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標的型Sodinokibiランサムウェア攻撃の事後分析

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20
Feb 2020
20
Feb 2020
The power of Darktrace’s self-learning AI comes into play when threat-actors use off-the-shelf tooling, making detection more difficult.

はじめに

先週Darktraceはある中規模の企業において4週間のトライアルを実施中に、標的型Sodinokibiランサムウェアを検知しました。

本ブログ記事では攻撃ライフサイクルのすべての段階について、攻撃者の使用した戦術、技術、手順、およびDarktraceがどのようにこの攻撃を検知したかを詳しく見ていきます。

Sodinokibiグループは、 ‘二重の脅威’ として知られる革新的な脅威アクターです。ランサムウェアを使った標的型の攻撃を実行すると同時に被害者のデータを抜き出すその能力からそう呼ばれています。この能力により彼らは身代金が払わられなければデータを公開するという脅しをかけることができます。

DarktraceのAIはこの攻撃の発生とともにリアルタイムに識別することができましたが、セキュリティチームはDarktraceを注視しておらずアラートに対処できませんでした。またAntigena もアクティブモードに設定されていませんでした。設定されていれば攻撃を遅らせ脅威を即座に封じ込めていたはずです。

タイムライン

以下のタイムラインは主な攻撃のフェーズの概要です。ほとんどの攻撃が1週間内に発生しており、大半のアクティビティは最後の3日間に集中しています。

技術分析

Darktraceは2つの主なデバイスが攻撃されたことを検知しました。これらはインターネットに接続されたRDPサーバー(以後‘RDP サーバー’と呼びます)およびSMBファイルサーバーとしても機能していたドメインコントローラ(以後‘DC’と呼びます)でした。

過去の攻撃では、Sodinokibiはランサムウェアアクティビティにホストレベル暗号化を使用しました。これは侵害されたホスト自体で暗号化が行われるものです。これに比べてネットワークレベルの暗号化では多くのランサムウェアアクティビティがSMBなどのネットワークプロトコルを介して実行されます。

最初の侵入

数日間に渡り、被害企業の外部と接続されたRDPサーバーがウクライナにある未知の外部IPアドレスから成功したRDP接続を受信していました。

最初の偵察活動が開始される直前、Darktraceは別のRDP接続がRDPサーバーに対して前に見られたものと同じRDPアカウントを使って行われていることを観測しました。この接続は1時間近く継続しました。

この攻撃で使用されたRDPの認証情報は、攻撃前のどこかの時点で、一般的なブルートフォース攻撃、クレデンシャルスタッフィング攻撃、あるいはフィッシングにより漏えいしていたと思われます。

DarktraceのDeep-Packet Inspection機能により、接続とすべての関連情報を明確に確認することができます:

疑わしいRDP接続の情報:

時間: 2020-02-10 16:57:06 UTC
ソース: 46.150.70[.]86 (ウクライナ)
デスティネーション: 192.168.X.X
送信先ポート: 64347
プロトコル: RDP
Cookie: [REDACTED]
継続時間: 00h41m40s
データ出力: 8.44 MB
データ受信: 1.86 MB

Darktraceはこの組織に通常接続しないIPアドレスから着信RDP接続を検知しました。

攻撃ツールのダウンロード

ウクライナからの不審なRDP接続から約54分後、RDPサーバーは人気のあるファイル共有プラットフォームMegauploadに接続し、そこから300MB近いデータをダウンロードしました。

DarktraceのAIはこのサーバーも、自動的に検知されたピアグループも、そして同じネットワーク上の誰も、Megauploadを利用しておらず、その結果これを即座に異常な動作として検知し、通常とは異なる動作であるとのフラグを立てました。

フルホスト名およびダウンロードに実際に使われたIP同様、Megauploadはこの組織にとって100%稀であったのです。

その後、40GBを超えるデータがMegauploadにアップロードされることになります。おそらく最初の300MBのダウンロードは、脅威アクターが追加のツールとC2インプラントを被害者の環境に導入したものと思われます。

内部偵察

MegauploadからRDPサーバーへのダウンロードのわずか3分後、Darktrace はRDPサーバーが異常なネットワークスキャンを行っていると警告しました:

RDPサーバーは同じサブネット上の9台の内部デバイスを7つのポート21、80、139、445、3389、4899、8080に対してスキャンしました。
攻撃的セキュリティのノウハウを多少持っている人であれば誰でも、これらのポートのほとんどがWindows環境で水平移動を行うためにスキャンするデフォルトポートであることに気づくでしょう。このRDPサーバーは通常ネットワークスキャンを行いませんので、Darktraceはこのアクティビティについても高度に異常であると識別しました。

その後、脅威アクターがさらなるネットワークスキャンを行う様子が観測されます。彼らは大胆になり、より汎用のスキャンを使うようになりました。そのうちの1つはNmapでデフォルトユーザーエージェントを使っていました:

さらなるコマンドアンドコントロールトラフィック

最初のC2トラフィックは主にRDPを使っていたと思われますが、脅威アクターは、今度はさらなる永続性を確立し、より弾力性の高いC2チャネルを構築しようとしました。

最初のネットワークスキャン(2020年2月10日19:17頃)実施後ほどなく、RDPサーバーは被害者の環境において通常は見られない不審な外部サービスを使った通信を開始しました。

Reddcoinへの通信

Reddcoinについても、ネットワーク上で他に使っている人はいませんでした。さらにこのアプリケーションプロトコルと外部ポートの組み合わせはネットワークにとってもきわめて不審なものでした。

通信はReddcoin APIに対しても行われ、手動の接続ではなくソフトウェアエージェントをインストールしようとしていることがわかりました。これが検知されたのは、Reddcoinがネットワークから見て稀であっただけでなく、「若い」ことも理由でした。つまり、この外部接続先は25分前まではネットワーク上で接続された形跡がなかったのです。

Reddcoin APIへの通信

Exceptionless[.io]への通信

このように、exceptionalness[.]io への通信はビーコニングの要領で Let’s Encrypt 証明書を使って行われていました。これはネットワークにとって稀であり通常とは異なる JA3 クライアントハッシュを使っていました。これらのことは、脅威アクターが300MBのツール類をダウンロードした直後に、デバイス上に新しいソフトウェアが存在していることを示しています。

上記のネットワークアクティビティのほとんどは、脅威アクターがツールをRDPサーバーに投下した直後に発生していますが、ReddcoinおよびExceptionlessとの接続の具体的な目的は不明です。この攻撃者は市販のツール(Megaupload、Nmap等)を使うことを好むようなので、これらのサービスをC2あるいはテレメトリー収集目的で使ったのかもしれません。

これで2月10日のほとんどのアクティビティが終了しました。

さらなるコマンドアンドコントロールトラフィック

攻撃者がなぜこのようなことをするのでしょうか?多くのC2を一度に使うことは1つか2つのチャネルを使うよりもずっとノイズが大きくなります。

2月12日と13日にも、著しいアクティビティの増加がみられました。

RDPサーバーは多数の高度に異常かつ稀な接続を外部デスティネーションに対して実行し始めました。以下のサービス、IPおよびドメインがC2目的でのみ使われたものかどうかは不確定ですが、高い確度で攻撃者のアクティビティとリンクされたものです:

  • vkmuz[.]netへのHTTPビーコニング
  • 著しいTorの使用量
  • 非標準RDPポート29348番を使った198-0-244-153-static.hfc.comcastbusiness[.]netへのRDP接続
  • 管理者アカウント(ジオロケーションがロシア)を使った92.119.160[.]60へのRDP接続
  • Megauploadへの接続継続
  • Exceptionless[.]io へのSSLビーコニング継続
  • api.reddcoin[.]comへの接続継続
  • freevpn[.]zoneへのSSLビーコニング
  • 31.41.116[.]201 の/index.php への新しいユーザーエージェントを使ったHTTPビーコニング
  • aj1713[.]onlineへの不審なSSL接続
  • Pastebinへの接続
  • 不審なJA3クライアントハッシュを使ったwww.itjx3no[.]comへのSSLビーコニング
  • safe-proxy[.]comへのSSLビーコニング
  • 事前のDNSホスト名ルックアップのないwestchange[.]topへのSSL接続(マシンドリブンの可能性)

ここで目立っているのは、(潜在的)C2チャネルの多様性です。Tor、ダイナミックISPアドレスへのRDP、VPNソリューションおよびおそらくカスタム / カスタマイズされた市販のインプラント(DGA様のドメインおよびIPから/index.phpへのHTTP)などです。

攻撃者がなぜこのようなことをするのでしょうか?多くのC2を一度に使うことは1つか2つのチャネルを使うよりもずっとノイズが大きくなります。

一つの答えは、攻撃者がステルス性よりも短期的なレジリエンスを重視していたということかもしれません。このネットワーク内の攻撃全体が7日間しかかかっておらず、大半のアクティビティが2.5日間で発生していたことを考えると、これは理解できます。別の可能性としては、攻撃時にさまざまな人物が並行して関与していたということも考えられます。1人の攻撃者はハッキングにおいてRDPセッションを好み、別の攻撃者はよりスキルが高く特定のポストエクスプロイト用フレームワークを使用した、ということかもしれません。

金銭目的でのこの攻撃の全体としての手口は、Advanced Persistent Threat (APT)攻撃のようなステルス性の、スパイ関連インシデントに見られるものよりも、スマッシュアンドグラブ(ガラス窓を破ってひったくる)的なものだったと言えます。

データ漏えい

DCは24時間にわたりおよそ40GBのデータをMegauploadにアップロードしました。

上記のアクティビティはすべてRDPサーバー(最初の上陸拠点の役割を果たした)上で観測されましたが、次のデータ抜き出しはRDPサーバーと同じサブネット上のドメインコントローラー(DC)で観測されました。

DCは24時間にわたりおよそ40GBのデータをMegauploadにアップロードしました。

Darktraceはこのデータ抜き出しを進行中に検知しました。DC(または類似のデバイス)が同じような量のデータをインターネットにアップロードしたことはありませんでした。さらに、被害者企業の環境内のいずれのクライアントあるいはサーバーもMegauploadを使用していなかったのです。

脅迫文

最後に、Darktraceは2月13日には不審なファイルが内部SMB共有上でアクセスされていることを検知しました。これらのファイルは脅迫文のようでした。Sodinokibiグループの他の被害者が報告しているのと同様に、ランダムに生成されたファイル名を使っていました:

413x0h8l-readme.txt
4omxa93-readme.txt

まとめと考察

脅威アクターはほとんど市販のツールを使っており、これによりアトリビューションがしにくくなるとともに、検知もより難しくなります。

この攻撃は現在のランサムウェアの特徴の多くを備えていました。金銭目的で、動きが速く、標的型でした。

脅威アクターはほとんど市販のツール(RDP、Nmap、Mega、VPNソリューション)を使っており、これによりアトリビューションがしにくくなるとともに、検知もより難しくなります。こうしたツールの使用によりしばしば通常の管理アクティビティに紛れ込むことが可能になります。異常検知を使用しないと、このようなアクティビティは検知できません。

外部に送信される数千の普通のRDP接続のなかから、1つの異常な発信RDP接続をどうやって特定できるでしょうか?Megauploadの使用が、ユーザーによる普通の使い方ではなく、悪意のあるものであるとどうやって知ることができるでしょうか?Darktraceの自己学習型AIが威力を発揮するのはこうした点です。

Darktraceは脅威インテリジェンスや静的なシグネチャを一切使用することなく、攻撃ライフサイクルのあらゆる段階を検知しました。

以下の図は侵害された2つのデバイスでの検知結果の概要です。侵害されたこれらのデバイスはネットワーク内で最もスコアの高いアセットでした。Darktraceの使用経験があまりない初級レベルのアナリストであっても、このような進行中の攻撃をリアルタイムに識別することができます。

RDPサーバー

RDPサーバー上での検知結果には次が含まれていました:

  • Compliance / File Storage / Mega - Megauploadの不審な使用
  • Device / Network Scan - 不審なネットワークスキャンの検知
  • Anomalous Connection / Application Protocol on Uncommon Port - 通常と異なるポート上でのプロトコル使用の検知
  • Device / New Failed External Connections - 不審なC2の失敗を検知
  • Compromise / Unusual Connections to Let’s Encrypt - Let’s Encryptを使ったSSLによるC2の可能性を検知
  • Compromise / Beacon to Young Endpoint - ネットワークにとって新しい外部エンドポイントへのC2を検知
  • Device / Attack and Recon Tools - Nmap等の既知の攻撃的セキュリティツールの検知
  • Compromise / Tor Usage  - 不審なTor使用の検知
  • Compromise / SSL Beaconing to Rare Destination - ジェネリックSSL C2の検知
  • Compromise / HTTP Beaconing to Rare Destination  - ジェネリックHTTP C2の検知
  • Device / Long Agent Connection to New Endpoint  - デバイス上で通常と異なるサービスを検知
  • Anomalous Connection / Outbound RDP to Unusual Port  - 不審なRDP C2を検知

DC

DC上での検知結果には次が含まれていました:

  • Anomalous Activity / Anomalous External Activity from Critical Device - dcs上の不審な動作の検知
  • Compliance / File Storage / Mega - Megauploadの不審な使用
  • Anomalous Connection / Data Sent to New External Device - 不審なロケーションへのデータ抜き出し
  • Anomalous Connection / Uncommon 1GB Outbound - 不審な接続先への大量のデータ送信
  • Anomalous Server Activity / Outgoing from Server - インターネット上の不審なエンドポイントへのC2の可能性


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
Max Heinemeyer
Chief Product Officer

Max is a cyber security expert with over a decade of experience in the field, specializing in a wide range of areas such as Penetration Testing, Red-Teaming, SIEM and SOC consulting and hunting Advanced Persistent Threat (APT) groups. At Darktrace, Max is closely involved with Darktrace’s strategic customers & prospects. He works with the R&D team at Darktrace, shaping research into new AI innovations and their various defensive and offensive applications. Max’s insights are regularly featured in international media outlets such as the BBC, Forbes and WIRED. Max holds an MSc from the University of Duisburg-Essen and a BSc from the Cooperative State University Stuttgart in International Business Information Systems.

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Inside the SOC

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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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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