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September 28, 2023

How Darktrace Stopped an Account Hijack Fast

Learn how Darktrace detected an account hijack within days of deployment. Discover the strategies used to protect against cyber threats.
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
Min Kim
Cyber Security Analyst
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28
Sep 2023

Cloud Migration Expanding the Attack Surface

Cloud migration is here to stay – accelerated by pandemic lockdowns, there has been an ongoing increase in the use of public cloud services, and Gartner has forecasted worldwide public cloud spending to grow around 20%, or by almost USD 600 billion [1], in 2023. With more and more organizations utilizing cloud services and moving their operations to the cloud, there has also been a corresponding shift in malicious activity targeting cloud-based software and services, including Microsoft 365, a prominent and oft-used Software-as-a-Service (SaaS).

With the adoption and implementation of more SaaS products, the overall attack surface of an organization increases – this gives malicious actors additional opportunities to exploit and compromise a network, necessitating proper controls to be in place. This increased attack surface can leave organization’s open to cyber risks like cloud misconfigurations, supply chain attacks and zero-day vulnerabilities [2]. In order to achieve full visibility over cloud activity and prevent SaaS compromise, it is paramount for security teams to deploy sophisticated security measures that are able to learn an organization’s SaaS environment and detect suspicious activity at the earliest stage.

Darktrace Immediately Detects Hijacked Account

In May 2023, Darktrace observed a chain of suspicious SaaS activity on the network of a customer who was about to begin their trial of Darktrace/Apps™ and Darktrace/Email™. Despite being deployed on the network for less than a week, Darktrace DETECT™ recognized that the legitimate SaaS account, belonging to an executive at the organization, had been hijacked. Darktrace/Email was able to provide full visibility over inbound and outbound mail and identified that the compromised account was subsequently used to launch an internal spear-phishing campaign.

If Darktrace RESPOND™ were enabled in autonomous response mode at the time of this compromise, it would have been able to take swift preventative action to disrupt the account compromise and prevent the ensuing phishing attack.

Account Hijack Attack Overview

Unusual External Sources for SaaS Credentials

On May 9, 2023, Darktrace/Apps detected the first in a series of anomalous activities performed by a Microsoft 365 user account that was indicative of compromise, namely a failed login from an external IP address located in Virginia.

Figure 1: The failed login notice, as seen in Darktrace/Apps. The notice includes additional context about the failed login attempt to the SaaS account.

Just a few minutes later, Darktrace observed the same user credential being used to successfully login from the same unusual IP address, with multi-factor authentication (MFA) requirements satisfied.

Figure 2: The “Unusual External Source for SaaS Credential Use” model breach summary, showing the successful login to the SaaS user account (with MFA), from the rare external IP address.

A few hours after this, the user credential was once again used to login from a different city in the state of Virginia, with MFA requirements successfully met again. Around the time of this activity, the SaaS user account was also observed previewing various business-related files hosted on Microsoft SharePoint, behavior that, taken in isolation, did not appear to be out of the ordinary and could have represented legitimate activity.

The following day, May 10, however, there were additional login attempts observed from two different states within the US, namely Texas and Florida. Darktrace understood that this activity was extremely suspicious, as it was highly improbable that the legitimate user would be able to travel over 2,500 miles in such a short period of time. Both login attempts were successful and passed MFA requirements, suggesting that the malicious actor was employing techniques to bypass MFA. Such MFA bypass techniques could include inserting malicious infrastructure between the user and the application and intercepting user credentials and tokens, or by compromising browser cookies to bypass authentication controls [3]. There have also been high-profile cases in the recent years of legitimate users mistakenly (and perhaps even instinctively) accepting MFA prompts on their token or mobile device, believing it to be a legitimate process despite not having performed the login themselves.

New Email Rule

On the evening of May 10, following the successful logins from multiple US states, Darktrace observed the Microsoft 365 user creating a new inbox rule, named “.’, in Microsoft Outlook from an IP located in Florida. Threat actors are often observed naming new email rules with single characters, likely to evade detection, but also for the sake of expediency so as to not expend any additional time creating meaningful labels.

In this case the newly created email rules included several suspicious properties, including ‘AlwaysDeleteOutlookRulesBlob’, ‘StopProcessingRules’ and “MoveToFolder”.

Firstly, ‘AlwaysDeleteOutlookRulesBlob’ suppresses or hides warning messages that typically appear if modifications to email rules are made [4]. In this case, it is likely the malicious actor was attempting to implement this property to obfuscate the creation of new email rules.

The ‘StopProcessingRules’ rule meant that any subsequent email rules created by the legitimate user would be overridden by the email rule created by the malicious actor [5]. Finally, the implementation of “MoveToFolder” would allow the malicious actor to automatically move all outgoing emails from the “Sent” folder to the “Deleted Items” folder, for example, further obfuscating their malicious activities [6]. The utilization of these email rule properties is frequently observed during account hijackings as it allows attackers to delete and/or forward key emails, delete evidence of exploitation and launch phishing campaigns [7].

In this incident, the new email rule would likely have enabled the malicious actor to evade the detection of traditional security measures and achieve greater persistence using the Microsoft 365 account.

Figure 3: Screenshot of the “New Email Rule” model breach. The Office365 properties associated with the newly modified Microsoft Outlook inbox rule, “.”, are highlighted in red.

Account Update

A few hours after the creation of the new email rule, Darktrace observed the threat actor successfully changing the Microsoft 365 user’s account password, this time from a new IP address in Texas. As a result of this action, the attacker would have locked out the legitimate user, effectively gaining full access over the SaaS account.

Figure 4: The model breach event log showing the user password and token change updates performed by the compromised SaaS account.

Phishing Emails

The compromised SaaS account was then observed sending a high volume of suspicious emails to both internal and external email addresses. Darktrace was able to identify that the emails attempting to impersonate the legitimate service DocuSign and contained a malicious link prompting users to click on the text “Review Document”. Upon clicking this link, users would be redirected to a site hosted on Adobe Express, namely hxxps://express.adobe[.]com/page/A9ZKVObdXhN4p/.

Adobe Express is a free service that allows users to create web pages which can be hosted and shared publicly; it is likely that the threat actor here leveraged the service to use in their phishing campaign. When clicked, such links could result in a device unwittingly downloading malware hosted on the site, or direct unsuspecting users to a spoofed login page attempting to harvest user credentials by imitating legitimate companies like Microsoft.

Figure 5: Screenshot of the phishing email, containing a malicious link hidden behind the “Review Document” text. The embedded link directs to a now-defunct page that was hosted on Adobe Express.

The malicious site hosted on Adobe Express was subsequently taken down by Adobe, possibly in response to user reports of maliciousness. Unfortunately though, platforms like this that offer free webhosting services can easily and repeatedly be abused by malicious actors. Simply by creating new pages hosted on different IP addresses, actors are able to continue to carry out such phishing attacks against unsuspecting users.

In addition to the suspicious SaaS and email activity that took place between May 9 and May 10, Darktrace/Email also detected the compromised account sending and receiving suspicious emails starting on May 4, just two days after Darktrace’s initial deployment on the customer’s environment. It is probable that the SaaS account was compromised around this time, or even prior to Darktrace’s deployment on May 2, likely via a phishing and credential harvesting campaign similar to the one detailed above.

Figure 6: Event logs of the compromised SaaS user, here seen breaching several Darktrace/Email model breaches on 4th May.

Darktrace Coverage

As the customer was soon to begin their trial period, Darktrace RESPOND was set in “human confirmation” mode, meaning that any preventative RESPOND actions required manual application by the customer’s security team.

If Darktrace RESPOND had been enabled in autonomous response mode during this incident, it would have taken swift mitigative action by logging the suspicious user out of the SaaS account and disabling the account for a defined period of time, in doing so disrupting the attack at the earliest possible stage and giving the customer the necessary time to perform remediation steps.  As it was, however, these RESPOND actions were suggested to the customer’s security team for them to manually apply.

Figure 7: Example of Darktrace RESPOND notices, in response to the anomalous user activity.

Nevertheless, with Darktrace/Apps in place, visibility over the anomalous cloud-based activities was significantly increased, enabling the swift identification of the chain of suspicious activities involved in this compromise.

In this case, the prospective customer reached out to Darktrace directly through the Ask the Expert (ATE) service. Darktrace’s expert analyst team then conducted a timely and comprehensive investigation into the suspicious activity surrounding this SaaS compromise, and shared these findings with the customer’s security team.

Conclusion

Ultimately, this example of SaaS account compromise highlights Darktrace’s unique ability to learn an organization’s digital environment and recognize activity that is deemed to be unexpected, within a matter of days.

Due to the lack of obvious or known indicators of compromise (IoCs) associated with the malicious activity in this incident, this account hijack would likely have gone unnoticed by traditional security tools that rely on a rules and signatures-based approach to threat detection. However, Darktrace’s Self-Learning AI enables it to detect the subtle deviations in a device’s behavior that could be indicative of an ongoing compromise.

Despite being newly deployed on a prospective customer’s network, Darktrace DETECT was able to identify unusual login attempts from geographically improbable locations, suspicious email rule updates, password changes, as well as the subsequent mounting of a phishing campaign, all before the customer’s trial of Darktrace had even begun.

When enabled in autonomous response mode, Darktrace RESPOND would be able to take swift preventative action against such activity as soon as it is detected, effectively shutting down the compromise and mitigating any subsequent phishing attacks.

With the full deployment of Darktrace’s suite of products, including Darktrace/Apps and Darktrace/Email, customers can rest assured their critical data and systems are protected, even in the case of hybrid and multi-cloud environments.

Credit: Samuel Wee, Senior Analyst Consultant & Model Developer

Appendices

References

[1] https://www.gartner.com/en/newsroom/press-releases/2022-10-31-gartner-forecasts-worldwide-public-cloud-end-user-spending-to-reach-nearly-600-billion-in-2023

[2] https://www.upguard.com/blog/saas-security-risks

[3] https://www.microsoft.com/en-us/security/blog/2022/11/16/token-tactics-how-to-prevent-detect-and-respond-to-cloud-token-theft/

[4] https://learn.microsoft.com/en-us/powershell/module/exchange/disable-inboxrule?view=exchange-ps

[5] https://learn.microsoft.com/en-us/dotnet/api/microsoft.exchange.webservices.data.ruleactions.stopprocessingrules?view=exchange-ews-api

[6] https://learn.microsoft.com/en-us/dotnet/api/microsoft.exchange.webservices.data.ruleactions.movetofolder?view=exchange-ews-api

[7] https://blog.knowbe4.com/check-your-email-rules-for-maliciousness

Darktrace Model Detections

Darktrace DETECT and RESPOND Models Breached:

SaaS / Access / Unusual External Source for SaaS Credential Use

SaaS / Unusual Activity / Multiple Unusual External Sources for SaaS Credential

Antigena / SaaS / Antigena Unusual Activity Block (RESPOND Model)

SaaS / Compliance / New Email Rule

Antigena / SaaS / Antigena Significant Compliance Activity Block

SaaS / Compromise / Unusual Login and New Email Rule (Enhanced Monitoring Model)

Antigena / SaaS / Antigena Suspicious SaaS Activity Block (RESPOND Model)

SaaS / Compromise / SaaS Anomaly Following Anomalous Login (Enhanced Monitoring Model)

SaaS / Compromise / Unusual Login and Account Update

Antigena / SaaS / Antigena Suspicious SaaS Activity Block (RESPOND Model)

IoC – Type – Description & Confidence

hxxps://express.adobe[.]com/page/A9ZKVObdXhN4p/ - Domain – Probable Phishing Page (Now Defunct)

37.19.221[.]142 – IP Address – Unusual Login Source

35.174.4[.]92 – IP Address – Unusual Login Source

MITRE ATT&CK Mapping

Tactic - Techniques

INITIAL ACCESS, PRIVILEGE ESCALATION, DEFENSE EVASION, PERSISTENCE

T1078.004 – Cloud Accounts

DISCOVERY

T1538 – Cloud Service Dashboards

CREDENTIAL ACCESS

T1539 – Steal Web Session Cookie

RESOURCE DEVELOPMENT

T1586 – Compromise Accounts

PERSISTENCE

T1137.005 – Outlook Rules

Probability yardstick used to communicate the probability that statements or explanations given are correct.
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
Min Kim
Cyber Security Analyst

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May 7, 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, behavioural 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
Your data. Our AI.
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