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Darktrace’s Detection of a Hive Ransomware-as-Service

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23
May 2023
23
May 2023
This blog investigates a new strain of ransomware, Hive, a ransomware-as-a-service. Darktrace was able to provide full visibility over the attacks.

Update: On January 26, 2023, the Hive ransomware group was dismantled and servers associated with the sale of the ransomware were taken offline following an investigation by the FBI, German law enforcement and the National Crime Agency (NCA). The activity detailed in this blog took place in 2022, whilst the group was still active.

RaaS in Cyber Security

ランサムウェアの脅威は、サイバー脅威を取り巻く環境において、セキュリティチームにとって常に懸念され続けています。ランサムウェア・アズ・ア・サービス(RaaS)の普及に伴い、経験の浅い「自称」攻撃者にとっても、ランサムウェアはますますアクセスしやすくなっています。このような参入障壁の低さの結果、ランサムウェア攻撃の量は大幅に増加すると予想されます。

さらに、RaaSは、購入者がランサムウェアの展開に使用する様々なキットや機能を選択できる、非常にカスタマイズ可能な市場であるため、攻撃の挙動が同じになることはほとんどありません。このような差異を効果的に検知し、保護するためには、ランサムウェアの進化のスピードに追いつけない攻撃チェーンに焦点を当てた、減価したIoCリストやプレイブックに頼るのではなく、異常の検知と予想される動作の逸脱に重点を置いたセキュリティ対策を実施することが極めて重要です。

2022年初頭、Darktraceの DETECT /Network™は、複数の顧客のネットワーク上でHiveランサムウェアの複数のインスタンスを確認しました。 Darktrace は、その アノマリベースの検知機能を使用して、コマンド&コントロール(C2)活動、ラテラルムーブメント、データ流出、そして最終的にはデータの暗号化と身代金のメモの書き込みなど、攻撃とキルチェーンの複数の段階を正常に検知することができました。

Hiveランサムウェア 

Hiveランサムウェアは、2021年6月に初めて野生で観測された比較的新しいマルウェア株です。ヘルスケア、エネルギープロバイダー、小売業者などさまざまな業界をターゲットにすることが知られており、これまでに1,500以上の組織を攻撃し、1億米ドル以上の身代金の支払いを徴収したと報告されています。[1]

HiveはRaaSモデルで配布され、開発者は最終的な身代金の支払額の一定割合を受け取る代わりに、コードの更新と保守を行い、ユーザー(またはアフィリエイト)には、通常では使用できない高度で複雑なマルウェアを使用して攻撃を実行できるツールを提供します。Hiveは、ランサムウェアに関連する典型的な戦術、技術、手順(TTP)を使用しますが、それらは攻撃を実行するHiveのアフィリエイトによって変化します。

ほとんどの場合、身代金を要求する前に、まずデータを抜き取り、次に暗号化する二重の恐喝攻撃が行われます。被害者は、HiveLeaks のTORサイトなどで機密データが一般に流出する危険性があるため、攻撃者に有利に働くことになります。

攻撃のタイムライン

RaaSは高度にカスタマイズ可能なため、Hiveの攻撃者が採用する戦術や方法はケースバイケースで異なることが予想されます。しかし、Darktrace の顧客環境で確認されたHiveランサムウェアのインシデントの大半では、以下のような一般的な攻撃段階と特徴が確認されています、 Darktrace DETECTは、以下のような一般的な攻撃の段階と特徴を観察しました。これは、同じ脅威アクターから発生した攻撃、または特定の構成を持つバッチが様々な行為者に広く販売されていることを示している可能性があります。

図1:Darktrace が観測したHive攻撃の典型的なタイムライン

初期アクセス 

Hiveのアクターは、複数の異なるベクトルを通じてネットワークに初期アクセスすることが知られていますが、セキュリティ研究者によって報告された2つの主要な方法は、Microsoft Exchangeの脆弱性の悪用、または悪意のある添付ファイルを含むフィッシングメールの配信です。[2][3]

例えば、Darktrace の顧客のネットワーク上で観測されたある Hive ランサムウェア攻撃の初期段階で、Darktrace は、HTTP 経由で PowerShell ユーザーエージェントを使用して、稀な外部ロケーション 23.81.246[.]84 に接続するデバイスを検知しました。この接続中、デバイスは「file.exe」という名前の実行可能ファイルをダウンロードしようとしました。このファイルは、最初にフィッシングメール経由でアクセスされ、配信された可能性があります。しかし、攻撃時にDarktrace/Email  が有効になっていなかったため、これはDarktraceの権限の範囲外でした。幸いにも、図2のパケットキャプチャ(PCAP)にあるように、接続はプロキシ認証に失敗し、ブロックされました。 

このダウンロードの試みの直後、同じデバイスが、珍しい外部エンドポイントである 146.70.87[.]132から大量の受信SSL接続を受け始めました。Darktrace は、このエンドポイントがGo Daddy CAという簡単に入手してアクセスできるSSL証明書を使用しており、このエンドポイントからの受信SSL接続が増えたことはこのデバイスにとって珍しい挙動であると記録しました。 

Darktrace が検知したこの非常に異常なアクティビティは、ランサムウェア攻撃がいつ始まったかを示していると思われ、おそらく最初のペイロードのダウンロードだと思われます。  

Darktrace DETECT のモデル:

  • Anomalous Connection / Powershell to Rare External
  • Anomalous Server Activity / New Internet Facing System
図2:プロキシ認証に失敗したことを示す、希少なエンドポイント23.81.246[.]84へのHTTP接続のPCAP

C2 ビーコニング 

初期アクセスに成功した後、Hiveアクターは、C2サーバーへの多数の接続と追加のステージャのダウンロードを通じて、感染したネットワーク上にC2インフラを確立し始めます。 

Hiveランサムウェアに感染した顧客ネットワークにおいて、Darktrace は複数の希少なエンドポイントへの接続を大量に開始するデバイスを確認しました。これは、攻撃者のインフラに対するC2ビーコンである可能性が非常に高いです。ある特定の例では、オープンソースインテリジェンス(OSINT)のさらなる調査により、これらのエンドポイントがCobalt Strikeに関連していることが判明しました。

Darktrace DETECT のモデル:

  • Anomalous Connection / Multiple Connections to New External TCP
  • Anomalous Server Activity / Anomalous External Activity from Critical Network Device
  • Compromise / High Volume of Connections with Beacon Score
  • Compromise / Sustained SSL or HTTP Increase
  • Compromise / Suspicious HTTP Beacons to Dotted Quad 
  • Compromise / SSL or HTTP Beacon
  • Device / Lateral Movement and C2 Activity

内部偵察、ラテラルムーブメント、特権のエスカレーション

C2インフラが確立された後、Hiveアクターは通常、ネットワーク上で検知されないようにするため、アンチウイルス製品のアンインストールを開始します[3]。また、脆弱性やオープンチャネルを探すために内部偵察を行い、ネットワーク全体を横方向に移動することを試みます。

C2接続が行われる中、Darktraceは、ある顧客ネットワーク上のデバイスが他の内部デバイスへの接続を異常に大量に開始したことを確認し、攻撃に関連するネットワークスキャン活動を検知することができました。また、ある重要なネットワークデバイスがSMB経由で実行ファイル mimikatz.exe を書き込んでいるのが確認されましたが、これは一般的にクレデンシャルハーベスティングに用いられるMimikatz攻撃ツールであると思われます。 

また、RDPおよびDCE-RPCを介したラテラルムーブメントの試みが複数検知され、攻撃者はAdministratorクレデンシャルを使用して認証に成功しました。あるケースでは、デバイスが ITaskScheduler のアクティビティを実行していることも観察されました。このサービスは、マシン上で実行されているタスクをリモートで制御するために使用され、悪意のあるラテラルムーブメントの一部として一般的に観察されます。Darktrace DETECTは、上記の活動がデバイスの通常の行動パターンからの逸脱であり、以下のモデルが侵害されたものであると理解しました:

Darktrace DETECT のモデル:

  • Anomalous Connection / Anomalous DRSGetNCChanges Operation
  • Anomalous Connection / New or Uncommon Service Control
  • Anomalous Connection / Unusual Admin RDP Session
  • Anomalous Connection / Unusual SMB Version 1 Connectivity
  • Compliance / SMB Drive Write
  • Device / Anomalous ITaskScheduler Activity
  • Device / Attack and Recon Tools
  • Device / Attack and Recon Tools In SMB
  • Device / EXE Files Distributed to Multiple Devices
  • Device / Suspicious Network Scan Activity
  • Device / Increase in New RPC Services
  • User / New Admin Credentials on Server

データ漏えい

攻撃の現段階では、Hiveアクターは様々な異なる方法を用いて感染したネットワーク上でデータ流出活動を行うことが知られています。米国サイバーセキュリティ・社会基盤安全保障庁 (CISA) は、「Hiveアクターは、RcloneとクラウドストレージサービスMega[.]nzを組み合わせて使用してデータを流出させている可能性が高い」と報告しています [4]。Darktrace DETECT は、ある顧客ネットワーク上のデバイスが、ユーザーエージェント "rclone/v1.57.0" で "w.apa.mega.co[.]nz" など Mega関連のエンドポイントにHTTP接続し、外部へと少なくとも3Gibが移動したことが観察されています(図3)。また、同じデバイスがSSL経由で、希少な外部IPである 158.51.85[.]157 に少なくとも3.6GBのデータを転送していることが確認されました。

図3:デバイスが複数のエンドポイントに外部接続し、メガストレージエンドポイントに流出したそれぞれのデータ量をまとめたもの

別のケースでは、デバイスがSSH経由で珍しい外部エンドポイント93.115.27[.]71に16GB以上のデータをアップロードしていることが観測されました。このエンドポイントは、以前のビーコン活動で確認されており、これは流出イベントである可能性が高いことが示唆されました。 

しかし、Hiveランサムウェアは、他のRaaSキットと同様に、その技術や機能が大きく異なる可能性があり、Hiveランサムウェアの攻撃においてデータ流出が常に存在するとは限らないことに注意することが重要です。Darktrace が検知したあるインシデントでは、顧客環境からデータが流出した形跡はなく、データ流出がHiveの実行者の目的の一部ではなかったことを示しています。

Darktrace DETECT のモデル:

  • Anomalous Connection / Data Sent to Rare Domain
  • Anomalous Connection / Lots of New Connections
  • Anomalous Connection / Multiple HTTP POSTs to Rare Hostname
  • Anomalous Connection / Suspicious Self-Signed SSL
  • Anomalous Connection / Uncommon 1 GiB Outbound
  • Device / New User Agent and New IP
  • Unusual Activity / Unusual External Data to New Endpoints
  • Unusual Activity / Unusual External Data Transfer
  • Unusual Activity / Enhanced Unusual External Data Transfer

ランサムウェアの展開

典型的なHiveランサムウェア攻撃の最終段階では、ランサムウェアのペイロードが展開され、感染したデバイス上のファイルを暗号化し始めます。あるお客様のネットワークで、Darktrace 、ドメインコントローラー(DC)に接続して「xxx.exe」という名前のファイルを読み込む複数のデバイスを検知しました。複数のソースが、このファイル名をHiveランサムウェアのペイロードと関連付けています。[5]

別の例ですが、Darktrace DETECTは、複数のデバイスが 194.156.90[.]25という珍しい外部の場所から実行ファイル「nua64.exe」および「nua64.dll」をダウンロードするのを観測しました。OSINTの調査により、このファイルがHiveランサムウェアに関連していることが判明しました。

図4:Hiveランサムウェアに関連する悪質なファイルハッシュ [6] のセキュリティベンダーによる解析結果 

この実行ファイルをダウンロードした直後、複数のデバイスで、ファイルの拡張子にランダムに生成された文字列を付加する、異常な量のファイル暗号化が行われていることが確認されました。 

Hiveランサムウェアの初期バージョンでは、拡張子が「.hive」のファイルが暗号化されることが報告されていますが [7]、Darktraceは、暗号化されたファイルの拡張子が、部分的にランダム化されているものの、一貫して20文字で、正規表現 “[a-zA-Z0-9\-\_]{8}[\-\_]{1}[A-Za-z0-9\-\_]{11}” と一致していたことが複数のお客様によって確認されました。

図5:デバイスのイベントログに、ランダムに生成された20文字の拡張子を持つ暗号化ファイルのSMBの読み取りと書き込みが表示されています 

ファイルの暗号化に成功すると、Hiveは「HOW_TO_DECRYPT.txt」と名付けられた身代金メモを、影響を受けた各ディレクトリに投下するようになります。通常、身代金要求書には、Hiveの「営業部」へのリンクと、流出が行われた場合には、攻撃者が要求が満たされない場合に流出したデータを公開すると脅す「HiveLeaks」サイトへのリンクが含まれています(図6)。 Darktrace で検知されたHiveランサムウェアのケースでは、複数のデバイスが「HiveLeaks」のTORドメインにコンタクトしようとする様子が観察されており、エンドポイントユーザーがランサムノートに記載されたリンクに従っていたことが示唆されています。

図6:Hiveのランサムノートのサンプル [4]

ファイル拡張子の例:

  • 36C-AT9-_wm82GvBoCPC
  • 36C-AT9--y6Z1G-RFHDT
  • 36C-AT9-_x2x7FctFJ_q
  • 36C-AT9-_zK16HRC3QiL
  • 8KAIgoDP-wkQ5gnYGhrd
  • kPemi_iF_11GRoa9vb29
  • kPemi_iF_0RERIS1m7x8
  • kPemi_iF_7u7e5zp6enp
  • kPemi_iF_y4u7pB3d3f3
  • U-9Xb0-k__T0U9NJPz-_
  • U-9Xb0-k_6SkA8Njo5pa
  • zm4RoSR1_5HMd_r4a5a9 

Darktrace DETECT のモデル:

  • Anomalous Connection / SMB Enumeration
  • Anomalous Connection / Sustained MIME Type Conversion
  • Anomalous Connection / Unusual Admin SMB Session
  • Anomalous File / Internal / Additional Extension Appended to SMB File
  • Compliance / SMB Drive Write
  • Compromise / Ransomware / Suspicious SMB Activity
  • Compromise / Ransomware / Ransom or Offensive Words Written to SMB
  • Compromise / Ransomware / Possible Ransom Note Write
  • Compromise / High Priority Tor2Web
  • Compromise / Tor2Web
  • Device / EXE Files Distributed to Multiple Devices

結論

Hiveランサムウェアの攻撃は、さまざまなアフィリエイトがさまざまな展開キットを使用して実行されるため、採用される戦術は異なる傾向にあり、新しいIoCが定期的に確認されています。さらに、2022年には、プログラミング言語Rustを使用してHiveの新しい亜種が作成されました。これはHiveの大幅なアップグレードであり、防御回避技術を向上させ、検知をさらに困難にしています [8]。 

Hiveは、現在市場にある数多くのRaaSの1つに過ぎず、この市場は利用率とプレゼンテーションの多様性が高まる一方であると予想されます。 ランサムウェアがより身近になり、展開が容易になるにつれ、組織はランサムウェアをできるだけ早い段階で特定するための効率的なセキュリティ対策を導入することが不可欠となります。 

Darktrace DETECTの自己学習型AIは、顧客ネットワークを理解し、組織のデジタルエステート全体で予想される行動パターンを学習します。このようなアノマリーベースのツールである Darktrace を使用すると、ルールやシグネチャ、既知のIoCに依存することなく、異常な動作や予期せぬ動作の自律検知を通じて新たな脅威を瞬時に特定することができます。 

寄稿者:Emily Megan Lim(Cyber Analyst)、Hyeongyung Yeom(Senior Cyber Analyst & Analyst Team Lead)

付録

MITRE AT&CK マッピング

偵察

T1595.001 – Scanning IP Blocks

T1595.002 – Vulnerability Scanning

リソース開発

T1583.006 – Web Services

初期アクセス

T1078 – Valid Accounts

T1190 – Exploit Public-Facing Application

T1200 – Hardware Additions

実行

T1053.005 – Scheduled Task

T1059.001 – PowerShell

永続性/特権昇格

T1053.005 – Scheduled Task

T1078 – Valid Accounts

防衛回避

T1078 – Valid Accounts

T1207 – Rogue Domain Controller

T1550.002 – Pass the Hash

探索

T1018 – Remote System Discovery

T1046 – Network Service Discovery

T1083 – File and Directory Discovery

T1135 – Network Share Discovery

ラテラルムーブメント

T1021.001 – Remote Desktop Protocol

T1021.002 – SMB/Windows Admin Shares

T1021.003 – Distributed Component Object Model

T1080 – Taint Shared Content

T1210 – Exploitation of Remote Services

T1550.002 – Pass the Hash

T1570 – Lateral Tool Transfer

収集

T1185 – Man in the Browser

コマンド&コントロール

T1001 – Data Obfuscation

T1071 – Application Layer Protocol

T1071.001 – Web Protocols

T1090.003 – Multi-hop proxy

T1095 – Non-Application Layer Protocol

T1102.003 – One-Way Communication

T1571 – Non-Standard Port

持ち出し

T1041 – Exfiltration Over C2 Channel

T1567.002 – Exfiltration to Cloud Storage

影響

T1486 – Data Encrypted for Impact

T1489 – Service Stop

IoC一覧 

23.81.246[.]84 - IP Address - Likely Malicious File Download Endpoint

146.70.87[.]132 - IP Address - Possible Ransomware Endpoint

5.199.162[.]220 - IP Address - C2 Endpoint

23.227.178[.]65 - IP Address - C2 Endpoint

46.166.161[.]68 - IP Address - C2 Endpoint

46.166.161[.]93 - IP Address - C2 Endpoint

93.115.25[.]139 - IP Address - C2 Endpoint

185.150.1117[.]189 - IP Address - C2 Endpoint

192.53.123[.]202 - IP Address - C2 Endpoint

209.133.223[.]164 - IP Address - Likely C2 Endpoint

cltrixworkspace1[.]com - Domain - C2 Endpoint

vpnupdaters[.]com - Domain - C2 Endpoint

93.115.27[.]71 - IP Address - Possible Exfiltration Endpoint

158.51.85[.]157 - IP Address - Possible Exfiltration Endpoint

w.api.mega.co[.]nz - Domain - Possible Exfiltration Endpoint

*.userstorage.mega.co[.]nz - Domain - Possible Exfiltration Endpoint

741cc67d2e75b6048e96db9d9e2e78bb9a327e87 - SHA1 Hash - Hive Ransomware File

2f9da37641b204ef2645661df9f075005e2295a5 - SHA1 Hash - Likely Hive Ransomware File

hiveleakdbtnp76ulyhi52eag6c6tyc3xw7ez7iqy6wc34gd2nekazyd[.]onion - TOR Domain - Likely Hive Endpoint

参考文献

[1] https://www.justice.gov/opa/pr/us-department-justice-disrupts-hive-ransomware-variant

[2] https://www.varonis.com/blog/hive-ransomware-analysis

[3] https://www.trendmicro.com/vinfo/us/security/news/ransomware-spotlight/ransomware-spotlight-hive 

[4]https://www.cisa.gov/news-events/cybersecurity-advisories/aa22-321a

[5] https://www.trendmicro.com/en_us/research/22/c/nokoyawa-ransomware-possibly-related-to-hive-.html

[6] https://www.virustotal.com/gui/file/60f6a63e366e6729e97949622abd9de6d7988bba66f85a4ac8a52f99d3cb4764/detection

[7] https://heimdalsecurity.com/blog/what-is-hive-ransomware/

[8] https://www.microsoft.com/en-us/security/blog/2022/07/05/hive-ransomware-gets-upgrades-in-rust/ 

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
Emily Megan Lim
Cyber Analyst
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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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Tiana Kelly
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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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