Blog

Inside the SOC

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

Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
05
2023年6月
05
2023年6月
Over the past few months, Darktrace has observed several cases of malicious actors registering an application called ‘PerfectData Software’ during hijackings of Microsoft 365 accounts. In this blog, we will provide details of these account hijackings, along with details of Darktrace’s coverage.

日々変化する脅威の中で、新たな戦術、技術、手順(TTP)が日々出現しており、セキュリティチームにとって非常に大きな課題となっています。攻撃者が利用する攻撃手法は多岐にわたるため、「まだ存在しないプレイブックをどのように防御するか」という克服不可能な問題が生じているように思われます。

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.

Darktrace DETECT™は、アノマリーベースの検知機能により、このアプリケーションを使用する際のアクティビティチェーンを特定することができ、その過程で脅威アクターによる新しい技巧を発見する可能性があります。

Microsoft 365の不正侵入

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はMicrosoft 365環境にアクセスした悪意ある行為者が、予測可能な方法で行動することを定期的に観察しています。典型的な例としては、新しい受信トレイのルールを作成し、悪意のあるリンクをたどったり、機密情報を提供したりといった後続のアクションを実行するよう受信者を説得することを目的とした詐欺的なメールを送信することが挙げられます。また、行為者が新しいアプリケーションをAzure ADに登録し、マスメールやデータ窃盗などのフォローアップ活動に使用できるようにすることも一般的です。したがって、Azure ADへのアプリケーションの登録は、比較的予測可能な脅威行為と思われます[3][4]。Darktrace DETECT は、Azure ADにおける異常なアプリケーション登録が、期待される行動からの逸脱を構成し、したがってアカウント侵害の可能性を示す指標となり得ることを理解します。

これらのAzure ADにおけるアプリケーションの登録は、Azure ADにおけるサービスプリンシパルの作成および権限の割り当てによって証明されます。Darktraceは脅威アクターがPerfectData Softwareという名前のサービスプリンシパルに権限を作成および割り当てる傾向が高まっていることを検知しています。このAzure ADの活動をさらに調査したところ、進行中のアカウント乗っ取りの一部であることが判明しました。 

PerfectData Software の活動 

Darktrace は、PerfectData Software という名前のアプリケーションに関する次のような活動パターンのバリエーションを顧客基盤において観察しました:

  1. 脅威アクターは、仮想専用サーバー(VPS)または仮想専用ネットワーク(VPN)サービスに関連するエンドポイントから、Microsoft 365アカウントにサインインします。
  2. 脅威アクターは、PerfectData SoftwareというアプリケーションをAzure ADに登録し、アプリケーションにアクセス権を付与します。
  3. 脅威アクターがEメールボックスデータにアクセスし、受信ルールを作成する。 

2つの別々のインシデントにおいて、悪意のあるアクターは、VPNサービス(それぞれHideMyAss (HMA) VPNとSurfshark VPN)に関連するエンドポイントから、および自律システムAS396073 MAJESTIC-HOSTING-01 内のエンドポイントから活動を行うことが確認されました。 

2023年3月、Darktraceは自律防御システム内でクウェートベースのIPアドレス、AS198605 AVAST Software s.r.o. からMicrosoft 365アカウントにサインインする悪意のあるアクターを確認しました。このIPアドレスはVPNサービス、HMA VPNと関連しています。その後数日間、あるアクター(おそらく同じ悪意あるアクター)が、ナイジェリアベースの2つの異なるエンドポイント、VPS関連のエンドポイント、HMA VPNのエンドポイントから、さらに数回アカウントにサインインしています。 

ログインセッション中、アクターは様々なアクションを実行しました。まず、PerfectData Softwareという名前のサービスプリンシパルを作成し、権限を割り当てました。このサービスプリンシパルの作成は、Azure ADにPerfectData Softwareというアプリケーションを登録したことを意味します。 このアプリケーションを登録した理由は不明ですが、数日以内に、行為者は別のアプリケーションであるNewsletter Software Supermailerを登録して許可を与え、乗っ取られたアカウントのメールボックスに新しい受信トレイルール名 's' を作成しました。この受信箱ルールは、特定の条件を満たしたメールをRSS Subscriptionという名前のフォルダに移動させる。このNewsletter Software Supermailerアプリケーションは、大量送信を容易にするために行為者が登録したものと思われます。

これらの行為の直後、Darktraceはこの脅威アクターがこのアカウントから数千通の悪意のあるメールを送信していることを検知しました。このメールには、Credit Transfer Copy.htmlという名前の添付ファイルが含まれており、この中には不審なリンクが含まれていました。さらに調査を進めると、この最初の侵入行為の前に、顧客のネットワークが偽の請求書メールを数回受信していたことが判明しました。さらに、最初のアクセス時に、侵害されたアカウントへのログイン失敗が異常に多く発生していたことも判明しました。 

図1: Microsoft 365アカウントにログインした後、行為者が行った手順を示す詳細検索のログ
図1: Microsoft 365アカウントにログインした後、行為者が行った手順を示す詳細検索のログ

2023年3月にDarktrace が観測した別のケースでは、悪意のあるアクターが、自律防御システムAS397086 LAYER-HOST-HOUSTON内のエンドポイントからMicrosoft 365アカウントにサインインしていることが観測されています。このエンドポイントは、VPNサービスであるSurfshark VPNに関連しているようです。このログインに続いて、自律防御システムAS396073 MAJESTIC-HOSTING-01内のVPS関連からのログインが何度か失敗したり成功したりしました。その後、PerfectData Softwareと呼ばれるアプリケーションを登録し、権限を付与していることが確認されました。前例と同様、この登録の動機は不明である。このアクターは、Surfshark VPNエンドポイントからさらに数回ログインを繰り返しましたが、それ以上の不審な行為を行う様子は確認されていません。 

ユーザーのMicrosoft 365アカウントにログインした後の手順を示す高度な検索ログです。
図2: Microsoft 365アカウントにログインした後、脅威アクターが行った手順を示す詳細検索のログ

これらの例でも、また、Darktrace が観察したどの例でも、脅威アクターが PerfectData Software と呼ばれるアプリケーションを登録し、許可を与えた理由は明らかではありませんでした。また、この名前のアプリケーションの悪意のある使用に関するオープンソースインテリジェンス(OSINT)リソースやオンライン文献は存在しないようです。とはいえ、PerfectData Software という名称のEメール移行ツールやデータ復旧およびバックアップツールを提供していると思われるウェブサイトはいくつか存在するようです。 

Darktrace の顧客のネットワーク上で観察された悪意のあるアクターによるPerfectData Softwareの使用が、これらのツールの1つであったかどうかは不明であります。しかし、ツールの性質を考えると、悪意のあるアクターは、侵害されたEメールボックスからのEメールデータの流出を促進するために、ツールを使用することを意図していた可能性があります。

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 のカバレッジ

Darktrace によって検知された PerfectData Software アクティビティチェーンのケースは、通常、VPNまたはVPS関連のエンドポイントから内部ユーザーのMicrosoft 365アカウントにサインインする行為から始まります。これらのログインイベントは、それに先立つ不審なEメールやブルートフォースアクティビティとともに、以下のDETECT モデルが侵入する原因となりました:

  • 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

その後、受信箱ルールの作成、Azure ADへのアプリケーションの登録、大量のEメール送信などの活動により、以下のDETECT モデルが侵害されました。

  • 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 モデルブリーチのハイライトは、悪意のあるアクターによる異常なログインと PerfectData Software の登録活動です。
図3: DETECT モデルブリーチの場合、悪意のあるアクターによる異常なログインとPerfectData Softwareの登録活動がハイライトされます

Darktrace RESPOND™が自律応答モードで有効になっている場合、PerfectData Softwareの活動チェーンは、以下のRESPOND モデルの違反につながりました:

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.

図4:悪意のあるアクターによるPerfectData Softwareの登録に対処する形で作成されたRESPONDのモデルブリーチ

また、Darktrace Cyber AI Analystは、PerfectData Softwareアプリケーションの登録内容を自律的に調査し、その結果を消化しやすいレポートにまとめることができました。 

Cyber AI Analystのインシデントイベントログ
図5:Cyber AI Analystのインシデントイベントログで、AI AnalystがSaaS / Admin / OAuth Permission Grantの違反から自律的にピボットして、アカウントハイジャックの詳細を明らかにする様子が示されています。

結論 

Microsoft 365サービスの職場への普及とリモートワークの継続的な重視により、アカウントの乗っ取りは、世界中の組織にとって以前よりも深刻な脅威になりました。ここで取り上げた事例は、悪意のある行為者がVPNサービスに関連するエンドポイントから活動を行う傾向を示すとともに、PerfectData Softwareのように悪意のある新しいアプリケーションを登録することもあります。 

悪意あるアクターがアカウントハイジャックにPerfectData Softwareを使用した理由は不明ですが、このアプリケーションの正規版または偽装版が、脅威行為者の手口として出現する可能性が非常に高くなっていることは明らかです。

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.

付録

MITRE ATT&CK マッピング

偵察:

T1598 - フィッシングによる情報提供

クレデンシャルアクセス:

-T1110 - ブルートフォース

初期アクセス:

- T1078.004 - 有効なアカウント:クラウドアカウント

コマンド&コントロール:

- T1105 - Ingressツール転送

永続性:

- T1098.003 - アカウントの操作:クラウドの役割の追加 

収集:

- T1114 - Eメールコレクション 

防御回避:

T1564.008 - アーティファクトを隠す:Eメール非表示ルール

ラテラルムーブメント:

- T1534 - 社内向けスピアフィッシング

異常なソースIP

- 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)

参考文献

[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

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
Dariush Onsori
Cyber Security Analyst
Sam Lister
SOC Analyst
Book a 1-1 meeting with one of our experts
この記事を共有

More in this series

該当する項目はありません。

Blog

Inside the SOC

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

Default blog imageDefault blog image
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

続きを読む
著者について
Ashiq Shafee
Cyber Security Analyst

Blog

該当する項目はありません。

Seven Cyber Security Predictions for 2024

Default blog imageDefault blog image
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

続きを読む
著者について
Darktrace 脅威リサーチチーム

Good news for your business.
Bad news for the bad guys.

無償トライアルを開始

無償トライアルを開始

柔軟な導入
Cloud-based deployment.
迅速なインストール
設定時間はわずか1時間、メールセキュリティのトライアルはさらに短時間で完了します。
製品を選ぶ
クラウド、ネットワーク、Eメールなど、最も必要とされる領域で自己学習型AIの能力をお試しください。
購入義務なし
Darktrace Threat Visualizerと組織毎にカスタマイズされた3回の脅威レポートへのフルアクセスを提供しますが、購入の義務はありません。
For more information, please see our Privacy Notice.
Thanks, your request has been received
A member of our team will be in touch with you shortly.
YOU MAY FIND INTERESTING
フォームを送信する際に何らかの問題が発生しました。

デモを見る

柔軟な導入
仮想的にインストールすることも、ハードウェアでインストールすることも可能です。
迅速なインストール
設定時間はわずか1時間、メールセキュリティのトライアルはさらに短時間で完了します。
製品を選ぶ
クラウド、ネットワーク、Eメールなど、最も必要とされる領域で自己学習型AIの能力をお試しください。
購入義務なし
Darktrace Threat Visualizerと組織毎にカスタマイズされた3回の脅威レポートへのフルアクセスを提供しますが、購入の義務はありません。
ありがとうございます!あなたの投稿を受け取りました。
フォームを送信する際に何らかの問題が発生しました。