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クラウドの安全性はクラウドを理解することから始まる

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01
Nov 2023
01
Nov 2023
多くのクラウドセキュリティベンダーは「レスポンス」を提供すると称していますが、その本当の意味は何でしょうか。クラウド関連のサイバー脅威に対する意味のある「対応」とはどのようなもので、どのように実現されるのでしょうか。このブログでは、そのすべてを明らかにします。

クラウドの広範な利用がビジネスを変革し続ける一方で、サイバーセキュリティソリューションもそれに追いつこうと競争しています。今日のマルチクラウド環境は、複雑さと可視性のギャップをもたらし、攻撃者に門戸を開いています。クラウドは動的な性質を持っているため、これらの盲点は常に変化しています。また、クラウドの拡張性を考えると、ちょっとした設定ミスなどの単純なミスが、不釣り合いなほど大規模なセキュリティインシデントにつながる可能性もあります。

企業はもはや、バラバラのツールや静的でポイント・イン・タイムのリスクビューに頼る余裕はありません。クラウドは本質的に複雑であり、セキュリティツールはその複雑さを単純化することを目的とするのではなく、そのスケールと複雑さを利用することで、そのメリットを活かすべきです。

クラウドが高度にカスタマイズ可能で、クラウドごとに異なる世界では、クラウドセキュリティに対する画一的なアプローチでは、個々の環境のニュアンスに対応できません。このブログでは、独自の組織を機械学習・理解するAIを活用することで、セキュリティチームがクラウドにおけるセキュリティ確保に必要な可視性、理解、リアルタイムの検知と対応をどのように実現できるかを探ります。

セキュリティは行動にかかっている

一般的に、クラウドのセキュリティは2つの陣営のどちらかに分類される傾向があります:

  • ほとんどのクラウドセキュリティポスチャ管理(CSPM)ベンダーが採用しているエージェントレスのアプローチは、運用の中断を最小限に抑え、迅速かつ容易なインストールを約束する
  • エージェントベースのアプローチは、より細かい粒度を提供するが、セットアップに時間がかかり、コストがかかる可能性がある

どちらのアプローチにも固有の欠点があります。エージェントレスのソリューションは通常、悪意のあるインサイダーやゼロデイエクスプロイトなど、新たな脅威を検知するために必要なリアルタイムの認識をセキュリティチームに提供しません。一方、エージェントベースのソリューションでは、到達範囲と拡張性に限界があり、通常、セキュリティチームがすでにリスクがあることを知っているクラウドの領域に導入されるため、新たな洞察が得られず、死角がそのまま残ってしまいます。

そのため、今日のクラウドセキュリティはジレンマに陥っているようです。そして、どちらの方法にも共通するもう1つの問題は、これらの製品では、何か問題が発生したときにアナリストに警告を発することはできても、本格的な対応を行う能力がないということです。自動対処を謳う新しいソリューションでさえ、通常はアラートの送信やチケットの開設のプロセスを自動化することを指していることが多いのです。

迅速な対処は見果てぬ夢

組織にとってクラウドが非常に便利で魅力的なのは、スピード、敏捷性、可用性、スケールといった同じ属性が、攻撃者にとっても対称的に魅力的だからです。クラウド上でサイバー攻撃が急速に展開される場合、単にチケットを発行し、相手側の誰かが対応してくれるのを待つだけでは不十分です(むしろ、あまりに多くのチケットに対応することは、トリアージや調査をかえって停滞させ、対応を早めるどころか遅らせることになりかねません)。有用なレスポンスの最終的なテストは、セキュリティチームがそのレスポンス機能を使いたがるかどうかに帰着します。セキュリティチームが中断を恐れて、一向にオンにならないレスポンス機能は、まったく的外れなのです。

効果的な対処には、いつ、どのように対応すべきかを理解することと、対応を実行するためのクラウドネイティブなメカニズムが必要です。これは3つのステップに分けることができます:

ステップ1:可視性を超える:リアルタイム理解

今日の静的なクラウドセキュリティソリューションは、統合やインストールの前に環境のスナップショットを提供します。静的な洞察は、導入前のコントロールの検証と設定に役立ちますが、クラウド移行に関連する真のリスクは後から現れるのです。

適切な対処を推進するためには、セキュリティソリューションが、組織のクラウド環境について一般的な感覚ではなく、リアルタイムで全体的なビューを提供する必要があります。

クラウドに関連するリスクを理解するには、単に可視化するだけでは不十分です。環境全体の様々な行動パターンを理解し、アプリケーションやワークロードのアーキテクチャのニュアンスを知る必要があります。誰が何にアクセスできるのか?通常、どの仮想マシンが互いに接続しているのか?このコンテナは期待通りに動作しているか?この新しいLambda関数は期待通りか?などです。

Darktrace/Cloudは、自己学習型AIを使用して、クラウドネットワーク、アーキテクチャ、管理の各レイヤーでお客様独自の組織を学習し、理解します。膨大な量のデータからパターンを認識するAIの能力は、セキュリティチームにクラウド環境で今何が起きているのかについての真の洞察を与えるユニークな立場にあります。

AIの導入や具体的な使用方法は(個々の組織の環境に基づいて)それぞれ異なりますが、導入ライフサイクル全体を通じてセキュリティチームとDevOpsチームを連携させるクラウドフットプリントのアーキテクチャビューが常に含まれます。  

あるベータ版の顧客は、Darktrace/Cloudを導入した際の感想として、次のように述べています:

暗い部屋で電気のスイッチを入れるような感覚です。

ステップ2:検知はコンテキストを適用する必要がある

どのユーザーがどのリソースに接続しているのか、誰が特定のワークロードにアクセスできるのか、グループ、重複、権限など、クラウドにおける「正常」を正確に理解することで、ソリューションは、普通でないことを発見するよう自らに教え込むことで、対処に向けて前進します。

クラウドセキュリティ体制の静的なスナップショットでは、パッチが適用されていない脆弱性や問題のある誤設定が表示されますが、洞察はそこで終わってしまいます。静的なビューとポイントインタイムの可視性に基づくクラウドセキュリティソリューションでは、最終目標であるリアルタイムの脅威を発見する能力を提供するために、点と点をつなぐことはできません。

Darktrace/Cloudは、脆弱性や設定ミスに対する有意義な洞察を提供するだけでなく、そのリアルタイムの理解により、新たな脅威の検知も可能にします。また、Darktrace/Network や Darktrace/Email のような他の Darktrace モジュールと組み合わせることで、これらの調査結果をビジネスコンテキストで充実させ、新たな脅威を数秒で検知してシャットダウンします。それは、クラウドのフットプリントと、それがオンプレミスのインフラ、エンドポイント、アプリケーションとどのように相互作用するかを理解するためのビジネス全体のコンテキストです。

ステップ3:対処は真に自律的でなければならない

Darktrace/Cloudは、貴社独自のクラウドフットプリントを貴社ビジネスの文脈で理解することで、今すぐ対処が必要な異常事態が発生したことを独自に検知します。

お客様の環境を理解するためにAIを使用することで、真に自律的で正確なクラウドネイティブの対処が可能になります。プラットフォームは、通常の業務を中断することなく、脅威となる行動のみを停止させるため、ピンポイントかつ的を絞った行動を取ることができます。

プラットフォームはクラウドアーキテクチャを完全に理解しているため、どのようなクラウドネイティブのメカニズムが実際の対処を開始するために自由に使えるかも把握しています。自動化されたリアルタイムのレスポンスには、EC2インスタンスのデタッチや、リスクの高い資産を封じ込めるためのセキュリティグループの適用など、クラウドネイティブなアクションが含まれます。

実際に体験する

Darktrace は、Darktrace/Cloudの30日間無償トライアルを提供しています。このトライアルは、簡単なインストールとマルチクラウド環境に関するこれまでにない理解を組み合わせたものです。ご興味のある方はこちらをクリックしてご登録ください。

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
Nabil Zoldjalali
VP, Technology Innovation

Based in Toronto, Nabil develops innovative ways to continuously realize the Darktrace technology vision, working closely with Darktrace’s Research & Development team. He advises strategic Fortune 500 customers across North America on advanced threat detection, Self-Learning AI, and Autonomous Response. Nabil is a frequent speaker at leading industry conferences across North America, including Microsoft Ignite, Black Hat, and the World AI Forum. He holds a Bachelor’s degree in Electrical and Electronic Engineering from McGill University and is an advisory board member of the EC Council.

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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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