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AIを活用したEメールソリューションがセキュリティチームをレベルアップする方法

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02
Apr 2023
02
Apr 2023
このブログでは、Eメールベースの攻撃から組織を保護するためにセキュリティチームが直面する課題を概説します。最新のAIベースのセキュリティソリューションが、標的型の自律行動、ストレスのないUI、最適化されたワークフロー、アカウントユーザーの完全な可視化によって、これらのペインポイントにどのように対処できるかを探ります。

現代のセキュリティチームは、あらゆる面で課題に直面しています。増大する攻撃対象への対応、安全なリモートワークのためのワークフォースの有効化、そのワークフォースを保護するための複数のセキュリティツールの管理などに追われることがあまりにも多いのです。さらに、AIツールによってサポートされるようになった、より洗練されたフィッシングキャンペーンが急増したことで、攻撃を先制することがこれまで以上に難しくなっています。 

Eメールセキュリティソリューションを導入する際には、セキュリティチームのニーズを考慮する必要があります。信頼性の高い検知・対処テクノロジーと直感的なレポート、最適化されたワークフローを組み合わせることで、ユーザーインターフェースに費やす時間を最小限に抑えることは、ベンダーにとって、チームの価値を保証するための最重要事項であるはずです。

セキュリティチームを最前線から引き離す 

従来のメールセキュリティソリューションでは、メールセキュリティポリシーを維持したり、公開すべきでないメールを公開したり、公開すべきメールを保留したりすることに、すべての時間を費やしていたのではありません。管理者の1日に、メールセキュリティダッシュボードに何十分も、何百分も費やすことはないはずです。 

現在、チームはあまりにも頻繁にログインしており、その際、ドメインの安全なリストアップやブロック、Eメールの公開など、個別の判断を迫られています。このような場合、包括的なルールが作成され、攻撃者に将来の窓を開くことになり、意図しない結果で将来の仕事が増えることになりかねません。このような一騎打ちは、セキュリティチームを最前線に立たせ、本来なら人間が得意とする高度な戦略的業務に時間を割くべきところを、そのような状況に追い込んでしまいます。  

自社を理解する:Eメールセキュリティの異なるアプローチ

今日のEメールセキュリティに関する議論では、ゲートウェイに依存することはもはや実現不可能であるというコンセンサスが得られています。新しい時代は、人工知能やAPIを活用したICES(統合クラウドメールセキュリティ)ソリューションやその他のツールの時代です。しかし、古い理念のまま新しいテクノロジーを採用しても意味がありません。これらのソリューションのほとんどは、AIを使って、過去の攻撃を見て次の攻撃を阻止しようとするという、従来と同じアプローチを自動化しているに過ぎないのです。 

そこで、Darktrace/Emailでは、根本的に異なる独自のアプローチをとっています。単にAIを使うのではなく、適切な容量で使うことが重要なのです。私たちのAIは、ユーザーがどこからログインし、誰にEメールを送り、一日中どのような行動をとっているかを学習し、個々のプロファイルに応じて検知・対処プロセスを調整します。Darktrace/Emailは、脅威を無効化するために必要な最小限のアクションを実行します。一律に許可・不許可を決めるのではなく、ユーザーの普段の受信行動を把握した上で、リンクを書き換えたり、添付ファイルを保留したりします。悪意のあるEメールを阻止し、リスクのある要素を排除した正規のEメールを通過させることで、セキュリティチームは前述の不毛な消火活動から解放され、より戦略的で価値のある意思決定に時間を割くことができるようになります。

これは、私の現在のEメールセキュリティスタックを減らすことにつながります。私が必要とするレベルまで使い続けるでしょう。

Darktrace/Emailのアーリーアダプター 

Account Takeover 

アカウント乗っ取り防止機能の組み込みは、最新のEメールセキュリティにとって不可欠な要素です。セキュリティチームが必要としているのは、Eメール侵害だけでなく、攻撃者が受信トレイをコントロールした後に何が起こるのか、特にビジネスメール侵害(BEC)やランサムウェアのような最も有害なユースケースにおいての可視化です。これには、受信トレイ、送信メール、さらに幅広いアカウントのアクティビティにおけるユーザーの行動を理解することが必要です。Darktrace がEメールとMicrosoftまたはGoogleアカウントにわたるユーザーのアクティビティを一元的にキャプチャし、侵害されたアカウントを示す可能性のあるすべてのマーカーを検知して対策します。  

Darktrace から得られる他のクラウドアプリケーションやネットワーク機器からのインサイトにより、ユーザーを360° 理解することができ、アカウントの乗っ取りやその他の有害行為の検知をさらに強化することができます。

図1:ユーザーを360°理解することで、マイクロソフト以外のデジタルタッチポイントが見えてくる

「ユーザーフレンドリー」とは、実際にはどのようなものか 

最高のユーザーインターフェイスとは、ログインする必要がないものです。理想的な世界では、インテリジェントなAIがこれまで人間が行っていた作業を自動化するため、チームがツールにアクセスする頻度が少なくなります。これは、Darktraceの精密な検知と遮断技術によって実現され、Eメールやアカウントに対して適切なアクションを取り、日常業務を中断させることなく脅威を無力化します。 

2番目に優れたユーザーインターフェースは、素早くログインして、実行したアクションやユーザーの現在の活動など、重要な洞察を素早く得ることができ、その後、外に出ることができるものです。Darktrace/Emailでは、高いレベルでも細かいレベルでも、チームが重要な情報を素早く得ることができます。 ダッシュボードでは、ユーザーやEメールに関する洞察を即座に得ることができ、アクティブなユーザーID、ターゲットユーザー、アクションを起こしたEメールのリアルタイムなスナップショットを、攻撃の種類ごとに区分して表示します。 

Darktrace は、あらゆるタッチポイントにおいて、最適化されたワークフローにより摩擦を軽減します。VIPの迅速な特定からリンクや添付ファイルの安全なプレビューまで、セキュリティチームはウィンドウを切り替えたり、アクセスしにくいインターフェースを操作したりすることなく、必要な情報を入手することができます。説明可能なAIは、個々のEメールやEメール環境全体の健全性を自然な言葉で要約し、シンプルなアクションフローにより、セキュリティチームは、例えば、VIPに独自の通知を送ったり、会計に携わる従業員に特別な注意を払うなど、従業員ごとにセキュリティをパーソナライズすることができます。このように、管理者はポリシーの管理に費やす時間をさらに短縮することができるのです。 

図2:Darktrace/Email ダッシュボードでEメール環境の主要情報を1枚の画面に表示

理想的なインターフェースは、最も利用しやすいものでもあります。モバイルアプリは、セキュリティチームの利便性を保証し、時間や場所を問わず、外出先で分析できるインターフェースの主要機能をすべて利用できるようにします。チームは、重要なインシデントが発生した場合、デスクに戻らなくてもデータを即座に可視化し、対策を講じることができるという安心感を保ちながら、出張や退社をすることができます。  

図3:セキュリティ管理者は、Darktraceモバイルアプリから直接Eメールをプレビュー、分析、対処することができる

日を追うごとに、セキュリティチームは安心できるようになります。すべてのアクティビティが考慮され、AIが時間をかけてチューニングし、適応することで、脅威の検知と対処はさらに優れたものになります。   

アプリでEメールを使えるようになることは、ゲームチェンジにつながります。 

Darktrace/Emailのアーリーアダプター 

全体像の把握

多くの場合、Eメールは、脅威アクターが情報および資産を収集するために組織内を密かに移動する際の入口となります。ほとんどのソリューションは、Eメールを単独で見ており、異なる事象に優先順位をつけたり、より広いパターンにつなげたりはしていません。 

一方、Darktrace/Emailは、Darktrace のCyber AI Analystとシームレスに統合されています。このテクノロジーは、Darktrace のプラットフォームが生成するすべてのアラートを対象に、企業全体の調査を自律的に実施するものです。この統合により、悪意のあるEメールのアクティビティは、それが属するセキュリティインシデント全体のコンテキストで分析・表示されます。その結果、セキュリティチームは、Eメールに端を発し、他のアプリやエンドポイントより広い企業ネットワークに広がった可能性がある問題の理由や原因を確認することができます。

従業員をセキュリティに積極的に参加させる

従業員がセキュリティに無関心であったり、甘かったりすると、セキュリティチームの役割はより困難なものになりかねません。特に、フィッシング詐欺のシミュレーションがあまり効果的でないことが証明されているため、セキュリティ手順に関する従業員のトレーニングも、繁忙期には後回しにされがちな課題です。 

このため、Darktrace/Emailは、XAI(説明可能なAI)を使用して、Eメールについてどう思ったかを自然言語で説明し、その結果をセキュリティチームだけでなく、オプションでより多くの従業員にも提供します。Eメール内のコンテキストバナー、定期的なダイジェスト、またはOutlookで直接配信されるこれらのインサイトは、セキュリティ教育を四半期または年1回の演習からリアルタイムのセキュリティ意識に変えます。次回のブログでは、従業員エンゲージメントがセキュリティチームの取り組みを支援し、組織全体の防御を強化する方法について詳しく説明します。 

Darktrace は根本的に異なるアプローチで構築されているため、斬新で標的型の高度な攻撃を阻止するだけでなく、正規のEメールを通過させることができます。このため、セキュリティチームが行っていた作業をAIが代行する、まさに全自動の技術となっています。 

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
Dan Fein
VP, Product

Based in New York, Dan joined Darktrace’s technical team in 2015, helping customers quickly achieve a complete and granular understanding of Darktrace’s product suite. Dan has a particular focus on Darktrace/Email, ensuring that it is effectively deployed in complex digital environments, and works closely with the development, marketing, sales, and technical teams. Dan holds a Bachelor’s degree in Computer Science from New York University.

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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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