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Living off the Land (環境に寄生する)手法:ハッカー達はあなたの環境にどうやって紛れ込むのか

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03
Nov 2021
03
Nov 2021

サイバー犯罪者達はそれぞれの襲撃ごとに専用のマルウェアを記述する必要はありません。その組織のインフラを攻撃に利用したほうが安上がりであり、簡単であり、より効果的なことが多いのです。 ‘Living off the Land’ (環境に寄生する)と呼ばれているこの手法では、脅威アクター達は標的とした組織のデジタル環境内に既にあるツールを使用してサイバーキルチェーンを進めていきます。

こうした不正な目的のために最もよく悪用されるツールとしては、Powershell、Windows Management Interface (WMI)、PsExecがあります。これらのツールはネットワーク管理者の日々のルーチン作業の一部として頻繁に使用されており、静的なルールやシグネチャに依存する従来のセキュリティツールは、多くの場合正当な使用と悪意ある使用を区別するのに苦労します。

Living off the Land という言葉が最初に使われたのは2013年でしたが、こうしたツール、テクニック、および手順(TTP)は近年ブームとなっています。その理由の一つは、防御セキュリティのこれまでのアプローチ(例:以前の攻撃で遭遇したファイルハッシュ、ドメイン、およびその他の脅威の痕跡のブラックリスト化)がこれらの攻撃の識別に不十分であるからです。こうして、これらのステルス性の、しばしばファイルレスな攻撃はメインストリームに進出してきました。

そして困ったことに、Living off the Land攻撃は高度に組織化された、標的を絞ったハッキングに特に実績があるのです。APTグループは長いことLiving off the LandのTTPを好んできました。検知を免れるのが最優先であるためです。そして現在の傾向として、多くのランサムウェアグループが汎用品のマルウェアを使う代わりに、Living off the Landテクニックに大きく依存した、人間が操作するランサムウェアを選択しつつあります。

Living off the Land 攻撃の特徴

Living off the Land攻撃において、脅威アクターが組織のインフラを使って攻撃を始めるには、彼らは標的のシステム上でコマンドを実行できなければなりません。つまり、Living off the Land攻撃とはネットワーク偵察、水平移動、永続化のための感染後のフレームワークであると言えます。

デバイスが一旦感染すれば、攻撃者は何百ものシステムツールを自由に使えます。これらはシステム上にプリインストールされているものもあれば、Microsoftの署名付きバイナリでダウンロードされるものもあります。そして、攻撃者の手によって、ネットワーク上の他の信頼されるサードパーティ製管理ツールも友から敵へと変貌します。

Living off the Land テクニックは進化するため、単一の典型的な 攻撃パターンを特定することは困難です。しかし、これらのTTPは大きくカテゴリ分けすることができます。

Microsoft署名付きLiving off the Land TTP

Microsoftはビジネスの世界で業界を超えて遍在しています。Living off the Land Binaries and Scripts (LOLBAS) プロジェクトでは、Living off the Land 攻撃においてAPTグループが使用する機能を含むすべてのMicrosoft署名付きバイナリおよびスクリプトを文書化することを目的としています。これまでに、それぞれ異なる不正目的に利用される恐れのある、135のシステムツールがこのリストに掲載されています。これらには新しいユーザーアカウントの作成、データ圧縮および抜き出し、システム情報の収集、ターゲットシステム上でのプロセスの起動、果てはセキュリティサービスの無効化までが含まれています。プリインストール済みの脆弱なツールについてのMicrosoftのドキュメンテーション、そしてLOLBASプロジェクトのリストはどちらも拡大中であり、すべてを網羅することはできないでしょう。

コマンドライン

ターゲットに悪意あるペイロードを届ける方法に関しては、最近の研究では WMI (WMIC.exe)、コマンドラインツール (cmd.exe)、そしてPowerShell (powershell.exe) が最もよく攻撃者に使われていることがわかっています。これらのよく悪用されるコマンドラインユーティリティは、セキュリティ設定やシステムプロパティの変更、ネットワークやデバイスステータスについての機密性情報の提供、そしてデバイス間でファイルの転送や実行を行わせるのに使用されています。

具体的には、これらコマンドライングループには3つの主要な特徴が共通しています:

  1. Windowsシステム上に既にある。
  2. ほとんどの管理者や社内プロセスによって日常のタスクに頻繁に使用されている。
  3. それぞれのコア機能を、ディスクにデータを書き込むことなく実行できる。

Mimikatz

Mimikatzはほとんどのシステムにプリインストールされていない点が他のツールとは異なります。これはパスワード、ハッシュ、PIN、Kerberosチケットのダンプに使われるオープンソースユーティリティです。一部のネットワーク管理者は脆弱性評価にMimikatzを使っているケースもありますが、Windowsシステムにプリインストールされているものではありません。

しかしMimikatz のダウンロード、インストール、使用を検知する従来型のセキュリティアプローチでは多くの場合不十分です。Mimikatzのようなツールを隠すための、検証済みの詳しく文書化されたさまざまなテクニックが存在しており、それほど高度でない攻撃者であっても文字列またはハッシュベースの検知を回避することは可能です。

Living off the Land攻撃と戦う自己学習型AI

Living off the Land テクニックは犯罪者を組織のデジタル環境に溶け込ませるのにきわめて効果的であることが実証されています。1つのデジタルエコシステムのログには、日々何百万もの認証、ネットワークツール、プロセスが記録されることも珍しくありません。この膨大なデジタルノイズの中から正当なツールの悪意ある利用をどうやって特定することができるでしょうか?

ほとんどの脅威同様、基本的なネットワーク衛生管理は最初のステップです。これには最小権限の原則の適用、必要のないすべてのプログラムを無効化する、ソフトウェアホワイトリストを設定する、アセットおよびアプリケーションの在庫管理を実施する、などが含まれます。しかし、これらの対策は正しい方向に向けた第一歩ではあるものの、高度な攻撃者なら十分な時間があれば必ずこれらをすり抜けることができるでしょう。

自己学習型AI技術は、組織内のインフラを悪用する攻撃者に光を当てるための基礎となっています。AIは、あらゆるデバイスやユーザーの「生活パターン」を理解し、組織固有のデジタル環境をゼロから学習します。そのため、Living off the Land攻撃は、一連の微妙な逸脱からリアルタイムで特定されます。例えば、新しいクレデンシャルやSMB/DCE-RPCの異常な使用などが挙げられます。

それぞれのビジネスに対する深い理解により、他のツールのレーダーには引っかからない攻撃も特定することができます。Living off the Land攻撃に対し、AIは特定のツールの利用がその組織にとって正常であることを認識しつつも、そのツールの使われ方によっては一見無害な動作も間違いなく悪性であることを識別できるのです。

たとえば、自己学習型AIが Powershell ユーザーエージェントの頻繁な使用を複数のデバイスで観測したとしても、そのユーザーエージェントが普段と異なる時間に観測されたときにのみインシデントを報告します。

同様に、Darktraceは、毎日何千ものデバイスの組み合わせの間で送信されるWMIコマンドを観察するかもしれませんが、コマンドの送信元と送信先の双方にとって珍しい場合にのみ、そのような活動に対して警告を発します。

そしてMimikatz悪用のかすかな兆候、たとえば新しい認証情報の使用や珍しいSMBトラフィックなども、インフラ内の通常のオペレーションに埋もれてしまうことはありません。

Living off the Landテクニックは当分なくならないでしょう。これを踏まえて、多くのセキュリティチームは過去の攻撃データに頼って次の攻撃を発見しようとするレガシーベースの防御から脱却し、周囲環境についての個別の、また変化する理解をもとに脅威の兆候であるかすかな逸脱を、その脅威が正当なツールを使ったものであっても検知する、AIに移行しつつあります。

この脅威事例についての考察およびMITRE ATT&CKマッピングにはDarktraceアナリストIsabel Finn とPaul Jennings が協力しました。

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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.
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Oakley Cox
Analyst Technical Director, APAC

Oakley is a technical expert with 5 years’ experience as a Cyber Analyst. After leading a team of Cyber Analysts at the Cambridge headquarters, he relocated to New Zealand and now oversees the defense of critical infrastructure and industrial control systems across the APAC region. His research into cyber-physical security has been published by Cyber Security journals and CISA. Oakley is GIAC certified in Response and Industrial Defense (GRID), and has a Doctorate (PhD) from the University of Oxford.

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Inside the SOC

How Abuse of ‘PerfectData Software’ May Create a Perfect Storm: An Emerging Trend in Account Takeovers

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05
Jun 2023

Amidst the ever-changing threat landscape, new tactics, techniques, and procedures (TTPs) seem to emerge daily, creating extreme challenges for security teams. The broad range of attack methods utilized by attackers seems to present an insurmountable problem: how do you defend against a playbook that does not yet exist?

Faced with the growing number of novel and uncommon attack methods, it is essential for organizations to adopt a security solution able to detect threats based on their anomalies, rather than relying on threat intelligence alone.   

In March 2023, Darktrace observed an emerging trend in the use of an application known as ‘PerfectData Software’ for probable malicious purposes in several Microsoft 365 account takeovers.

Using its anomaly-based detection, Darktrace DETECT™ was able to identify the activity chain surrounding the use of this application, potentially uncovering a novel piece of threat actor tradecraft in the process.

Microsoft 365 Intrusions

In recent years, Microsoft’s Software-as-a-Service (SaaS) suite, Microsoft 365, along with its built-in identity and access management (IAM) service, Azure Active Directory (Azure AD), have been heavily targeted by threat actors due to their near-ubiquitous usage across industries. Four out of every five Fortune 500 companies, for example, use Microsoft 365 services [1].  

Malicious actors typically gain entry to organizations’ Microsoft 365 environments by abusing either stolen account credentials or stolen session cookies [2]. Once inside, actors can access sensitive data within mailboxes or SharePoint repositories, and send out emails or Teams messages. This activity can often result in serious financial harm, especially in cases where the malicious actor’s end-goal is to elicit fraudulent transactions.  

Darktrace regularly observes malicious actors behaving in predictable ways once they gain access to customer Microsoft 365 environment. One typical example is the creation of new inbox rules and sending deceitful emails intended to convince recipients to carry out subsequent actions, such as following a malicious link or providing sensitive information. It is also common for actors to register new applications in Azure AD so that they can be used to conduct follow-up activities, like mass-mailing or data theft. The registration of applications in Azure AD therefore seems to be a relatively predictable threat actor behavior [3][4]. Darktrace DETECT understands that unusual application registrations in Azure AD may constitute a deviation in expected behavior, and therefore a possible indicator of account compromise.

These registrations of applications in Azure AD are evidenced by creations of, as well as assignments of permissions to, Service Principals in Azure AD. Darktrace has detected a growing trend in actors creating and assigning permissions to a Service Principal named ‘PerfectData Software’. Further investigation of this Azure AD activity revealed it to be part of an ongoing account takeover. 

 ‘PerfectData Software’ Activity 

Darktrace observed variations of the following pattern of activity relating to an application named ‘PerfectData Software’ within its customer base:

  1. Actor signs in to a Microsoft 365 account from an endpoint associated with a Virtual Private Server (VPS) or Virtual Private Network (VPN) service
  2. Actor registers an application called 'PerfectData Software' with Azure AD, and then grants permissions to the application
  3. Actor accesses mailbox data and creates inbox rule 

In two separate incidents, malicious actors were observed conducting their activities from endpoints associated with VPN services (HideMyAss (HMA) VPN and Surfshark VPN, respectively) and from endpoints within the Autonomous System AS396073 MAJESTIC-HOSTING-01. 

In March 2023, Darktrace observed a malicious actor signing in to a Microsoft 365 account from a Kuwait-based IP address within the Autonomous System, AS198605 AVAST Software s.r.o. This IP address is associated with the VPN service, HMA VPN. Over the next couple of days, an actor (likely the same malicious actor) signed in to the account several more times from two different Nigeria-based endpoints, as well as a VPS-related endpoint and a HMA VPN endpoint. 

During their login sessions, the actor performed a variety of actions. First, they created and assigned permissions to a Service Principal named ‘PerfectData Software’. This Service Principal creation represents the registration of an application called ‘PerfectData Software’ in Azure AD.  Although the reason for registering this application is unclear, within a few days the actor registered and granted permission to another application, ‘Newsletter Software Supermailer’, and created a new inbox rule names ‘s’ on the mailbox of the hijacked account. This inbox rule moved emails meeting certain conditions to a folder named ‘RSS Subscription. The ‘Newsletter Software Supermailer’ application was likely registered by the actor to facilitate mass-mailing activity.

Immediately after these actions, Darktrace detected the actor sending out thousands of malicious emails from the account. The emails included an attachment named ‘Credit Transfer Copy.html’, which contained a suspicious link. Further investigation revealed that the customer’s network had received several fake invoice emails prior to this initial intrusion activity. Additionally, there was an unusually high volume of failed logins to the compromised account around the time of the initial access. 

Figure 1: Advanced Search logs depicting the steps which the actor took after logging in to a user’s Microsoft 365 account.
Figure 1: Advanced Search logs depicting the steps which the actor took after logging in to a user’s Microsoft 365 account.

In a separate case also observed by Darktrace in March 2023, a malicious actor was observed signing in to a Microsoft 365 account from an endpoint within the Autonomous System, AS397086 LAYER-HOST-HOUSTON. The endpoint appears to be related to the VPN service, Surfshark VPN. This login was followed by several failed and successful logins from a VPS-related within the Autonomous System, AS396073 MAJESTIC-HOSTING-01. The actor was then seen registering and assigning permissions to an application called ‘PerfectData Software’. As with the previous example, the motives for this registration are unclear. The actor proceeded to log in several more times from a Surfshark VPN endpoint, however, they were not observed carrying out any further suspicious activity. 

Advanced Search logs depicting the steps which the actor took after logging in to a user’s Microsoft 365 account.
Figure 2: Advanced Search logs depicting the steps which the actor took after logging in to a user’s Microsoft 365 account.

It was not clear in either of these examples, nor in fact any of cases observed by Darktrace, why actors had registered and assigned permissions to an application called ‘PerfectData Software’, and there do not appear to be any open-source intelligence (OSINT) resources or online literature related to the malicious usage of an application by that name. That said, there are several websites which appear to provide email migration and data recovery/backup tools under the moniker ‘PerfectData Software’. 

It is unclear whether the use of ‘PerfectData Software’ by malicious actors observed on the networks of Darktrace customers was one of these tools. However, given the nature of the tools, it is possible that the actors intended to use them to facilitate the exfiltration of email data from compromises mailboxes.

If the legitimate software ‘PerfectData’ is the application in question in these incidents, it is likely being purchased and misused by attackers for malicious purposes. It is also possible the application referenced in the incidents is a spoof of the legitimate ‘PerfectData’ software designed to masquerade a malicious application as legitimate.

Darktrace Coverage

Cases of ‘PerfectData Software’ activity chains detected by Darktrace typically began with an actor signing into an internal user’s Microsoft 365 account from a VPN or VPS-related endpoint. These login events, along with the suspicious email and/or brute-force activity which preceded them, caused the following DETECT models to breach:

  • SaaS / Access / Unusual External Source for SaaS Credential Use
  • SaaS / Access / Suspicious Login Attempt
  • SaaS / Compromise / Login From Rare Following Suspicious Login Attempt(s)
  • SaaS / Email Nexus / Unusual Location for SaaS and Email Activity

Subsequent activities, including inbox rule creations, registration of applications in Azure AD, and mass-mailing activity, resulted in breaches of the following DETECT models.

  • SaaS / Admin / OAuth Permission Grant 
  • SaaS / Compromise / Unusual Logic Following OAuth Grant 
  • SaaS / Admin / New Application Service Principal
  • IaaS / Admin / Azure Application Administration Activities
  • SaaS / Compliance / New Email Rule
  • SaaS / Compromise / Unusual Login and New Email Rule
  • SaaS / Email Nexus / Suspicious Internal Exchange Activity
  • SaaS / Email Nexus / Possible Outbound Email Spam
  • SaaS / Compromise / Unusual Login and Outbound Email Spam
  • SaaS / Compromise / Suspicious Login and Suspicious Outbound Email(s)
DETECT Model Breaches highlighting unusual login and 'PerfectData Software' registration activity from a malicious actor
Figure 3: DETECT Model Breaches highlighting unusual login and 'PerfectData Software' registration activity from a malicious actor.

In cases where Darktrace RESPOND™ was enabled in autonomous response mode, ‘PerfectData Software’ activity chains resulted in breaches of the following RESPOND models:

• Antigena / SaaS / Antigena Suspicious SaaS Activity Block

• Antigena / SaaS / Antigena Significant Compliance Activity Block

In response to these model breaches, Darktrace RESPOND took immediate action, performing aggressive, inhibitive actions, such as forcing the actor to log out of the SaaS platform, and disabling the user entirely. When applied autonomously, these RESPOND actions would seriously impede an attacker’s progress and minimize network disruption.

Figure 4: A RESPOND model breach created in response to a malicious actor's registration of 'PerfectData Software'

In addition, Darktrace Cyber AI Analyst was able to autonomously investigate registrations of the ‘PerfectData Software’ application and summarized its findings into digestible reports. 

A Cyber AI Analyst Incident Event log
Figure 5: A Cyber AI Analyst Incident Event log showing AI Analyst autonomously pivoting off a breach of 'SaaS / Admin / OAuth Permission Grant' to uncover details of an account hijacking.

結論 

Due to the widespread adoption of Microsoft 365 services in the workplace and continued emphasis on a remote workforce, account hijackings now pose a more serious threat to organizations around the world than ever before. The cases discussed here illustrate the tendency of malicious actors to conduct their activities from endpoints associated with VPN services, while also registering new applications, like PerfectData Software, with malicious intent. 

While it was unclear exactly why the malicious actors were using ‘PerfectData Software’ as part of their account hijacking, it is clear that either the legitimate or spoofed version of the application is becoming an very likely emergent piece of threat actor tradecraft.

Darktrace DETECT’s anomaly-based approach to threat detection allowed it to recognize that the use of ‘PerfectData Software’ represented a deviation in the SaaS user’s expected behavior. While Darktrace RESPOND, when enabled in autonomous response mode, was able to quickly take preventative action against threat actors, blocking the potential use of the application for data exfiltration or other nefarious purposes.

Appendices

MITRE ATT&CK Mapping

Reconnaissance:

T1598 ­– Phishing for Information

Credential Access:

T1110 – Brute Force

Initial Access:

T1078.004 – Valid Accounts: Cloud Accounts

Command and Control:

T1105 ­– Ingress Tool Transfer

Persistence:

T1098.003 – Account Manipulation: Additional Cloud Roles 

Collection:

• T1114 – Email Collection 

Defense Evasion:

• T1564.008 ­– Hide Artifacts: Email Hiding Rules­

Lateral Movement:

T1534 – Internal Spearphishing

Unusual Source IPs

• 5.62.60[.]202  (AS198605 AVAST Software s.r.o.) 

• 160.152.10[.]215 (AS37637 Smile-Nigeria-AS)

• 197.244.250[.]155 (AS37705 TOPNET)

• 169.159.92[.]36  (AS37122 SMILE)

• 45.62.170[.]237 (AS396073 MAJESTIC-HOSTING-01)

• 92.38.180[.]49 (AS202422 G-Core Labs S.A)

• 129.56.36[.]26 (AS327952 AS-NATCOM)

• 92.38.180[.]47 (AS202422 G-Core Labs S.A.)

• 107.179.20[.]214 (AS397086 LAYER-HOST-HOUSTON)

• 45.62.170[.]31 (AS396073 MAJESTIC-HOSTING-01)

References

[1] https://www.investing.com/academy/statistics/microsoft-facts/

[2] https://intel471.com/blog/countering-the-problem-of-credential-theft

[3] https://darktrace.com/blog/business-email-compromise-to-mass-phishing-campaign-attack-analysis

[4] https://darktrace.com/blog/breakdown-of-a-multi-account-compromise-within-office-365

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About the author
Sam Lister
SOC Analyst

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クラウド

Darktrace Integrates Self-Learning AI with Amazon Security Lake to Support Security Investigations

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31
May 2023

Darktrace has deepened its relationship with AWS by integrating its detection and response capabilities with Amazon Security Lake

This development will allow mutual customers to seamlessly combine Darktrace AI’s bespoke understanding of their organization with the Threat Intelligence offered by other security tools, and investigate all of their alerts in one central location. 

This integration will improve the value security teams get from both products, streamlining analyst workflows and improving their ability to detect and respond to the full spectrum of known and unknown cyber-threats. 

How Darktrace and Amazon Security Lake augment security teams

Amazon Security Lake is a newly-released service that automatically centralizes an organization’s security data from cloud, on-premises, and custom sources into a customer owned purpose-built data lake. Both Darktrace and Amazon Security Lake support the Open Cybersecurity Schema Framework (OCSF), an open standard to simplify, combine, and analyze security logs.  

Customers can store security logs, events, alerts, and other relevant data generated by various AWS services and security tools. By consolidating security data in a central lake, organizations can gain a holistic view of their security posture, perform advanced analytics, detect anomalies and open investigations to improve their security practices.

With Darktrace DETECT and RESPOND AI engines covering all assets across IT, OT, network, endpoint, IoT, email and cloud, organizations can augment the value of their security data lakes by feeding Darktrace’s rich and context-aware datapoints to Amazon Security Lake. 

Amazon Security Lake empowers security teams to improve the protection of your digital estate:

  • Quick and painless data normalization 
  • Fast-tracks ability to investigate, triage and respond to security events
  • Broader visibility aids more effective decision-making
  • Surfaces and prioritizes anomalies for further investigation
  • Single interface for seamless data management

How will Darktrace customers benefit?

Across the Cyber AI Loop, all Darktrace solutions have been architected with AWS best practices in mind. With this integration, Darktrace is bringing together its understanding of ‘self’ for every organization with the centralized data visibility of the Amazon Security Lake. Darktrace’s unique approach to cyber security, powered by groundbreaking AI research, delivers a superior dataset based on a deep and interconnected understanding of the enterprise. 

Where other cyber security solutions are trained to identify threats based on historical attack data and techniques, Darktrace DETECT gains a bespoke understanding of every digital environment, continuously analyzing users, assets, devices and the complex relationships between them. Our AI analyzes thousands of metrics to reveal subtle deviations that may signal an evolving issue – even unknown techniques and novel malware. It distinguishes between malicious and benign behavior, identifying harmful activity that typically goes unnoticed. This rich dataset is fed into RESPOND, which takes precise action to neutralize threats against any and every asset, no matter where data resides.

Both DETECT and RESPOND are supported by Darktrace Self-Learning AI, which provides full, real-time visibility into an organization’s systems and data. This always-on threat analysis already makes humans better at cyber security, improving decisions and outcomes based on total visibility of the digital ecosystem, supporting human performance with AI coverage and empowering security teams to proactively protect critical assets.  

Converting Darktrace alerts to the Amazon Security Lake Open Cybersecurity Schema Framework (OCSF) supplies the Security Operations Center (SOC) and incident response team with contextualized data, empowering them to accelerate their investigation, triage and response to potential cyber threats. 

Darktrace is available for purchase on the AWS Marketplace.

Learn more about how Darktrace provides full-coverage, AI-powered cloud security for AWS, or see how our customers use Darktrace in their AWS cloud environments.

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About the author
Nabil Zoldjalali
VP, Technology Innovation

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