paloaltonetworks.com/plugx-variants-in-usbs/

3. https://news.sophos.com/en-us/2023/03/09/border-hopping-plugx-usb-worm/

4. https://thehackernews.com/2023/07/chinese-hackers-use-html-smuggling-to.html

5. https://www.cyfirma.com/outofband/html-smuggling-a-stealthier-approach-to-deliver-malware/

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
Nahisha Nobregas
SOC Analyst

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May 8, 2026

The Next Step After Mythos: Defending in a World Where Compromise is Expected

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Is Anthropic’s Mythos a turning point for cybersecurity?

Anthropic’s recent announcements around their Mythos model, alongside the launch of Project Glasswing, have generated significant interest across the cybersecurity industry.

The closed-source nature of the Mythos model has understandably attracted a degree of skepticism around some of the claims being made. Additionally, Project Glasswing was initially positioned as a way for software vendors to accelerate the proactive discovery of vulnerabilities in their own code; however, much of the attention has focused on the potential for AI to identify exploitable vulnerabilities for those with malicious intent.

Putting questions around the veracity of those claims to one side – which, for what it’s worth, do appear to be at least partially endorsed by independent bodies such as the UK’s AI Security Institute – this should not be viewed as a critical turning point for the industry. Rather, it reflects the natural direction of travel.

How Mythos affects cybersecurity teams  

At Darktrace, extolling the virtues of AI within cybersecurity is understandably close to our hearts. However, taking a step back from the hype, we’d like to consider what developments like this mean for security teams.

Whether it’s Mythos or another model yet to be released, it’s worth remembering that there is no fundamental difference between an AI discovered vulnerability and one discovered by a human. The change is in the pace of discovery and, some may argue, the lower the barrier to entry.

In the hands of a software developer, this is unquestionably positive. Faster discovery enables earlier remediation and more proactive security. But in the hands of an attacker, the same capability will likely lead to a greater number of exploitable vulnerabilities being used in the wild and, critically, vulnerabilities that are not yet known to either the vendor or the end user.

That said, attackers have always been able to find exploitable vulnerabilities and use them undetected for extended periods of time. The use of AI does not fundamentally change this reality, but it does make the process faster and, unfortunately, more likely to occur at scale.

While tools such as Darktrace / Attack Surface Management and / Proactive Exposure Management  can help security teams prioritize where to patch, the emergence of AI-driven vulnerability discovery reinforces an important point: patching alone is not a sufficient control against modern cyber-attacks.

Rethinking defense for a world where compromise is expected

Rather than assuming vulnerabilities can simply be patched away, defenders are better served by working from the assumption that their software is already vulnerable - and always will be -and build their security strategy accordingly.

Under that assumption, defenders should expect initial access, particularly across internet exposed assets, to become easier for attackers. What matters then is how quickly that foothold is detected, contained, and prevented from expanding.

For defenders, this places renewed emphasis on a few core capabilities:

  • Secure-by-design architectures and blast radius reduction, particularly around identity, MFA, segmentation, and Zero Trust principles
  • Early, scalable detection and containment, favoring behavioral and context-driven signals over signatures alone
  • Operational resilience, with the expectation of more frequent early-stage incidents that must be managed without burning out teams

How Darktrace helps organizations proactively defend against cyber threats

At Darktrace, we support security teams across all three of these critical capabilities through a multi-layered AI approach. Our Self-Learning AI learns what’s normal for your organization, enabling real-time threat detection, behavioral prediction, incident investigation and autonomous response. - all while empowering your security team with visibility and control.

To learn more about Darktrace’s application of AI to cybersecurity download our White Paper here.  

Reducing blast radius through visibility and control

Secure-by-design principles depend on understanding how users, devices, and systems behave. By learning the normal patterns of identity and network activity, Darktrace helps teams identify when access is being misused or when activity begins to move beyond expected boundaries. This makes it possible to detect and contain lateral movement early, limiting how far an attacker can progress even after initial access.

Detecting and containing threats at the earliest stage  

As AI accelerates vulnerability discovery, defenders need to identify exploitation before it is formally recognized. Darktrace’s behavioral understanding approach enables detection of subtle deviations from normal activity, including those linked to previously unknown vulnerabilities.

A key example of this is our research on identifying cyber threats before public CVE disclosures, demonstrating that assessing activity against what is normal for a specific environment, rather than relying on predefined indicators of compromise, enables detection of intrusions exploiting previously unknown vulnerabilities days or even weeks before details become publicly available.

Additionally, our Autonomous Response capability provides fast, targeted containment focused on the most concerning events, while allowing normal business operations to continue. This has consistently shown that even when attackers use techniques never seen before, Darktrace’s Autonomous Response can contain threats before they have a chance to escalate.

Scaling response without increasing operational burden

As early-stage incidents become more frequent, the ability to investigate and respond efficiently becomes critical. Darktrace’s Cyber AI Analyst’s AI-driven investigation capabilities automatically correlate activity across the environment, prioritizing the most significant threats and reducing the need for manual triage. This allows security teams to respond faster and more consistently, without increasing workload or burnout.

What effective defense looks like in an AI-accelerated landscape

Developments like Mythos highlight a reality that has been building for some time: the window between exposure and exploitation is shrinking, and in many cases, it may disappear entirely. In that environment, relying on patching alone becomes increasingly reactive, leaving little room to respond once access has been established.

The more durable approach is to assume that compromise will occur and focus on controlling what happens next. That means identifying early signs of misuse, containing threats before they spread, and maintaining visibility across the environment so that isolated signals can be understood in context.

AI plays a role on both sides of this equation. While it enables attackers to move faster, it also gives defenders the ability to detect subtle changes in behavior, prioritize what matters, and respond in real time. The advantage will not come from adopting AI in isolation, but from applying it in a way that reduces the gap between detection and action.

AI may be accelerating parts of the attack lifecycle, but the fundamentals of defense, detection, and containment still apply. If anything, they matter more than ever – and AI is just as powerful a tool for defenders as it is for attackers.

To learn more about Darktrace and Mythos read more on our blog: Mythos vs Ethos: Defending in an Era of AI‑Accelerated Vulnerability Discovery

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Toby Lewis
Head of Threat Analysis

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May 6, 2026

When Trust Becomes the Attack Surface: Supply-Chain Attacks in an Era of Automation and Implicit Trust

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Software supply-chain attacks in 2026

Software supply-chain attacks now represent the primary threat shaping the 2026 security landscape. Rather than relying on exploits at the perimeter, attackers are targeting the connective tissue of modern engineering environments: package managers, CI/CD automation, developer systems, and even the security tools organizations inherently trust.

These incidents are not isolated cases of poisoned code. They reflect a structural shift toward abusing trusted automation and identity at ecosystem scale, where compromise propagates through systems designed for speed, not scrutiny. Ephemeral build runners, regardless of provider, represent high‑trust, low‑visibility execution zones.

The Axios compromise and the cascading Trivy campaign illustrate how quickly this abuse can move once attacker activity enters build and delivery workflows. This blog provides an overview of the latest supply chain and security tool incidents with Darktrace telemetry and defensive actions to improve organizations defensive cyber posture.

1. Why the Axios Compromise Scaled

On 31 March 2026, attackers hijacked the npm account of Axios’s lead maintainer, publishing malicious versions 1.14.1 and 0.30.4 that silently pulled in a malicious dependency, plain‑crypto‑[email protected]. Axios is a popular HTTP client for node.js and  processes 100 million weekly downloads and appears in around 80% of cloud and application environments, making this a high‑leverage breach [1].

The attack chain was simple yet effective:

  • A compromised maintainer account enabled legitimate‑looking malicious releases.
  • The poisoned dependency executed Remote Access Trojans (RATs) across Linux, macOS and Windows systems.
  • The malware beaconed to a remote command-and-control (C2) server every 60 seconds in a loop, awaiting further instructions.
  • The installer self‑cleaned by deleting malicious artifacts.

All of this matters because a single maintainer compromise was enough to project attacker access into thousands of trusted production environments without exploiting a single vulnerability.

A view from Darktrace

Multiple cases linked with the Axios compromise were identified across Darktrace’s customer base in March 2026, across both Darktrace / NETWORK and Darktrace / CLOUD deployments.

In one Darktrace / CLOUD deployment, an Azure Cloud Asset was observed establishing new external HTTP connectivity to the IP 142.11.206[.]73 on port 8000. Darktrace deemed this activity as highly anomalous for the device based on several factors, including the rarity of the endpoint across the network and the unusual combination of protocol and port for this asset. As a result, the triggering the "Anomalous Connection / Application Protocol on Uncommon Port" model was triggered in Darktrace / CLOUD. Detection was driven by environmental context rather than a known indicator at the time. Subsequent reporting later classified the destination as malicious in relation to the Axios supply‑chain compromise, reinforcing the gap that often exists between initial attacker activity and the availability of actionable intelligence. [5]

Additionally, shortly before this C2 connection, the device was observed communicating with various endpoints associated with the NPM package manager, further reinforcing the association with this attack.

Darktrace’s detection of the unusual external connection to 142.11[.]206[.]73 via port 8000.  
Figure 1: Darktrace’s detection of the unusual external connection to 142.11[.]206[.]73 via port 8000.  

Within Axios cases observed within Darktrace / NETWORK customer environments, activity generally focused on the use of newly observed cURL user agents in outbound connections to the C2 URL sfrclak[.]com/6202033, alongside the download of malicious files.

In other cases, Darktrace / NETWORK customers with Microsoft Defender for Endpoint integration received alerts flagging newly observed system executables and process launches associated with C2 communication.

A Security Integration Alert from Microsoft Defender for Endpoint associated with the Axios supply chain attack.
Figure 2: A Security Integration Alert from Microsoft Defender for Endpoint associated with the Axios supply chain attack.

2. Why Trivy bypassed security tooling trust

Between late February and March 22, 2026, the threat group TeamPCP leveraged credentials from a previous incident to insert malicious artifacts across Trivy’s distribution ecosystem, including its CI automation, release binaries, Visual Studio Code extensions, and Docker container images [2].

While public reporting has emphasized GitHub Actions, Darktrace telemetry highlights attacker execution within CI/CD runner environments, including ephemeral build runners. These execution contexts are typically granted broad trust and limited visibility, allowing malicious activity within build automation to blend into expected operational workflows, regardless of provider.

This was a coordinated multi‑phase attack:

  • 75 of 76  of trivy-action tags and all setup‑trivy tags were force‑pushed to deliver a malicious payload.
  • A malicious binary (v0.69.4) was distributed across all major distribution channels.
  • Developer machines were compromised, receiving a persistent backdoor and a self-propagating worm.
  • Secrets were exfiltrated at scale, including SSH keys, Kuberenetes tokens, database passwords, and cloud credentials across Amazon Web Service (AWS), Azure, and Google Cloud Platform (GCP).

Within Darktrace’s customer base, an AWS EC2 instance monitored by Darktrace / CLOUD  appeared to have been impacted by the Trivy attack. On March 19, the device was seen connecting to the attacker-controlled C2 server scan[.]aquasecurtiy[.]org (45.148.10[.]212), triggering the model 'Anomalous Server Activity / Outgoing from Server’ in Darktrace / CLOUD.

Despite this limited historical context, Darktrace assessed this activity as suspicious due to the rarity of the destination endpoint across the wider deployment. This resulted in the triggering of a model alert and the generation of a Cyber AI Analyst incident to further analyze and correlate the attack activity.

TeamPCP’s continued abused of GitHub Actions against security and IT tooling has also been observed more recently in Darktrace’s customer base. On April 22, an AWS asset was seen connecting to the C2 endpoint audit.checkmarx[.]cx (94.154.172[.]43). The timing of this activity suggests a potential link to a malicious Bitwarden package distributed by the threat actor, which was only available for a short timeframe on April 22. [4][3]

Figure 3: A model alert flagging unusual external connectivity from the AWS asset, as seen in Darktrace / CLOUD .

While the Trivy activity originated within build automation, the underlying failure mode mirrors later intrusions observed via management tooling. In both cases, attackers leveraged platforms designed for scale and trust to execute actions that blended into normal operational noise until downstream effects became visible.

Quest KACE: Legacy Risk, Real Impact

The Quest KACE System Management Appliance (SMA) incident reinforces that software risk is not confined to development pipelines alone. High‑trust infrastructure and management platforms are increasingly leveraged by adversaries when left unpatched or exposed to the internet.

Throughout March 2026, attackers exploited CVE 2025-32975 to authentication on outdated, internet-facing KACE appliances, gaining administrative control and pushing remote payloads into enterprise environments. Organizations still running pre-patch versions effectively handed adversaries a turnkey foothold, reaffirming a simple strategic truth: legacy management systems are now part of the supply-chain threat surface, and treating them as “low-risk utilities” is no longer defensible [3].

Within the Darktrace customer base, a potential case was identified in mid-March involving an internet-facing server that exhibited the use of a new user agent alongside unusual file downloads and unexpected external connectivity. Darktrace identified the device downloading file downloads from "216.126.225[.]156/x", "216.126.225[.]156/ct.py" and "216.126.225[.]156/n", using the user agents, "curl/8.5.0" & "Python-urllib/3.9".

The timeframe and IoCs observed point towards likely exploitation of CVE‑2025‑32975. As with earlier incidents, the activity became visible through deviations in expected system behavior rather than through advance knowledge of exploitation or attacker infrastructure. The delay between observed exploitation and its addition to the Known Exploited Vulnerabilities (KEV) catalogue underscores a recurring failure: retrospective validation cannot keep pace with adversaries operating at automation speed.

The strategic pattern: Ecosystem‑scale adversaries

The Axios and Trivy compromises are not anomalies; they are signals of a structural shift in the threat landscape. In this post-trust era, the compromise of a single maintainer, repository token, or CI/CD tag can produce large-scale blast radiuses with downstream victims numbering in the thousands. Attackers are no longer just exploiting vulnerabilities; they are exploiting infrastructure privileges, developer trust relationships, and automated build systems that the industry has generally under secured.

Supply‑chain compromise should now be treated as an assumed breach scenario, not a specialized threat class, particularly across build, integration, and management infrastructure. Organizations must operate under the assumption that compromise will occur within trusted software and automation layers, not solely at the network edge or user endpoint. Defenders should therefore expect compromise to emerge from trusted automation layers before it is labelled, validated, or widely understood.

The future of supply‑chain defense lies in continuous behavioral visibility, autonomous detection across developer and build environments, and real‑time anomaly identification.

As AI increasingly shapes software development and security operations, defenders must assume adversaries will also operate with AI in the loop. The defensive edge will come not from predicting specific compromises, but from continuously interrogating behavior across environments humans can no longer feasibly monitor at scale.

Credit to Nathaniel Jones (VP, Security & AI Strategy, FCISCO), Emma Foulger (Global Threat Research Operations Lead), Justin Torres (Senior Cyber Analyst), Tara Gould (Malware Research Lead)

Edited by Ryan Traill (Content Manager)

Appendices

References:

1)         https://www.infosecurity-magazine.com/news/hackers-hijack-axios-npm-package/

2)         https://thehackernews.com/2026/03/trivy-hack-spreads-infostealer-via.html

3)         https://thehackernews.com/2026/03/hackers-exploit-cve-2025-32975-cvss-100.html

4)         https://www.endorlabs.com/learn/shai-hulud-the-third-coming----inside-the-bitwarden-cli-2026-4-0-supply-chain-attack

5)         https://socket.dev/blog/axios-npm-package-compromised?trk=public_post_comment-text

IoCs

- 142.11.206[.]73 – IP Address – Axios supply chain C2

- sfrclak[.]com – Hostname – Axios supply chain C2

- hxxp://sfrclak[.]com:8000/6202033 - URI – Axios supply chain payload

- 45.148.10[.]212 – IP Address – Trivy supply chain C2

- scan.aquasecurtiy[.]org – Hostname - Trivy supply chain C2

- 94.154.172[.]43 – IP Address - Checkmarx/Bitwarden supply chain C2

- audit.checkmarx[.]cx – Hostname - Checkmarx/Bitwarder supply chain C2

- 216.126.225[.]156 – IP Address – Quest KACE exploitation C2

- 216.126.225[.]156/32 - URI – Possible Quest KACE exploitation payload

- 216.126.225[.]156/ct.py - URI - Possible Quest KACE exploitation payload

- 216.126.225[.]156/n - URI - Possible Quest KACE exploitation payload

- 216.126.225[.]156/x - URI - Possible Quest KACE exploitation payload

- e1ec76a0e1f48901566d53828c34b5dc – MD5 - Possible Quest KACE exploitation payload

- d3beab2e2252a13d5689e9911c2b2b2fc3a41086 – SHA1 - Possible Quest KACE exploitation payload

- ab6677fcbbb1ff4a22cc3e7355e1c36768ba30bbf5cce36f4ec7ae99f850e6c5 – SHA256 - Possible Quest KACE exploitation payload

- 83b7a106a5e810a1781e62b278909396 – MD5 - Possible Quest KACE exploitation payload

- deb4b5841eea43cb8c5777ee33ee09bf294a670d – SHA1 - Possible Quest KACE exploitation payload

- b1b2f1e36dcaa36bc587fda1ddc3cbb8e04c3df5f1e3f1341c9d2ec0b0b0ffaf – SHA256 - Possible Quest KACE exploitation payload

Darktrace Model Detections

Anomalous Connection / Application Protocol on Uncommon Port

Anomalous Server Activity / Outgoing from Server

Anomalous Connection / New User Agent to IP Without Hostname

Anomalous File / EXE from Rare External Location

Anomalous File / Script from Rare External Location

Anomalous Server Activity / New User Agent from Internet Facing System

Anomalous Server Activity / Rare External from Server

Antigena / Network / External Threat / Antigena Suspicious File Block

Antigena / Network / External Threat / Antigena Suspicious File Pattern of Life Block

Device / New User Agent

Device / Internet Facing Device with High Priority Alert

Anomalous File / New User Agent Followed By Numeric File Download

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About the author
Nathaniel Jones
VP, Security & AI Strategy, Field CISO
あなたのデータ × DarktraceのAI
唯一無二のDarktrace AIで、ネットワークセキュリティを次の次元へ