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信用組合のセキュリティ確保:Darktrace がコンプライアンスに準拠したEメールセキュリティとリスク管理を支援

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02
Feb 2023
02
Feb 2023
金融機関は、定期的に変更される特定のITセキュリティコンプライアンス基準に従わなければなりません。ある信用金庫では、コンプライアンスとリスクに対するアプローチに合わせるため、Darktrace によるEメール保護とプロアクティブな攻撃対象領域の管理の恩恵を受けることができました。

アメリカ太平洋岸北西部にある信用組合のITIS担当ディレクターとして、マルウェアが内部システムに侵入すれば、私たちは困惑し、1万人におよぶ会員の財務状況に影響を与えることを理解しています。 

私のセキュリティチームは、オンラインバンキング、内部ネットワーク、従業員のEメールシステムなど、当社のサイバーインフラを保護する必要があります。その一環として、私たちは全米信用組合協会(CUNA)と連邦政府から、私たちのITセキュリティについて定期的に変更される特定の基準に従うよう、大きな課題を課せられています。 

これらのコンプライアンス基準を満たすために、私たちはDarktrace を導入しました。そのAIが私たちのデジタルランドスケープを学習すると、コンプライアンスフレームワークに準拠した特定の方法で反応するように設定をカスタマイズでき、私たちが目にしたすべての変化に簡単に適応できるようになりました。

Darktrace は、デジタル環境におけるすべてのデバイスとユーザーの通常の行動を学習します。そして、この理解をもとに、数秒以内に脅威を特定し、自律的で正確な判断を下し、業務を中断させることなく攻撃を無効化するのです。 

当社は5つの拠点に数百台のコンピューター、サーバー、スイッチを抱えているため、すべてのシステムを監視する能力はありません。しかし、ネットワークマッピングとトラフィック調整機能を使って、Darktrace は私が必要とするすべての情報を収集します。そして、説明可能なAI(XAI)によって明確で詳細なレポートを生成してくれます。 

Darktrace は、その自律的な機能により、人間よりも速く確実にコンプライアンスを維持し、攻撃を阻止することができるため、私のチームは時間と資金の双方を節約することができます。 

巧妙な介入でEメールによる脅威を阻止

私の経験では、ほとんどの侵入はEメールで起こります。私は、ファイアウォールのルール設定やサードパーティツールで、ほとんどのウェブトラフィックを制御することができます。しかし、ユーザーが悪意のあるメールに記載されているものをクリックするかどうかは、私にはコントロールできません。 

Darktrace/Emailは、AIを利用して、悪意のあるメール活動をユーザーの受信トレイに届く前に特定し、停止させることができます。単にEメールを許可またはブロックするだけでなく、より詳細なアクションを取ることができます。その代わり、Eメールの脅威となる要素を無効化します。特に、あらゆる添付ファイルをPDFに変換する機能が気に入っています。 

Darktrace は、外部のスパムフォルダや内部のExchangeフィルターを通過してきた悪意のあるEメールさえもブロックしてくれました。 

内部で提供される指標も素晴らしいです。誰がファイルを移動しているのか、どこに移動しているのか、どんなファイルを移動しているのか、それがプレーンテキストのパスワードや共有情報などの機密情報なのかどうかがわかります。Darktrace は、私が何時間もかけて辿り着いたようなことを、一目瞭然でやってのけてしまうのです。 

この総合的な可視化により、Darktrace/Email をユニークな方法で利用するようになりました。例えば、DarktraceのEメールトラフィックのメトリックの内訳を取り出し、データマイニングプログラムに送り込むことで、マーケティングメールキャンペーンの効果を確認しています。 

指標だけでなく、Darktraceによる脅威への自律的な対応能力は、私に安心感を与えてくれます。私たちのEメールとネットワークを24時間体制で監視してくれるマシンがあるのです。Darktrace は、Eメールシステムからの侵入を阻止し、ネットワークでの悪意ある活動を停止させるだけでなく、Eメールとネットワークのデータを統合して、AIをさらに賢くします。私たちがサイバー攻撃の犠牲になったとき、Darktrace は自律的に対処してくれることを知っています。 

外部への足跡を把握し、攻撃を未然に防ぐ

外部フットプリントの監視は、内部セキュリティに不可欠な要素です。なぜなら、攻撃が開始されたら、それを検知して阻止することは一つの方法ですが、攻撃を先制することができれば、さらに良い方法だからです。そのため、私はDarktrace PREVENT/Attack Surface Management™ (ASM)をできる限り早く導入しました。ASMを導入することで、プロアクティブなアプローチが可能になり、攻撃が起こる前にリスクを最小化することができるようになりました。 

PREVENT/ASMは、私独自のフットプリントのみに基づいて客観的なレポートを生成します。導入してから、私たちが気づいていないものも含めて、世の中にあるすべての資産を特定するまで、わずか10日しかかかりませんでした。 

2か月後の現在も、シャドーIT、設定ミス、ブランドの乱用など、刻々と変化する攻撃対象を監視し、脆弱性を知らせてくれています。脅威を特定すると、わかりやすいレポートが作成されるので、私はそれをサードパーティの契約者に渡して対処してもらっています。  

しかし、PREVENTの力は、Darktrace DETECT™ およびDarktrace RESPOND™ と組み合わせたときに増幅されます。これら3つのツールはCyber AI Loop™で連携し、セキュリティスタック全体を強固なものにします。  

PREVENT では、潜在的な攻撃経路を事前に確認できるため、Loop はこのデータを活用して、これらの重要なアクセスポイント周辺のDETECT とRESPOND の感度を高め、私のセキュリティチームに、最も高い効果を得るためにリソースの優先順位をどこに置くべきかを通知することができます。

Darktrace のどの機能が私のチームを最も助けたかを選ぶのは難しいです。なぜなら、フィードバックループによって、今では総合的に考えることができるからです。Darktrace は、私が支払った分の価値を漏れなく提供してくれ、私はそれを運用することを嬉しく思っています。セキュリティソフトウェアとしては、30年間この仕事に携わってきた私の人生の中で、おそらく最も洗練されたソフトウェアだと思います。 

他の金融機関へのアドバイスとしては、もしAIセキュリティシステムを導入していないのであれば、必要だということです。脅威の主体がAIを攻撃に使い始めており、AIで防御する必要があるのです。そうでなければ、石と棒でジェット機と戦っているようなものです。このようなプロアクティブなアプローチ、特にPREVENTによって、Darktrace は当社のデジタルエステートを保護し、セキュリティ姿勢を固め、コンプライアンス基準を満たすために常に取り組んでくれているのです。 

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

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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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