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November 6, 2022

Behind Yanluowang: Unveiling Cyber Threat Tactics

Discover the latest insights into the Yanluowang leak organization, uncovering its members and tactics.
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
Taisiia Garkava
Security Analyst
Written by
Dillon Ashmore
Security and Research
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06
Nov 2022

Background of Yanluowang

Yanluowang ransomware, also known as Dryxiphia, was first spotted in October 2021 by Symantec’s Threat Hunter Team. However, it has been operational since August 2021, when a threat actor used it to attack U.S. corporations. Said attack shared similar TTPs with ransomware Thieflock, designed by Fivehands ransomware gangs. This connection alluded to a possible link between the two through the presence or influence of an affiliate. The group has been known for successfully ransoming organisations globally, particularly those in the financial, manufacturing, IT services, consultancy, and engineering sectors.

Yanluowang attacks typically begin with initial reconnaissance, followed by credential harvesting and data exfiltration before finally encrypting the victim’s files. Once deployed on compromised networks, Yanluowang halts hypervisor virtual machines, all running processes and encrypts files using the “.yanluowang” extension. A file with name README.txt, containing a ransom note is also dropped. The note also warns victims against contacting law enforcement, recovery companies or attempting to decrypt the files themselves. Failure to follow this advice would result in distributed denial of service attacks against a victim, its employees and business partners. Followed by another attack, a few weeks later, in which all the victim’s files would be deleted.

The group’s name “Yanluowang” was inspired by the Chinese mythological figure Yanluowang, suggesting the group’s possible Chinese origin. However, the recent leak of chat logs belonging to the group, revealed those involved in the organisation spoke Russian. 

 Leak of Yanluowang’s chat logs

 On the 31st of October, a Twitter user named @yanluowangleaks shared the matrix chat and server leaks of the Yanluowang ransomware gang, alongside the builder and decryption source. In total, six files contained internal conversations between the group’s members. From the analysis of these chats, at least eighteen people have been involved in Yanluowang operations.

Twitter account where the leaks and decryption source were shared
Figure 1: Twitter account where the leaks and decryption source were shared

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Potential members: ‘@killanas', '@saint', '@stealer', '@djonny', '@calls', '@felix', '@win32', '@nets', '@seeyousoon', '@shoker', '@ddos', '@gykko', '@loader1', '@guki', '@shiwa', '@zztop', '@al', '@coder1'‍

Most active members: ‘@saint’, ‘@killanas’, ‘@guki’, ‘@felix’, ‘@stealer’. 

To make the most sense out of the data that we analyzed, we combined the findings into two categories: tactics and organization.‍

Tactics ‍

From the leaked chat logs, several insights into the group’s operational security and TTPs were gained. Firstly, members were not aware of each other’s offline identities. Secondly, discussions surrounding security precautions for moving finances were discussed by members @killanas and @felix. The two exchanged recommendations on reliable currency exchange platforms as well as which ones to avoid that were known to leak data to law enforcement. The members also expressed paranoia over being caught with substantial amounts of money and therefore took precautions such as withdrawing smaller amounts of cash or using QR codes for withdrawals.

Additionally, the chat logs exposed the TTPs of Yanluowang. Exchanges between the group’s members @stealer, @calls and @saint, explored the possibilities of conducting attacks against critical infrastructure. One of these members, @call, was also quick to emphasise that Yanluowang would not target the critical infrastructure of former Soviet countries. Beyond targets, the chat logs also highlighted Yanluowang’s use of the ransomware, PayloadBIN but also that attacks that involved it may potentially have been misattributed to another ransomware actor, Evil Corp.

Further insight surrounding Yanluowang’s source code was also gained as it was revealed that it had been previously published on XSS.is as a downloadable file. The conversations surrounding this revealed that two members, @killanas and @saint, suspected @stealer was responsible for the leak. This suspicion was supported by @saint, defending another member whom he had known for eight years. It was later revealed that the code had been shared after a request to purchase it was made by a Chinese national. @saint also used their personal connections to have the download link removed from XSS.is. These connections indicate that some members of Yanluowang are well embedded in the ransomware and wider cybercrime community.

Another insight gained from the leaked chat logs was an expression by @saint in support of Ukraine, stating, “We stand with Ukraine” on the negotiation page of Yanluowang’s website. This action reflects a similar trend observed among threat actors where they have taken sides in the Russia-Ukraine conflict.

Regarding Yanluowang’s engagement with other groups, it was found that a former member of Conti had joined the group. This inference was made by @saint when a conversation regarding the Conti leak revolved around the possible identification of the now Yanluowang member @guki, in the Conti files. It was also commented that Conti was losing a considerable number of its members who were then looking for new work. Conversations about other ransomware groups were had with the mentioning of the REVIL group by @saint, specifically stating that five arrested members of the gang were former classmates. He backed his statement by attaching the article about it, to which @djonny replies that those are indeed REVIL members and that he knows it from his sources.‍

Organization ‍

When going through the chat logs, several observations were made that can offer some insights into the group's organizational structure. In one of the leaked files, user @saint was the one to publish the requirements for the group's ".onion" website and was also observed instructing other users on the tasks they had to complete. Based on this, @saint could be considered the leader of the group. Additionally, there was evidence indicating that a few users could be in their 30s or 40s, while most participants are in their 20s.

More details regarding Yanluowang's organizational structure were discussed deeper into the leak. The examples indicate various sub-groups within the Yanlouwang group and that a specific person coordinates each group. From the logs, there is a high probability that @killanas is the leader of the development team and has several people working under him. It is also possible that @stealer is on the same level as @killanas and is potentially the supervisor of another team within the group. This was corroborated when @stealer expressed concerns about the absence of certain group members on several occasions. There is also evidence showing that he was one of three people with access to the source code of the group. 

Role delineation within the group was also quite clear, with each user having specific tasks: DDoS (distributed denial of service) attacks, social engineering, victim negotiations, pentesting or development, to mention a few. When it came to recruiting new members, mostly pentesters, Yanluowang would recruit through XSS.is and Exploit.in forums.‍

Underground analysis and members’ identification ‍

From the leaked chat logs, several “.onion” URLs were extracted; however, upon further investigation, each site had been taken offline and removed from the TOR hashring. This suggests that Yanluowang may have halted all operations. One of the users on XSS.is posted a picture showing that the Yanluowang onion website was hacked, stating, “CHECKMATE!! YANLUOWANG CHATS HACKED @YANLUOWANGLEAKS TIME’S UP!!”.‍

Figure 2: The screenshot of Yanluowang website on Tor (currently offline)

After learning that Yanluowang used Russian Web Forums, we did an additional search to see what we could find about the group and the mentioned nicknames. 

By searching through XSS.Is we managed to identify the user registered as @yanluowang. The date of the registration on the forum dates to 15 March 2022. Curiously, at the time of analysis, we noticed the user was online. There were in total 20 messages posted by @yanluowang, with a few publications indicating the group is looking for new pentesters.

Figure 3: The screenshot of Yanluowang profile on XSS.is 

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Figure 4: The screenshot of Yanluowang posts about pentester recruitment on XSS.is 

While going through the messages, it was noticed the reaction posted by another user identified as @Sa1ntJohn, which could be the gang member @saint.

‍Figure 5: The screenshot of Sa1ntJohn’s profile on XSS.is

‍Looking further, we identified that user @Ekranoplan published three links to the website doxbin.com containing information about three potential members of the YanLuoWang gang: @killanas/coder, @hardbass and @Joe/Uncle. The profile information was published by the user @Xander2727.‍

Figure 6: The screenshot of Yanlouwang member-profile leak on XSS.is
Figure 7: The screenshot of @hardbass Yanlouwang member profile leak
Figure 8: The screenshot of @killanas/coder Yanlouwang member profile leak.

‍If the provided information is correct, two group members are Russian and in their 30s, while another member is Ukrainian and in his 20s. One of the members, @killanas, who was also referenced in chat logs, is identified as the lead developer of the Yanluowang group; giving the interpretation of the chat leaks a high-level of confidence. Another two members, who were not referenced in the logs, took roles as Cracked Software/Malware provider and English translator/Victim Negotiator.‍

Implications for the wider ransomware landscape‍

To conclude with the potential implications of this leak, we have corroborated the evidence gathered throughout this investigation and employed contrarian analytical techniques. The ascertained implications that follow our mainline judgement, supporting evidence and our current analytical view on the matter can be categorized into three key components of this leak:

‍Impact on the ransomware landscape‍

The leak of Yanluowang’s chat logs has several implications for the broader ransomware landscape. This leak, much like the Conti leak in March, spells the end for Yanluowang operations for the time being, given how much of the group’s inner workings it has exposed. This could have an adverse effect. While Yanluowang did not control as large of a share of the ransomware market as Conti did, their downfall will undoubtedly create a vacuum space for established groups for their market share. The latter being a consequence of the release of their source code and build tools. 

‍Source code‍

The release of Yanluowang’s source code has several outcomes. If the recipients have no malintent, it could aid in reverse engineering the ransomware, like how a decryption tool for Yanluowng was released earlier this year. An alternative scenario is that the publication of the source code will increase the reach and deployment of this ransomware in the future, in adapted or modified versions by other threat actors. Reusing leaked material is notorious among ransomware actors, as seen in the past, when Babuk’s source code was leaked and led to the development of several variants based on this leak, including Rook and Pandora. This could also make it harder to attribute attacks to one specific group.

‍Members‍

The migration of unexposed Yanluowang members to other ransomware gangs could further add to the proliferation of ransomware groups. Such forms of spreading ransomware have been documented in the past when former Conti members repurposed their tactics to join efforts with an initial access broker, UAC-0098. Yet, the absence of evidence from members expressing and/or acting upon this claim requires further investigation and analysis. However, as there is no evidence of absence – this implication is based on the previously observed behavior from members of other ransomware gangs.

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
Taisiia Garkava
Security Analyst
Written by
Dillon Ashmore
Security and Research

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October 26, 2026

PHP脆弱性、ARTEX、そしてサイバー攻撃におけるAIの役割拡大

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BCVE-2026-109618およびCVE-2026-109619の公開により、PHPを運用している組織は緊急対応を余儀なくされました。どちらの脆弱性も許可のないリモートコード実行を可能にするものであり、対象はPHPが組み込まれ、サードパーティベンダーにアップデートを依存する製品およびアプライアンスも含まれていました[1]。

初期のガイダンスではインターネットに接続されたシステムにパッチを適用し、予期しないコマンド実行やWebroot変更、PHPサーバーからのアウトバウンド接続など、エクスプロイトの成功に関連した振る舞いを監視することに重点が置かれました。

Darktraceは監視中の環境においてスキャニングが広範に発生していることを観測し、これにはPHP脆弱性を標的としたアクティビティに関連すると報告されている数百の個別のIPアドレスが関係していました。スキャニングの量はエクスプロイトの成功を示す証拠の数を著しく上回るものでした。アナリストにとってはこの違いが重要です。スキャニングは露出したインフラへの関心を表すものです。侵害を確認するには、標的とされたシステム上でこれに続く振る舞い、たとえばコマンド実行、ファイル変更、予期しないアウトバウンド接続などの証拠が必要です。

PHPは例外的なケースではありません。その後、Imperva社が脆弱なNode.jsビルドに対するリモートコード実行を悪意あるBrotliデータを通じて実証し、圧縮HTTPレスポンスおよび設定済みリクエストパーサーを通じたコード実行を再現しました。同じ入力はパッチ適用済みのランタイムからは拒否されました。Imperva社はNode2ShellおよびPHP2Shellに対する研究結果を、脆弱性探索とエクスプロイト開発スピードの上昇と結びつけています。[2]

DarktraceはCVE-2026-109618あるいはCVE-2026-109619エクスプロイトの直接的証拠を観測していませんが、10月21日にゼロデイエクスプロイトのアクティビティと一致する過去6か月間で最大の脅威検知を観測し、これは過去のデータと比較して64%上昇を示すものでした。この上昇とPHP脆弱性との関連性は確認されていません。Darktraceの振る舞いベースのアプローチは、特定のエクスプロイトに対して記述されたルールだけに頼ることなく異常なアクティビティを検知するよう設計されています。同様の検知の増加はLog4j脆弱性の公表、およびその他の世界的に重大な脆弱性公表時にも観測されています。

AI支援による脆弱性探索

AIシステムが高い脆弱性探索能力を持つようになるなかで、PHPの脆弱性が発見されました[3]。OpenAIは2026年6月にDaybreakプログラムを発表し、GPT-5.5-CyberおよびCodex Securityをセキュリティ研究者やソフトウェア維持管理者とのパートナーシップと結びつけました。OpenAIはこれらのモデルがブラウザ、ネットワークインフラ、FreeBSDおよびLinuxカーネルの脆弱性の発見およびパッチ作成に適用されていると説明しています。ダークトレースは6月にOpenAI Daybreak Cyber Partner Programに参加し、OpenAIの提供するサイバー能力をDarktrace製品およびサービスにどのように統合できるかを研究しています [4][10]。

OpenAIは8月に、Codex Security Cloudが30,000以上のコードベースにおいて3000万件以上のコミットを分析したと報告しています。OpenAIによると、Cloudflare社はDaybreakを通じてアクセスするモデルを利用して、顧客の承認を受けたコードを調査し、その調査結果をリアルタイムのトラフィックやセキュリティシグナルと組み合わせて、影響を受けたルートがアクティブかどうか、または不審なトラフィックを受信しているかを評価し、顧客によるレビュー対象として緩和策やパッチを提案しているということです[5][6]。

迅速に発見することができても、影響を受けたソフトウェアを特定し、修正をテストし、是正措置を完了するという作業は、依然として防御者が行わなければなりません。PHPの事例は、特に脆弱なランタイムが他の製品に組み込まれている場合に、このギャップが問題となることを明確に示しています。

アタックサーフェスとしての企業AIエージェント

DarktraceSignal Labsは、攻撃者がすでに環境へのアクセス権を取得した後、信頼されたAIエージェントがどのように悪用される可能性があるかについても調査しました。ダークトレースの研究者は管理されたシミュレーション環境において、侵害後のシナリオとして、Claudeプラットフォームのメモリストア機能が悪用され、外部オペレーターと内部のClaude Codeエージェント間にライブC2チャネルを確立できることを実証しました。外部オペレーターは、このC2チャネルを介して、ネットワーク探索、認証情報へのアクセス、データの持ち出しといったタスクをエージェントに動的に割り当てることができました。エージェントのアクティビティの検知は、エージェントハーネスプロセスからのプロセス作成とネットワークトラフィックの相関付け、および予期された動作からの逸脱を特定するためのビヘイビア分析に基づいて行われました。ダークトレースはこのメモリストアを使ったC2テクニックを実際の攻撃で観測したとは主張していません[7]。

日本で観測されたAI支援による攻撃

日本で観測された証拠は、研究用環境を超えて、実際の脆弱性探索と攻撃にAIが使用されていることを示しています。10月21日、JPCERT/CCは最近の日本国内の組織に対する不正アクセスインシデントについての調査結果を発表しました。JPCERT/CCは攻撃者がAIを使って既知の脆弱性をスキャンしAPIを通じて攻撃を実行していることを確認したと報告しています。JPCERT/CCによると、攻撃インフラを調査した結果、Androidアプリケーションの分析、APIの探索、サーバーサイドリクエストフォージェリを含む脆弱性テストの痕跡が確認され、また、この攻撃インフラは日本国外のユーザー向けサービスも標的としていました[8]。

JPCERT/CCはこの公開資料の中ではARTEXを特定していません。ARTEXに対するアトリビューションは、Microsoft社によるStorm-0940の分析を含む、別の調査に基づいています。

攻撃オペレーションにおけるAI

Microsoft社は、ARTEXを限定的な人間の介入でアクティビティを自動化できる、オープンソースのマルチエージェント型ペネトレーションテストシステムと説明しています。Microsoft社は、2021年から活動している中国政府と連携した攻撃者と評価しているStorm-0940が、数百の組織に対してARTEXを使用したと報告し、ConnectWiseのサプライチェーン侵害がStorm-0940によるものであるとしました[9]。

Microsoft社は、ARTEXがスキャン、偵察、パスワードスプレー、OAuthアプリケーションの悪用を加速させていることを確認しました。ARTEXに駆動されたいくつかの攻撃オペレーションは、最初の標的設定から3時間未満で特権クラウドアクセスに到達しました。ConnectWiseの侵害後、Storm-0940は最大で毎分2,900回の頻度で、2,250を超えるテナントへの認証を試みました[9]。

ダークトレースの脅威調査チームは、後にこのキャンペーンとの関連が判明したインフラに関するアクティビティを、Darktraceテレメトリー内で発見しました。10月13日、Darktraceは、Microsoftが後にConnectWiseの顧客環境でサインインおよびMicrosoft Graphのアクティビティを実行していたと特定したアドレスの1つである144.172.64[.]128に関連する認証アクティビティの失敗を記録しました。Darktraceの分析では、約20分間に65回の認証失敗が確認されました。

図1:2026年10月13日、144.172.64[.]128が関与した認証失敗イベントを示すDarktrace Advanced Searchの結果(顧客を特定できる情報は削除済み)。

Darktraceのテレメトリーは、後にこのキャンペーンとの関連が確認されたインフラから、認証の失敗が繰り返し発生していたことを明らかにしています。これはARTEXの実行や侵害の成功を立証するものではありません。観測時点では、Microsoft社による後のアトリビューションについての情報はありませんでした。つまり、アナリストが把握していたのは振る舞いそのものでした。短時間に同一の送信元から認証に繰り返し失敗したということ、および関連するアイデンティティ、アプリケーション、ネットワークティビティについてのデータです。

Microsoft社は、10月10日から14日にかけて、8組織の327アカウントを対象とした、より広範なパスワードスプレー攻撃を報告しました。151,000件を超えるログオン失敗が記録され、なかでも11月10日には111,000件を超えていましたが、このキャンペーンによる認証成功、トークン発行、Graph呼び出し、ディレクトリ変更はいずれもありませんでした。また、Microsoftは、Storm-0940による標的化の大半が成功しなかったとも報告しています[9]。

攻撃者が認証を突破したケースでは、Microsoft社はサービスプリンシパルによるサインインに続いて、Graphおよびディレクトリ操作が行われたことを確認しました。アクティビティには、偵察、アプリケーション認証情報の変更、権限の変更を試みる行為が含まれていました。Microsoft社はサービスプリンシパルによるサインインとGraphアクティビティ、ディレクトリ変更およびリソースアクセスを相関づけることを推奨しています[9]。

アトリビューションの前に振る舞い

PHPとARTEXの事例は、異なる情報から始まっています。PHPの防御担当者は、どのソフトウェアに緊急の対策が必要かを把握していたものの、当初はエクスプロイトついての情報が限られていました。それでも、プロセスの実行、ファイルの変更、外部への通信は、侵害の証拠となったでしょう。

PHPとARTEXの観測結果は、量と影響範囲の違いも示しています。DarktraceはPHPの脆弱性公開時期に広範なスキャンを観測しました。一方ARTEX関連のインフラでは認証アクティビティが集中して発生していました。どちらの観察結果も、それ単独では侵害を実証するものではなく、いずれのケースにおいても、最初のやり取りに続く振る舞いを調べることが調査上の手がかりとなります。

DarktraceのARTEX関連の検知は、認証関連の振る舞いから始まりました。Microsoft社が攻撃インフラのアトリビューションを公表したのはその8日後でした。アトリビューションはコンテキストを提供するものではありましたが、環境内で最初に記録された事象を変更するものではありませんでした。

AIは今や攻撃サイクルの複数のポイントに存在しています。Daybreakは脆弱性の発見と修正にモデルを適用しています。Darktrace Signal Labsは信頼される企業内AIエージェントがどのように悪用されうるかを、管理された環境内で実証しました。JPCERT/CCは最近のインシデントにおけるAI支援による脆弱性探索およびAPI攻撃を確認しました。Microsoft社は実際の攻撃でStorm-0940がARTEXを使用していることを報告しました [4][7][8][9]。

Microsoft社の研究結果はまた、攻撃の規模と影響は別に評価しなければならないことも示しています。ARTEXを使った1つのキャンペーンは151,000回以上のログオン失敗を生成し、アクセスに至らなかったものの、他のキャンペーンでは3時間未満で特権クラウドアクセスに到達した例もありました。セキュリティチームは大量の試行アクティビティと、認証を突破し権限の変更やリソースアクセスへと進むものを区別しなければなりません。

これらのケースを評価するのに必要な証拠は、これまでに良く知られているものです。つまり認証記録、プロセス実行、アプリケーションやディレクトリの変更、ファイルアクティビティやネットワーク通信です。AIはこれらの振る舞いの発生頻度を増大させます。防御者はこのような状況下でもそれらのシーケンスと影響を判断しなければならないのです。

担当:Emma Foulger、Sam Lister、Dylan Evans、Moishe Tajtelbaum

参考資料

[1] NCSC-NL, php2shell vulnerabilities (CVE-2026-109618, CVE-2026-109619), 21 October 2026. https://github.com/NCSC-NL/php2shell

[2] Imperva, https://www.imperva.com/blog/node2shell-from-brotli-data-to-remote-code-execution/

[3] Cyber Security Agency of Singapore, https://www.csa.gov.sg/alerts-and-advisories/alerts/al-2026-151/

[4] OpenAI, Daybreak: Tools for securing every organization in the world, 22 June 2026. https://openai.com/index/daybreak-securing-the-world/

[5] OpenAI Developers, Scaling cyber defenders with Daybreak, 21 August 2026. https://developers.openai.com/blog/scaling-cyber-defenders-with-daybreak

[6] OpenAI, Cloudflare links vulnerability discovery to defense with OpenAI, 21 October 2026. https://openai.com/index/cloudflare-cyber/

[7] Darktrace Signal Labs, Shared Memories as a Covert C2 Channel, draft research supplied for review.

[8] JPCERT/CC, Recent AI-Assisted Cyber Attacks in Japan: Investigating Attack Infrastructure and Techniques, 21 October 2026. https://blogs.jpcert.or.jp/en/2026/10/web_api_attacks.html

[9] Microsoft Security Research and Microsoft Threat Intelligence, AI-driven, large-scale nation-state campaign using ARTEX enables supply chain compromise, 21 October 2026. https://www.microsoft.com/en-us/security/blog/2026/10/21/storm-0940-uses-artex-agentic-ai-connectwise-supply-chain-compromise/

[10] Darktrace, Advancing the Use of Frontier AI in Cybersecurity: Darktrace Joins the OpenAI Daybreak Cyber Partner Program to Explore Defensive AI Integrations, 22 June 2026. https://www.darktrace.com/blog/advancing-the-use-of-frontier-ai-in-cybersecurity-darktrace-joins-the-openai-daybreak-cyber-partner-program-to-explore-defensive-ai-integrations

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Nathaniel Jones
SVP, Global Threat Intelligence

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October 23, 2026

Beyond the Fridge: Exposed Industrial Control Systems

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Introduction

In October 2026, hundreds of supermarkets across France were reportedly affected by a cyberattack targeting their refrigeration systems. According to public reports, the attackers gained access to internet-connected controllers and modified their settings, forcing refrigeration units into high and extremely low temperatures and causing significant disruption. Total losses have been reported to reach several million euros.

The incident drew attention to the security of industrial refrigeration systems, particularly older devices with exposed management interfaces and known vulnerabilities.

The exact details of how the attackers gained access have not been confirmed, however it is speculated that the public-facing web server could be accessed with the username “admin” and password being the current date. Researchers from Claroty’s Team82 identified a vulnerability in Danfoss AK-SM 8xxA Series in 2025, “CVE-2025-41450", allowing for administrative access using a time-based “code-of-the-day" for authentication [1].

Default credentials, outdated firmware and publicly accessible administrative interfaces have been an issue for years. And yet these systems continue to appear in internet scans and require little sophistication to gain admin access. A simple search of internet-connected devices shows a range of exposed devices from Programmable Logic Controllers (PLCs) and remote gateways, to, yes, more fridges.

Darktrace malware researchers identified hundreds of IoT and OT devices publicly exposed on the internet, many of which are configured with no authentication, weak credentials, or default credentials. As shown in Figure 1, an exposed Copeland XWEB web interface, used to manage Dixell equipment, including refrigerators, can provide the ability to remotely control connected devices.

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Figure 1: Copeland XWEB interface used to control systems including refrigerators and air conditioning.

However, it’s not only fridges; web management interfaces for industrial controls are also publicly accessible, often protected only by weak credentials. Figure 2 shows an example of a publicly exposed WAGO interface. The WAGO management interface is a configuration and administration panel for controllers. Through it, a logged-in user can view device details and diagnostics, manage user accounts and passwords, update firmware, back up or restore the full configuration, set the clock, and manage SD card storage. While it typically doesn’t manage switch outputs or read live process values, someone with access could still disrupt operation by changing network or Modbus settings, loading bad firmware or configurations, or by resetting passwords and enabling insecure services.

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Figure 2: WAGO Management interface.

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The issue extends beyond management interfaces. During our research, we identified publicly accessible web interfaces belonging to PLCs, including Rockwell Automation Allen-Bradley devices. In each case, the risk arises from how the devices have been deployed and configured, not from a flaw in the vendors’ products.

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Figure 3: Web interface for Allen-Bradley CompactLogix controller.

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Figure 3 shows the web interface of an Allen-Bradley CompactLogix controller. Unlike the previous examples, this interface provides a view into the controller's operation, including running tasks, network connections, memory usage and diagnostic information. Rockwell Automation's CompactLogix controllers are commonly used to automate industrial processes, from manufacturing and packaging lines to water treatment and material handling systems. Depending on their configuration, these controllers can operate motors, pumps, valves and other physical equipment.

Although in this example the interface shown does not provide direct control over the PLC's logic, it exposes information about the model, firmware, network layout, and connections, which is useful reconnaissance for a bigger attack.

The concern is not necessarily that every exposed interface allows an attacker to immediately manipulate industrial processes. However, these devices are accessible from the public internet in the first place, providing information about systems that may be responsible for controlling physical equipment.

The attacks on refrigeration systems in France highlight the consequences of poorly secured industrial devices. As demonstrated throughout this research, publicly accessible management interfaces are not limited to refrigeration controllers but extend to PLCs and other systems used to manage industrial equipment.

Finding these devices requires little effort. Internet scanners make it possible to identify publicly exposed interfaces quickly, and in some cases these interfaces rely on publicly documented default credentials or have no authentication at all. As attackers increasingly use AI tools, such attacks may be identified and carried out faster and at a greater scale.

The consequences of this access depend on the device and the functionality exposed. While some interfaces provide little more than diagnostic information, others allow users to modify configurations, disrupt communications, or change settings that affect physical equipment. In industrial environments, this can result in operational downtime, damaged equipment and financial losses.

Weak passwords, default credentials and exposed administrative interfaces are not new security issues. Yet their continued presence on internet-connected industrial systems demonstrates how easily preventable weaknesses can leave physical operations vulnerable to attack.

Exposed devices often come from third-party suppliers and contractors, who frequently install refrigeration controllers, gateways and PLCs without the organization ever being aware they are connected to the internet. Asset visibility remains an important foundation, but organizations should assume that some unknown assets and services will exist. Effective security therefore also depends on continuous monitoring, anomaly detection, network segmentation and rapid response, so that risky exposure and unusual activity can be identified and addressed before it becomes disruptive.

Darktrace helps security teams gain visibility across IT and OT and respond to risks: https://www.darktrace.com/products/operational-technology.

Copeland, Dixell, WAGO, Rockwell Automation, Allen-Bradley and CompactLogix are trademarks of their respective owners. Their use here is for identification only and does not imply any affiliation with or endorsement by those owners.

References

1.        https://claroty.com/team82/research/freeze-the-controller-defrost-the-food-uncovering-vulnerabilities-in-danfoss-refrigeration-controllers

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About the author
Tara Gould
Malware Research Lead
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