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September 30, 2020

Exploring AI Email Security & Human Behavior

Read how Darktrace AI is revolutionizing email security. Understand the human behavior of email attacks and how to mitigate your team's malware risks.
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
Dan Fein
VP, Product
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30
Sep 2020

At the heart of any email attack is the goal of moving the recipient to engage: whether that’s clicking a link, filling in a form, or opening an attachment. And with over nine in ten cyber-attacks starting with an email, this attack vector continues to prove successful, despite organizations’ best efforts to safeguard their workforce by deploying email gateways and training employees to spot phishing attempts.

Email attackers have seen such success because they understand their victims. They know that, ultimately, human beings are creatures of habit, prone to error, and susceptible to their emotions. Years of experience has allowed attackers to fine tune their emails making them more plausible and more provocative. Automated tools are now increasing the speed and scale at which criminals can buy new domains and send emails en masse. This makes it even easier to ‘A/B test’ attack methods: abandoning those that don’t see high success rates and capitalizing on those that do.

We can classify phishing attempts into five broad categories, each aiming to trigger a different emotional reaction and elicit a response.

  • Fear: “We have detected a virus on your device, log in to your McAfee account.”
  • Curiosity: “You have 3 new voicemails, click here.”
  • Generosity: “COVID-19 has greatly impacted homelessness in your area. Donate now.”
  • Greed: “Only 23 iPhones left to give away, act now!”
  • Concern: “Coronavirus outbreak in your area: Find out more.”

It’s worth noting that today’s increasingly dynamic workforces are more susceptible to these techniques, isolated in their homes and hungry for new information.

Turning to tech

As email attacks continue to trick employees and find success, many organizations have realized that the built-in security tools that come with their email provider aren’t enough to defend against today’s attacks. Additional email gateways are successful in catching spam and other low-hanging fruit, but fail to stop advanced attacks – particularly those leveraging novel malware, new domains, or advanced techniques. These advanced attacks are also the most damaging to businesses.

This failure is due to an inherent weakness in the legacy approach of traditional security tools. They compare inbound mail against lists of ‘known bad’ IPs, domains, and file hashes. Senders and recipients are treated simply as data points – ignoring the nuances of the human beings behind the keyboards.

Looking at these metrics in isolation fails to take into account the full context that can only be gained by understanding the people behind email interactions: where they usually log in from, who they communicate with, how they write, and what types of attachments they send and receive. It is this rich, personal context that reveals seemingly benign emails to be unmistakably malicious, especially when other data fails to reveal the danger.

Misunderstanding the human

Frustrated with the ineffectiveness of traditional tools, many organizations think that the solution is to minimize the chances that employees engage with malicious emails through comprehensive employee training. Indeed, companies often attempt to train their employees to spot malicious emails to compensate for their technology’s lack of detection.

Considering humans to be the last line of defense is dangerous, and this approach overlooks the fact that today’s sophisticated fakes can appear indistinguishable to legitimate mails. It's only when you really break an email down beyond the text, beyond the personal name, beyond the domain and email address (in the case of compromised trusted senders), that you can decipher between real and fake.

Large data breaches of recent years have given attackers greater access than ever to corporate emails and stolen passwords, and so supply chain attacks are becoming increasingly common. When attackers take over a trusted account or an existing email thread, how can an employee be expected to notice a subtle change in wording or the different type of attached document? However rigorous the internal training program and regardless of how vigilant employees are, we are now at the point where humans cannot spot these very subtle indicators. And one click is all it takes.

Understanding the human

Email security, for a long time, remains an unsolved piece of the complex cyber security puzzle. The failure of both traditional tools and employee training has prompted organizations to take a radically different approach. Thousands of businesses across the world, in both the public and private sector, use artificial intelligence that understands the human behind the keyboard and forms a nuanced and continually evolving understanding of email interactions across the business.

By learning what a human does, who they interact with, how they write, and the substance of a typical conversation between any two or more people, AI begins to understand the habits of employees, and over time it builds a comprehensive picture of their normal patterns of behavior. Most importantly, AI is self-learning, continuously revising its understanding of ‘normal’ so that when employees’ habits change, so does the AI’s understanding.

This enables the technology to detect behavioral anomalies that fall outside of an employee’s ‘pattern of life’, or the pattern of life for the organization as a whole.

This fundamentally new approach to email security enables the system to recognize the subtle indicators of a threat and make accurate decisions to stop or allow emails to pass through, even if a threat has never been seen before.

Sitting behind email gateways, this self-learning technology has extremely high catch rates. It has caught countless malicious emails that other tools missed, from impersonations of senior financial personnel to ‘fearware’ that played on the workforce’s uncertainties at a time of pandemic.

Attackers are continuing to innovate, and automation has led to a new wave of email threats. 88% of security leaders now believe that cyber-attacks powered by offensive AI are inevitable. The email threat landscape is rapidly changing, and we can expect to receive more hoax emails that are more convincing. Now is a crucial moment for organizations to prepare for this eventuality by adopting AI in their email defenses.

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
Dan Fein
VP, Product

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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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