Blog

Threat Finds

RESPOND

Inside the SOC

SQLサーバーエクスプロイトを振り返る

Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
27
Jun 2021
27
Jun 2021
Deep dive into how an attacker leveraged compromised credentials to infect multiple servers and spread laterally through the organization. This detailed threat find is an excellent use case for Autonomous Response and the importance of patching vulnerabilities.

SaaSやIoTデバイスは侵入経路としてますます一般的になっていますが、一方でサーバーサイド攻撃も世界中の企業にとって現在も深刻な脅威です。高度な脆弱性スキャンツールを用いることで、攻撃者はわずか数秒のうちにセキュリティの欠陥を特定し、アタックサーフェス全体から侵入場所を探し出すことができるようになっています。人間のセキュリティチームは、絶えず更新される脆弱性の文書やパッチの波についていくのに苦労しています。

Darktraceは最近、未知の攻撃者による標的型サイバー攻撃を阻止しました。最初の侵入後、攻撃者はパッチのない脆弱性(CVE-2020-0618)をエクスプロイトし、権限の低いアカウントにコードをリモートで実行する機能を付与しました。これにより攻撃者は水平方向に勢力を広げ、やがて新しいユーザーアカウントを作成してシステム内に足場を築くことができました。

The server-side attack cycle: authenticates user; scans network; infects three servers; downloads malware; c2 traffic; creates new user.

図1:サーバーサイド攻撃サイクルの概要

本ブログでは、この侵入事例を細かく分析し、Darktraceの自律遮断技術が3つのピンポイントなアクションにより攻撃者の動きを阻止した方法について詳しく説明します。

未知の脅威アクターが脆弱性をエクスプロイト

最初の侵入

Cyber AIは、カナダにある約3,000台のデバイスを持つ金融企業で、新たなアカウントparentsが使用されているのを検知しました。攻撃者はこの認証情報を用いて、VPN経由で社内環境にアクセスしました。そこから、NT LAN Manager(NTLM)を使用するデスクトップコンピュータへの認証を行いました。それ以上の疑わしいアクティビティは観測されませんでした。

NTLMは、ブルートフォースやpass the hash(ハッシュを渡す)など、複数の侵害手法に対して脆弱なため、サイバー犯罪者がよく使う攻撃ベクトルとなっています。このアカウントへの初めてのアクセスは、Darktraceの導入前にフィッシングによって得られた可能性があります。

図2:このアカウントがデバイスで始めて観測されたのは、偵察の5日前でした。攻撃者は、侵害を受けたデバイスが切断されるまで、偵察と水平移動を2日間実行しました。

内部偵察

その5日後、parentsアカウントがデスクトップPCにログインしているのが観測されました。このデスクトップPCはネットワークのスキャンを開始し、80個を超える内部IPアドレスのポート443と445をスキャンしました。

Shortly after the scan, the device used Nmap to attempt to establish SMBv1 sessions to 139 internal IPs, using guest / user credentials. 79 out of the 278 sessions were successful, all using the login.

図3:同様のインシデントにおいて、最初に感染したデスクトップPCが行った新たな内部接続の失敗。このグラフでは、内部接続の失敗とモデル違反の急上昇が目立っています。

ネットワークスキャンは侵入後の第一段階で、それにより攻撃者はどのサービスが稼働中かを突き止めてから、パッチが適用されていない脆弱性を探すことができました。

Nmapには、偵察や水平移動によく悪用される複数の機能があります。この場合は、ドメインコントローラへのSMBv1セッションを確立するためにそれが使われました。これにより攻撃者はそれぞれの接続先とのSMBv1セッションを1回ずつ開始する必要がなくなりました。SMBv1には既知の脆弱性があるため、可能な限り無効にするのがベストプラクティスです。

ラテラルムーブメント

このデスクトップPCは、SQLサーバー上のサービス(svcctlエンドポイント)をコントロールし始めました。サービスの作成と開始の両方が観測されました(CreateServiceW、StartServiceW)。

次に、このデスクトップPCは、SQL Reportingサーバーに対して暗号化されていないHTTP接続を開始しました。これは、この2つのデバイス間に確立された初めてのHTTP接続であり、このユーザーエージェントがSQL Reportingサーバー上で観測された初めての機会でもありました。

接続のパケットキャプチャによって、CVE-2020-0613のエクスプロイトにみられるPOSTが判明しました。この脆弱性はデシリアライゼーションの問題です。これは、注意深く作成されたページリクエストにより、処理をサーバーが誤り、権限の低いアカウントがリバースシェルを確立し、サーバー上でリモートにコードを実行できるようにするものです。

図4:HTTP接続のPCAPの一部。このトラフィックは。SQL Server Reporting Services(SSRS)内におけるRemote Code Execution(RCE)を可能にするCVE-2020-0618のエクスプロイトに一致します。

ほとんどの動作はEast-Westトラフィックで観測され、すぐに使用できるリモートプロシージャコール(RPC)メソッドを使用していました。このような接続は、システム内に数多くあります。組織の「生活パターン」を学ばなければ、この悪意ある接続に注目することはほとんど不可能だったでしょう。

Cyber AIは、DCE-RPCエンドポイントを経由する、svcctlエンドポイントへの接続を検知しました。これは「サービス制御」エンドポイントと呼ばれ、デバイス上で稼働中のプロセスをリモートで制御するために使用されます。

このデスクトップPCからの水平移動中のHTTP POSTリクエストにより、CVE-2020-0613のエクスプロイトであることが判明しました。攻撃者は、パッチが適用されていない既存の脆弱性を発見し、悪用することに成功したのです。

Darktraceは、このHTTP接続について警告し、そこに潜む(そして最終的な)エクスプロイトを明らかにした唯一のツールでした。Cyber AIは、このユーザーエージェントがこのデバイス、そして企業全体にとって普段と異なるものあり、高度に異常であると判定しました。HTTP接続はほとんどのデジタル環境で一般的なので、この発見がなければ見逃されるところでした。

デスクトップPCに侵入した攻撃者は、Nmap、DCE-RPC、HTTPなど既存のツールやプロトコルを使用したため、他のあらゆるサイバー防衛手段では検知されませんでした。しかしCyber AIはスキャンと水平移動に関する複数の異常に気づき、確度の高い検知結果をトリガーしました。これは、Proactive Threat Notifications (PTN) によって通知される情報です。

コマンド&コントロール(C2)通信

翌日、攻撃者はVPN経由でSNMPサーバーに接続しました。この接続は、parentsのRDPクッキーを使用していました。

RDP接続の開始直後、サーバーはPastebinに接続し、暗号化された少量のデータをダウンロードしました。Pastebinはおそらく、悪意あるスクリプトをデバイスに導入するための経路として使用されたと思われます。

次に、SNMPサーバーは、SQLサーバー上のサービス (svcttl) を制御し始め、再びサービスの作成や開始を行いました。

これに続き、SQLサーバーとSNMPサーバーの両方が、未知の外部ドメインに大量のSSL接続を行いました。この接続先へのアップロードの1つは21MBありましたが、それ以外のほとんどの接続は同じパケットサイズでした。これは、他の要素とともに、接続先がC2サーバーとして使用されていたことを示しています。

図5:SQLサーバーによるビーコニングアクティビティを対象とする、Cyber AI Analyst での調査の例。

たった1つのアカウントが侵害されただけで、攻撃者はVPNに接続し、企業の内部ネットワーク上にある複数のサーバーを感染させました。

攻撃者はPastebinを使用してスクリプトをホストに導入しました。Darktraceはこれに対しアラートを発行しました。Pastebinはこの組織にとってきわめて稀だったからです。実際、こうした接続が観測されたのは初めてでした。ほとんどのセキュリティツールはこれを見逃してしまいます。Pastebinは正当なサイトで、オープンソースインテリジェンス(OSINT)によってブロックされないためです。

たとえPastebinの代わりに知名度の低い代替手段を使った場合でも(Pastebinはファイアウォールでブロックされるが、代替手段はブロックされないような環境でも)、Darktraceはまったく同じ手法で検知できたはずです。

また、このC2ビーコニングエンドポイント(dropbox16[.]com)については、オンラインで利用できるOSINT情報がありません。接続はポート443上で行われましたが、同社のシステム内で稀であることを除けば接続に注目すべき点はありませんでした。Darktraceは既知のシグネチャに頼るのではなく、非常に稀であることから警告を送信したのです。

永続性の確立

さらに1回のPastebinプルの後、攻撃者は足場をさらに大きくしようと試み、SamrCreateUser2InDomainオペレーション(エンドポイント: samr)を使用して新しいユーザーを作成することによって、権限を昇格させました。

永続性を確立するため、攻撃者は次にドメインコントローラに対するDCE-RPCコマンドを通じて、新しいユーザーを作成しました。これはデバイスにとって普段ときわめて異なるアクティビティであったため ‘New or Uncommon Occurrence’ (新規または未知の発生)モデルに対して異常スコア100%を与えられました。

Darktraceがこのアクティビティについて警告していなければ、攻撃者は引き続きファイルにアクセスしてこの会社にさらに深く侵入し、機密データを抽出したり、場合によってはランサムウェアをインストールしたりすることもできたのです。その場合、機密データの損失、評判の毀損、経済的損失につながるおそれがありました。

自律遮断(Autonomous Response)の価値

組織としては、Darktrace RESPONDをパッシブモードで使っていたため、自律的な対処はできませんでしたが、もし有効にしていた場合に実行されるはずだったアクションは確認することができます。

RESPOND は、最初に感染したデスクトップPCに対して、次の表に示す3つのアクションをとるはずでした。これらのアクションは、最初のスキャンと、最初のサービスコントロールリクエストに対応して即座に実行されるはずであったものです。

2日間の偵察と水平移動の間、RESPONDが推奨したステップはこれだけでした。これらのステップはすべて、侵入に直接関係していました。攻撃に関係ないものをブロックしようとするものはなく、この期間中にトリガーされたRESPONDアクションもありませんでした。

スキャンアクティビティ中に特定のポートへの接続をピンポイントにブロックし、感染したデスクトップPCに対して「生活パターン」を強制することで、RESPONDは攻撃者の偵察活動を麻痺させることができたはずでした。

さらに、このデバイスによって行われた不審なサービスコントロールの試みも阻止され、標的への被害も最小化されていたはずです。

RESPOND はこれらのブロックを直接、または顧客にとって最適なインテグレーション(ファイアウォールインテグレーションやNACインテグレーションなど)を通じて実現していたはずでした。

教訓

上記のような事例は、権限の低いアカウントに付与されるアクセスをコントロールすることと、セキュリティパッチを最新に保つことの重要性を示しています。このような攻撃は既存のネットワークインフラを利用するため、AIを使用せずにこれらの異常な接続を検知するのはきわめて困難です。

parentアカウントが最初に使用されてから、水平移動の最初の兆候が現れるまで、数日間の遅延がありました。侵入から内部活動の開始までのこのような休眠期間は、多くの攻撃でよく見られます。これは、攻撃者が最初にアクセスがうまくいったかどうかを確認してから、被害者のところをもう一度訪れて、スケジュールの都合がよいところでさらなる侵害を実行している高い可能性を示しています。

サーバーサイド攻撃の阻止

この事例は、現実に発生している多くの侵入を反映しています。つまり、攻撃の原因を突き止めることは簡単ではなく、また攻撃はしばしば、高度な技術を持つ、正体不明の脅威アクターによって行われるということです。

それにもかかわらず、Darktraceは攻撃サイクルの各段階、つまり最初の侵害、偵察、水平移動、足掛かりの確立、権限の昇格の検知に成功しています。もしRESPONDがアクティブモードであったならば、これらの接続をブロックするとともに、コードのリモート実行を可能にした、デスクトップPCによる最初のSQL脆弱性のエクスプロイトも完全に防ぐことができたはずでした。

翌日、自律遮断技術の威力を見たこの会社は、RESPONDをアクティブモードで運用することを決めました。

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

Darktraceによるモデル検知:

  • Device / Anomalous Nmap SMB Activity
  • Device / Network Scan - Low Anomaly Score
  • Device / Network Scan
  • Device / ICMP Address Scan
  • Device / Suspicious Network Scan Activity
  • Anomalous Connection / New or Uncommon Service Control
  • Device / Multiple Lateral Movement Model Breaches
  • Device / New User Agent To Internal Server
  • Compliance / Pastebin
  • Device / Repeated Unknown RPC Service Bind Errors
  • Anomalous Server Activity / Rare External from Server
  • Compromise / Unusual Connections to Rare Lets Encrypt
  • User / Anomalous Domain User Creation Or Addition To Group


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.

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