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製品統合について:サードパーティのEDRアラートに機械学習を導入

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12
Dec 2022
12
Dec 2022
このブログでは、EDRテクノロジーとDarktrace の統合による主なメリットを説明します。

このブログでは、Darktrace の EDR インテグレーションを検知と調査にどのように使用しているかを紹介します。4つの主要な機能について、以下に例を挙げて説明します:  

1) 既存のDarktrace情報の文脈化 –「インターネット上の異常な宛先へのデバイスのビーコンを確認した5分後にMicrosoft Defender for Endpoint (MDE) アラートが発生しました。Defender UIにピボットバックさせてください」

2) クロスデータ検知エンジニアリング –「Darktrace、一定期間内に同じエンティティ上で特定のMDEアラートとネイティブなDarktrace検知を見た場合、アラートを作成するか対処をトリガーしてください」

3) サードパーティのEDRアラートに教師なし機械学習を適用 – 「Darktrace、コンテキストを考慮して組織にとって異常な特定のMDEアラートがある場合、アラートを作成するか対処をトリガーしてください」

4) AI AnalystをトリガーするためにサードパーティEDRアラートを使用 – 「AI Analyst、この低信頼度のMDEアラートがエンドポイントに何かフラグを立てています。Defenderのアラート時にそのデバイスを深く観察し、Darktraceのデータで調査を行い、それ以上のことがあるかどうかについて結論を共有してください」 

上記ではMDEを例にしていますが、DarktraceのEDR統合機能はMDEだけでなく、例えばSentinel OneやCrowdStrike EDRなど、他のEDRにも適用されています。

Darktraceは自己学習型AIを、データがどこに存在しようともそのデータに適用します。データは、例えばEメール環境、クラウド、SaaS、OT、エンドポイント、従来ネットワークなど、どこにでも存在しています。通常、機械学習のための最大限のコンテキストを得るために、可能な限り生データに近づきたいと考えます。 

Darktraceにさらなるコンテキストをもたらすために、各テクノロジーパートナーからの価値の高い統合を活用する方法だけでなく、サードパーティのデータに自己学習型AIを適用する方法について説明します。統合や機能は多岐にわたりますが、本ブログでは主にMicrosoft Defender for Endpoint、CrowdStrike、SentinelOneを取り上げ、本稿では検知にフォーカスして説明します。 

要点 - 統合機能の設定

Darktraceはオープンプラットフォームであり、ほぼすべての機能がAPIで駆動します。当社のシステムと機械学習は、新しいタイプのデータを取り込み、既存の情報と組み合わせるのに十分な柔軟性を備えています。  

ここで言及されているEDR統合は、Darktraceによるワンクリック統合の一部です。必要なのは、EDRソリューションからの適切なレベルのAPIアクセスと、DarktraceがEDRのAPIと通信する能力だけです。このタイプの統合は数分以内にセットアップすることができます 。それは現在、追加のDarktraceのライセンスを必要としません。

図1:Darktrace Graph Security API統合のセットアップ

セットアップが完了すると同時に、さまざまな追加機能が有効になります。ここでは、主要な検知・調査に特化した機能を順を追って見ていきましょう。

既存のDarktrace情報の文脈化

最も基本的でありながら非常に有用な統合は、既存のDarktrace情報をEDRアラートで強化することです。Darktraceは、組織のイベントログで観測された、各組織が関連するテレメトリーと機械学習の時系列履歴を表示します。 

EDRの統合を有効にすると、それぞれの組織におけるEDRアラートが正しいタイミングで組織のイベントログに表示されるようになり、多くのコンテキストとネイティブEDRコンソールへのワンクリックでのピボットバックが提供されます: 

図2:Darktrace Threat VisualizerからMicrosoft Defenderへのピボット

このようなコンテキストは、調査中に1つの画面で確認できるため、非常に便利です。コンテキストは極めて重要であり、アラートを理解するのに必要な意味付けの時間やスキルを短縮することができます。

クロスデータ検知エンジニアリング

EDR統合が有効化されると、Darktraceは、新しいEDRアラートを活用した追加の検知セットを有効にします。これは即時利用できるもので、さらなる検知エンジニアリングは必要ありません。しかし、経験値が高いユーザーがこれらをカスタムメトリクスとして活用したい場合、新しいEDR情報はカスタム検知エンジニアリングのためにバックグラウンドで利用できるようにされていることは言及する価値があります。

ここでは、追加のEDRアラートによって提供される追加のコンテキストによって、より洗練された検知、つまり主に悪意のある活動をより高い信頼性で検知することができるようになる、ということが重要です。ネットワーク検知で、珍しいプロトコルやポートの組み合わせでインターネット上の珍しい宛先へのビーコンを検知するのは素晴らしいことですが、同じデバイスでビーコン検知の3分前にCrowdStrikeが潜在的に敵対的なファイルやプロセスを検知したことをDarktraceで確認すると、検知の優先順位付けやその後の調査に大きく役立ちます。

以下は、Darktraceでこのような表示をする例です:

図3:Threat Visualizerにおける結合モデルブリーチの例

サードパーティーのEDRアラートに教師なし機械学習を適用

DarktraceでEDRアラートを見始めたら、教師なし機械学習を適用して、それを他のデータと同様に扱うことができます。つまり、あるEDR検知が、問題のある各デバイスに対してどの程度異常であるかを理解することができるのです。これは非常に強力で、継続的なEDRアラートチューニングを必要とすることなくノイズの多いアラートを減らすことができ、新たな検知機能の世界を広げることができます。

例として、特定のデバイスのEDRから低レベルのマルウェアの警告が出続けているとします。これはEDRの偽陽性かもしれないし、セキュリティチームにとって興味のないことかもしれませんが、EDRをさらにチューニングしてこのノイズとなるアラートを取り除くためのリソースや知識がない可能性があります。

Darktraceは、デバイスのイベントログにコンテキスト情報としてこれを追加し続けますが、デバイス、EDRアラート、および環境全体のコンテキストに応じて、この特定のデバイス上の特定のEDRマルウェアアラートが異常でなくなった場合、そのアラートを停止することができます。しかし、その特定のEDRアラートが別のデバイス、または別のコンテキストで同じデバイスに表示された場合、与えられたコンテキストで異常であるため、再びフラグが立つ可能性があります。

Darktraceは、さらに一歩進んで、これらの異常なEDRアラートを、例えばネットワークのような他のDarktraceのカバーエリアで見られる異常なアクティビティと組み合わせます。例えば、異常なEDRアラートと異常な横移動の試みを組み合わせることで、「異常」がどのようなものかを事前に正確に定義することなく、活発なサイバー攻撃を強く示唆する、高精度でデータセット間の異常な出来事を見つけることができます。

図4:Darktraceの教師なし機械学習によるEDRとネットワークの複合検知

AI AnalystをトリガーするためにサードパーティEDRアラートを使用

これまで述べてきたことは、初期検知の精度を高め、コンテキストを追加し、アラートノイズをカットするのに適しています。しかし、それだけに留まらず、サードパーティのEDRアラートを使って、調査エンジンであるAI Analystを起動することができるようになりました。

Cyber AI Analystは、典型的なレベル1およびレベル2のセキュリティオペレーションセンター(SOC)のワークフローを複製し、自動化することができます。通常、Darktraceによるネイティブな検知があるたびにトリガーされます。これは、プレイブックが静的に定義されているSOARではなく、AI Analystは、仮説を構築し、データを収集し、データを評価し、個々のシナリオと調査のコンテキストに基づいてその結果について報告します。 

Darktraceは、EDRアラートを調査の出発点として使用することができ、取り込まれたすべてのEDRアラートがAI Analystをトリガーするようになります。これは、人間のアナリストに(低レベルの)EDRアラートを渡して、次のように伝えるのと似ています: 「Darktraceの情報を見て、このEDRアラートに何かあるのかないのか結論を出してみてください」

AI Analystはその後、EDRアラートを引き起こしたエンティティを調べ、そのエンティティに関する利用可能なすべてのDarktraceデータを、そのEDRアラートに照らして一定期間にわたって調査します。その調査のためにDarktrace自体の外にピボット(例えば、Microsoftコンソールに戻る)せず、Darktraceでネイティブに利用可能なすべてのコンテキストを調べます。このEDRアラートにはもっと大きなインシデントが関連していると結論づけた場合、それについて報告し、明確にフラグを立てます。もちろん、レポートはPDFとして直接ダウンロードし、他の関係者と共有することができます。

これは様々な理由で便利なのですが、主にセキュリティ運用をさらに自動化し、人間のチームからのプレッシャーを軽減するためです。AI Analystの調査機能は、これまで説明してきたこと(EDRの検知と他のカバーエリアからの検知を組み合わせ、その結果を適用する)の上に成り立っています。

しかし、EDRアラートのフォローアップを行うための人的リソースがないような、深刻度の低いEDRアラートのフォローアップを行う場合にも便利です。

以下のスクリーンショットは、EDRアラートをきっかけにAI Analystの調査が終了した際の例です:

図5:第三者データで訓練されたAI Analystのインシデント

EDRの統合がもたらす影響

これらすべての背景には、人間のチームを増強し、時間を節約し、セキュリティの自動化を促進する目的があります。

サードパーティのエンドポイントアラートを取り込み、それを既存のインテリジェンスと組み合わせ、教師なし機械学習を適用することで、さらなるセキュリティの自動化を実現します。 

アナリストは、調査のためにコンソールを切り替える必要はありません。アナリストは、クラウドやEメールシステム、ゼロトラストアーキテクチャ、ITおよびOTネットワークなど、すでに強力な検知機能を備えているDarktraceの検知機能と組み合わせて、異常なエンドポイントアラートを探す高信頼度の検知機能を活用できます。 

私たちの経験では、これは干し草の山の中の針をピンポイントで検知するようなもので、ノイズをカットし、平均検知時間と平均調査時間を劇的に短縮することができます。

エンドポイントとの統合を有効にすると、Darktraceでは、このすべてが即座に実行されます。機械学習を機能させるために、データサイエンティストは必要ありません。また、カスタマイズされた、意味のある検知結果をもたらすために、検知エンジニアや脅威ハンターも必要ありません。私たちは、検知・調査ソリューションを利用する際の参入障壁を、必要なスキルや経験という点で低くしたいと考えています。Darktraceのシステムは、柔軟性、透明性、オープン性を備えています。つまり、上級ユーザーは、数回のクリックで、さまざまなデータセットで教師なし機械学習を活用し、独自の複合検知を作成できるのです。

もちろん、今回取り上げた以外にもエンドポイントの統合機能はあり、今後のブログ記事で紹介していく予定です。

INSIDE THE SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
AUTHOR
ABOUT ThE AUTHOR
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

Stemming the Citrix Bleed Vulnerability with Darktrace’s ActiveAI Platform

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28
May 2024

What is Citrix Bleed?

Since August 2023, cyber threat actors have been actively exploiting one of the most significant critical vulnerabilities disclosed in recent years: Citrix Bleed. Citrix Bleed, also known as CVE-2023-4966, remained undiscovered and even unpatched for several months, resulting in a wide range of security incidents across business and government sectors [1].

How does Citrix Bleed vulnerability work?

The vulnerability, which impacts the Citrix Netscaler Gateway and Netscaler ADC products, allows for outside parties to hijack legitimate user sessions, thereby bypassing password and multifactor authentication (MFA) requirements.

When used as a means of initial network access, the vulnerability has resulted in the exfiltration of sensitive data, as in the case of Xfinity, and even the deployment of ransomware variants including Lockbit [2]. Although Citrix has released a patch to address the vulnerability, slow patching procedures and the widespread use of these products has resulted in the continuing exploitation of Citrix Bleed into 2024 [3].

How Does Darktrace Handle Citrix Bleed?

Darktrace has demonstrated its proficiency in handling the exploitation of Citrix Bleed since it was disclosed back in 2023; its anomaly-based approach allows it to efficiently identify and inhibit post-exploitation activity as soon as it surfaces.  Rather than relying upon traditional rules and signatures, Darktrace’s Self-Learning AI enables it to understand the subtle deviations in a device’s behavior that would indicate an emerging compromise, thus allowing it to detect anomalous activity related to the exploitation of Citrix Bleed.

In late 2023, Darktrace identified an instance of Citrix Bleed exploitation on a customer network. As this customer had subscribed to the Proactive Threat Notification (PTN) service, the suspicious network activity surrounding the compromise was escalated to Darktrace’s Security Operation Center (SOC) for triage and investigation by Darktrace Analysts, who then alerted the customer’s security team to the incident.

Darktrace’s Coverage

Initial Access and Beaconing of Citrix Bleed

Darktrace’s initial detection of indicators of compromise (IoCs) associated with the exploitation of Citrix Bleed actually came a few days prior to the SOC alert, with unusual external connectivity observed from a critical server. The suspicious connection in question, a SSH connection to the rare external IP 168.100.9[.]137, lasted several hours and utilized the Windows PuTTY client. Darktrace also identified an additional suspicious IP, namely 45.134.26[.]2, attempting to contact the server. Both rare endpoints had been linked with the exploitation of the Citrix Bleed vulnerability by multiple open-source intelligence (OSINT) vendors [4] [5].

Darktrace model alert highlighting an affected device making an unusual SSH connection to 168.100.9[.]137 via port 22.
Figure 1: Darktrace model alert highlighting an affected device making an unusual SSH connection to 168.100.9[.]137 via port 22.

As Darktrace is designed to identify network-level anomalies, rather than monitor edge infrastructure, the initial exploitation via the typical HTTP buffer overflow associated with this vulnerability fell outside the scope of Darktrace’s visibility. However, the aforementioned suspicious connectivity likely constituted initial access and beaconing activity following the successful exploitation of Citrix Bleed.

Command and Control (C2) and Payload Download

Around the same time, Darktrace also detected other devices on the customer’s network conducting external connectivity to various endpoints associated with remote management and IT services, including Action1, ScreenConnect and Fixme IT. Additionally, Darktrace observed devices downloading suspicious executable files, including “tniwinagent.exe”, which is associated with the tool Total Network Inventory. While this tool is typically used for auditing and inventory management purposes, it could also be leveraged by attackers for the purpose of lateral movement.

防衛回避

In the days surrounding this compromise, Darktrace observed multiple devices engaging in potential defense evasion tactics using the ScreenConnect and Fixme IT services. Although ScreenConnect is a legitimate remote management tool, it has also been used by threat actors to carry out C2 communication [6]. ScreenConnect itself was the subject of a separate critical vulnerability which Darktrace investigated in early 2024. Meanwhile, CISA observed that domains associated with Fixme It (“fixme[.]it”) have been used by threat actors attempting to exploit the Citrix Bleed vulnerability [7].

Reconnaissance and Lateral Movement

A few days after the detection of the initial beaconing communication, Darktrace identified several devices on the customer’s network carrying out reconnaissance and lateral movement activity. This included SMB writes of “PSEXESVC.exe”, network scanning, DCE-RPC binds of numerous internal devices to IPC$ shares and the transfer of compromise-related tools. It was at this point that Darktrace’s Self-Learning AI deemed the activity to be likely indicative of an ongoing compromise and several Enhanced Monitoring models alerted, triggering the aforementioned PTNs and investigation by Darktrace’s SOC.

Darktrace observed a server on the network initiating a wide range of connections to more than 600 internal IPs across several critical ports, suggesting port scanning, as well as conducting unexpected DCE-RPC service control (svcctl) activity on multiple internal devices, amongst them domain controllers. Additionally, several binds to server service (srvsvc) and security account manager (samr) endpoints via IPC$ shares on destination devices were detected, indicating further reconnaissance activity. The querying of these endpoints was also observed through RPC commands to enumerate services running on the device, as well as Security Account Manager (SAM) accounts.  

Darktrace also identified devices performing SMB writes of the WinRAR data compression tool, in what likely represented preparation for the compression of data prior to data exfiltration. Further SMB file writes were observed around this time including PSEXESVC.exe, which was ultimately used by attackers to conduct remote code execution, and one device was observed making widespread failed NTLM authentication attempts on the network, indicating NTLM brute-forcing. Darktrace observed several devices using administrative credentials to carry out the above activity.

In addition to the transfer of tools and executables via SMB, Darktrace also identified numerous devices deleting files through SMB around this time. In one example, an MSI file associated with the patch management and remediation service, Action1, was deleted by an attacker. This legitimate security tool, if leveraged by attackers, could be used to uncover additional vulnerabilities on target networks.

A server on the customer’s network was also observed writing the file “m.exe” to multiple internal devices. OSINT investigation into the executable indicated that it could be a malicious tool used to prevent antivirus programs from launching or running on a network [8].

Impact and Data Exfiltration

Following the initial steps of the breach chain, Darktrace observed numerous devices on the customer’s network engaging in data exfiltration and impact events, resulting in additional PTN alerts and a SOC investigation into data egress. Specifically, two servers on the network proceeded to read and download large volumes of data via SMB from multiple internal devices over the course of a few hours. These hosts sent large outbound volumes of data to MEGA file storage sites using TLS/SSL over port 443. Darktrace also identified the use of additional file storage services during this exfiltration event, including 4sync, file[.]io, and easyupload[.]io. In total the threat actor exfiltrated over 8.5 GB of data from the customer’s network.

Darktrace Cyber AI Analyst investigation highlighting the details of a data exfiltration attempt.
Figure 2: Darktrace Cyber AI Analyst investigation highlighting the details of a data exfiltration attempt.

Finally, Darktrace detected a user account within the customer’s Software-as-a-Service (SaaS) environment conducting several suspicious Office365 and AzureAD actions from a rare IP for the network, including uncommon file reads, creations and the deletion of a large number of files.

Unfortunately for the customer in this case, Darktrace RESPOND™ was not enabled on the network and the post-exploitation activity was able to progress until the customer was made aware of the attack by Darktrace’s SOC team. Had RESPOND been active and configured in autonomous response mode at the time of the attack, it would have been able to promptly contain the post-exploitation activity by blocking external connections, shutting down any C2 activity and preventing the download of suspicious files, blocking incoming traffic, and enforcing a learned ‘pattern of life’ on offending devices.

結論

Given the widespread use of Netscaler Gateway and Netscaler ADC, Citrix Bleed remains an impactful and potentially disruptive vulnerability that will likely continue to affect organizations who fail to address affected assets. In this instance, Darktrace demonstrated its ability to track and inhibit malicious activity stemming from Citrix Bleed exploitation, enabling the customer to identify affected devices and enact their own remediation.

Darktrace’s anomaly-based approach to threat detection allows it to identify such post-exploitation activity resulting from the exploitation of a vulnerability, regardless of whether it is a known CVE or a zero-day threat. Unlike traditional security tools that rely on existing threat intelligence and rules and signatures, Darktrace’s ability to identify the subtle deviations in a compromised device’s behavior gives it a unique advantage when it comes to identifying emerging threats.

Credit to Vivek Rajan, Cyber Analyst, Adam Potter, Cyber Analyst

付録

Darktrace モデルカバレッジ

Device / Suspicious SMB Scanning Activity

Device / ICMP Address Scan

Device / Possible SMB/NTLM Reconnaissance

Device / Network Scan

Device / SMB Lateral Movement

Device / Possible SMB/NTLM Brute Force

Device / Suspicious Network Scan Activity

User / New Admin Credentials on Server

Anomalous File / Internal::Unusual Internal EXE File Transfer

Compliance / SMB Drive Write

Device / New or Unusual Remote Command Execution

Anomalous Connection / New or Uncommon Service Control

Anomalous Connection / Rare WinRM Incoming

Anomalous Connection / Unusual Admin SMB Session

Device / Unauthorised Device

User / New Admin Credentials on Server

Anomalous Server Activity / Outgoing from Server

Device / Long Agent Connection to New Endpoint

Anomalous Connection / Multiple Connections to New External TCP Port

Device / New or Uncommon SMB Named Pipe

Device / Multiple Lateral Movement Model Breaches

Device / Large Number of Model Breaches

Compliance / Remote Management Tool On Server

Device / Anomalous RDP Followed By Multiple Model Breaches

Device / SMB Session Brute Force (Admin)

Device / New User Agent

Compromise / Large Number of Suspicious Failed Connections

Unusual Activity / Unusual External Data Transfer

Unusual Activity / Enhanced Unusual External Data Transfer

Device / Increased External Connectivity

Unusual Activity / Unusual External Data to New Endpoints

Anomalous Connection / Data Sent to Rare Domain

Anomalous Connection / Uncommon 1 GiB Outbound

Anomalous Connection / Active Remote Desktop Tunnel

Anomalous Server Activity / Anomalous External Activity from Critical Network Device

Compliance / Possible Unencrypted Password File On Server

Anomalous Connection / Suspicious Read Write Ratio and Rare External

Device / Reverse DNS Sweep]

Unusual Activity / Possible RPC Recon Activity

Anomalous File / Internal::Executable Uploaded to DC

Compliance / SMB Version 1 Usage

Darktrace AI Analyst Incidents

Scanning of Multiple Devices

Suspicious Remote Service Control Activity

SMB Writes of Suspicious Files to Multiple Devices

Possible SSL Command and Control to Multiple Devices

Extensive Suspicious DCE-RPC Activity

Suspicious DCE-RPC Activity

Internal Downloads and External Uploads

Unusual External Data Transfer

Unusual External Data Transfer to Multiple Related Endpoints

MITRE ATT&CK マッピング

Technique – Tactic – ID – Sub technique of

Network Scanning – Reconnaissance - T1595 - T1595.002

Valid Accounts – Defense Evasion, Persistence, Privilege Escalation, Initial Access – T1078 – N/A

Remote Access Software – Command and Control – T1219 – N/A

Lateral Tool Transfer – Lateral Movement – T1570 – N/A

Data Transfers – Exfiltration – T1567 – T1567.002

Compressed Data – Exfiltration – T1030 – N/A

NTLM Brute Force – Brute Force – T1110 - T1110.001

AntiVirus Deflection – T1553 - NA

Ingress Tool Transfer   - COMMAND AND CONTROL - T1105 - NA

Indicators of Compromise (IoCs)

204.155.149[.]37 – IP – Possible Malicious Endpoint

199.80.53[.]177 – IP – Possible Malicious Endpoint

168.100.9[.]137 – IP – Malicious Endpoint

45.134.26[.]2 – IP – Malicious Endpoint

13.35.147[.]18 – IP – Likely Malicious Endpoint

13.248.193[.]251 – IP – Possible Malicious Endpoint

76.223.1[.]166 – IP – Possible Malicious Endpoint

179.60.147[.]10 – IP – Likely Malicious Endpoint

185.220.101[.]25 – IP – Likely Malicious Endpoint

141.255.167[.]250 – IP – Malicious Endpoint

106.71.177[.]68 – IP – Possible Malicious Endpoint

cat2.hbwrapper[.]com – Hostname – Likely Malicious Endpoint

aj1090[.]online – Hostname – Likely Malicious Endpoint

dc535[.]4sync[.]com – Hostname – Likely Malicious Endpoint

204.155.149[.]140 – IP - Likely Malicious Endpoint

204.155.149[.]132 – IP - Likely Malicious Endpoint

204.155.145[.]52 – IP - Likely Malicious Endpoint

204.155.145[.]49 – IP - Likely Malicious Endpoint

参考文献

  1. https://www.axios.com/2024/01/02/citrix-bleed-security-hacks-impact
  2. https://www.csoonline.com/article/1267774/hackers-steal-data-from-millions-of-xfinity-customers-via-citrix-bleed-vulnerability.html
  3. https://www.cybersecuritydive.com/news/citrixbleed-security-critical-vulnerability/702505/
  4. https://www.virustotal.com/gui/ip-address/168.100.9.137
  5. https://www.virustotal.com/gui/ip-address/45.134.26.2
  6. https://www.trendmicro.com/en_us/research/24/b/threat-actor-groups-including-black-basta-are-exploiting-recent-.html
  7. https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-325a
  8. https://www.file.net/process/m.exe.html
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著者について
Vivek Rajan
Cyber Analyst

Blog

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How to Protect your Organization Against Microsoft Teams Phishing Attacks

Default blog imageDefault blog image
21
May 2024

The problem: Microsoft Teams phishing attacks are on the rise

Around 83% of Fortune 500 companies rely on Microsoft Office products and services1, with Microsoft Teams and Microsoft SharePoint in particular emerging as critical platforms to the business operations of the everyday workplace. Researchers across the threat landscape have begun to observe these legitimate services being leveraged more and more by malicious actors as an initial access method.

As Teams becomes a more prominent feature of the workplace many employees rely on it for daily internal and external communication, even surpassing email usage in some organizations. As Microsoft2 states, "Teams changes your relationship with email. When your whole group is working in Teams, it means you'll all get fewer emails. And you'll spend less time in your inbox, because you'll use Teams for more of your conversations."

However, Teams can be exploited to send targeted phishing messages to individuals either internally or externally, while appearing legitimate and safe. Users might receive an external message request from a Teams account claiming to be an IT support service or otherwise affiliated with the organization. Once a user has accepted, the threat actor can launch a social engineering campaign or deliver a malicious payload. As a primarily internal tool there is naturally less training and security awareness around Teams – due to the nature of the channel it is assumed to be a trusted source, meaning that social engineering is already one step ahead.

Screenshot of a Microsoft Teams message request from a Midnight Blizzard-controlled account (courtesy of Microsoft)
Figure 1: Screenshot of a Microsoft Teams message request from a Midnight Blizzard-controlled account (courtesy of Microsoft)

Microsoft Teams Phishing Examples

Microsoft has identified several major phishing attacks using Teams within the past year.

In July 2023, Microsoft announced that the threat actor known as Midnight Blizzard – identified by the United States as a Russian state-sponsored group – had launched a series of phishing campaigns via Teams with the aim of stealing user credentials. These attacks used previously compromised Microsoft 365 accounts and set up new domain names that impersonated legitimate IT support organizations. The threat actors then used social engineering tactics to trick targeted users into sharing their credentials via Teams, enabling them to access sensitive data.  

At a similar time, threat actor Storm-0324 was observed sending phishing lures via Teams containing links to malicious SharePoint-hosted files. The group targeted organizations that allow Teams users to interact and share files externally. Storm-0324’s goal is to gain initial access to hand over to other threat actors to pursue more dangerous follow-on attacks like ransomware.

Darktrace がMicrosoft Teamsのフィッシングを阻止する方法について、さらに詳しく知りたい方は、ブログをお読みください: 餌に喰いつくな:Darktrace Microsoft Teamsのフィッシング攻撃を阻止する方法

The market: Existing Microsoft Teams security solutions are insufficient

Microsoft’s native Teams security focuses on payloads, namely links and attachments, as the principal malicious component of any phishing. These payloads are relatively straightforward to detect with their experience in anti-virus, sandboxing, and IOCs. However, this approach is unable to intervene before the stage at which payloads are delivered, before the user even gets the chance to accept or deny an external message request. At the same time, it risks missing more subtle threats that don’t include attachments or links – like early stage phishing, which is pure social engineering – or completely new payloads.

Equally, the market offering for Teams security is limited. Security solutions available on the market are always payload-focused, rather than taking into account the content and context in which a link or attachment is sent. Answering questions like:

  • Does it make sense for these two accounts to speak to each other?
  • Are there any linguistic indicators of inducement?

Furthermore, they do not correlate with email to track threats across multiple communication environments which could signal a wider campaign. Effectively, other market solutions aren’t adding extra value – they are protecting against the same types of threats that Microsoft is already covering by default.

The other aspect of Teams security that native and market solutions fail to address is the account itself. As well as focusing on Teams threats, it’s important to analyze messages to understand the normal mode of communication for a user, and spot when a user’s Teams activity might signal account takeover.

The solution: How Darktrace protects Microsoft Teams against sophisticated threats

With its biggest update to Darktrace/Email ever, Darktrace now offers support for Microsoft Teams. With that, we are bringing the same AI philosophy that protects your email and accounts to your messaging environment.  

Our Self-Learning AI looks at content and context for every communication, whether that’s sent in an email or Teams message. It looks at actual user behavior, including language patterns, relationship history of sender and recipient, tone and payloads, to understand if a message poses a threat. This approach allows Darktrace to detect threats such as social engineering and payloadless attacks using visibility and forensic capabilities that Microsoft security doesn’t currently offer, as well as early symptoms of account compromise.  

Unlike market solutions, Darktrace doesn’t offer a siloed approach to Teams security. Data and signals from Teams are shared across email to inform detection, and also with the wider Darktrace ActiveAI security platform. By correlating information from email and Teams with network and apps security, Darktrace is able to better identify suspicious Teams activity and vice versa.  

Interested in the other ways Darktrace/Email augments threat detection? Read our latest blog on how improving the quality of end-user reporting can decrease the burden on the SOC. To find our more about Darktrace's enduring partnership with Microsoft, click here.

参考文献

[1] Essential Microsoft Office Statistics in 2024

[2] Microsoft blog, Microsoft Teams and email, living in harmony, 2024

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Carlos Gray
Product Manager
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