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Inside the SOC

Breakdown of a multi-account compromise within Office 365

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25
2022年5月
25
2022年5月
このブログでは、社内のフィッシングキャンペーンによってアカウントが急速に危険にさらされる可能性があることを詳しく説明します。また、Darktrace/Appsが今後この種の攻撃を阻止するために取ることができるアクションを紹介しています。

2022年2月、Darktraceは顧客のOffice 365環境における3つのSaaSアカウントの侵害を検知しました。このインシデントは、Darktrace/AppsとDarktrace/Emailがどのように連携して、異常なログイン、アプリの権限変更、新しいEメールルール、および送信スパムに警告を発することができるかを強調するための効果的なユースケースを提供します。また、Darktrace RESPOND/Appsが自律モードに設定されていれば、さらなる侵害を阻止できたかもしれなかった事例をお伝えします。

Account Compromise Timeline

February 9 2022

アカウントAは、一般的にSaaSアカウント攻撃と関連しているBAV2ROPCユーザーエージェントで、ナイジェリアからの稀なIPからログインされました。BAV2ROPCは「Basic Authentication Version 2 Resource Owner Password Credential」の略で、iOS Mailなどの古いEメールアプリで一般的に使用されています。BAV2ROPCは、アカウントが「レガシー認証」を有効にしているSaaS/メールアカウントの侵害でよく見られます。これは、多要素認証(MFA)が有効になっていても、IMAP/POP3のようなレガシーなプロトコルはMFA用に設定されていないため、MFA通知が送信されないためです。

その後、アカウントAはシングルフルストップと名付けられた新たなEメールルールを作成しました。攻撃者は一般的に、自分が所有する外部のメールアカウントに特定のメールを転送する機能を使用して、自分自身に永続的なアクセスを与えるために新たなメールルールを作成します。つまり、そのアカウントのパスワードが変更されたり、MFAがオンになったりしても、そのルールが適用されている限り、攻撃者は転送されたメールを受け取り続けることになります。このケースでは、攻撃者は以下のフィールドと機能を使用して新しいEメールルールを構成しました:

  • AlwaysDeleteOutlookRulesBlob - Outlook on the WebまたはPowershellを使用して受信トレイルールを編集する際の警告メッセージを非表示にします。これは、攻撃者が実行するコマンドのリストが決まっており、確認メッセージをクリックすることでアカウントの搾取に時間がかかることを避けたかったためと考えられます。
  • Force - 警告または確認メッセージを非表示にします。
  • MoveToFolder - Eメールをフォルダに移動します。これは、アカウントが攻撃者によってメール送信に使用されているという事実を隠すために、バウンスされたメールを受信トレイから遠ざけるためによく使用されます。
  • 名前 - ルールの名前を指定します。この場合、シングルフルストップです。
  • SubjectOrBodyContainsWords - キーワードを含むEメールがアクションされます。
  • StopProcessingRules - このルールの条件が満たされた場合、後続のルールが処理されるかどうかを決定します。この場合、攻撃者はこれを false に設定し、疑惑を持たれないように後続のルールが処理されるようにしたと思われます。

その後、アカウントAがメール管理アプリ「Spike」に許可を与えていることが確認されました。これは、侵害されたアカウントの迅速な自動搾取を可能にするためと思われます。攻撃者は、アカウントの侵害から悪意のある使用までの時間を短縮するため、このプロセスを高速化し、セキュリティチームが対応する時間を短縮したいと考えています。

図1:メール管理アプリケーション「Spike」への同意と新しい受信トレイルールの作成を時系列で示したSaaSコンソールのスクリーンショット

その後、このアカウントは15分間に794通のメールを社内外の受信者に送信していることが確認されました。これらのメールには、同じ件名や関連するフィッシングリンクなど、類似した性質がありました。この大量のスパムは、攻撃者が最短時間内にできるだけ多くのアカウントと認証情報を侵害したかったためと思われます。メールで送信されたリンクのドメインはspikenow[.]comで、「共有リンクを表示」というテキストで隠されていました。これは、攻撃者がメールの送信とフィッシングリンクのホスティングにSpikeを使用したことを示唆しています。

図2:漏えいしたアカウントからの送信メッセージの急増を示すAGE UIのスクリーンショット。(メッセージはすべて同じフォーマットであるように見える)
図3:Darktrace/Email におけるリンクとリンクをマスクしたテキストのスクリーンショット:'共有ファイルを見る'

アカウントAからこの大量の送信メールが送信されてから15分以内に、ナイジェリアにある同じ稀なIPからアカウントBにアクセスされました。アカウントBはまた、シングルフルストップという名前の新しいEメールルールを作成しました。これまでのルールに加えて、以下のルールが観測されました:

  • From - 特定のアドレスからのEメールがこのルールで処理されることを指定します。
  • MarkAsRead - メールを既読としてマークすることを指定します。

フィッシングメールの送信とアカウントBの異常な挙動との間の時間枠が短いため、アカウントBが最初のフィッシング被害者であった可能性があります。

図4:SaaSコンソールのスクリーンショット。アカウントBのログインに失敗した後、稀なナイジェリアのIPからのログインと受信トレイのルール作成に成功したことを示す。

2022年2月10日

翌日、3つ目のアカウント(アカウントC)も同じく稀なIPからアクセスされました。これは2回発生し、1回はユーザーエージェントMozilla/5.0、もう1回はBAV2ROPCでした。13:08にBAV2ROPCでログインした後、このアカウントはメール管理アプリSpikeにアカウントAと同じ権限を与えました。その後、同じメールルールと思われるものが作成され、名前はシングルフルストップでした。アカウントBと同様に、このアカウントはアカウントAから送信されたフィッシングメールの1つによって侵害された可能性があります。

図5:Darktrace/Appsのアクションを伴った主要インシデントのタイムライン

脅威アクターの動機は不明ですが、これは以下の結果を招いた可能性があります:

  • 将来、組織に対して使用するため、またはサードパーティに売却するためのクレデンシャルハーベスティング。
  • 専門的なウェブサイト(LinkedIn、Indeed)において侵害されたユーザーになりすまし、さらに企業アカウントをフィッシングした可能性:
  • LinkedInで1人のユーザーの偽アカウントが発見された。
  • この同じユーザーがIndeedに登録するEメールが、侵害の際に確認された。

攻撃は他のセキュリティスタックをどのようにすり抜けたか?

  • Office 365の認証情報が侵害され、ユーザーエージェントBAV2ROPCが使用されていたため、MFAでは不審なログインを阻止することができませんでした。
  • RESPONDは人間による確認を求める設定(Human Confirmation Mode)であったため、自律的なアクションを取ったことは確認できず、自律検知されたものだけが表示されました。アカウントAを無効にすれば、フィッシングメールとそれに続くアカウントBとCの侵害を防げた可能性は高かったでしょう。
  • この組織は、DarktraceのProactive Threat Notification および Ask The Expertの各サービスに登録していなかったため、Darktrace SOC アナリストによるさらなるトリアージが可能であったはずです。

Cyber AI Analyst Investigates

DarktraceのCyber AI Analystは、人間を遥かに凌駕するスピードとスケールで調査を自動化し、関連するインシデントに即座に優先順位を付け、実用的なインサイトを自動作成することで、セキュリティチームが脅威を迅速に理解し、対処できるようにします。

In this case, AI Analyst automatically investigated all three account compromises, saving time for the customer’s security team and allowing them to quickly investigate the incident themselves in more detail. The technology also highlighted some of the viewed files by the compromised accounts which was not immediately obvious from the model breaches alone.

図6:AI AnalystによるアカウントAのスクリーンショット
図7:AI AnalystによるアカウントBのスクリーンショット
図8:AI AnalystによるアカウントCのスクリーンショット

Darktrace RESPOND (Antigena) actions

問題の組織では、アクティブモードでRESPOND/Appsが設定されていなかったため、このケースでは何の対策も取ることができませんでした。下の表は、RESPOND が取ったであろう重要な防御アクションを示しています。

それにもかかわらず、自律遮断技術が有効になっていれば、RESPOND がいつ、どのようなアクションを取ったかを知ることができるのです。

上の表は、RESPONDが有効になっていれば、インシデントが発生している間、3名のユーザーすべてが無効になっていたことを示しています。ハイライトされた行は、内部フィッシングメールが送信されたときにアカウントAが無効化され、その後、侵害されたEメールアカウント(BとC)の連鎖を防げた可能性があることを示しています。

結論

SaaSアカウントは、企業の攻撃対象領域を大きく拡大します。侵害されたアカウントの悪用が迅速に行われるだけでなく、1つの侵害されたアカウントが社内のフィッシングキャンペーンを経由してさらなる侵害につながることもあります。このことは、既存のITチームを補完し、侵害の時点で脅威を軽減する自律的かつプロアクティブなセキュリティの継続的な必要性を補強しています。すべてのアカウントの「レガシー認証」を無効にし、MFAを提供することである程度の保護が得られますが、Darktrace/Appsはそれ以上の感染をすべてブロックする能力を備えています。

Credit to: Adam Stevens and Anthony Wong for their contributions.

付録

Darktraceによるモデル検知の一覧

ユーザーA - 2022年2月9日

  • 04:55:51 UTC | SaaS / Access / Suspicious Login User-Agent
  • 04:55:51 UTC | SaaS / Access / Unusual External Source for SaaS Credential Use
  • 04:55:52 UTC | Antigena / SaaS / Antigena Suspicious SaaS and Email Activity Block
  • 04:55:52 UTC | Antigena / SaaS / Antigena Suspicious SaaS Activity Block
  • 14:16:48 UTC | SaaS / Compliance / New Email Rule
  • 14:16:48 UTC | SaaS / Compromise / Unusual Login and New Email Rule
  • 14:16:49 UTC | Antigena / SaaS / Antigena Significant Compliance Activity Block
  • 14:16:49 UTC | Antigena / SaaS / Antigena Suspicious SaaS Activity Block
  • 14:45:06 UTC | IaaS / Admin / Azure Application Administration Activities
  • 14:45:07 UTC | SaaS / Admin / OAuth Permission Grant
  • 14:45:07 UTC | Device / Multiple Model Breaches
  • 14:45:08 UTC | SaaS / Compliance / Multiple Unusual SaaS Activities
  • 15:03:25 UTC | SaaS / Email Nexus / Possible Outbound Email Spam
  • 15:03:25 UTC | SaaS / Compromise / Unusual Login and Outbound Email Spam

ユーザーB - 2022年2月9日

  • 15:18:21 UTC | SaaS / Compromise / Unusual Login and New Email Rule
  • 15:18:21 UTC | SaaS / Compromise / Unusual Login and New Email Rule
  • 15:18:22 UTC | Antigena / SaaS / Antigena Significant Compliance Activity Block
  • 15:18:22 UTC | Antigena / SaaS / Antigena Suspicious SaaS Activity Block

ユーザーC - 2022年2月10日

  • 14:25:20 UTC | SaaS / Admin / OAuth Permission Grant
  • 14:38:09 UTC | SaaS / Compliance / New Email Rule
  • 14:38:09 UTC | SaaS / Compromise / Unusual Login and New Email Rule
  • 14:38:10 UTC | Antigena / SaaS / Antigena Significant Compliance Activity Block
  • 14:38:10 UTC | Antigena / SaaS / Antigena Suspicious SaaS Activity Block

Refrences

1.https://www.ncsc.gov.uk/guidance/phishing#section_3

2.https://www.bleepingcomputer.com/news/security/microsoft-scammers-bypass-office-365-mfa-in-bec-attacks/

3.https://customerportal.darktrace.com/product-guides/main/antigena-saas-inhibitors

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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Laura Leyland
Cyber Analyst
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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

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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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