Blog

Ransomware

REvilのRansomware-as-a-Service(RaaS)ビジネスモデルに対する備え

Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
13
Feb 2022
13
Feb 2022
This blog assesses the impact of the recent arrests associated with cyber-criminal group REvil in the wider context of the Ransomware-as-a-Service business model, exploring a real-world REvil ransomware campaign discovered by Darktrace’s AI.

REvil(Sodinokibiとしても知られています)は、過去最大のランサムウェア攻撃の1つを実行したRansomware-as-a-Service (RaaS) ギャングです。2022年1月14日、この犯罪集団の構成員14名を逮捕したとロシアが発表 しました。これは、国際的強力によりREvil撲滅に力を注いだ米国当局の求めに応じたものでした。昨年、大きな話題となった複数の攻撃がREvil グループによるものとされており、これにはJBSランサムウェアおよび Kaseya サプライチェーンインシデントも含まれています。

REvil 構成員の逮捕は西側の法執行機関にとって勝利であることは確かであり、昨年11月には欧州刑事警察機構がREvil関連グループに対して数か月間に7件の逮捕を行ったと発表しています。問題は、これらの逮捕がREvilのオペレーションをどの程度まで、またどのくらいの期間、中断させることができるのか、ということです。

ReversingLabs研究所の 調査が示す早期の兆候によれば、REvilの活動にこれまでのところ影響は出ていません。ロシアによる逮捕から2週間後のREvilインプラントが示す統計情報に変化はなく、むしろ穏やかな増加が見られるほどです。

アクティビティの継続は次のシナリオのいずれかを意味しています:

  • 一連の逮捕は犯罪集団のヒエラルキーの中の中間層にしか影響していない
  • REvilのRaaSモデルは法執行機関による妨害に耐える十分なレジリエンスを有している

ランサムウェアギャングの襲撃に遭うかもしれない人達にとってはどちらも心配なシナリオであり、現実はこれらに加えてその他の要素が複雑に混じり合ったものとなるでしょう。ランサムウェアの撲滅は長年の懸案ですが、この戦いは長くなることが予想されます。法執行機関に必要なのは、ランサムウェアビジネスを手がけることがもはや利益を生む、あるいは有利なことではなくなるほどに、ビジネスモデルを破壊することです。そしてこれには何か月も、あるいは何年もかかるでしょう。

さて、ランサムウェアの撲滅活動が大きな舞台で展開されつつあるなか、最近の出来事から、セキュリティチームにとって少しでも安心できる材料はないでしょうか?

進化するRaaSモデルにAIで対抗

FBI、CISA、NCSC、ACSC、NSA が最近共同で発表したランサムウェアについての報告書では、昨年の主要な傾向が解説されています:

  • RaaSはビジネスモデルおよびプロセスが十分に確立され、ますますプロフェッショナル度が高まっています。
  • 開発者、アフィリエイト、フリーランスなどで構成される複雑なネットワークの存在により、このモデルはアトリビューションを複雑にしています。
  • ランサムウェアグループは標的についての情報を相互に共有し、被害組織に対する脅威を多様化させています。

まとめると、この報告書では、ランサムウェアギャングが法執行機関の追跡を回避し身代金の支払いを最大化するために、ますます適応性を高めているということが解説されています。複数のグループが消滅し、あるいは解散しましたが、結局は別の名前と若干更新されたプレイブックとともに再出現しています。戦術、テクニック、手順(TTP)は被害を受けた組織によってさまざまですが、それは主にこれらの攻撃が異なるランサムウェアグループやアフィリエイトによって実行されていることによります。

これらの攻撃の背後にいる者たちを摘発しようとしている法執行機関にとって、これはやっかいです。REvil のようなRaaSグループを構成する関係者のネットワークは決まった形を持たず常に変化しているため、個別に逮捕してもいたちごっこの連続となり、グループ全体を壊滅させることにはならないでしょう。

それぞれの攻撃事例においても同様の戦いが展開しています。以前に遭遇した脅威の特徴に的を絞ったセキュリティツールも、いつまで経っても彼らに追いつけません。1つの攻撃が検知され、特徴が記録され、次回に備えて保存されるころには、攻撃者とそのテクニックはその先に進んでいます。

しかし防御側には別の選択肢もあります。ますます多くのセキュリティチームが、攻撃者に対抗するために自己学習型AIを取り入れているのです。自己学習型AIはその周囲環境を学習し、攻撃の兆候であるかすかな変化を識別することにより、新種の攻撃に対しても初回遭遇時に検知し対処することができます。以下に、REvil によって実行された攻撃を、自己学習型AIがルールやシグネチャを使用することなくどのように検知したかを示す実例を紹介します。

REvil脅威検知結果

2021年夏、REvil のアフィリエイトがある医療および介護業界の組織に攻撃を仕掛けました。このセクターは、世界的なパンデミックが発生して以来サイバー攻撃が大幅に増加しています。この攻撃はルールやシグネチャを使うことなくDarktraceのAIによって検知されましたが、セキュリティチームはその当時、Darktraceを監視していませんでした。的を絞ったアクションにより脅威を封じ込めることのできたAutonomous Responseが適用されていなかったため、この攻撃は進行してしまいました。

1人のリモートワーカーのラップトップPCからネットワークにアクセスした攻撃者は、正当なRDP(Remote Desktop)接続を悪用してこの企業のジャンプサーバーに移動し、ブルートフォースで認証情報を抽出しました。

多数の認証情報を入手した攻撃者は、RDPを使って2台目のジャンプサーバーを含む複数の内部デバイスに接続しました。最初に侵入されたサーバーから、RDPポート3389番を使ってデータ抜き出しが開始されました。

2週間後、攻撃者は3台目のサーバーに格納されていたこの組織の重要情報を特定し、C2(コマンド&コントロール)通信の開始を試みました。このサーバーは多数の不審な外部接続を行い、これにはREvilが以前行ったKaseya ランサムウェア攻撃と関係したアクティビティのパターンに似た、未知のドメインへの接続試行が含まれていました。

リモートユーザーのデバイス上で実行されていた Darktrace for Endpointがこれらに対する可視性を提供し、セキュリティチームは最初に侵入されたユーザーのデバイスを特定することができました。もしこのエンドポイント上でAntigenaが適用されていれば、普段と異なる特定の接続をブロックすることでこの不審なアクティビティを中断させ、通常の業務に影響を与えることなく攻撃を封じ込めることができたでしょう。

ローアンドスロー攻撃の点と点を結ぶ

この攻撃者の合計滞留時間は22日間でした。彼らは忍耐強く、多くの場合数日の間隔を空けて、まとまったアクティビティでアクションを実行していました。この行動パターンはランサムウェア攻撃では珍しくなく、特にRaaSモデルを使ったものでは、各ステップを別のメンバーやアフィリエイトが実行する場合もあるためです。

DarktraceのCyber AI Analystは数週間に渡る攻撃ライフサイクルのすべてをリアルタイムに追跡し、攻撃の各フェーズをつなぎ合わせてセキュリティインシデント全体を構成しました。

図1:Cyber AI Analystが攻撃キルチェーン全体を明らかに

新しい名前、同じ手口

この攻撃も、攻撃者達がLiving off the Land (環境に寄生する)手法を使っている一例です。これは環境内で既に使われていた正当なプログラムやプロセスを使って悪意あるアクティビティを実行する手法です。これらを、静的なユースケースに基づいた、正当なRDPセッションと悪意あるセッションの区別ができない、従来のツールで検知することは非常に困難でしょう。

REvilのようなサイバー犯罪グループが引き続き法執行機関の摘発を逃れている現在、防御側も環境を学習し、その変化に適応して成長し、攻撃の出現を示すわずかな変化に基づいて脅威に対処できるAIテクノロジーを使って対抗する必要があります。Autonomous Responseは数千を超える組織に採用され、Eメールやクラウドサービスからエンドポイントデバイスに至るまでデジタルエステートのあらゆるエリアをカバーし、ランサムウェア攻撃を早期に、暗号化が行われる前に阻止しています。

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

技術的詳細

Darktraceによるモデル検知:

  • Device / RDP Scan
  • Device / Bruteforce Activity
  • Compliance / Outbound Remote Desktop
  • Anomalous Connection / Upload via Remote Desktop
  • Anomalous Connection / Download and Upload
  • Anomalous Connection / Uncommon 1 GiB Outbound
  • Anomalous Connection / Active Remote Desktop Tunnel
  • Device / New or Uncommon SMB Named Pipe
  • Device / Large Number of Connections to New Endpoints

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
Oakley Cox
Analyst Technical Director, APAC

Oakley is a technical expert with 5 years’ experience as a Cyber Analyst. After leading a team of Cyber Analysts at the Cambridge headquarters, he relocated to New Zealand and now oversees the defense of critical infrastructure and industrial control systems across the APAC region. His research into cyber-physical security has been published by Cyber Security journals and CISA. Oakley is GIAC certified in Response and Industrial Defense (GRID), and has a Doctorate (PhD) from the University of Oxford.

Book a 1-1 meeting with one of our experts
この記事を共有

More in this series

該当する項目はありません。

Blog

Inside the SOC

A Thorn in Attackers’ Sides: How Darktrace Uncovered a CACTUS Ransomware Infection

Default blog imageDefault blog image
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

続きを読む
著者について
Tiana Kelly
Deputy Team Lead, London & Cyber Analyst

Blog

該当する項目はありません。

The State of AI in Cybersecurity: How AI will impact the cyber threat landscape in 2024

Default blog imageDefault blog image
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

続きを読む
著者について
Our ai. Your data.

Elevate your cyber defenses with Darktrace AI

無償トライアルを開始
Darktrace AI protecting a business from cyber threats.