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Darktrace AIがEmotetのアウトバウンドマルスパムキャンペーンを検知・遮断

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27
Apr 2022
27
Apr 2022
This blog explores the resurgence of Emotet malware through a recent outbound malspam campaign on a wholesale trade, and explains how Autonomous Response interrupted the attack.


2021年1月、国際的な協力による法執行により、Emotetのインフラストラクチャの解体に成功したことが賞賛されました。これは、2014年の初期展開以来、被害者に機密データの損失、多額の金銭的損失、風評被害をもたらした最も多発したマルウェアおよびバンキングトロイの木馬の1つでした。1

しかし、2021年11月以降、Emotetの復活の兆しが見えてきました。Emotetは、別のDarktrace ブログでも取り上げたTrickbotなどのかつてのパートナーキャンペーンを活用し、すでに感染したマシンを使って新しいEmotetバイナリをダウンロードし、インフラを再構築していると思われます。2

Emotetの復活の初期兆候は、そのオリジナルのキルチェーンと攻撃ベクトルと同義であるように見えます。マルウェアが展開され、ゾンビマシンとしてデバイスが危険にさらされます。このデバイスは、その後、アウトバウンドのマルスパムキャンペーンを送信するために使用されます。これらのキャンペーンは、アプリケーションインストーラパッケージや偽の返信Eメールチェーンとして偽装され、スパムの信頼性を高めることができます。マルウェアは、このスパムによって拡散すると、他のデバイス(内部および他のネットワークのアウトバウンド)に感染しようとします。3

2022年2月、Darktrace はお客様の環境でこのキルチェーンの要素を検知しました。特に、アウトバウンドスパムキャンペーンの特徴である大量のSMTP接続を観察しています。

図1:キルチェーンに沿ってEmotetの侵入が進行している様子を示す攻撃のタイムライン
図2:VirusTotalのスクリーンショット。この稀なエンドポイントは、他のセキュリティベンダーから悪意のあるものとしてフラグが立てられていることが分かる


残りのセキュリティスタックを回避

この攻撃は、ネットワーク内の既存のユーザーエージェントを介してPowerShell接続を行うことで、Living off the Land(環境寄生型)のテクニックを使用しています。PowerShell接続は正当な理由で使用されることがあるため、この活動は顧客の他のセキュリティスタックを迂回するように見え、顧客のツールによって承認されていると思われました。しかし、Darktrace は、デバイスが PowerShell ユーザーエージェントを使用して外部ロケーションに接続していることを検知しました。これは、より広範なネットワーク動作と比較すると稀なことです。

お客様の既存のセキュリティでは、侵害されたデバイスが異常なポートで行う送信SMTP接続をブロックすることはできませんでした。しかし、Darktrace RESPOND はメールポート25と587の発信接続を71%ブロックし、スパムの拡散規模を大幅に縮小させました。

Darktrace のインサイトとサービス

Darktrace は、新しいPowerShellの使用、C2ビーコン活動の増加、スパムなど、さまざまな異常な行動を迅速に検知しました。これは、モデル違反の急増によって強調することができます(図3)。DarktraceのCyber AI Analyst は、デバイスの疑わしいネットワークスキャンアクティビティの調査も開始しました。これは、組織のセキュリティチームが迅速に対応するために必要な調査プロセスと技術的な詳細をまとめたインシデントサマリーを作成するために不可欠なものでした(図4)。

RESPONDはインシデントの間中、最初の侵入デバイスに自律的に対応し、ビジネスプロセスを中断させることなく「生活パターン」を実施しました。これは、さらなる横の動きを止めることで、侵害の範囲を大幅に縮小させました。悪意のある送信メールスパムに対応するため、RESPONDはデバイスの通常の「生活パターン」を30分間実施し、ポート25、80、587への接続を1時間ブロックしました(図5)。コマンド&コントロール活動に対しては、ポート8080経由の91.207.181[.]106への接続も3時間ブロックされました。

このお客様は、Darktraceの Proactive Threat Notification (PTN) と Ask the Expert (ATE) サービスを契約していたため、この侵害は追加のトリアージとアラートによって支援されることになりました。PTNは、Darktrace SOCチームが侵害について迅速にアラートされ、アナリストがお客様のセキュリティチームと一緒に詳細な調査を行うことを確実にしました。同時に、ATEサービスは、脅威が再び発生する可能性を低くするための追加情報をお客様に提供することを確実にしました。このように、ATEサービスにより、お客様は、迅速かつ正確に復旧するために必要な重要な情報を得ることができました。

図3:Darktrace は攻撃期間中にデバイスのアクティビティと関連するモデルブリーチが異常に急増することが判明(グラフのドットで表現)


図4:侵害デバイスのネットワークスキャン活動に関するAI Analystのレポート抜粋
図5:外部接続活動をブロックし、デバイスの「生活パターン」を強制するDarktrace RESPOND


Emotetの復活は、Eメールがいかに重要な攻撃経路および侵害源として機能し続けるかを示しています。特に、広範なマルスパムキャンペーンは、依然として適応力があり、効果的です。このブログで紹介した事件は、マルウェア組織の驚くべき可変性とネットワーク化された性質を強調するもう1つの例です。このため、マルウェア組織は、解体された後でも、長い時間をかけて復活することができるのです。幸いなことに、この事件では、自律的な対応によりEmotetの侵害を最小限に抑えることができ、PTNとATEサービスは、セキュリティチームを終始警告し、さらにサポートしました。

付録

Darktrace モデルブリーチ

·    Device / Multiple Lateral Movement Model Breaches

·    Device / Large Number of Model Breaches

·    Device / Suspicious Network Scan Activity

·    Device / Network Scan

·    Device / External Address Scan

·    Device / Multiple C2 Model Breaches

·    Device / Large Number of Connections to New Endpoints

·    Device / Increased External Connectivity

·    Device / New User Agent and New IP

·    Device / New PowerShell User Agent

·    Compromise / Suspicious Beaconing Behavior

·    Compromise / Beacon to Young Endpoint

·    Compromise / Agent Beacon to New Endpoint

·    Compromise / Sustained SSL or HTTP Increase

·    Compromise / Suspicious Spam Activity

·    Anomalous Connection / Possible Outbound Spam

·    Anomalous Connection / Suspicious Expired SSL

·    Anomalous Connection / Rare External SSL Self-Signed

·    Anomalous Connection / Suspicious Self-Signed SSL

·    Anomalous Connection / Anomalous SSL without SNI to New External

·    Anomalous Connection / PowerShell to Rare External

·    AI Analyst / AI Analyst Investigation

·    Unusual Activity / Unusual External Activity

IoCs

MITRE ATT&CK Techniques Observed

脚注

1. https://www.cisa.gov/uscert/ncas/alerts/TA18-201A

2. https://blog.malwarebytes.com/threat-intelligence/2021/11/trickbot-helps-emotet-come-back-from-the-dead/

3. https://www.kaspersky.com/resource-center/threats/emotet

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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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Zoe Tilsiter
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Gootloader Malware: Detecting and Containing Multi-Functional Threats with Darktrace

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15
Feb 2024

What is multi-functional malware?

While traditional malware variants were designed with one specific objective in mind, the emergence of multi-functional malware, such as loader malware, means that organizations are likely to be confronted with multiple malicious tools and strains of malware at once. These threats often have non-linear attack patterns and kill chains that can quickly adapt and progress quicker than human security teams are able to react. Therefore, it is more important than ever for organizations to adopt an anomaly approach to combat increasingly versatile and fast-moving threats.

Example of Multi-functional malware

One example of a multi-functional malware recently observed by Darktrace can be seen in Gootloader, a multi-payload loader variant that has been observed in the wild since 2020. It is known to primarily target Windows-based systems across multiple industries in the US, Canada, France, Germany, and South Korea [1].  

How does Gootloader malware work?

Once installed on a target network, Gootloader can download additional malicious payloads that allow threat actors to carry out a range of harmful activities, such as stealing sensitive information or encrypting files for ransom.

The Gootloader malware is known to infect networks via search engine optimization (SEO) poisoning, directing users searching for legitimate documents to compromised websites hosting a malicious payload masquerading as the desired file.

If the malware remains undetected, it paves the way for a second stage payload known as Gootkit, which functions as a banking trojan and information-stealer, or other malware tools including Cobalt Strike and Osiris [2].

Darktrace detection of Gootloader malware

In late 2023, Darktrace observed one instance of Gootloader affecting a customer in the US. Thanks to its anomaly-focused approach, Darktrace DETECT™ quickly identified the anomalous activity surrounding this emerging attack and brought it to the immediate attention of the customer’s security team. All the while, Darktrace RESPOND™ was in place and able to autonomously intervene, containing the suspicious activity and ensuring the Gootloader compromise could not progress any further.

In September 2023, Darktrace identified an instance of the Gootloader malware attempting to propagate within the network of a customer in the US. Darktrace identified the first indications of the compromise when it detected a device beaconing to an unusual external location and performing network scanning. Following this, the device was observed making additional command-and-control (C2) connections, before finally downloading an executable (.exe) file which likely represented the download of a further malicious payload.

As this customer had subscribed to the Proactive Notification Service (PTN), the suspicious activity was escalated to the Darktrace Security Operations Center (SOC) for further investigation by Darktrace’s expert analysts. The SOC team were able to promptly triage the incident and advise urgent follow-up actions.

Gootloader Attack Overview

Figure 1: Timeline of Anomalous Activities seen on the breach device.

Initial Beaconing and Scanning Activity

On September 21, 2023, Darktrace observed the first indications of compromise on the network when a device began to make regular connections to an external endpoint that was considered extremely rare for the network, namely ‘analyzetest[.]ir’.

Although the endpoint did not overtly seem malicious in nature (it appeared to be related to laboratory testing), Darktrace recognized that it had never previously been seen on the customer’s network and therefore should be treated with caution.  This initial beaconing activity was just the beginning of the malicious C2 communications, with several additional instances of beaconing detected to numerous suspicious endpoints, including funadhoo.gov[.]mv, tdgroup[.]ru’ and ‘army.mil[.]ng.

Figure 2: Initial beaconing activity detected on the breach device.

Soon thereafter, Darktrace detected the device performing internal reconnaissance, with an unusually large number of connections to other internal locations observed. This scanning activity appeared to primarily be targeting the SMB protocol by scanning port 445.

Within seconds of DETECT’s detection of this suspicious SMB scanning activity, Darktrace RESPOND moved to contain the compromise by blocking the device from connecting to port 445 and enforcing its ‘pattern of life’. Darktrace’s Self-Learning AI enables it to learn a device’s normal behavior and recognize if it deviates from this; by enforcing a pattern of life on an affected device, malicious activity is inhibited but the device is allowed to continue its expected activity, minimizing disruption to business operations.

Figure 3: The breach device Model Breach Event Log showing Darktrace DETECT identifying suspicious SMB scanning activity and the corresponding RESPOND actions.

Following the initial detection of this anomalous activity, Darktrace’s Cyber AI Analyst launched an autonomous investigation into the beaconing and scanning activity and was able to connect these seemingly separate events into one incident. AI Analyst analyzes thousands of connections to hundreds of different endpoints at machine speed and then summarizes its findings in a single pane of glass, giving customers the necessary information to assess the threat and begin remediation if necessary. This significantly lessens the burden for human security teams, saving them previous time and resources, while ensuring they maintain full visibility over any suspicious activity on their network.

Figure 4: Cyber AI Analyst incident log summarizing the technical details of the device’s beaconing and scanning behavior.

Beaconing Continues

Darktrace continued to observe the device carrying out beaconing activity over the next few days, likely representing threat actors attempting to establish communication with their malicious infrastructure and setting up a foothold within the customer’s environment. In one such example, the device was seen connecting to the suspicious endpoint ‘fysiotherapie-panken[.]nl’. Multiple open-source intelligence (OSINT) vendors reported this endpoint to be a known malware delivery host [3].

Once again, Darktrace RESPOND was in place to quickly intervene in response to these suspicious external connection attempts. Over the course of several days, RESPOND blocked the offending device from connecting to suspicious endpoints via port 443 and enforced its pattern of life. These autonomous actions by RESPOND effectively mitigated and contained the attack, preventing it from escalating further along the kill chain and providing the customer’s security team crucial time to take act and employ their own remediation.

Figure 5: A sample of the autonomous RESPOND actions that was applied on the affected device.

Possible Payload Retrieval

A few days later, on September 26, 2023, Darktrace observed the affected device attempting to download a Windows Portable Executable via file transfer protocol (FTP) from the external location ‘ftp2[.]sim-networks[.]com’, which had never previously been seen on the network. This download likely represented the next step in the Gootloader infection, wherein additional malicious tooling is downloaded to further cement the malicious actors’ control over the device. In response, Darktrace RESPOND immediately blocked the device from making any external connections, ensuring it could not download any suspicious files that may have rapidly escalated the attackers’ efforts.

Figure 6: DETECT’s identification of the offending device downloading a suspicious executable file via FTP.

The observed combination of beaconing activity and a suspicious file download triggered an Enhanced Monitoring breach, a high-fidelity DETECT model designed to detect activities that are more likely to be indicative of compromise. These models are monitored by the Darktrace SOC round the clock and investigated by Darktrace’s expert team of analysts as soon as suspicious activity emerges.

In this case, Darktrace’s SOC triaged the emerging activity and sent an additional notice directly to the customer’s security team, informing them of the compromise and advising on next steps. As this customer had subscribed to Darktrace’s Ask the Expert (ATE) service, they also had a team of expert analysts available to them at any time to aid their investigations.

Figure 7: Enhanced Monitoring Model investigated by the Darktrace SOC.

結論

Loader malware variants such as Gootloader often lay the groundwork for further, potentially more severe threats to be deployed within compromised networks. As such, it is crucial for organizations and their security teams to identify these threats as soon as they emerge and ensure they are effectively contained before additional payloads, like information-stealing malware or ransomware, can be downloaded.

In this instance, Darktrace demonstrated its value when faced with a multi-payload threat by detecting Gootloader at the earliest stage and responding to it with swift targeted actions, halting any suspicious connections and preventing the download of any additional malicious tooling.

Darktrace DETECT recognized that the beaconing and scanning activity performed by the affected device represented a deviation from its expected behavior and was indicative of a potential network compromise. Meanwhile, Darktrace RESPOND ensured that any suspicious activity was promptly shut down, buying crucial time for the customer’s security team to work with Darktrace’s SOC to investigate the threat and quarantine the compromised device.

Credit to: Ashiq Shafee, Cyber Security Analyst, Qing Hong Kwa, Senior Cyber Analyst and Deputy Analyst Team Lead, Singapore

付録

Darktrace DETECT によるモデル検知

Anomalous Connection / Rare External SSL Self-Signed

Device / Suspicious SMB Scanning Activity

Anomalous Connection / Young or Invalid Certificate SSL Connections to Rare

Compromise / High Volume of Connections with Beacon Score

Compromise / Beacon to Young Endpoint

Compromise / Beaconing Activity To External Rare

Compromise / Slow Beaconing Activity To External Rare

Compromise / Beacon for 4 Days

Anomalous Connection / Suspicious Expired SSL

Anomalous Connection / Multiple Failed Connections to Rare Endpoint

Compromise / Sustained SSL or HTTP Increase

Compromise / Large Number of Suspicious Successful Connections

Compromise / Large Number of Suspicious Failed Connections

Device / Large Number of Model Breaches

Anomalous File / FTP Executable from Rare External Location

Device / Initial Breach Chain Compromise

RESPOND Models

Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block

Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block

Antigena / Network/Insider Threat/Antigena Network Scan Block

Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Client Block

Antigena / Network / External Threat / Antigena Suspicious File Block

Antigena / Network / External Threat / Antigena File then New Outbound Block

Antigena / Network / External Threat / Antigena Suspicious Activity Block

侵害指標(IoC)一覧

Type

Hostname

IoCs + Description

explorer[.]ee - C2 Endpoint

fysiotherapie-panken[.]nl- C2 Endpoint

devcxp2019.theclearingexperience[.]com- C2 Endpoint

campsite.bplaced[.]net- C2 Endpoint

coup2pompes[.]fr- C2 Endpoint

analyzetest[.]ir- Possible C2 Endpoint

tdgroup[.]ru- C2 Endpoint

ciedespuys[.]com- C2 Endpoint

fi.sexydate[.]world- C2 Endpoint

funadhoo.gov[.]mv- C2 Endpoint

geying.qiwufeng[.]com- C2 Endpoint

goodcomix[.]fun- C2 Endpoint

ftp2[.]sim-networks[.]com- Possible Payload Download Host

MITRE ATT&CK マッピング

Tactic – Technique

Reconnaissance - Scanning IP blocks (T1595.001, T1595)

Command and Control - Web Protocols , Application Layer Protocol, One-Way Communication, External Proxy, Non-Application Layer Protocol, Non-Standard Port (T1071.001/T1071, T1071, T1102.003/T1102, T1090.002/T1090, T1095, T1571)

Collection – Man in the Browser (T1185)

Resource Development - Web Services, Malware (T1583.006/T1583, T1588.001/T1588)

Persistence - Browser Extensions (T1176)

参考文献

1.     https://www.blackberry.com/us/en/solutions/endpoint-security/ransomware-protection/gootloader

2.     https://redcanary.com/threat-detection-report/threats/gootloader/

3.     https://www.virustotal.com/gui/domain/fysiotherapie-panken.nl

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Ashiq Shafee
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Seven Cyber Security Predictions for 2024

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13
Feb 2024

2024 Cyber Threat Predictions

After analyzing the observed threats and trends that have affected customers across the Darktrace fleet in the second half of 2023, the Darktrace Threat Research team have made a series of predictions. These assessments highlight the threats that are expected to impact Darktrace customers and the wider threat landscape in 2024.  

1. Initial access broker malware, especially loader malware, is likely to be a prominent threat.  

Initial access malware such as loaders, information stealers, remote access trojans (RATs), and downloaders, will probably remain some of the most relevant threats to most organizations, especially when noted in the context that many are interoperable, tailorable Malware-as-a-Service (MaaS) tools.  

These types of malware often serve as a gateway for threat actors to compromise a target network before launching subsequent, and often more severe, attacks. Would-be cyber criminals are now able to purchase and deploy these malware without the need for technical expertise.  

2. Infrastructure complexity will increase SaaS attacks and leave cloud environments vulnerable.

The increasing reliance on SaaS solutions and platforms for business operations, coupled with larger attack surfaces than ever before, make it likely that attackers will continue targeting organizations’ cloud environments with account takeovers granting unauthorized access to privileged accounts. These account hijacks can be further exploited to perform a variety of nefarious activities, such as data exfiltration or launching phishing campaigns.  

It is paramount for organizations to not only fortify their SaaS environments with security strategies including multifactor authentication (MFA), regular monitoring of credential usage, and strict access control, but moreover augment SaaS security using anomaly detection.  

3. The prevalence and evolution of ransomware will surge.

The Darktrace Threat Research team anticipates a surge in Ransomware-as-a-Service (RaaS) attacks, marking a shift away from conventional ransomware. The uptick in RaaS observed in 2023 evidences that ransomware itself is becoming increasingly accessible, lowering the barrier to entry for threat actors. This surge also demonstrates how lucrative RaaS is for ransomware operators in the current threat landscape, further reinforcing a rise in RaaS.  

This development is likely to coincide with a pivot away from traditional encryption-centric ransomware tactics towards more sophisticated and advanced extortion methods. Rather than relying solely on encrypting a target’s data for ransom, malicious actors are expected to employ double or even triple extortion strategies, encrypting sensitive data but also threatening to leak or sell stolen data unless their ransom demands are met.  

4. Threat actors will continue to rely on living-off-the-land techniques.

With evolving sophistication of security tools and greater industry adoption of AI techniques, threat actors have focused more and more on living-off-the-land. The extremely high volume of vulnerabilities discovered in 2023 highlights threat actors’ persistent need to compromise trusted organizational mechanisms and infrastructure to gain a foothold in networks. Although inbox intrusions remain prevalent, the exploitation of edge infrastructure has demonstrably expanded compared to previously endpoint-focused attacks.

Given the prevalence of endpoint evasion techniques and the high proportion of tactics utilizing native programs, threat actors will likely progressively live off the land, even utilizing new techniques or vulnerabilities to do so, rather than relying on unidentified malicious programs which evade traditional detection.

5. The “as-a-Service” marketplace will contribute to an increase in multi-phase compromises.

With the increasing “as-a-Service” marketplaces, it is likely that organizations will face more multi-phase compromises, where one strain of malware is observed stealing information and that data is sold to additional threat actors or utilized for second and/or third-stage malware or ransomware.  

This trend builds on the concept of initial access brokers but utilizes basic browser scraping and data harvesting to make as much profit throughout the compromise process as possible. This will likely result in security teams observing multiple malicious tools and strains of malware during incident response and/or multi-functional malware, with attack cycles and kill chains morphing into less linear and more abstract chains of activity. This makes it more essential than ever for security teams to apply an anomaly approach to stay ahead of asymmetric threats.  

6. Generative AI will let attackers phish across language barriers.

Classic phishing scams play a numbers game, targeting as many inboxes as possible and hoping that some users take the bait, even if there are spelling and grammar errors in the email. Now, Generative AI has reduced the barrier for entry, so malicious actors do not have to speak English to produce a convincing phishing email.  

In 2024, we anticipate this to extend to other languages and regions. For example, many countries in Asia have not yet been greatly impacted by phishing. Yet Generative AI continues to develop, with improved data input yielding improved output. More phishing emails will start to be generated in various languages with increasing sophistication.    

7. AI regulation and data privacy rules will stifle AI adoption.

AI regulation, like the European Union’s AI Act and NIS2, is starting to be implemented around the world. As policies continue to come out about AI and data privacy, practical and pragmatic AI adoption becomes more complex.  

Businesses will likely have to take a second look at AI they are adopting into their tech stacks to consider what may happen if a tool is suddenly deprecated because it is no longer fit for purpose or loses the approvals in place. Many will also have to use completely different supply chain evaluations from their usual ones based on developing compliance registrars. This increased complication may make businesses reticent to adopt innovative AI solutions as legislation scrambles to keep up.  

Learn more about observed threat trends and future predictions in the 2023 End of Year Threat Report

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