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DarktraceによるOTへの脅威の発見:国際空港を標的とした高度なICS攻撃の検知

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23
2020年9月
23
2020年9月
As IT and OT converges, cyber-attacks are increasingly spreading to Industrial Control Systems, causing operational outages and physical disruption. Darktrace’s AI recently detected a simulation of an advanced threat in the environment of a major international airport that used a range of ICS attack techniques.

産業用制御システム(ICS)と従来型ITネットワークの統合が進む中で、企業のネットワーク内で開始してからオペレーショナルテクノロジーに拡散されるサイバー攻撃の数は、過去12か月間に劇的に増加しました。北朝鮮のハッカーがインドの原子力発電所を標的にしたことから、米国のガス施設やホンダの工場の操業を停止させたランサムウェアに至るまで、2020年はOTへの攻撃がメインストリームとなった年でした。

Darktraceは最近、ある国際空港における最先端の攻撃のシミュレーションを検知し、ICSの偵察、水平移動、脆弱性スキャン、プロトコルファジングを特定しました。プロトコルファジングとは、攻撃者がICSの通信チャネル上で無意味なコマンドを送信し、標的のデバイスを混乱させて故障または再起動させるという手法です。

DarktraceのIndustrial Immune Systemは、この巧妙な攻撃のすべての段階を検知しました。その際、AIを使った異常検知によって、既知のエクスプロイト、企業のアセット、ファームウェアバージョンのリストを使うことなくICSへの攻撃ベクトルを特定しました。攻撃者はICSのキルチェーンの全段階でツールを駆使しました。その中には、ICS固有の攻撃手法もありました。

1個のコイル、オブジェクト、その他のデータブロックを読み取ろうとする、または再プログラムするための、あらゆる不審な試みがCyber AIによって検知されました。DarktraceのCyber AI Analystはこのアクティビティを自動的に特定し、主な対応策を詳しく説明するサマリーレポートを作成しました。

攻撃は数日間に及び、ビル管理システム(BMS)と手荷物受取所のネットワークを標的としました。その中で、攻撃者は2つの一般的なICSプロトコル(BacNetとS7Comm)を利用し、正当なツール(ICSの再プログラミングコマンドや、SMBサービスパイプ経由の接続)を活用して、従来型のシグネチャベースのセキュリティツールを回避しました。

攻撃の詳細

図1: 攻撃のタイムライン

攻撃の最初の段階では、ARPスプーフィングを使って従来型セキュリティツールからの検出を回避しながら、ネットワークに新しいデバイスが導入されました。午前11時40分に、攻撃者は標的デバイスをスキャンし、開いているサービスへのブルートフォース攻撃を試みました。標的デバイスを乗っ取ると、インターネットへの外部接続を確立しようとしました。ICSネットワークでは外部接続は許可されないはずですが、攻撃者はしばしばファイアウォールやネットワーク隔離ルールをバイパスし、コマンド&コントロール(C2)チャネルを作成しようとします。

図2:侵入テストの開始から15分経過後のDarktrace脅威トレイ。ハイレベルのモデル違反により、攻撃デバイスについての警告がアナリストチームに既に送信されている。

その後、乗っ取られたデバイスは、DiscoverおよびReadコマンドを使用してICSの偵察を開始しました。Darktraceは、この偵察の一環として標的にされた新しいオブジェクトとデータブロックを特定し、通常とは異なるBacNetおよびSiemens S7Commプロトコルコマンドの標的になっていたICSデバイスを検知しました。

図3:BacNet上のICS偵察に関連するモデルアラート。ICSコマンドレベルでの機械学習により、新しい、通常とは異なるBacNetオブジェクトが攻撃者によって標的とされていたことが検知されました。

攻撃者はICSシステム全体で水平移動を行うために、複数のICSデバイスにわたって列挙を行いました。デバイスの設定と構成を把握すると、攻撃者はICSのReprogramおよびWriteコマンドを使用してマシンの設定を変更しました。攻撃者は標的デバイスを悪用するために、SMB、SMBv1、HTTP、RDP、およびICSプロトコルのファジングなど、既知の脆弱性を使おうとしました。

図4:攻撃者が複数のICSコントローラに対してデバイスの列挙を実行した様子の可視化。攻撃者は、最初の偵察の一環としてICS Discoverコマンドを使用しました。

攻撃者は空港のサイバーセキュリティスタックを回避するための行動をとりました。ネットワーク上で一般的に使用されているICSプロトコルを使って、これらのプロトコルを一般的に使用しているデバイスに接続するといったことです。従来型のセキュリティツールはこのアクティビティを認識できませんでしたが、Darktraceのディープパケットインスペクションでは、これらの「通常の」接続に紛れた、攻撃者の異常なコマンドを特定することができました。

攻撃者はARPスプーフィングを使用して、アセットマネジメントベースのセキュリティツールによる調査を遅らせました。これらのツールには、空港がトライアル利用していた他の2つのソリューションも含まれていました。また、侵入全体にわたって複数のデバイスを使用し、防御チームを煙に巻きました。

さらに、DarktraceのAIテクノロジーは、自動化されたインシデント調査を開始しました。Cyber AI Analystはすべての攻撃デバイスを特定し、それぞれについてサマリーレポートを生成しました。これにより、セキュリティチームの貴重な時間を節約しただけではなく、ITチームとICSエンジニアの間のスキルギャップを埋める能力を披露しました。

図5:1日目の終わりにおけるCyber AI Analystの脅威トレイ。攻撃者の使用したデバイスが両方とも特定されています。

Cyber AI Analystは最初のモデル違反の直後に調査を開始し、続いてネットワーク全体にわたる個々のイベントをつなぎ合わせ、自然言語で書かれたインシデントサマリーを生成しました。サマリーには、推奨される対応策も含まれていました。

図6:2日目の終わりにおけるAIAのインシデントサマリー。SMBエクスプロイトを、ICSデバイスに対する攻撃チェーンの一部として説明しています。

起こり得る結果

この攻撃を続けられていたとしたら、攻撃者(活動家グループ、テロリスト組織、組織的犯罪者の可能性もある)は空港に対し、重大なオペレーション中断を引き起こすことができた可能性があります。たとえば、制限エリアの内外における温度設定、スプリンクラーシステム、火災警報器、非常口、照明、ドアは、おそらくビル管理システムによって制御されています。これらの1つでもみだりに変更されていれば、空港で重大な混乱が発生し、コストと評判の面で著しい悪影響が発生する恐れがありました。同様に、手荷物受取所のネットワークへのアクセスを犯罪者が利用すると、不正な商品の密輸や、貴重な貨物の盗難につながるおそれがあります。

このシミュレーションは、ITとOTが統合されたネットワークを侵害しようとする高度なサイバー犯罪者にとっての可能性を示しています。大手ICS「セキュリティ」ベンダーの大半はシグネチャベースのため、新たな手法を発見できず、悪意のある結果を引き起こすために一般的なプロトコルが使用されても認識できません。これこそが、今年もICS攻撃が引き続きニュースの見出しを飾っていた理由です。

このインシデントは、実世界のICS環境におけるCyber AIの検知の範囲と、攻撃を受けてDarktraceが提供できる情報の詳細さを実証しています。ICSと広義のITネットワークとの統合が進むに従い、こうした重要システムのセキュリティ保護は最重要課題となります。Darktraceは、デジタル環境全体にわたって可視化と検知を実現する、統一されたセキュリティの傘を提供します。

この調査結果についての考察はDarktraceアナリストOakley Cox が協力しました。

Industrial Immune Systemについて詳しく知る

Darktraceによるモデル検知:

  • ICS / Unusual ICS Commands
  • ICS / Multiple New Reprograms
  • ICS / Uncommon ICS Protocol Warning
  • ICS / Rare External from OT Device
  • ICS / Uncommon ICS Protocol Warning
  • ICS / Multiple Failed Connections to ICS Device
  • ICS / Anomalous IT to ICS Connection
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
David Masson
Director of Enterprise Security

David Masson is Darktrace’s Director of Enterprise Security, and has over two decades of experience working in fast moving security and intelligence environments in the UK, Canada and worldwide. With skills developed in the civilian, military and diplomatic worlds, he has been influential in the efficient and effective resolution of various unique national security issues. David is an operational solutions expert and has a solid reputation across the UK and Canada for delivery tailored to customer needs. At Darktrace, David advises strategic customers across North America and is also a regular contributor to major international and national media outlets in Canada where he is based. He holds a master’s degree from Edinburgh 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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