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1通のEメールが物流企業を悪夢に陥れる

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11
Aug 2021
11
Aug 2021
SaaSの利用拡大やグローバルな供給体制によって複雑化したサプライチェーンは、サイバーセキュリティが直面する最も緊急な懸念事項です。このブログでは、Darktrace が信頼できる第三者からのフィッシングメールを検知し、悪循環に陥った事例を検証しています。

組織は、その最も脆弱な部分がある限り、その他の部分が安全であるとは言えません。多くの場合、その弱点は、組織が依存するさまざまなクラウドアプリケーションに存在します。APT28を含むいくつかの有名なグループは、一般的に使用されているパスワードを悪用して、世界中の企業にブルートフォースで侵入することが知られています。これらの「スプレー」キャンペーンは、Microsoft Office 365のアカウントを標的とすることが多く、SaaSの利用が増加するにつれて、さらに頻度が高くなると思われます。

このブログでは、1通のフィッシングメールが、ゲートウェイやその他の従来のツールの目を潜り抜け、最終的にヨーロッパの物流会社で大規模な侵害を引き起こしたことを分析しています。

ロジスティクスの悪夢

物流オペレーターは、あらゆる産業分野で重要な役割を担っています。売り手から顧客までの商品やサービスの流通を管理することで、効率的なサプライチェーンを実現したり、ボトルネックになったりするのです。物流業者は、多くの組織と関わりを持ち、納期厳守のプレッシャーにさらされ、機密データを扱うことが多いため、必然的にサイバー犯罪者の格好のターゲットになっています。

攻撃者にとっては単純な方程式です。厳重に守られた20の組織に侵入するために労力を費やすのか、それともたった1つの組織を攻撃し、そこから20以上の組織すべてにアクセスするのか?今年、Darktrace が観測したサイバー脅威の大半は後者で、保護が手薄な第三者を悪用して、さまざまな企業への足がかりを得ようとするものでした。

特にワクチンの供給は、何度も攻撃にさらされています。昨年秋には、ドイツの生物医学組織に脅威者が侵入し、フィッシングキャンペーンを展開して認証情報を取得し、COVID-19コールドチェーンに関わる複数の組織を危険にさらしました。

ランサムウェアと並んで、フィッシング攻撃は業界が直面する最も緊急な懸念事項の1つです。

連鎖を断ち切る

ある中堅物流企業で、あるユーザーが乗っ取られた第三者から1通のフィッシングメールを受け取りました。そのメールは、メール送信履歴のある信頼できる送信元から送られてきたため、ゲートウェイを簡単に通過してしまいました。

フィッシングメールが受信箱に届くと、ユーザーは悪意のあるリンクをクリックし、偽のログインページに誘導され、そこで認証情報を漏えいさせられてしまうのです。

その4日後、攻撃者はいつもと違う場所からアカウントにログインし、機密情報を含むファイルの読み取りを開始したのです。

翌日、Darktraceは、別の異常な場所からの新しいEメールルールを検知しました。その直後、このアカウントから大量の送信メールが送信され、そのすべてに不審なリンクが含まれていました。

図1:攻撃のタイムライン - 総滞在時間は5日間

供給と破壊

一度組織のデジタルエコシステムの中に入ってしまえば、簡単に動き回り、より多くのアカウントを危険にさらすことができます。ほとんどのセキュリティツールや従業員は、信頼できるユーザーから送信された社内メール、特にそのユーザーが権限を持つ上級者である場合は、それを疑うことはありません。

そのため、この一連の送信メールの後、他の会社のアカウントで異常な場所からの異常なアクティビティが正規に確認されたのです。これらのユーザーは、同僚が送ったと思われるメールに騙され、自分の情報を渡してしまっていたのです。

さらに機密性の高い顧客ファイルが読み取られ、その後、乗っ取られたアカウントから送信されるEメールが急増しました。

今回は、社内ではなく、社外の連絡先にメールを送信していました。この連絡先は、当時、物流会社と取引をしていたため、そのアカウントからのメールを受け取ることに慣れていたようです。

合計で450通以上のフィッシングメールが、さまざまな第三者に送られました。このフィッシングメールは、さまざまな第三者に送られ、その多くが認証情報を流出させられ、また同じことが繰り返されました。

図2: Cyber AI Analyst は、侵入したユーザーの不審な行動を調査し、異常なログイン場所や実行されたアクションを含む詳細なサマリーを提供します

危機一髪:サードパーティ攻撃の脅威

この攻撃のきっかけとなった最初のフィッシングメールの送信元は、お客様が知っている正規の第三者であり、おそらく同じようなことが起こったのだと思われます。

このようなベンダーメールの不正使用は、何度も繰り返されることで悪循環に陥り、Eメールセキュリティソリューションでは発見が困難で、風評被害や経済的なダメージにつながる可能性があります。さらに問題を複雑にするのは、既知の送信者からの疑わしいEメールに対して対処しても、それが正当なものであると判明した場合、ビジネスに大きな支障をきたす可能性があることです。

このため、セキュリティは「良い」「悪い」という二元的なアプローチを超えて、あらゆるEメールのやり取りを取り巻くコンテキストをより総合的に理解する必要があります。

Darktrace は、同じドメインの送信者からの他のメールと比較することで、複数の異常を正確に検知しました。セキュリティチームに優先度の高いアラートを送信しましたが、検知モードのみだったため、受信箱にメールが届くのを防ぐことはできませんでした。

図3:Darktraceによる最初のフィッシングメールの自動要約では、メールの疑わしい点の概要を知ることができます。

この攻撃では、Piktochartと呼ばれるサードパーティツールが使用されており、インフォグラフィック、チャート、フォームなど様々なタイプのファイルを作成するように設計されています。Piktochartは、いくつかの正当な用途がある一方で、悪用される可能性もあります。そのため、ゲートウェイはPiktochartのリンクを正規のものと悪意のあるものとを区別するのに苦労しています。このケースでは、ゲートウェイは解析のために最初のリンクを書き直しましたが、悪意のあるリンクとは認識しませんでした。

これに対し、Darktrace/Emailは、その送信者の特徴から外れていること、またリンク自体が疑わしいことから、簡単に不審なメールであることを特定しました。アクティブモードでは、AIはリンクをロックし、メールを迷惑フォルダに移動させ、攻撃の最初のステップを効果的に防ぎ、それ以上の侵害を回避したことでしょう。

図4:Piktochartはこの時点まで展開上ほとんど見られず、ドメインは100%稀でした。Darktraceは、このサードパーティツールの使用の異常性を容易に検知することができました

バタフライ効果

ほとんどのサイバー攻撃は、たった1つの侵入口から始まります。フィッシングメール1つで、サプライチェーン全体を崩壊させることができるのです。サイバー攻撃の94%は受信トレイから始まり、サプライヤーやベンダーはMicrosoft TeamsやGoogle Cloudなど複数のSaaSプラットフォームで常にコミュニケーションを取っているため、メールセキュリティツールは信頼できる第三者の異常な行動を検知する能力が必要なのです。

特にリモートワークの増加に伴い、世界中の企業でSaaSの利用が急増し、多くの企業が柔軟な労働力を実現するためにクラウドやSaaSを利用することを余儀なくされています。明らかな利点がある一方で、これらの追加により攻撃対象が拡大し、従来のセキュリティや人的セキュリティチームの限界も伸びています。

グローバルなオペレーションで中間的な役割を果たすことが多い物流企業に関して言えば、クレデンシャルハーヴェスティングは、顧客だけでなく、顧客のメール連絡先にいる誰に対しても深刻な影響を与え、多数の人々や企業にとって大きな違反につながる可能性があるのです。

図5: Darktraceのユーザーインターフェースから、侵害された企業アカウントから送信された2つの送信メールのスパイクを確認できます

この脅威事例についての考察はDarktraceアナリストEmma Foulgerが協力しました。

物流事業者が直面する脅威の詳細をもっと知る

Darktraceによるモデル検知:

  • SaaS / Compliance / New Email Rule
  • SaaS / Unusual Login and New Email Rule
  • Antigena Email models included
  • Unusual / Unusual Login Location and New Unknown Link
  • Link / Account Hijack Link
  • Link / Outlook Hijack
  • Internal Compromise / Recipient Surge from Unusual Login Location (outbound emails)
  • Internal Compromise / Recipient Surge with Suspicious Content (outbound emails)

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.
AUTHOR
ABOUT ThE AUTHOR
Mariana Pereira
VP, Cyber Innovation

Mariana is the VP of Cyber Innovation at Darktrace, and works closely with the development, analyst, and marketing teams to advise technical and non-technical audiences on how best to augment cyber resilience, and how to implement AI technology as a means of defense. She speaks regularly at international events, with a specialism in presenting on sophisticated, AI-powered email attacks. She holds an MBA from the University of Chicago, and speaks several languages including French, Italian, and Portuguese.

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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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著者について
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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