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November 16, 2021

The Tech Driving Arrow McLaren SP to the Top

As Arrow McLaren SP looks back on a positive season, the team reflects on key challenges, success, and how AI and automation is leveraged in their work!
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
Taylor Kiel
Team President, Arrow McLaren SP
Written by
Craig Hampson
Director of Trackside Engineering, Arrow McLaren SP
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16
Nov 2021

As Arrow McLaren SP looks back on a positive season and prepares to build momentum into next year, Taylor Kiel (Team President) and Craig Hampson (Director of Trackside Engineering) reflect on key challenges and successes. With Pato O’Ward’s No. 5 car in the running to win the championship until the final race of the season, they reveal the formula for success – and how the team leverages AI and automation in every aspect of their work – from driver simulation to cyber security.

Data as the lifeblood for performance

In INDYCAR qualifiying, the difference between P1 and P10 can be as little as half a second, and when margins are that tight, the finer details in preparation make the difference. For us, that preparation is driven by data. Every race weekend and every practice session, over 100 lightweight sensors and several computers on the cars produce masses of data that is stored and analyzed for performance optimization.

This ecosystem includes an engine controller, a gear shift controller computer, and a computer unit that controls the clutch, and these systems all talk to each other across what is called a Controller Area Network (CAN). So the key question for us becomes: how do we get useful insights from that data, securely, and in a short period of time?

If you can think of something that’s happening on the car, the likelihood is our team is doing everything we can to try and measure it. Air speed, acceleration, tyre temperature, and so much more – we currently record over 1,500 data channels on the car itself, and we then process another 838 ‘math channels’ from combinations of this data – giving us, for example, the ride height of and downforce on the car.

This is more data than we can ever process with human beings alone, and a lot of our work now is figuring out how to automate these processes, using AI to look for patterns that humans simply cannot identify.

Pitting: More than just a tyre change

Each of our cars have two cellular-based telemetry systems built into them, but we are still limited on the amount of throughput we can observe real time, which is why we need to offload this data each time we pit during practice. This involves plugging in what we call an ‘umbilical cord’ that has a communication line and also powers the car.

Figure 1: A typical INDYCAR would last only minutes on its own battery without the engine running

Any typical race produces between 2.5GB and 3.3GB of data, in addition to in-car video, and a GPS system recording the car’s position on the track, which not only goes back to us but also to the relevant television broadcasters. So, we need to have a lot of storage available both in the cloud and on hard drives using a server. That data needs to be available not just to us at trackside but virtually to engineers not present at the race. And most importantly, that data needs to be secure, and protected from outside interference.

The cyber side: Turning to AI

All that precious data coming from the car, residing in the cloud or elsewhere in our organization, is susceptible to tampering from insiders and outsiders who may – deliberately or indirectly – compromise our ability to access or use that data reliably. As the cyber-threat landscape evolves – with ransomware bringing organizations of all shapes and sizes to a halt – we need to make sure we’re prepared for whatever attack is around the corner.

Firewalls, email gateways, and other perimeter protections are one part of the puzzle. But while these tools are focussed on keeping an attacker out – we needed another layer of defense that ensures that if these defenses are bypassed, we have an autonomous system that knows our organization inside out and can fight back on our behalf to disrupt emerging threats.

That’s where Darktrace has provided a revolutionary solution – using Self-Learning AI that understands every person and device from the ground up and identifies subtle deviations that point to a cyber-threat. And if ransomware strikes, 24/7 Autonomous Response is there in the form of Darktrace Antigena, taking precise action to contain ransomware and other threats at machine speed.

Double wins at doubleheaders

Using automation and AI throughout our technology stack enables us to extract meaningful insights from large pools of data and take quick, decisive action in the form of changes to the car or on-the-fly changes in race strategy.

The ability to react and react quickly is really put to the test on doubleheader race weekends, where any room for improvement you identify from Saturday’s race can be rectified in the form of overnight changes and implemented on Sunday. We believe it’s no coincidence that both of Pato’s No. 5 car’s wins came on the back end of doubleheader events, at Texas and Detroit Belle Isle. With people working in harmony with technology, our engineering team were able to make significant improvements to the car, react on the fly, and ultimately ensure we ended up ahead of the competition.

Digital fakes: Breaking new ground at Nashville

This year’s INDYCAR season featured a brand new track in Nashville, an exciting but daunting prospect for both the drivers and the team as a whole. Having access to a driver simulator, thanks to our partners at Chevrolet, we were able to run a virtual version of our car to try different setups, different techniques, and in this case have the driver learn his way round a whole new circuit.

Figure 2: The Chevrolet simulator projects a digital twin of the Nashville circuit

The track is recreated down to the nearest millimetre using a laser scanner, and then there is a lot of digital rendering involved, making it as realistic as possible with stands, fencing, and sponsor banners. Using this ‘digital fake’ representation was super helpful to the drivers in determining the correct approaches to corners, and for our engineers, enabling them to use the outputs to characterize the track.

The setup of the car in the simulator is effectively the same as the setup of the car in the real world: you set the spring rate and the ride height, it has the aerodynamic map, it knows the inertias and the masses of the car. It’s an incredibly complicated and powerful physics engine, but it gives us the ability to test things out in a controlled environment, and contributed toward one of Felix Rosenqvist’s strongest races of the season in the No. 7 car.

Simulations like these are the way of the future – not just for new circuits but in general. Rather than going through tyres and engines, we can replicate practice sessions in digital form, and the software gets closer to reality every day.

Looking ahead

What is next for Arrow McLaren SP? As we are now a part of the McLaren Racing family, new efficiencies and synergies are realized every month. We’ll certainly continue to leverage that valuable partnership, as well as our technology partnership with Darktrace, continuing to roll out their technology across our digital estate, including our email and cloud services.

In the INDYCAR Series, if you stay still, you go backwards, and the competition hots up every year. We know that now more than ever, the answer lies in using cutting-edge technologies across every aspect of the business to make our lives easier and ultimately propel us to the very top.

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
Taylor Kiel
Team President, Arrow McLaren SP
Written by
Craig Hampson
Director of Trackside Engineering, Arrow McLaren SP

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November 27, 2025

From Amazon to Louis Vuitton: How Darktrace Detects Black Friday Phishing Attacks

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Why Black Friday Drives a Surge in Phishing Attacks

In recent years, Black Friday has shifted from a single day of online retail sales and discounts to an extended ‘Black Friday Week’, often preceded by weeks of online hype. During this period, consumers are inundated with promotional emails and marketing campaigns as legitimate retailers compete for attention.

Unsurprisingly, this surge in legitimate communications creates an ideal environment for threat actors to launch targeted phishing campaigns designed to mimic legitimate retail emails. These campaigns often employ social engineering techniques that exploit urgency, exclusivity, and consumer trust in well-known brands, tactics designed to entice recipients into opening emails and clicking on malicious links.

Additionally, given the seasonal nature of Black Friday and the ever-changing habits of consumers, attackers adopt new tactics and register fresh domains each year, rather than reusing domains previously flagged as spam or phishing endpoints. While this may pose a challenge for traditional email security tools, it presents no such difficulty for Darktrace / EMAIL and its anomaly-based approach.

In the days and weeks leading up to ‘Black Friday’, Darktrace observed a spike in sophisticated phishing campaigns targeting consumers, demonstrating how attackers combine phycological manipulation with technical evasion to bypass basic security checks during this high-traffic period. This blog showcases several notable examples of highly convincing phishing emails detected and contained by Darktrace / EMAIL in mid to late November 2025.

Darktrace’s Black Friday Detections

Brand Impersonation: Deal Watchdogs’ Amazon Deals

The impersonation major online retailers has become a common tactic in retail-focused attacks, none more so than Amazon, which ranked as the fourth most impersonated brand in 2024, only behind Microsoft, Apple, Google, and Facebook [1]. Darktrace’s own research found Amazon to be the most mimicked brand, making up 80% of phishing attacks in its analysis of global consumer brands.

When faced with an email that appears to come from a trusted sender like Amazon, recipients are far more likely to engage, increasing the success rate of these phishing campaigns.

In one case observed on November 16, Darktrace detected an email with the subject line “NOW LIVE: Amazon’s Best Early Black Friday Deals on Gadgets Under $60”. The email was sent to a customer by the sender ‘Deal Watchdogs’, in what appeared to be an attempt to masquerade as a legitimate discount-finding platform. No evidence indicated that the company was legitimate. In fact, the threat actor made no attempt to create a convincing name, and the domain appeared to be generated by a domain generation algorithm (DGA), as shown in Figure 2.

Although the email was sent by ‘Deal Watchdogs’, it attempted to impersonate Amazon by featuring realistic branding, including the Amazon logo and a shade of orange similar to that used by them for the ‘CLICK HERE’ button and headline text.

Figure 1: The contents of the email observed by Darktrace, featuring authentic-looking Amazon branding.

Darktrace identified that the email, marked as urgent by the sender, contained a suspicious link to a Google storage endpoint (storage.googleapis[.]com), which had been hidden by the text “CLICK HERE”. If clicked, the link could have led to a credential harvester or served as a delivery vector for a malicious payload hosted on the Google storage platform.

Fortunately, Darktrace immediately identified the suspicious nature of this email and held it before delivery, preventing recipients from ever receiving or interacting with the malicious content.

Figure 2: Darktrace / EMAIL’s detection of the malicious phishing email sent to a customer.

Around the same time, Darktrace detected a similar email attempting to spoof Amazon on another customer’s network with the subject line “Our 10 Favorite Deals on Amazon That Started Today”, also sent by ‘Deal Watchdogs,’ suggesting a broader campaign.

Analysis revealed that this email originated from the domain petplatz[.]com, a fake marketing domain previously linked to spam activity according to open-source intelligence (OSINT) [2].

Brand Impersonation: Louis Vuitton

A few days later, on November 20, Darktrace / EMAIL detected a phishing email attempting to impersonate the luxury fashion brand Louis Vuitton. At first glance, the email, sent under the name ‘Louis Vuitton’ and titled “[Black Friday 2025] Discover Your New Favorite Louis Vuitton Bag – Elegance Starts Here”, appeared to be a legitimate Black Friday promotion. However, Darktrace’s analysis uncovered several red flags indicating a elaborate brand impersonation attempt.

The email was not sent by Louis Vuitton but by rskkqxyu@bookaaatop[.]ru, a Russia-based domain never before observed on the customer’s network. Darktrace flagged this as suspicious, noting that .ru domains were highly unusual for this recipient’s environment, further reinforcing the likelihood of malicious intent. Subsequent analysis revealed that the domain had only recently registered and was flagged as malicious by multiple OSINT sources [3].

Figure 3: Darktrace / EMAIL’s detection of the malicious email attempting to spoofLouis Vuitton, originating from a suspicious Russia-based domain.

Darktrace further noted that the email contained a highly suspicious link hidden behind the text “View Collection” and “Unsubscribe,” ensuring that any interaction, whether visiting the supposed ‘handbag store’ or attempting to opt out of marketing emails, would direct recipients to the same endpoint. The link resolved to xn--80aaae9btead2a[.]xn--p1ai (топааабоок[.]рф), a domain confirmed as malicious by multiple OSINT sources [4]. At the time of analysis, the domain was inaccessible, likely due to takedown efforts or the short-lived nature of the campaign.

Darktrace / EMAIL blocked this email before it reached customer inboxes, preventing recipients from interacting with the malicious content and averting any disruption.

Figure 4: The suspicious domain linked in the Louis Vuitton phishing email, now defunct.

Too good to be true?

Aside from spoofing well-known brands, threat actors frequently lure consumers with “too good to be true” luxury offers, a trend Darktrace observed in multiple cases throughout November.

In one instance, Darktrace identified an email with the subject line “[Black Friday 2025] Luxury Watches Starting at $250.” Emails contained a malicious phishing link, hidden behind text like “Rolex Starting from $250”, “Shop Now”, and “Unsubscribe”.

Figure 5: Example of a phishing email detected by Darktrace, containing malicious links concealed behind seemingly innocuous text.

Similarly to the Louis Vuitton email campaign described above, this malicious link led to a .ru domain (hxxps://x.wwwtopsalebooks[.]ru/.../d65fg4er[.]html), which had been flagged as malicious by multiple sources [5].

Figure 6: Darktrace / EMAIL’s detection of a malicious email promoting a fake luxury watch store, which was successfully held from recipient inboxes.

If accessed, this domain would redirect users to luxy-rox[.]com, a recently created domain (15 days old at the time of writing) that has also been flagged as malicious by OSINT sources [6]. When visited, the redirect domain displayed a convincing storefront advertising high-end watches at heavily discounted prices.

Figure 7: The fake storefront presented upon visiting the redirectdomain, luxy-rox[.]com.

Although the true intent of this domain could not be confirmed, it was likely a scam site or a credential-harvesting operation, as users were required to create an account to complete a purchase. As of the time or writing, the domain in no longer accessible .

This email illustrates a layered evasion tactic: attackers employed multiple domains, rapid domain registration, and concealed redirects to bypass detection. By leveraging luxury branding and urgency-driven discounts, the campaign sought to exploit seasonal shopping behaviors and entice victims into clicking.

Staying Protected During Seasonal Retail Scams

The investigation into these Black Friday-themed phishing emails highlights a clear trend: attackers are exploiting seasonal shopping events with highly convincing campaigns. Common tactics observed include brand impersonation (Amazon, Louis Vuitton, luxury watch brands), urgency-driven subject lines, and hidden malicious links often hosted on newly registered domains or cloud services.

These campaigns frequently use redirect chains, short-lived infrastructure, and psychological hooks like exclusivity and luxury appeal to bypass user scepticism and security filters. Organizations should remain vigilant during retail-heavy periods, reinforcing user awareness training, link inspection practices, and anomaly-based detection to mitigate these evolving threats.

Credit to Ryan Traill (Analyst Content Lead) and Owen Finn (Cyber Analyst)

Appendices

References

1.        https://keepnetlabs.com/blog/top-5-most-spoofed-brands-in-2024

2.        https://www.virustotal.com/gui/domain/petplatz.com

3.        https://www.virustotal.com/gui/domain/bookaaatop.ru

4.        https://www.virustotal.com/gui/domain/xn--80aaae9btead2a.xn--p1ai

5.        https://www.virustotal.com/gui/url/e2b868a74531cd779d8f4a0e1e610ec7f4efae7c29d8b8ab32c7a6740d770897?nocache=1

6.        https://www.virustotal.com/gui/domain/luxy-rox.com

Indicators of Compromise (IoCs)

IoC – Type – Description + Confidence

petplatz[.]com – Hostname – Spam domain

bookaaatop[.]ru – Hostname – Malicious Domain

xn--80aaae9btead2a[.]xn--p1ai (топааабоок[.]рф) – Hostname - Malicious Domain

hxxps://x.wwwtopsalebooks[.]ru/.../d65fg4er[.]html) – URL – Malicious Domain

luxy-rox[.]com – Hostname -  Malicious Domain

MITRE ATT&CK Mapping  

Tactic – Technique – Sub-Technique  

Initial Access - Phishing – (T1566)  

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About the author
Ryan Traill
Analyst Content Lead

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November 27, 2025

CastleLoader & CastleRAT: Behind TAG150’s Modular Malware Delivery System

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What is TAG-150?

TAG-150, a relatively new Malware-as-a-Service (MaaS) operator, has been active since March 2025, demonstrating rapid development and an expansive, evolving infrastructure designed to support its malicious operations. The group employs two custom malware families, CastleLoader and CastleRAT, to compromise target systems, with a primary focus on the United States [1]. TAG-150’s infrastructure included numerous victim-facing components, such as IP addresses and domains functioning as command-and-control (C2) servers associated with malware families like SecTopRAT and WarmCookie, in addition to CastleLoader and CastleRAT [2].

As of May 2025, CastleLoader alone had infected a reported 469 devices, underscoring the scale and sophistication of TAG-150’s campaign [1].

What are CastleLoader and CastleRAT?

CastleLoader is a loader malware, primarily designed to download and install additional malware, enabling chain infections across compromised systems [3]. TAG-150 employs a technique known as ClickFix, which uses deceptive domains that mimic document verification systems or browser update notifications to trick victims into executing malicious scripts. Furthermore, CastleLoader leverages fake GitHub repositories that impersonate legitimate tools as a distribution method, luring unsuspecting users into downloading and installing malware on their devices [4].

CastleRAT, meanwhile, is a remote access trojan (RAT) that serves as one of the primary payloads delivered by CastleLoader. Once deployed, CastleRAT grants attackers extensive control over the compromised system, enabling capabilities such as keylogging, screen capturing, and remote shell access.

TAG-150 leverages CastleLoader as its initial delivery mechanism, with CastleRAT acting as the main payload. This two-stage attack strategy enhances the resilience and effectiveness of their operations by separating the initial infection vector from the final payload deployment.

How are they deployed?

Castleloader uses code-obfuscation methods such as dead-code insertion and packing to hinder both static and dynamic analysis. After the payload is unpacked, it connects to its command-and-control server to retrieve and running additional, targeted components.

Its modular architecture enables it to function both as a delivery mechanism and a staging utility, allowing threat actors to decouple the initial infection from payload deployment. CastleLoader typically delivers its payloads as Portable Executables (PEs) containing embedded shellcode. This shellcode activates the loader’s core module, which then connects to the C2 server to retrieve and execute the next-stage malware.[6]

Following this, attackers deploy the ClickFix technique, impersonating legitimate software distribution platforms like Google Meet or browser update notifications. These deceptive sites trick victims into copying and executing PowerShell commands, thereby initiating the infection kill chain. [1]

When a user clicks on a spoofed Cloudflare “Verification Stepprompt, a background request is sent to a PHP script on the distribution domain (e.g., /s.php?an=0). The server’s response is then automatically copied to the user’s clipboard using the ‘unsecuredCopyToClipboard()’ function. [7].

The Python-based variant of CastleRAT, known as “PyNightShade,” has been engineered with stealth in mind, showing minimal detection across antivirus platforms [2]. As illustrated in Figure 1, PyNightShade communicates with the geolocation API service ip-api[.]com, demonstrating both request and response behavior

Packet Capture (PCAP) of PyNightShade, the Python-based variant of CastleRAT, communicating with the geolocation API service ip-api[.]com.
Figure 1: Packet Capture (PCAP) of PyNightShade, the Python-based variant of CastleRAT, communicating with the geolocation API service ip-api[.]com.

Darktrace Coverage

In mid-2025, Darktrace observed a range of anomalous activities across its customer base that appeared linked to CastleLoader, including the example below from a US based organization.

The activity began on June 26, when a device on the customer’s network was observed connecting to the IP address 173.44.141[.]89, a previously unseen IP for this network along with the use of multiple user agents, which was also rare for the user.  It was later determined that the IP address was a known indicator of compromise (IoC) associated with TAG-150’s CastleRAT and CastleLoader operations [2][5].

Figure 2: Darktrace’s detection of a device making unusual connections to the malicious endpoint 173.44.141[.]89.

The device was observed downloading two scripts from this endpoint, namely ‘/service/download/data_5x.bin’ and ‘/service/download/data_6x.bin’, which have both been linked to CastleLoader infections by open-source intelligence (OSINT) [8]. The archives contains embedded shellcode, which enables attackers to execute arbitrary code directly in memory, bypassing disk writes and making detection by endpoint detection and response (EDR) tools significantly more difficult [2].

 Darktrace’s detection of two scripts from the malicious endpoint.
Figure 3: Darktrace’s detection of two scripts from the malicious endpoint.

In addition to this, the affected device exhibited a high volume of internal connections to a broad range of endpoints, indicating potential scanning activity. Such behavior is often associated with reconnaissance efforts aimed at mapping internal infrastructure.

Darktrace / NETWORK correlated these behaviors and generated an Enhanced Monitoring model, a high-fidelity security model designed to detect activity consistent with the early stages of an attack. These high-priority models are continuously monitored and triaged by Darktrace’s Security Operations Center (SOC) as part of the Managed Threat Detection and Managed Detection & Response services, ensuring that subscribed customers are promptly alerted to emerging threats.

Darktrace detected an unusual ZIP file download alongside the anomalous script, followed by internal connectivity. This activity was correlated under an Enhanced Monitoring model.
Figure 4: Darktrace detected an unusual ZIP file download alongside the anomalous script, followed by internal connectivity. This activity was correlated under an Enhanced Monitoring model.

Darktrace Autonomous Response

Fortunately, Darktrace’s Autonomous Response capability was fully configured, enabling it to take immediate action against the offending device by blocking any further connections external to the malicious endpoint, 173.44.141[.]89. Additionally, Darktrace enforced a ‘group pattern of life’ on the device, restricting its behavior to match other devices in its peer group, ensuring it could not deviate from expected activity, while also blocking connections over 443, shutting down any unwanted internal scanning.

Figure 5: Actions performed by Darktrace’s Autonomous Response to contain the ongoing attack.

Conclusion

The rise of the MaaS ecosystem, coupled with attackers’ growing ability to customize tools and techniques for specific targets, is making intrusion prevention increasingly challenging for security teams. Many threat actors now leverage modular toolkits, dynamic infrastructure, and tailored payloads to evade static defenses and exploit even minor visibility gaps. In this instance, Darktrace demonstrated its capability to counter these evolving tactics by identifying early-stage attack chain behaviors such as network scanning and the initial infection attempt. Autonomous Response then blocked the CastleLoader IP delivering the malicious ZIP payload, halting the attack before escalation and protecting the organization from a potentially damaging multi-stage compromise

Credit to Ahmed Gardezi (Cyber Analyst) Tyler Rhea (Senior Cyber Analyst)
Edited by Ryan Traill (Analyst Content Lead)

Appendices

Darktrace Model Detections

  • Anomalous Connection / Unusual Internal Connections
  • Anomalous File / Zip or Gzip from Rare External Location
  • Anomalous File / Script from Rare External Location
  • Initial Attack Chain Activity (Enhanced Monitoring Model)

MITRE ATT&CK Mapping

  • T15588.001 - Resource Development – Malware
  • TG1599 – Defence Evasion – Network Boundary Bridging
  • T1046 – Discovery – Network Service Scanning
  • T1189 – Initial Access

List of IoCs
IoC - Type - Description + Confidence

  • 173.44.141[.]89 – IP – CastleLoader C2 Infrastructure
  • 173.44.141[.]89/service/download/data_5x.bin – URI – CastleLoader Script
  • 173.44.141[.]89/service/download/data_6x.bin – URI  - CastleLoader Script
  • wsc.zip – ZIP file – Possible Payload

References

[1] - https://blog.polyswarm.io/castleloader

[2] - https://www.recordedfuture.com/research/from-castleloader-to-castlerat-tag-150-advances-operations

[3] - https://www.pcrisk.com/removal-guides/34160-castleloader-malware

[4] - https://www.scworld.com/brief/malware-loader-castleloader-targets-devices-via-fake-github-clickfix-phishing

[5] https://www.virustotal.com/gui/ip-address/173.44.141.89/community

[6] https://thehackernews.com/2025/07/castleloader-malware-infects-469.html

[7] https://www.cryptika.com/new-castleloader-attack-using-cloudflare-themed-clickfix-technique-to-infect-windows-computers/

[8] https://www.cryptika.com/castlebot-malware-as-a-service-deploys-range-of-payloads-linked-to-ransomware-attacks/

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