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May 25, 2021

How Autonomous Cyber AI Scaled to Protect Arrow McLaren SP

Darktrace's Cyber AI has seamlessly scaled, extended, and adapted to protect Arrow McLaren's Formula 1 and IndyCar teams from machine-speed cyberattacks.
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
Justin Fier
SVP, Red Team Operations
Written by
Nick Snyder
Performance Director, Arrow McLaren SP
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25
May 2021

It’s been decades since a racing team has had the ambition to compete at the highest level simultaneously in Formula 1 and in the NTT INDYCAR Series. And why would they? With hectic schedules, tight timelines, and the finest margins between victory and defeat, one series alone may seem a daunting enough feat. But to compete across both requires cross-continent collaboration, creativity, and innovation at every turn.

Rather than being daunted by the challenge, McLaren has embraced the unique advantages of racing in both series simultaneously. Arrow McLaren SP, in a strategic partnership with McLaren Racing, communicates on a daily basis with the McLaren Technology Centre in the UK, gathering and sharing data including car telemetry, on-board video and audio files, timing and scoring information, car set-ups, and reporting.

The security of this critical and highly sensitive data is paramount to the performance of AMSP, and after the success of Darktrace’s AI in protecting the cloud, email, and network environments of McLaren F1, AMSP recently announced they would be seamlessly extending the coverage to the US.

How adaptive, scalable AI drives success

Darktrace’s autonomous Cyber AI has protected the McLaren F1 team since early 2020, shielding their workforce and critical systems during a time of fundamental digital change, with conditions arising from COVID-19 forcing many employees to work from home. During this time the organization had a heightened reliance on cloud collaboration platforms, including video conferencing and file sharing.

Cyber AI technology adapted to these unforeseen changes, protecting the McLaren F1 team from novel and advanced attacks targeting their dynamic workforce. While traditional tools bound by set rules and playbooks had to be reconfigured, a self-learning approach allowed continuous protection of McLaren’s email systems, cloud services, and network traffic, with little maintenance required from busy human teams.

Now, the technology is being put to the test again. McLaren has extended Darktrace’s AI technology to protect the large volumes of sensitive data that travels back and forth between Arrow McLaren SP and the MTC.

Responding to machine-speed ransomware with Autonomous Response

As a wave of ransomware attacks brings fresh concerns to the cyber security industry, AMSP is turning to a technology fundamental to stopping these machine-speed attacks. With Autonomous Response, Darktrace not only detects emerging threats, but responds in real time, stopping attackers in their tracks without human teams having to lift a finger.

The response is surgical and proportionate: only the malicious activity is contained, whilst normal operations are allowed to continue. This will be a crucial capability for the AMSP team, as any unnecessary downtime severely undermines their ability to get access to the right data at the right time – ultimately having an impact on performance on race day.

With Darktrace’s autonomous Cyber AI protecting both its F1 and INDYCAR teams, McLaren’s human IT resources are augmented with real-time protection and Autonomous Response working across different time zones and providing that 24/7 overwatch they need.

Indianapolis 500: The toughest test yet

The month of May is a busy and critical period of the season for AMSP, with three races culminating in the 105th Running of the Indianapolis 500, which will be held in front of a reduced crowd of 135,000 spectators. The IT team has been busy preparing a temporary trackside data centre for this event, and the sheer volume of data circulating between that and the MTC is ramping up.

All of this data must be gathered, organized, and transferred securely back and forth between the two hubs. The speed of that transfer is absolutely vital, as speed of analysis and real-time decision-making is critical to race performance. AMSP’s engineering team and McLaren’s engineering team operate as if they’re sitting next to each other, despite being thousands of miles away.

Moreover, some data files can be extremely large, and reliable connectivity is key in ensuring that all files, no matter the size, can be transferred and downloaded as quickly as possible. Lack or loss of any data gathered trackside would prevent AMSP’s abilities to accurately recap on-track sessions.

This clearly represents an incredibly busy time for the security personnel on the ground both at Indianapolis and in the UK. Leaning on AI to facilitate the secure and reliable movement of highly sensitive data empowers AMSP’s IT team to stay proactive, rather than being reactive and playing catch up in the case of a security incident.

Facing the future with Cyber AI

AMSP is in a unique position in the INDYCAR paddock – no other team transmits so much data, so often or over so far of a distance. Darktrace’s Cyber AI technology is helping to protect AMSP’s at-track engineering crews, remote engineering teams, data transfer processes and cloud infrastructure, from an increasingly hostile cyber-threat landscape.

Relying on Darktrace to safeguard and protect its sensitive data and digital assets will become critical in securing AMSP’s overall approach to race weekend activation. As the collaboration between McLaren Racing and Arrow McLaren SP continues to drive success on the track, the targeted actions of Darktrace’s Autonomous Response capability ensures both sides of the technical partnership stay protected across different time zones, around the clock, no matter what threat is waiting round the corner.

Visit the McLaren hub

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
Justin Fier
SVP, Red Team Operations
Written by
Nick Snyder
Performance Director, Arrow McLaren SP

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Cloud

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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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Network

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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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