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June 3, 2024

Exploring the Benefits and Risks of Third-Party Data Solutions

Many companies use third-party data management for efficiency, global access, collaboration, and reliability. Find out what those organizations need to know about addressing the security risks and best practices associated with third-party data management.
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
Oakley Cox
Director of Product
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03
Jun 2024

Why do companies allow third parties to handle their data?

Companies seek out third parties to handle their data for operational efficiency.

The scale and cost of maintaining in-house infrastructure can be outsourced to third parties who specialize in data management or in certain business functions.

Third parties who handle an organization’s data can range from large public cloud providers such as Azure or AWS, to boutique companies who handle specific business functions such as telemarketing, payment systems, or webpage hosting.

The operational efficiencies gained through third-party data management can be summarized by three key benefits:

  • Global accessibility: Third-party data storage enables data access across the globe, allowing businesses to access data from anywhere.
  • Enhanced collaboration: Third-party data storage allows for file sharing, real-time editing, and integration with other applications and services enhancing a business’s collaboration efforts.
  • Reliability and uptime: Reputable third-party storage providers offer high reliability and uptime guarantees, ensuring that data is available whenever needed. They typically have robust disaster recovery and backup systems in place to prevent data loss.

Given these benefits, it is no surprise that businesses are using these services to expand their operations and scale efforts with the need of a growing business. This strategic move not only optimizes resource allocation but also enhances operational agility, enabling businesses to adapt swiftly to evolving data demands and maintain a competitive edge in a dynamic market.

Security risks of entrusted data to third-party vendors

Entrusting data to third parties can expose businesses to supply chain risks and increase the risk of data breaches and unauthorized access. A business has less control over its data and becomes dependent on the third party's policies, practices, and uptime. Many third-party vendors are the target of hackers who specialize in monetizing sensitive data and exploiting gray areas around who is responsible for securing the data.

Thus, businesses are vulnerable when they entrust sensitive data to third-party platforms, which often lack transparency about data usage and security. The platforms, chosen mainly for cost, efficiency, and user experience, are frequent targets for cyber criminals, hacktivists, and opportunistic lone hackers looking for sensitive data accidentally exposed due to misconfigurations or poor data management policies.

Consumers are putting pressure on businesses to improve cybersecurity when handling their personal data. Businesses who suffer a data breach face a high level of scrutiny from customers, investors, the media, and governments, even when the data breach is the result of a third party’s being hacked. For example, Uber made headlines in 2022 for a data breach which was the result of a compromised vendor who had access to data regarding Uber’s employees.

Similarly, the UK’s Ministry of Defence was the victim of a data breach earlier this year when hackers targeted a third party payroll system used by the government department.

Why do cyber-criminals target third parties?

Cyber-criminals can potentially gain access to multiple networks when targeting a third-party storage provider. A successful attack could give attackers access to the networks and systems of all its clients, amplifying the impact of a single breach.

For example, when Illuminate Education was the target of a cyber-attack, the data of 23 US School Districts was stolen via its student-tracking software. It included student data from the country's two largest school systems - New York City Public Schools and Los Angeles Unified School District.

Common third-party security risks

When collaborating with third parties, organizations should be aware of the most common types of security risks posed to their cybersecurity.

  • Software supply chain attacks: Software supply chain attacks occur when cyber criminals infiltrate and compromise software products or updates at any point in the development or distribution process. This allows attackers to insert malicious code into legitimate software, which then gets distributed to users through trusted channels.
  • Human error: Human error in cybersecurity refers to mistakes made by individuals that lead to security breaches or vulnerabilities. These errors can result from lack of awareness, insufficient training, negligence, or simple mistakes.
  • Privileged access misuse: Privileged access misuse involves the inappropriate or unauthorized use of elevated access rights by individuals within an organization. This can include intentionally malicious actions or unintentional misuse of administrative privileges.

What to look for in a security solution when using third parties to store or manage data

Understanding the security posture of a third party is important when partnering with it and entrusting it with your organization’s data. Understanding how basic cyber hygiene policies are implemented is a good place to start, such as data retention policies, use of encryption for data in storage, and how identity and access are managed.

In some circumstances, it is important to understand who is responsible for the data’s security. For example, when using public cloud infrastructure, it is generally the responsibility of the data owner to manage how the data is accessed and stored.

In that situation, an organization needs to ensure it has solutions in place which gives it full visibility of that third-party environment, and which can proactively identify misconfigurations and detect and respond to suspicious activity in real time.

Benefits of using AI tools to aid in managing sensitive data

According to research performed by IBM, organizations with extensive use of security AI and automation identified and contained a data breach 108 days faster in 2023 than organizations that did not use AI for cybersecurity. (1) This figure is only likely to improve as companies mature in their adoption of AI for cyber security and can be a key indicator in the security posture of a third-party vendor.

Example of third-party security incidents

Sumo data breach

Sumo, an Australian energy and internet provider, suffered a data breach which they became aware of on May 13th, 2024. Further investigation into the cyber incident has found that “the personal details of approximately 40,000 customers were compromised, including approximately 3,000 Australian passport numbers.” (2)

While none of Sumo’s systems were allegedly accessed or affected and the third-party application also worked as designed (3), the incident was blamed on an unnamed third party. The breach may have been the result of a misconfiguration or human error.

This incident underscores the importance of not only selecting third-party providers with robust security measures but also continuously monitoring and assessing their security practices.

How Darktrace helps monitor third-party data usage

Darktrace/Cloud uses Self-Learning AI to provide complete cyber resilience for multi-cloud environments.

Benefits of Darktrace/Cloud:

Architectural awareness: Gives users an understanding of their cloud footprint, including real-time visibility into cloud assets, architectures, users and permissions. Combines asset enumeration, modeled architectures, and flow log analysis. Cost insights give a better understanding of resource allocation, helping teams contextualize resources.

Cloud-native detection and response: AI understands ‘normal’ for your unique business and stops cyber-threats with autonomous response. Near-real-time response goes beyond simple email alerts or opening a ticket; and includes cloud-native actions like detaching EC2 instances and applying security groups to contain risky assets.

Cloud protection and compliance: Identify compliance issues and potential misconfigurations with attack path modeling and prioritized remediation steps. Darktrace’s attack surface management (ASM) adds a critical external view of your organization, highlighting vulnerabilities most impactful to your specific situation and revealing shadow IT.

Learn more about securing cloud environments by reading: The CISO’s Guide to Cloud Security here.

References

1.    https://www.ibm.com/reports/data-breach

2.    https://www.passports.gov.au/news/sumo-data-breach

3.    https://www.smh.com.au/technology/sumo-slammed-by-data-breach-as-energy-and-internet-customers-have-details-leaked-20240515-p5jdwp.html

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
Oakley Cox
Director of Product

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August 8, 2025

Ivanti Under Siege: Investigating the Ivanti Endpoint Manager Mobile Vulnerabilities (CVE-2025-4427 & CVE-2025-4428)

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Ivanti & Edge infrastructure exploitation

Edge infrastructure exploitations continue to prevail in today’s cyber threat landscape; therefore, it was no surprise that recent Ivanti Endpoint Manager Mobile (EPMM) vulnerabilities CVE-2025-4427 and CVE-2025-4428 were exploited targeting organizations in critical sectors such as healthcare, telecommunications, and finance across the globe, including across the Darktrace customer base in May 2025.

Exploiting these types of vulnerabilities remains a popular choice for threat actors seeking to enter an organization’s network to perform malicious activity such as cyber espionage, data exfiltration and ransomware detonation.

Vulnerabilities in Ivanti EPMM

Ivanti EPMM allows organizations to manage and configure enterprise mobile devices. On May 13, 2025, Ivanti published a security advisory [1] for their Ivanti Endpoint Manager Mobile (EPMM) devices addressing a medium and high severity vulnerability:

  • CVE-2025-4427, CVSS: 5.6: An authentication bypass vulnerability
  • CVE-2025-4428, CVSS: 7.2: Remote code execution vulnerability

Successfully exploiting both vulnerabilities at the same time could lead to unauthenticated remote code execution from an unauthenticated threat actor, which could allow them to control, manipulate, and compromise managed devices on a network [2].

Shortly after the disclosure of these vulnerabilities, external researchers uncovered evidence that they were being actively exploited in the wild and identified multiple indicators of compromise (IoCs) related to post-exploitation activities for these vulnerabilities [2] [3]. Research drew particular attention to the infrastructure utilized in ongoing exploitation activity, such as leveraging the two vulnerabilities to eventually deliver malware contained within ELF files from Amazon Web Services (AWS) S3 bucket endpoints and to deliver KrustyLoader malware for persistence. KrustyLoader is a Rust based malware that was discovered being downloaded in compromised Ivanti Connect Secure systems back in January 2024 when the zero-day critical vulnerabilities; CVE-2024-21887 and CVE-2023-46805 [10].

This suggests the involvement of the threat actor UNC5221, a suspected China-nexus espionage actor [3].

In addition to exploring the post-exploit tactics, techniques, and procedures (TTPs) observed for these vulnerabilities across Darktrace’s customer base, this blog will also examine the subtle changes and similarities in the exploitation of earlier Ivanti vulnerabilities—specifically Ivanti Connect Secure (CS) and Policy Secure (PS) vulnerabilities CVE-2023-46805 and CVE-2024-21887 in early 2024, as well as CVE-2025-0282 and CVE-2025-0283, which affected CS, PS, and Zero Trust Access (ZTA) in January 2025.

Darktrace Coverage

In May 2025, shortly after Ivanti disclosed vulnerabilities in their EPMM product, Darktrace’s Threat Research team identified attack patterns potentially linked to the exploitation of these vulnerabilities across multiple customer environments. The most noteworthy attack chain activity observed included exploit validation, payload delivery via AWS S3 bucket endpoints, subsequent delivery of script-based payloads, and connections to dpaste[.]com, possibly for dynamic payload retrieval. In a limited number of cases, connections were also made to an IP address associated with infrastructure linked to SAP NetWeaver vulnerability CVE-2025-31324, which has been investigated by Darktrace in an earlier case.

Exploit Validation

Darktrace observed devices within multiple customer environments making connections related to Out-of-Band Application Security Testing (OAST). These included a range of DNS requests and connections, most of which featured a user agent associated with the command-line tool cURL, directed toward associated endpoints. The hostnames of these endpoints consisted of a string of randomly generated characters followed by an OAST domain, such as 'oast[.]live', 'oast[.]pro', 'oast[.]fun', 'oast[.]site', 'oast[.]online', or 'oast[.]me'. OAST endpoints can be leveraged by malicious actors to trigger callbacks from targeted systems, such as for exploit validation. This activity, likely representing the initial phase of the attack chain observed across multiple environments, was also seen in the early stages of previous investigations into the exploitation of Ivanti vulnerabilities [4]. Darktrace also observed similar exploit validation activity during investigations conducted in January 2024 into the Ivanti CS vulnerabilities CVE-2023-46805 and CVE-2024-21887.

Payload Delivery via AWS

Devices across multiple customer environments were subsequently observed downloading malicious ELF files—often with randomly generated filenames such as 'NVGAoZDmEe'—from AWS S3 bucket endpoints like 's3[.]amazonaws[.]com'. These downloads occurred over HTTP connections, typically using wget or cURL user agents. Some of the ELF files were later identified to be KrustyLoader payloads using open-source intelligence (OSINT). External researchers have reported that the KrustyLoader malware is executed in cases of Ivanti EPMM exploitation to gain and maintain a foothold in target networks [2].

In one customer environment, after connections were made to the endpoint fconnect[.]s3[.]amazonaws[.]com, Darktrace observed the target system downloading the ELF file mnQDqysNrlg via the user agent Wget/1.14 (linux-gnu). Further investigation of the file’s SHA1 hash (1dec9191606f8fc86e4ae4fdf07f09822f8a94f2) linked it to the KrustyLoader malware [5]. In another customer environment, connections were instead made to tnegadge[.]s3[.]amazonaws[.]com using the same user agent, from which the ELF file “/dfuJ8t1uhG” was downloaded. This file was also linked to KrustyLoader through its SHA1 hash (c47abdb1651f9f6d96d34313872e68fb132f39f5) [6].

The pattern of activity observed so far closely mirrors previous exploits associated with the Ivanti vulnerabilities CVE-2023-46805 and CVE-2024-21887 [4]. As in those cases, Darktrace observed exploit validation using OAST domains and services, along with the use of AWS endpoints to deliver ELF file payloads. However, in this instance, the delivered payload was identified as KrustyLoader malware.

Later-stage script file payload delivery

In addition to the ELF file downloads, Darktrace also detected other file downloads across several customer environments, potentially representing the delivery of later-stage payloads.

The downloaded files included script files with the .sh extension, featuring randomly generated alphanumeric filenames. One such example is “4l4md4r.sh”, which was retrieved during a connection to the IP address 15.188.246[.]198 using a cURL-associated user agent. This IP address was also linked to infrastructure associated with the SAP NetWeaver remote code execution vulnerability CVE-2025-31324, which enables remote code execution on NetWeaver Visual Composer. External reporting has attributed this infrastructure to a China-nexus state actor [7][8][9].

In addition to the script file downloads, devices on some customer networks were also observed making connections to pastebin[.]com and dpaste[.]com, two sites commonly used to host or share malicious payloads or exploitation instructions [2]. Exploits, including those targeting Ivanti EPMM vulnerabilities, can dynamically fetch malicious commands from sites like dpaste[.]com, enabling threat actors to update payloads. Unlike the previously detailed activity, this behavior was not identified in any prior Darktrace investigations into Ivanti-related vulnerabilities, suggesting a potential shift in the tactics used in post-exploitation stages of Ivanti attacks.

Conclusion

Edge infrastructure vulnerabilities, such as those found in Ivanti EPMM and investigated across customer environments with Darktrace / NETWORK, have become a key tool in the arsenal of attackers in today’s threat landscape. As highlighted in this investigation, while many of the tactics employed by threat actors following successful exploitation of vulnerabilities remain the same, subtle shifts in their methods can also be seen.

These subtle and often overlooked changes enable threat actors to remain undetected within networks, highlighting the critical need for organizations to maintain continuous extended visibility, leverage anomaly based behavioral analysis, and deploy machine speed intervention across their environments.

Credit to Nahisha Nobregas (Senior Cyber Analyst) and Anna Gilbertson (Senior Cyber Analyst)

Appendices

Mid-High Confidence IoCs

(IoC – Type - Description)

-       trkbucket.s3.amazonaws[.]com – Hostname – C2 endpoint

-       trkbucket.s3.amazonaws[.]com/NVGAoZDmEe – URL – Payload

-       tnegadge.s3.amazonaws[.]com – Hostname – C2 endpoint

-       tnegadge.s3.amazonaws[.]com/dfuJ8t1uhG – URL – Payload

-       c47abdb1651f9f6d96d34313872e68fb132f39f5 - SHA1 File Hash – Payload

-       4abfaeadcd5ab5f2c3acfac6454d1176 - MD5 File Hash - Payload

-       fconnect.s3.amazonaws[.]com – Hostname – C2 endpoint

-       fconnect.s3.amazonaws[.]com/mnQDqysNrlg – URL - Payload

-       15.188.246[.]198 – IP address – C2 endpoint

-       15.188.246[.]198/4l4md4r.sh?grep – URL – Payload

-       185.193.125[.]65 – IP address – C2 endpoint

-       185.193.125[.]65/c4qDsztEW6/TIGHT_UNIVERSITY – URL – C2 endpoint

-       d8d6fe1a268374088fb6a5dc7e5cbb54 – MD5 File Hash – Payload

-       64.52.80[.]21 – IP address – C2 endpoint

-       0d8da2d1.digimg[.]store – Hostname – C2 endpoint

-       134.209.107[.]209 – IP address – C2 endpoint

Darktrace Model Detections

-       Compromise / High Priority Tunnelling to Bin Services (Enhanced Monitoring Model)

-       Compromise / Possible Tunnelling to Bin Services

-       Anomalous Server Activity / New User Agent from Internet Facing System

-       Compliance / Pastebin

-       Device / Internet Facing Device with High Priority Alert

-       Anomalous Connection / Callback on Web Facing Device

-       Anomalous File / Script from Rare External Location

-       Anomalous File / Incoming ELF File

-       Device / Suspicious Domain

-       Device / New User Agent

-       Anomalous Connection / Multiple Connections to New External TCP Port

-       Anomalous Connection / New User Agent to IP Without Hostname

-       Anomalous File / EXE from Rare External Location

-       Anomalous File / Internet Facing System File Download

-       Anomalous File / Multiple EXE from Rare External Locations

-       Compromise / Suspicious HTTP and Anomalous Activity

-       Device / Attack and Recon Tools

-       Device / Initial Attack Chain Activity

-       Device / Large Number of Model Alerts

-       Device / Large Number of Model Alerts from Critical Network Device

References

1.     https://forums.ivanti.com/s/article/Security-Advisory-Ivanti-Endpoint-Manager-Mobile-EPMM?language=en_US

2.     https://blog.eclecticiq.com/china-nexus-threat-actor-actively-exploiting-ivanti-endpoint-manager-mobile-cve-2025-4428-vulnerability

3.     https://www.wiz.io/blog/ivanti-epmm-rce-vulnerability-chain-cve-2025-4427-cve-2025-4428

4.     https://www.darktrace.com/blog/the-unknown-unknowns-post-exploitation-activities-of-ivanti-cs-ps-appliances

5.     https://www.virustotal.com/gui/file/ac91c2c777c9e8638ec1628a199e396907fbb7dcf9c430ca712ec64a6f1fcbc9/community

6.     https://www.virustotal.com/gui/file/f3e0147d359f217e2aa0a3060d166f12e68314da84a4ecb5cb205bd711c71998/community

7.     https://www.virustotal.com/gui/ip-address/15.188.246.198

8.     https://blog.eclecticiq.com/china-nexus-nation-state-actors-exploit-sap-netweaver-cve-2025-31324-to-target-critical-infrastructures

9.     https://www.darktrace.com/blog/tracking-cve-2025-31324-darktraces-detection-of-sap-netweaver-exploitation-before-and-after-disclosure

10.  https://www.synacktiv.com/en/publications/krustyloader-rust-malware-linked-to-ivanti-connectsecure-compromises

The content provided in this blog is published by Darktrace for general informational purposes only and reflects our understanding of cybersecurity topics, trends, incidents, and developments at the time of publication. While we strive to ensure accuracy and relevance, the information is provided “as is” without any representations or warranties, express or implied. Darktrace makes no guarantees regarding the completeness, accuracy, reliability, or timeliness of any information presented and expressly disclaims all warranties.

Nothing in this blog constitutes legal, technical, or professional advice, and readers should consult qualified professionals before acting on any information contained herein.

Any references to third-party organizations, technologies, threat actors, or incidents are for informational purposes only and do not imply affiliation, endorsement, or recommendation.

Darktrace, its affiliates, employees, or agents shall not be held liable for any loss, damage, or harm arising from the use of or reliance on the information in this blog.

The cybersecurity landscape evolves rapidly, and blog content may become outdated or superseded. We reserve the right to update, modify, or remove any content without notice.

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About the author
Nahisha Nobregas
SOC Analyst

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August 7, 2025

How CDR & Automated Forensics Transform Cloud Incident Response

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Introduction: Cloud investigations

In cloud security, speed, automation and clarity are everything. However, for many SOC teams, responding to incidents in the cloud is often very difficult especially when attackers move fast, infrastructure is ephemeral, and forensic skills are scarce.

In this blog we will walk through an example that shows exactly how Darktrace Cloud Detection and Response (CDR) and automated cloud forensics together, solve these challenges, automating cloud detection, and deep forensic investigation in a way that’s fast, scalable, and deeply insightful.

The Problem: Cloud incidents are hard to investigate

Security teams often face three major hurdles when investigating cloud detections:

Lack of forensic expertise: Most SOCs and security teams aren’t natively staffed with forensics specialists.

Ephemeral infrastructure: Cloud assets spin up and down quickly, leaving little time to capture evidence.

Lack of existing automation: Gathering forensic-level data often requires manual effort and leaves teams scrambling around during incidents — accessing logs, snapshots, and system states before they disappear. This process is slow and often blocked by permissions, tooling gaps, or lack of visibility.

How Darktrace augments cloud investigations

1. Darktrace’s CDR finds anomalous activity in the cloud

An alert is generated for a large outbound data transfer from an externally facing EC2 instance to a rare external endpoint. It’s anomalous, unexpected, and potentially serious.

2. AI-led investigation stitches together the incident for a SOC analyst to look into

When a security incident unfolds, Darktrace’s Cyber AI Analyst TM is the first to surface it, automatically correlating behaviors, surfacing anomalies, and presenting a cohesive incident summary. It’s fast, detailed, and invaluable.

Once the incident is created, more questions are raised.

  • How were the impacted resources compromised?
  • How did the attack unfold over time – what tools and malware were used?
  • What data was accessed and exfiltrated?

What you’ll see as a SOC analyst: The incident begins in Darktrace’s Threat Visualizer, where a Cyber AI Analyst incident has been generated automatically highlighting large anomalous data transfer to a suspicious external IP. This isn’t just another alert, it’s a high-fidelity signal backed by Darktrace’s Self-Learning AI.

Cyber AI Analyst incident created for anomalous outbound data transfer
Figure 1: Cyber AI Analyst incident created for anomalous outbound data transfer

The analyst can then immediately pivot to Darktrace / CLOUD’s architecture view (see below), gaining context on the asset’s environment, ingress/egress points, connected systems, potential attack paths and whether there are any current misconfigurations detected on the asset.

Darktrace / CLOUD architecture view providing critical cloud context
Figure 2: Darktrace / CLOUD architecture view providing critical cloud context

3. Automated forensic capture — No expertise required

Then comes the game-changer, Darktrace’s recent acquisition of Cado enhances its cloud forensics capabilities. From the first alert triggered, Darktrace has already kicked in and automatically processed and analyzed a full volume capture of the EC2. Everything, past and present, is preserved. No need for manual snapshots, CLI commands, or specialist intervention.

Darktrace then provides a clear timeline highlighting the evidence and preserving it. In our example we identify:

  • A brute-force attempt on a file management app, followed by a successful login
  • A reverse shell used to gain unauthorized remote access to the EC2
  • A reverse TCP connection to the same suspicious IP flagged by Darktrace
  • Attacker commands showing how the data was split and prepared for exfiltration
  • A file (a.tar) created from two sensitive archives: product_plans.zip and research_data.zip

All of this is surfaced through the timeline view, ranked by significance using machine learning. The analyst can pivot through time, correlate events, and build a complete picture of the attack — without needing cloud forensics expertise.

Darktrace even gives the ability to:

  • Download and inspect gathered files in full detail, enabling teams to verify exactly what data was accessed or exfiltrated.
  • Interact with the file system as if it were live, allowing investigators to explore directories, uncover hidden artifacts, and understand attacker movement with precision.
Figure 3 Cado critical forensic investigation automated insights
Figure 3: Cado critical forensic investigation automated insights
Figure 4: Cado forensic file analysis of reverse shell and download option
Figure 5: a.tar created from two sensitive archives: product_plans.zip and research_data.zip
Figure 6: Traverse the full file system of the asset

Why this matters?

This workflow solves the hardest parts of cloud investigation:

  1. Capturing evidence before it disappears
  2. Understanding attacker behavior in detail - automatically
  3. Linking detections to impact with full incident visibility

This kind of insight is invaluable for organizations especially regulated industries, where knowing exactly what data was affected is critical for compliance and reporting. It’s also a powerful tool for detecting insider threats, not just external attackers.

Darktrace / CLOUD and Cado together acts as a force multiplier helping with:

  • Reducing investigation time from hours to minutes
  • Preserving ephemeral evidence automatically
  • Empowering analysts with forensic-level visibility

Cloud threats aren’t slowing down. Your response shouldn’t either. Darktrace / CLOUD + Cado gives your SOC the tools to detect, contain, and investigate cloud incidents — automatically, accurately, and at scale.

[related-resource]

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About the author
Adam Stevens
Director of Product, Cloud Security
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