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November 27, 2024

Behind the Veil: Darktrace's Detection of VPN Exploitation in SaaS Environments

A recent phishing attack compromised an internal email account, but Darktrace’s advanced AI quickly intervened. By identifying unusual activity across email and SaaS environments, Darktrace uncovered the attacker’s use of VPNs to mask their location and shut down the threat.
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
Priya Thapa
Cyber Analyst
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27
Nov 2024

Introduction

In today’s digital landscape, Software-as-a-Service (SaaS) platforms have become indispensable for businesses, offering unparalleled flexibly, scalability, and accessibly across locations. However, this convenience comes with a significant caveat - an expanded attack surface that cyber criminals are increasingly exploiting. In 2023, 96.7% of organizations reported security incidents involving at least one SaaS application [1].

Virtual private networks (VPNs) play a crucial role in SaaS security, acting as gateways for secure remote access and safeguarding sensitive data and systems when properly configured. However, vulnerabilities in VPNs can create openings for attacks to exploit, allowing them to infiltrate SaaS environments, compromise data, and disrupt business operations. Notably, in early 2024, the Darktrace Threat Research team investigated the exploitation of zero-day vulnerabilities in Ivanti Connect Secure VPNs, which would allow threat actors to gain access to sensitive systems and execute remote code.

More recently, in August, Darktrace identified a SaaS compromise where a threat actor logged into a customer’s VPN from an unusual IP address, following an initial email compromise. The attacker then used a separate VPN to create a new email rule designed to obfuscate the phishing campaign they would later launch.

Attack Overview

The initial attack vector in this case appeared to be through the customer’s email environment. A trusted external contact received a malicious email from another mutual contact who had been compromised and forwarded it to several of the organization’s employees, believing it to be legitimate. Attackers often send malicious emails from compromised accounts to their past contacts, leveraging the trust associated with familiar email addresses. In this case, that trust caused an external victim to unknowingly propagate the attack further. Unfortunately, an internal user then interacted with a malicious payload included in the reply section of the forwarded email.

Later the same day, Darktrace / IDENTITY detected unusual login attempts from the IP 5.62.57[.]7, which had never been accessed by other SaaS users before. There were two failed attempts prior to the successful logins, with the error messages “Authentication failed due to flow token expired” and “This occurred due to 'Keep me signed in' interrupt when the user was signing in.” These failed attempts indicate that the threat actor may have been attempting to gain unauthorized access using stolen credentials or exploiting session management vulnerabilities. Furthermore, there was no attempt to use multi-factor authentication (MFA) during the successful login, suggesting that the threat actor had compromised the account’s credentials.

Following this, Darktrace detected the now compromised account creating a new email rule named “.” – a telltale sign of a malicious actor attempting to hide behind an ambiguous or generic rule name.

The email rule itself was designed to archive incoming emails and mark them as read, effectively hiding them from the user’s immediate view. By moving emails to the “Archive” folder, which is not frequently checked by end users, the attacker can conceal malicious communications and avoid detection. The settings also prevent any automatic deletion of the rules or forced overrides, indicating a cautious approach to maintaining control over the mailbox without raising suspicion. This technique allows the attacker to manipulate email visibility while maintaining a façade of normality in the compromised account.

Email Rule:

  • AlwaysDeleteOutlookRulesBlob: False
  • Force: False
  • MoveToFolder: Archive
  • Name: .
  • MarkAsRead: True
  • StopProcessingRules: True

Darktrace further identified that this email rule had been created from another IP address, 95.142.124[.]42, this time located in Canada. Open-source intelligence (OSINT) sources indicated this endpoint may have been malicious [2].

Given that this new email rule was created just three minutes after the initial login from a different IP in a different country, Darktrace recognized a geographic inconsistency. By analyzing the timing and rarity of the involved IP addresses, Darktrace identified the likelihood of malicious activity rather than legitimate user behavior, prompting further investigation.

Figure 1: The compromised SaaS account making anomalous login attempts from an unusual IP address in the US, followed by the creation of a new email rule from another VPN IP in Canada.

Just one minute later, Darktrace observed the attacker sending a large number of phishing emails to both internal and external recipients.

Figure 2: The compromised SaaS user account sending a high volume of outbound emails to new recipients or containing suspicious content.

Darktrace / EMAIL detected a significant spike in inbound emails for the compromised account, likely indicating replies to phishing emails.

Figure 3: The figure demonstrates the spike in inbound emails detected for the compromised account, including phishing-related replies.

Furthermore, Darktrace identified that these phishing emails contained a malicious DocSend link. While docsend[.]com is generally recognized as a legitimate file-sharing service belonging to Dropbox, it can be vulnerable to exploitation for hosting malicious content. In this instance, the DocSend domain in question, ‘hxxps://docsend[.]com/view/h9t85su8njxtugmq’, was flagged as malicious by various OSINT vendors [3][4].

Figure 4: Phishing emails detected containing a malicious DocSend link.

In this case, Darktrace Autonomous Response was not in active mode in the customer’s environment, which allowed the compromise to escalate until their security team intervened based on Darktrace’s alerts. Had Autonomous Response been enabled during the incident, it could have quickly mitigated the threat by disabling users and inbox rules, as suggested by Darktrace as actions that could be manually applied, exhibiting unusual behavior within the customer’s SaaS environment.

Figure 5: Suggested Autonomous Response actions for this incident that required human confirmation.

Despite this, Darktrace’s Managed Threat Detection service promptly alerted the Security Operations Center (SOC) team about the compromise, allowing them to conduct a thorough investigation and inform the customer before any further damage could take place.

Conclusion

This incident highlights the role of Darktrace in enhancing cyber security through its advanced AI capabilities. By detecting the initial phishing email and tracking the threat actor's actions across the SaaS environment, Darktrace effectively identified the threat and brought it to the attention of the customer’s security team.

Darktrace’s proactive monitoring was crucial in recognizing the unusual behavior of the compromised account. Darktrace / IDENTITY detected unauthorized access attempts from rare IP addresses, revealing the attacker’s use of a VPN to hide their location.

Correlating these anomalies allowed Darktrace to prompt immediate investigation, showcasing its ability to identify malicious activities that traditional security tools might miss. By leveraging AI-driven insights, organizations can strengthen their defense posture and prevent further exploitation of compromised accounts.

Credit to Priya Thapa (Cyber Analyst), Ben Atkins (Senior Model Developer) and Ryan Traill (Analyst Content Lead)

Appendices

Real-time Detection Models

  • SaaS / Compromise / Unusual Login and New Email Rule
  • SaaS / Compromise / High Priority New Email Rule
  • SaaS / Compromise / New Email Rule and Unusual Email Activity
  • SaaS / Compromise / Unusual Login and Outbound Email Spam
  • SaaS / Compliance / Anomalous New Email Rule
  • SaaS / Compromise / Suspicious Login and Suspicious Outbound Email(s)
  • SaaS / Email Nexus / Possible Outbound Email Spam

Autonomous Response Models

  • Antigena / SaaS / Antigena Email Rule Block
  • Antigena / SaaS / Antigena Enhanced Monitoring from SaaS User Block
  • Antigena / SaaS / Antigena Suspicious SaaS Activity Block

MITRE ATT&CK Mapping

Technique Name Tactic ID Sub-Technique of

  • Cloud Accounts. DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS T1078.004 T1078
  • Compromise Accounts RESOURCE DEVELOPMENT T1586
  • Email Accounts RESOURCE DEVELOPMENT T1586.002 T1586
  • Internal Spearphishing LATERAL MOVEMENT T1534 -
  • Outlook Rules PERSISTENCE T1137.005 T1137
  • Phishing INITIAL ACCESS T1566 -

Indicators of Compromise (IoCs)

IoC – Type – Description

5.62.57[.]7 – Unusual Login Source

95.142.124[.]42– IP – Unusual Source for Email Rule

hxxps://docsend[.]com/view/h9t85su8njxtugmq - Domain - Phishing Link

References

[1] https://wing.security/wp-content/uploads/2024/02/2024-State-of-SaaS-Report-Wing-Security.pdf

[2] https://www.virustotal.com/gui/ip-address/95.142.124.42

[3] https://urlscan.io/result/0caf3eee-9275-4cda-a28f-6d3c6c3c1039/

[4] https://www.virustotal.com/gui/url/8631f8004ee000b3f74461e5060e6972759c8d38ea8c359d85da9014101daddb

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
Priya Thapa
Cyber 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
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