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March 9, 2021

How VPC Traffic Mirroring Boosts Darktrace Security

Find out how Amazon VPC Traffic Mirroring enhances Darktrace's cloud security. Learn about its impact on advanced threat detection and management.
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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.
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09
Mar 2021

Darktrace's Cyber AI brings real-time visibility and adaptive, autonomous defense to your AWS cloud security strategy.

The platform continuously learns what normal behavior looks like for every user, device, and workload in your AWS environment. With this deep understanding of usual ‘patterns of life,’ Darktrace  can recognize the subtle deviations that point to a threat, from account takeovers to critical misconfigurations.

This bespoke, real-time knowledge of usual activity allows Darktrace to spot the unknown and unpredictable threats that get through policy-based defenses – all without relying on any rules, signatures, or prior assumptions.

With Amazon Virtual Private Cloud (Amazon VPC) Traffic Mirroring, Darktrace’s self-learning AI can seamlessly access granular packet data in AWS cloud environments, helping the platform build a rich understanding of context. AWS’s recent announcement of the extension of VPC Traffic Mirroring to non-Nitro instance types now allows our customers to gain agentless Cyber AI defense across these instances as well.

Expanding VPC traffic mirroring to non-Nitro instances

Amazon VPC Traffic Mirroring replicates the network traffic from EC2 instances within VPCs and allows customers to leverage this traffic for Darktrace’s AI-driven threat detection and investigation. Darktrace’s Cyber AI learns ‘on the job’ what normal activity looks like in customer AWS environments, in part using the real-time visibility provided by VPC Traffic Mirroring. The platform continuously adapts as each customer’s business evolves, a critical feature given the speed and scale of development in the cloud.

Previously, customers could only enable VPC Traffic Mirroring on their Nitro-based EC2 instances. Now, AWS has announced that this seamless access to hundreds of features from network traffic is extended to select non-Nitro instance types, supporting Darktrace’s ability to easily learn the bespoke behavioral patterns of our customers’ Amazon VPCs.

Customers can now enable VPC Traffic Mirroring on additional instances types such as C4, D2, G3, G3s, H1, I3, M4, P2, P3, R4, X1 and X1e that use the Xen-based hypervisor.* This feature is available in all 20 regions where VPC Traffic Mirroring is currently supported.

VPC Traffic Mirroring supports many of Darktrace’s extensive use cases across AWS, which include:

  • Data exfiltration and destruction: Detects anomalous device connections and user access, as well as unusual resource deletion, modification, and movement;
  • Critical misconfigurations: Catches open S3 buckets, anomalous permission changes, and unusual activity around compliance-related data and devices;
  • Compromised credentials: Spots unusual logins, including brute force attempts and unusual login source/time, as well as unusual user behavior, from rule changes to password resets;
  • Insider threat and admin abuse: Identifies the subtle signs of malicious insiders – including sensitive file access, resource modification, role changes, and adding/deleting users.

Figure 1: Darktrace illuminates activity in AWS

Autonomous investigation and response for AWS cloud environments

The Darktrace Security Module for AWS provides additional visibility across AWS environments via interaction with AWS CloudTrail, allowing for AI-powered monitoring of management and administration activity. With this deep knowledge of how your business operates in the cloud, Darktrace delivers total coverage across all your AWS services, including:

  • EC2
  • IAM
  • S3
  • VPC
  • Lambda
  • Athena
  • DynamoDB
  • Route 53
  • ACM
  • RDS

The recently announced Version 5 of the Darktrace, which focuses on protecting the cloud and the remote workforce, further augments Darktrace’s coverage of AWS environments. Among many other exciting new features, Version 5 extends the reach of Cyber AI Analyst and Darktrace RESPOND to cloud environments like AWS VPCs.

Cyber AI Analyst augments the work of security teams by autonomously reporting on the full scope of security incidents and reduces triage time by up to 92%. Cyber AI Analyst can now also conduct on-demand investigations into users and devices of interest, ingest third-party alerts to trigger new investigations, and automatically feed AI-generated Incident Reports to any SIEM, SOAR, or downstream ticketing system.

Meanwhile, Darktrace RESPOND brings Autonomous Response to the critical infrastructure which AWS VPCs provide. Darktrace's responses are surgically precise and intelligently maintain normal business operations while stopping emerging threats in real time.**

“Darktrace's innovations are outstanding and have really meshed with our current needs as a security team, from the flexibility of our new cloud-delivered deployment to the extended visibility of the Darktrace Client Sensors.”

– CISO, Real Estate

We have also launched a dedicated user interface for visualization and intuitive analysis of cloud-based threats identified across AWS via the Darktrace Security Module.

Self-Learning AI defense across the enterprise

Darktrace offers AI-driven defense of cloud infrastructure in AWS, as well as across SaaS applications, email, corporate networks, industrial systems, and remote endpoints. Taking a fundamentally unique approach, Darktrace provides the industry’s only self-learning platform that gives complete coverage and visibility across the organization.

This is a critical benefit, as businesses and workforces today are increasingly complex and dynamic. Darktrace can connect the dots between unusual behavior in disparate infrastructure areas and ensure cloud security is not siloed from the monitoring of the rest of the organization.

Darktrace’s adaptive and unified approach allows the solution to detect, investigate, and respond to the full range of threats facing the enterprise – even those unpredictable threats that move across dynamic and diverse environments.

Learn more about Darktrace and AWS

* VPC Traffic Mirroring is not supported on the T2, R3 and I2 instance types and previous generation instances.
** This product is only available in AWS for customers who leverage Darktrace osSensors.

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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.
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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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