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February 22, 2024

Attack Trends: VIP Impersonation in the Business Hierarchy

VIP Impersonation occurs when a cyber-threat actor impersonates a prominent employee to obtain sensitive data. Learn all about VIP impersonation here.
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
Kendra Gonzalez Duran
Principal Analyst
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22
Feb 2024

What is VIP impersonation?

VIP impersonation involves a threat actor impersonating a trusted, prominent figure at an organization in an attempt to solicit sensitive information from an employee.

VIP impersonation is a high-priority issue for security teams, but it can be difficult to assess the exact risks, and whether those are more critical than other types of compromise. Looking across a range of Darktrace/Email™ customer deployments, this blog explores the patterns of individuals targeted for impersonation and evaluates if these target priorities correspond with security teams' focus on protecting attack pathways to critical assets.

How do security teams stop VIP Impersonation?

Protecting VIP entities within an organization has long been a traditional focus for security teams. The assumption is that VIPs, due to their prominence, possess the greatest access to critical assets, making them prime targets for cyber threats.  

Email remains the predominant vector for attacks, with over 90% of breaches originating from malicious emails. However, the dynamics of email-based attacks are shifting, as the widespread use of generative AI is lowering the barrier to entry by allowing adversaries to create hyper-realistic emails with minimal errors.

Given these developments, it's worth asking the question – which entities (VIP/non-VIP) are most targeted by threat actors via email? And, more importantly – which entities (VIP/non-VIP) are more valuable if they are successfully compromised?

There are two types of VIPs:  

1. When referring to emails and phishing, VIPs are the users in an organization who are well known publicly.  

2. When referring to attack paths, VIPs are users in an organization that are known publicly and have access to highly privileged assets.  

Not every prominent user has access to critical assets, and not every user that has access to critical assets is prominent.  

Darktrace analysis of VIP impersonation

We analyzed patterns of attack pathways and phishing attempts across 20 customer deployments from a large, randomized pool encompassing a diverse range of organizations.  

Understanding Attack Pathways

Our observations revealed that 57% of low-difficulty attack paths originated from VIP entities, while 43% of observed low-difficulty attack paths towards critical assets or entities began through non-VIP users. This means that targeting VIPs is not the only way attackers can reach critical assets, and that non-VIP users must be considered as well.  

While the sample size prevents us from establishing statistical significance across all customers, the randomized selection lends credence to the generalizability of these findings to other environments.

Phishing Attempts  

On average, 1.35% of total emails sent to these customers exhibited significantly malicious properties associated with phishing or some form of impersonation. Strikingly, nearly half of these malicious emails (49.6%) were directed towards VIPs, while the rest were sent to non-VIPs. This near-equal split is worth noting, as attack paths show that non-VIPs also serve as potential entry points for targeting critical assets.  

Darktrace/Email UI
Figure 1: A phishing email actioned by Darktrace, sent to multiple VIP and non-VIP entities

For example, a recent phishing campaign targeted multiple customers across deployments, with five out of 13 emails specifically aimed at VIP users. Darktrace/Email actioned the malicious emails by double locking the links, holding the messages, and stripping the attachments.

Given that non-VIP users receive nearly half of the phishing or impersonation emails, it underscores the critical importance for security teams to recognize their blind spots in protecting critical assets. Overlooking the potential threat originating from non-VIP entities could lead to severe consequences. For instance, if a non-VIP user falls victim to a phishing attack or gets compromised, their credentials could be exploited to move laterally within the organization, potentially reaching critical assets.

This highlights the necessity for a sophisticated security tool that can identify targeted users, without the need for extensive customization and regardless of VIP status. By deploying a solution capable of promptly responding to email threats – including solicitation, phishing attempts, and impersonation – regardless of the status of the targeted user, security teams can significantly enhance their defense postures.

Darktrace vs Traditional Email Detection Methods

Traditional rules and signatures-based detection mechanisms fall short in identifying the evolving threats we’ve observed, due to their reliance on knowledge of past attacks to categorize emails.

Secure Email Gateway (SEG) or Integrated Cloud Email Security (ICES) tools categorize emails based on previous or known attacks, operating on a known-good or known-bad model. Even if tools use AI to automate this process, the approach is still fundamentally looking to the past and therefore vulnerable to unknown and zero-day threats.  

Darktrace uses AI to understand each unique organization and how its email environment interoperates with each user and device on the network. Consequently, it is able to identify the subtle deviations from normal behavior that qualify as suspicious. This approach goes beyond simplistic categorizations, considering factors such as the sender’s history and recipient’s exposure score.  

This nuanced analysis enables Darktrace to differentiate between genuine communications and malicious impersonation attempts. It automatically understands who is a VIP, without the need for manual input, and will action more strongly on incoming malicious emails  based on a user’s status.

Email does determine who is a VIP, without a need of manual input, and will action more strongly on incoming malicious emails.

Darktrace/Email also feeds into Darktrace’s preventative security tools, giving the interconnected AI engines further context for assessing the high-value targets and pathways to vital internal systems and assets that start via the inbox.

Leveraging AI for Enhanced Protection Across the Enterprise  

The efficacy of AI-driven security solutions lies in their ability to make informed decisions and recommendations based on real-time business data. By leveraging this data, AI driven solutions can identify exploitable attack pathways and an organizations most critical assets. Darktrace uniquely uses several forms of AI to equip security teams with the insights needed to make informed decisions about which pathways to secure, reducing human bias around the importance of protecting VIPs.

With the emergence of tools like AutoGPT, identifying potential targets for phishing attacks has become increasingly simplified. However, the real challenge lies in gaining a comprehensive understanding of all possible and low-difficulty attack paths leading to critical assets and identities within the organization.

At the same time, organizations need email tools that can leverage the understanding of users to prevent email threats from succeeding in the first instance. For every email and user, Darktrace/Email takes into consideration changes in behavior from the sender, recipient, content, and language, and many other factors.

Integrating Darktrace/Email with Darktrace’s attack path modeling capabilities enables comprehensive threat contextualization and facilitates a deeper understanding of attack pathways. This holistic approach ensures that all potential vulnerabilities, irrespective of the user's status, are addressed, strengthening the overall security posture.  

Conclusion

Contrary to conventional wisdom, our analysis suggests that the distinction between VIPs and non-VIPs in terms of susceptibility to impersonation and low-difficulty attack paths is not as pronounced as presumed. Therefore, security teams must adopt a proactive stance in safeguarding all pathways, rather than solely focusing on VIPs.  

Attack path modeling enhances Darktrace/Email's capabilities by providing crucial metrics on potential impact, damage, exposure, and weakness, enabling more targeted and effective threat mitigation strategies. For example, stronger email actions can be enforced for users who are known to have a high potential impact in case of compromise. 

In an era where cyber threats continue to evolve in complexity, an adaptive and non-siloed approach to securing inboxes, high-priority individuals, and critical assets is indispensable.  

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
Kendra Gonzalez Duran
Principal Analyst

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March 5, 2026

Inside Cloud Compromise: Investigating Attacker Activity with Darktrace / Forensic Acquisition & Investigation

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Investigating Cloud Attacks with Forensic Acquisition & Investigation

Darktrace / Forensic Acquisition & Investigation™ is the industry’s first truly automated forensic solution purpose-built for the cloud. This blog will demonstrate how an investigation can be carried out against a compromised cloud server in minutes, rather than hours or days.

The compromised server investigated in this case originates from Darktrace’s Cloudypots system, a global honeypot network designed to observe adversary activity in real time across a wide range of cloud services. Whenever an attacker successfully compromises one of these honeypots, a forensic copy of the virtual server's disk is preserved for later analysis. Using Forensic Acquisition & Investigation, analysts can then investigate further and obtain detailed insights into the compromise including complete attacker timelines and root cause analysis.

Forensic Acquisition & Investigation supports importing artifacts from a variety of sources, including EC2 instances, ECS, S3 buckets, and more. The Cloudypots system produces a raw disk image whenever an attack is detected and stores it in an S3 bucket. This allows the image to be directly imported into Forensic Acquisition & Investigation using the S3 bucket import option.

As Forensic Acquisition & Investigation runs cloud-natively, no additional configuration is required to add a specific S3 bucket. Analysts can browse and acquire forensic assets from any bucket that the configured IAM role is permitted to access. Operators can also add additional IAM credentials, including those from other cloud providers, to extend access across multiple cloud accounts and environments.

Figure 1: Forensic Acquisition & Investigation import screen.

Forensic Acquisition & Investigation then retrieves a copy of the file and automatically begins running the analysis pipeline on the artifact. This pipeline performs a full forensic analysis of the disk and builds a timeline of the activity that took place on the compromised asset. By leveraging Forensic Acquisition & Investigation’s cloud-native analysis system, this process condenses hour of manual work into just minutes.

Successful import of a forensic artifact and initiation of the analysis pipeline.
Figure 2: Successful import of a forensic artifact and initiation of the analysis pipeline.

Once processing is complete, the preserved artifact is visible in the Evidence tab, along with a summary of key information obtained during analysis, such as the compromised asset’s hostname, operating system, cloud provider, and key event count.

The Evidence overview showing the acquired disk image.
Figure 3: The Evidence overview showing the acquired disk image.

Clicking on the “Key events” field in the listing opens the timeline view, automatically filtered to show system- generated alarms.

The timeline provides a chronological record of every event that occurred on the system, derived from multiple sources, including:

  • Parsed log files such as the systemd journal, audit logs, application specific logs, and others.
  • Parsed history files such as .bash_history, allowing executed commands to be shown on the timeline.
  • File-specific events, such as files being created, accessed, modified, or executables being run, etc.

This approach allows timestamped information and events from multiple sources to be aggregated and parsed into a single, concise view, greatly simplifying the data review process.

Alarms are created for specific timeline events that match either a built-in system rule, curated by Darktrace’s Threat Research team or an operator-defined created at the project level. These alarms help quickly filter out noise and highlight on events of interest, such as the creation of a file containing known malware, access to sensitive files like Amazon Web Service (AWS) credentials, suspicious arguments or commands, and more.

 The timeline view filtered to alarm_severity: “1” OR alarm_severity: “3”, showing only events that matched an alarm rule.
Figure 4: The timeline view filtered to alarm_severity: “1” OR alarm_severity: “3”, showing only events that matched an alarm rule.

In this case, several alarms were generated for suspicious Base64 arguments being passed to Selenium. Examining the event data, it appears the attacker spawned a Selenium Grid session with the following payload:

"request.payload": "[Capabilities {browserName: chrome, goog:chromeOptions: {args: [-cimport base64;exec(base64...], binary: /usr/bin/python3, extensions: []}, pageLoadStrategy: normal}]"

This is a common attack vector for Selenium Grid. The chromeOptions object is intended to specify arguments for how Google Chrome should be launched; however, in this case the attacker has abused the binary field to execute the Python3 binary instead of Chrome. Combined with the option to specify command-line arguments, the attacker can use Python3’s -c option to execute arbitrary Python code, in this instance, decoding and executing a Base64 payload.

Selenium’s logs truncate the Arguments field automatically, so an alternate method is required to retrieve the full payload. To do this, the search bar can be used to find all events that occurred around the same time as this flagged event.

Pivoting off the previous event by filtering the timeline to events within the same window using timestamp: [“2026-02-18T09:09:00Z” TO “2026-02-18T09:12:00Z”].
Figure 5: Pivoting off the previous event by filtering the timeline to events within the same window using timestamp: [“2026-02-18T09:09:00Z” TO “2026-02-18T09:12:00Z”].

Scrolling through the search results, an entry from Java’s systemd journal can be identified. This log contains the full, unaltered payload. GCHQ’s CyberChef can then be used to decode the Base64 data into the attacker’s script, which will ultimately be executed.[NJ9]

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About the author
Nathaniel Bill
Malware Research Engineer

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February 19, 2026

CVE-2026-1731: How Darktrace Sees the BeyondTrust Exploitation Wave Unfolding

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Note: Darktrace's Threat Research team is publishing now to help defenders. We will continue updating this blog as our investigations unfold.

Background

On February 6, 2026, the Identity & Access Management solution BeyondTrust announced patches for a vulnerability, CVE-2026-1731, which enables unauthenticated remote code execution using specially crafted requests.  This vulnerability affects BeyondTrust Remote Support (RS) and particular older versions of Privileged Remote Access (PRA) [1].

A Proof of Concept (PoC) exploit for this vulnerability was released publicly on February 10, and open-source intelligence (OSINT) reported exploitation attempts within 24 hours [2].

Previous intrusions against Beyond Trust technology have been cited as being affiliated with nation-state attacks, including a 2024 breach targeting the U.S. Treasury Department. This incident led to subsequent emergency directives from  the Cybersecurity and Infrastructure Security Agency (CISA) and later showed attackers had chained previously unknown vulnerabilities to achieve their goals [3].

Additionally, there appears to be infrastructure overlap with React2Shell mass exploitation previously observed by Darktrace, with command-and-control (C2) domain  avg.domaininfo[.]top seen in potential post-exploitation activity for BeyondTrust, as well as in a React2Shell exploitation case involving possible EtherRAT deployment.

Darktrace Detections

Darktrace’s Threat Research team has identified highly anomalous activity across several customers that may relate to exploitation of BeyondTrust since February 10, 2026. Observed activities include:

Outbound connections and DNS requests for endpoints associated with Out-of-Band Application Security Testing; these services are commonly abused by threat actors for exploit validation.  Associated Darktrace models include:

  • Compromise / Possible Tunnelling to Bin Services

Suspicious executable file downloads. Associated Darktrace models include:

  • Anomalous File / EXE from Rare External Location

Outbound beaconing to rare domains. Associated Darktrace models include:

  • Compromise / Agent Beacon (Medium Period)
  • Compromise / Agent Beacon (Long Period)
  • Compromise / Sustained TCP Beaconing Activity To Rare Endpoint
  • Compromise / Beacon to Young Endpoint
  • Anomalous Server Activity / Rare External from Server
  • Compromise / SSL Beaconing to Rare Destination

Unusual cryptocurrency mining activity. Associated Darktrace models include:

  • Compromise / Monero Mining
  • Compromise / High Priority Crypto Currency Mining

And model alerts for:

  • Compromise / Rare Domain Pointing to Internal IP

IT Defenders: As part of best practices, we highly recommend employing an automated containment solution in your environment. For Darktrace customers, please ensure that Autonomous Response is configured correctly. More guidance regarding this activity and suggested actions can be found in the Darktrace Customer Portal.  

Appendices

Potential indicators of post-exploitation behavior:

·      217.76.57[.]78 – IP address - Likely C2 server

·      hXXp://217.76.57[.]78:8009/index.js - URL -  Likely payload

·      b6a15e1f2f3e1f651a5ad4a18ce39d411d385ac7  - SHA1 - Likely payload

·      195.154.119[.]194 – IP address – Likely C2 server

·      hXXp://195.154.119[.]194/index.js - URL – Likely payload

·      avg.domaininfo[.]top – Hostname – Likely C2 server

·      104.234.174[.]5 – IP address - Possible C2 server

·      35da45aeca4701764eb49185b11ef23432f7162a – SHA1 – Possible payload

·      hXXp://134.122.13[.]34:8979/c - URL – Possible payload

·      134.122.13[.]34 – IP address – Possible C2 server

·      28df16894a6732919c650cc5a3de94e434a81d80 - SHA1 - Possible payload

References:

1.        https://nvd.nist.gov/vuln/detail/CVE-2026-1731

2.        https://www.securityweek.com/beyondtrust-vulnerability-targeted-by-hackers-within-24-hours-of-poc-release/

3.        https://www.rapid7.com/blog/post/etr-cve-2026-1731-critical-unauthenticated-remote-code-execution-rce-beyondtrust-remote-support-rs-privileged-remote-access-pra/

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About the author
Emma Foulger
Global Threat Research Operations Lead
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