Blog

Ransomware

OT

Thought Leadership

米国連邦政府へのインシデント報告をDarktraceのCyber AI Analystが加速

Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
12
Apr 2022
12
Apr 2022
This blog explains how Darktrace helps defenders abide by US federal laws on reporting cyber security incidents, featuring a real-world example of a ransomware attack investigated by Cyber AI Analyst.

2022年3月15日、バイデン大統領は、議会オムニバス歳出法案の一部に含まれるCyber Incident Reporting for Critical Infrastructure Act(重要インフラに対するサイバーインシデント報告法)に署名しました。この法律は、重要インフラの所有者および運営者が、ランサムウェアの支払いや大きなサイバー攻撃についてCyber and Infrastructure Security Agency(CISA)に対し速やかに通知することを義務付けています。

このCyber Incident Reporting for Critical Infrastructure Actにより2つの新しい報告義務が生まれました。

  1. 特定のサイバーインシデントについてDHS CISAに72時間以内に報告すること
  2. ランサムウェアの支払いについて24時間以内に報告すること

DarktraceのAIはサイバーインシデントの報告プロセスを加速してこの新しい法律に対応します。具体的には、DarktraceのCyber AI Analystが個別のセキュリティインシデント間のつながりを教師あり機械学習により理解し、NLP(Natural Language Processing)を使って人間が読める言語でインシデントレポートを自律的に記述します。これらのDarktraceインシデントレポートに基づいて人間のアナリストがCISAに迅速かつ効率的に報告書を送付することができます。

以下のケーススタディでは、重要インフラを管理する組織がランサムウェアおよび悪意あるデータ抜き出しの被害に遭った際にCyber AI Analystがシームレスな報告書作成を促進した実際の事例を紹介します。人間のアナリストの行動に基づいてトレーニングされたAIテクノロジーは、調査をマシンスピードかつマシンスケールで再現することにより、関連のあるイベントを数分で洗い出し、セキュリティチームは何が起こったのかを正確に理解しこの情報を関連当局に共有することができます。

以下の脅威調査レポートは重大な脅威の検知結果をステップバイステップで技術的詳細とともに解説し、Cyber AI Analystの威力とスピードを実証しています。

Cyber AI Analystのインシデントレポート

ランサムウェアがこの組織を襲った時、Cyber AI Analystはインシデントの全貌を自律的に調査し、攻撃の進行を明確に示した自然言語で記述されたサマリーを生成し、きわめて有益でした。

図1:Cyber AI Analystがインシデントの全貌を明らかに

この攻撃の後、さらにDarktraceのテクノロジーは攻撃のタイムラインを整理し、どのファイルが侵害されたかを識別してアナリストを支援しました。これによりセキュリティチームはランサムウェア攻撃に関連した悪意あるアクティビティを特定することができました。

図2:Cyber AI Analystは侵害されたデバイスが経験した攻撃チェーンの各段階を表示

Darktrace AIからの情報を使って、チームは容易に攻撃のタイムライン、影響を受けたデバイス、使用された認証情報、アクセスされたファイル共有、抜き出されたファイル、そして接触された悪意あるエンドポイントを特定することができ、攻撃の規模を開示して必要な当事者に知らせることができました。

この事例は、Cyber AI Analystがどのように重要インフラの所有者および運用者を支援し重大なサイバー攻撃について連邦政府への迅速な報告を可能にしたかを実証しています。重大なインシデントについては報告の期限が72時間 — ランサムウェアへの支払いは24時間 — であることを考慮すると、Cyber AI Analyst は重要インフラにとってもはや、あったら良い程度の機能ではなく、必須のものとなったと言えるでしょう。

攻撃の詳細:ランサムウェアおよびデータ抜き取り

Cyber AI Analystは上に示したインシデントレポートにも見られるように、最も重要な情報を読みやすいレポートとして、人間の関与をまったく必要とせずに提供しました。次に、この攻撃をさらに分解してDarktraceの自己学習型AIが攻撃のライフサイクル全体を通じて不審なアクティビティをどう理解したのかを見ていきます。

この二重恐喝ランサムウェア攻撃において、攻撃者は22日間に渡ってデータを抜き出していました。Darktraceの自己学習型AIによる検知結果、および並行して行われたCyber AI Analystによる調査は、攻撃チェーンをマッピングし、どのデータがどのように抜き出され暗号化されたかを特定するのに使われました。

この攻撃は大きく分けて3つのイベントグループから構成されていました:

  • ブルガリアにある未知の悪意ある外部エンドポイントへの非暗号化 FTP (File Transfer Protocol) データ抜き出し (May 9 07:23:46 UTC – May 21 03:06:46 UTC)
  • ネットワークファイル共有内のファイルのランサムウェア暗号化 (May 25 01:00:27 UTC – May 30 07:09:53 UTC)
  • 未知の悪意あるエンドポイントへの暗号化 SSH (Secure Shell) データ抜き出し (May 29 16:43:37 UTC – May 30 13:23:59 UTC)
図3:攻撃のタイムラインとDarktraceモデル違反

まず、ブルガリアにある未知の悪意あるエンドポイントへの内部データのアップロードがネットワーク内で観測されました。データ抜き出しに先立って内部ファイル共有のSMB読み取りがありその後FTPを使っておよそ450GBのデータが抜き出されました。

DarktraceのAIはこの脅威アクティビティを単独で発見し、組織はどのデータが抜き出されたかをすばやく特定することができました。これらには‘人材獲得’や、‘エンジニアリングおよび建設’などのマーキングでカモフラージュされたファイルや、法務および財務関係文書も含まれており、これらは機密性の高い文書であったことが推察されます。

図4:FTPを使った外部アップロードについての2つのモデル違反を示すスクリーンショット
図5:FTPアップロードに先立ってのファイル共有からのSMB読み取りを示すスクリーンショット

モデルブリーチ:

  • Anomalous Connection / Unusual Incoming Data Volume
  • Anomalous File / Internal / Additional Extension Appended to SMB File
  • Compromise / Ransomware / Suspicious SMB Activity
  • Compromise / Ransomware / SMB Reads then Writes with Additional Extensions
  • Unusual Activity / Anomalous SMB Move & Write
  • Unusual Activity / High Volume Server Data Transfer
  • Unusual Activity / Sustained Anomalous SMB Activity
  • Device / SMB Lateral Movement

このアクティビティが観測された4日後、DarktraceのAIはランサムウェアが展開されたことを検知しました。感染した複数のデバイスが通常アクセスしないファイル共有に対して異常なSMB接続を行い同じようなボリュームを読み取りおよび書き込みし始め、SMBを使ってファイル拡張子を書き込むなどをしていることが観測されました。ファイル拡張子はランダムな文字列で構成されこの標的となった組織固有のものと見られました。

Darktraceを使って、この顧客は暗号化されたファイルすべてのリストを取得しました。このリストは‘Accounts’ファイル共有に格納された財務上の記録と思われるものも含まれていました。

図6:ランサムウェア暗号化の際に追加の拡張子が書き込まれたことを示すモデル違反

モデルブリーチ:

  • Anomalous Connection / Unusual Incoming Data Volume
  • Anomalous File / Internal / Additional Extension Appended to SMB File
  • Compromise / Ransomware / Suspicious SMB Activity
  • Compromise / Ransomware / SMB Reads then Writes with Additional Extensions
  • Unusual Activity / Anomalous SMB Move & Write
  • Unusual Activity / High Volume Server Data Transfer
  • Unusual Activity / Sustained Anomalous SMB Activity
  • Device / SMB Lateral Movement

これと同時に、未知の悪意あるエンドポイントへの内部データのアップロードがネットワーク内で観測されました。アップロードはすべて暗号化されたSSH/SFTPを使って行われていました。合計で、約3.5GBのデータがこの方法で抜き出されました。

攻撃者はデータの抜き出しに暗号化チャネルを使いましたが、Darktraceは外部アップロードの前に異常なSMBファイル転送を検知しており、これがどのファイルが抜き出されたかを示していました。このように、Darktraceの「時間をさかのぼる」能力がきわめて有用であることが実証されました。暗号化を使って抜き出されていたにも関わらず、どのファイルが抜き出されたかをアナリストが知る助けとなったのです。

図7:SSHを使ったアップロードの前の異常なSMBアクティビティを示すモデル違反

モデルブリーチ:

  • Anomalous Server Activity / Outgoing from Server
  • Compliance / SSH to Rare External Destination
  • Unusual Activity / Enhanced Unusual External Data Transfer
  • Device / Anomalous SMB Followed By Multiple Model Breaches
  • Device / Large Number of Model Breaches
  • Anomalous Connection / Uncommon 1 GiB Outbound
  • Anomalous Connection / Data Sent to Rare Domain
  • Anomalous Connection / Data Sent To New External Device

攻撃は他のセキュリティスタックをどのようにすり抜けたか?

ネットワーク内で権限を昇格し悪意あるアクティビティを実行するために既存の管理者認証情報が使われました。

もしDarktrace RESPONDが有効に設定されていれば、的を絞った自律的な対処を実行してこのアクティビティを早い段階で封じ込めていたはずです。RESPONDはこの異常なSMBアクティビティに関与していたデバイスに対して通常の「生活パターン」を強制し、普段接続しないファイル共有からのファイル読み取りや、ファイルへの拡張子の追加などのアクティビティを封じ込め、未知の外部エンドポイントへの接続をブロックしていたことでしょう。

しかしこのケースでは、Antigenaはアクションを実行するよう設定されていませんでした。人間の確認を必要とするモードに設定されていたのです。このインシデントはDarktraceにより明確に警告され、セキュリティチームのワークフロー上には最優先アイテムとして表示されていました。しかし、セキュリティチームはDarktraceのユーザーインターフェイスを監視しておらず、他のツールにより実行されたアクションもなかったため、攻撃は進行を許され、この組織はインシデントの詳細を開示しなければならないことになりました。

報告書作成プロセスを効率化

現在の脅威環境においては、動きの速い高度な攻撃に対し、AIを利用してマシンスピードおよびスケールで阻止することはきわめて重要です。今回の事例が示しているように、このテクノロジーは攻撃の後始末としての報告義務を果たすのにも役立ちます。

新しい法律はタイムリーな開示を求めています。多くの従来型セキュリティアプローチでは、攻撃に遭った後、組織はその詳細をすべて調べる手段を持っていません。これに加えて、これらの情報を相関づけるには何日も、あるいは何週間もかかります。重要インフラを運営する組織にとってDarktraceがもはや「あったら良い」レベルではなく、「なくてはならない」ものとなったのは、こうした理由によります。新しい法律によって重大インシデントについて迅速に報告しなければならなくなったためです。

DarktraceのAIは悪意あるアクティビティを発生次第検知し、侵害のタイムラインおよび攻撃者によりアクセスされ抜き出されたファイルについてすばやく理解する助けとなります。これにより組織は最も高度な攻撃に対しても抵抗する準備ができるだけでなく、データ侵害について報告するプロセスを加速し大幅に容易化します。

セキュリティチームは開示プロセスの手間を一人で抱える必要はありません。攻撃はあっという間に起こり、その後始末は面倒です。失われたデータを遡及的に調査することは従来のアプローチでは徒労に終わることもあります。Darktraceを使うことにより、セキュリティチームは突然の破壊的な攻撃に対して、正確かつ俊敏なデータ特定手法、そしてリスク検知および緩和策により対抗することができます。そして、その必要が生じれば、イベントについての迅速かつ正確なレポートをAIがすべて揃えて提示してくれます。

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
Justin Fier
SVP, Red Team Operations

Justin is one of the US’s leading cyber intelligence experts, and holds the position of SVP, Red Team Operations at Darktrace. His insights on cyber security and artificial intelligence have been widely reported in leading media outlets, including the Wall Street Journal, CNN, The Washington Post, and VICELAND. With over 10 years’ experience in cyber defense, Justin has supported various elements in the US intelligence community, holding mission-critical security roles with Lockheed Martin, Northrop Grumman Mission Systems and Abraxas. Justin is also a highly-skilled technical specialist, and works with Darktrace’s strategic global customers on threat analysis, defensive cyber operations, protecting IoT, and machine learning.

Sally Kenyon Grant
VP, Darktrace Federal

Sally Kenyon Grant is Vice President of Federal at Darktrace, working with the US Department of Defense, the Intelligence Community and Federal Civilian Agencies.

Book a 1-1 meeting with one of our experts
この記事を共有
PRODUCT SPOTLIGHT
該当する項目はありません。
COre coverage

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.