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移り変わるEメール上のやり取り:Eメールセキュリティは過去から抜け出せない

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29
Mar 2023
29
Mar 2023
As attackers move from low sophistication, spray-and-pray campaigns to more targeted and sophisticated attacks, email security needs to understand the organization, not past attacks, to be able to keep up with attacker innovation and stop novel attacks on the first time of asking.

Eメールを主なターゲットとする脅威が拡大する中、ITチームは、十分なスピードで進化していない従来のEメールセキュリティの手法をはるかに超えることが必要です。過去の攻撃データに基づいて訓練されているため、以前に見たことのあるものしか検知できないのです。 

フィッシング攻撃は、攻撃者が配信戦術とソーシャルエンジニアリングという2つの重要な領域で革新を遂げるにつれて、より標的を絞り、洗練されてきています。マルウェアの配信面では、SharePointやOneDriveなどのサービスや、正規のメールアカウントなどの正規のインフラや評判を利用して、セキュリティツールを回避する攻撃者が増えてきています。

攻撃者は、Eメールの向こう側にいる人間から逃れるために、新しいソーシャルエンジニアリングの戦術を駆使し、これまでと同様に恐怖、不確実性、疑念(FUD)を悪用することで緊急性を喚起しています。

ChatGPTのようなツールの助けを借りて、脅威アクターはAI技術を活用し、信頼できる組織や連絡先になりすますことができます。具体的には、ビジネスメールの侵害、現実的なスピアフィッシング、スプーフィング、ソーシャルエンジニアリングなどの損害を与えることができます。実際、DarktraceはChatGPTのリリース以降、フィッシングメールの平均的な言語的複雑さが17%も跳ね上がったことを検知しています。

これは、攻撃の高度化が加速し、攻撃者の参入障壁が低くなり、攻撃結果が改善された一例です。これは、攻撃環境が、洗練度が低く、インパクトが小さい、一般的なフィッシング戦術(「スプレー&プレー」アプローチ)から、ルールやシグネチャに依存するあらゆるツールの典型的な検知範囲から外れる、より標的を絞った、洗練され、インパクトの大きい攻撃へと移行するという、より広いトレンドの一部を形成しています。攻撃者のツールキットに含まれる生成AIやその他のテクノロジーによって、こうした攻撃を大規模に行うことが可能になり、以前から見られていた既知の脅威を捕らえるだけでは、もはや十分ではなくなります。

図1:攻撃の進行とメールセキュリティツールの相対的な適用範囲の推移

Eメールを主なターゲットとする脅威が拡大する中、大半のEメールセキュリティツールは十分な進化を遂げていません。また、過去の攻撃データから次の攻撃を予測し、今日の攻撃を明日につなげるように設計されています。

組織ではAIシステムへの移行が進んでいますが、すべてのAIが同じというわけではなく、そのAIの応用が重要です。ITおよびセキュリティチームは、コンテキストを認識し、AIを活用して深い行動分析を行うメールセキュリティに移行する必要があります。これは、何千もの組織で、他のツールをすり抜ける攻撃を見事にキャッチしてきた、実績のあるアプローチです。また、今日のEメールセキュリティは、受信トレイを保護するだけではありません。悪意のあるメールだけでなく、メールメッセージやアカウントなど、ユーザーの全方位的な視点、さらにメールがコラボレーションツールやSaaSに侵入するような範囲にも対応する必要があるのです。多くの企業にとって、問題はメールセキュリティをアップグレードすべきかどうかではなく、いつアップグレードするか、つまり、過去にとらわれたメールセキュリティにいつまで頼ることができるのかということです。

メールセキュリティ業界はいたちごっこの世界

ゲートウェイやICES(Integrated Cloud Email Security)プロバイダーには、未来を予測するために過去の攻撃に目を向けるという共通点があります。これらのツールは、過去の脅威インテリジェンスや、すでに悪意があると判断されたメールの既知の悪い要素を集めた「拒否リスト」に頼ることが多く、現代の脅威状況の現実に対応できていないのです。これらのツールの中には、AIを使用してこの欠陥のあるアプローチを改善しようとするものもあり、直接一致するものを探すだけでなく、「データ拡張」を使用して類似したメールを見つけようとします。しかし、このアプローチでは、本質的に新しい脅威が見えないことに変わりはありません。

このようなツールは、リソースを過剰に必要とする傾向があり、常にポリシーを維持し、保持されている正当なメールを解放し、悪意のあるフィッシングメールを阻止するための手作業が必要となります。個々のEメールを手動で解除するこの負担は、通常、セキュリティチームに課せられますが、このチームは小規模で複数の担当領域を持つことが多いのです。解決策としては、悪質なメールを自律的に阻止 し、正規のメールを通過させ、組織の変化に適応するテクノロジー、つまり「セット&フォーゲット」という定義に実際に適合するテクノロジーを導入することです。

挙動と文脈を意識する  

業界では、「安全な」メールゲートウェイから、AIを活用したインテリジェントな思考への激変が進行中です。正しいアプローチは、エンドユーザーの行動を理解すること、つまり、各人が受信トレイをどのように使っているか、各ユーザーにとって何が「普通」であるかを理解することで、普通でないことを検知することです。また、いつ、どのように、誰と、どのようにコミュニケーションしているかというコンテキストを利用して、異常な点を発見し、何かおかしいと思ったら、その理由とともにユーザーに警告を発します。基本的には、(過去の攻撃ではなく)あなたを理解するためのシステムです。  

Darktrace は、過去のデータから危険なものを学習するのではなく、各組織とそのユーザーを深く継続的に理解することで、根本的に異なるアプローチのAIを開発しました。各従業員の通常の日々の行動を複雑に理解してこそ、メールが実際にその受信者の受信箱に属するかどうかを正確に判断することができるのです。 

フィッシング、ランサムウェア、請求書詐欺、役員なりすまし、あるいはもっと斬新な手法であっても、行動分析にAIを活用することでより迅速な意思決定が可能になります。悪質な脅威を初見で阻止できるため、新しい攻撃を封じるためにゼロ号患者を待つ必要がありません。検知の信頼性が高まることで、より的確な対応、つまり、警戒心から広範な包括的対応を行うのではなく、メールの最も危険な部分のみを削除する標的型対応を行うことができ、ビジネスの混乱を最小限に抑えながらリスクを低減することができます。

攻撃スペクトルに話を戻すと、マルウェアの配布や被害者の誘導に、斬新な、あるいは一見正当なインフラを使用する高度に洗練された攻撃への移行がますます進んでおり、こうしたインパクトの強い標的型攻撃を検知して適切な対応を行うことがかつてなく重要になってきています。 


図2:Darktrace をネイティブのEメールセキュリティと組み合わせることで、あらゆる攻撃をカバー可能

お客様を理解し、エンドユーザーを全方位で見渡す  

現代のEメールセキュリティは、受信箱だけに限定されるものではなく、Eメールやそれ以外の場所でのユーザーの通常の行動を完全に理解する必要があることを私たちは知っています。従来のEメールツールは、侵入のポイントとしてインバウンドメールにのみ焦点を当てており、アカウントが侵害された後、Eメール攻撃の成功によって引き起こされる潜在的に壊滅的なダメージから保護することができません。    

図3:ユーザーを360° 理解することで、Microsoft以外のデジタルタッチポイントが見えてくる


Microsoft 365、Google Workspace、Salesforce、Dropbox、そしてネットワーク上のデバイスでのユーザーの行動を把握することは、そのユーザーにとって何が正常であるかを完全に把握するために極めて重要です。デバイス(および受信箱)の感染症状を監視することは、悪意のあるメールかどうかを判断し、今後同様のメールを送信しないようにする必要があるかどうかを判断するために非常に重要です。クラウドアプリのデータと組み合わせることで、IDベースの攻撃をより全体的に把握することができます。

また、メールセキュリティと攻撃対象の外部データを結びつけることで、悪意のあるドメインをプロアクティブに発見し、攻撃が開始される前に防御を強化することができます。

従業員への教育および啓蒙活動

最終的に、Eメールに接するのは従業員です。このようなユーザーをうまく活用することができれば、よりスマートな従業員、より少ない攻撃回数、そしてより戦略的な業務に時間を割くことができるセキュリティチームを手に入れることができるのです。 

最も成功するツールは、AIを活用して従業員のセキュリティ意識を向上させることができるものでしょう。明らかに悪意があり、従業員の受信トレイに決して入ってはいけないメールもありますが、潜在的に危険な要素を持つメールには、かなりのグレーゾーンが存在します。大半のセキュリティツールは、これらのメールを、たとえビジネスクリティカルなものであったとしても、完全に受信を拒否するか、あるいは無傷で通過させるかのどちらかです。しかし、このようなグレーゾーンのメールが、実はトレーニングの機会として活用できるとしたらどうでしょうか。    

フィッシングシミュレーションベンダーとは対照的に、行動AIは、ユーザーの受信トレイを通じて軽いタッチでトレーニングを行うことで、組織全体のセキュリティ意識を総合的に向上させることができ、エンドユーザーを防御強化の輪に引き込むことができます。  

メールセキュリティの新境地は、AIとAIとの戦いであり、遅れをとった組織は、つらい思いをすることになるかもしれません。これらのテクノロジーは、従業員の体験をどのように変え、展開をダイナミックにし、セキュリティチームを増強し、統合された防御ループの一部を形成することができるかについて、Darktraceのブログシリーズをお読みください。    

[1] 複数のアクティブなフィッシングペイロードに対するDarktrace/Emailのレスポンスと、他のメールセキュリティ技術が提示した16の独立したフィードのうち最も早いものとの間に生じた検知期間の差の平均

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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