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To be Xor Not to Be: RESPOND が不意打ちのDDoSインシデントをいかに阻止できたか

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23
Nov 2022
23
Nov 2022
Out-of-hours attacks continue to be a large stress for security teams, however with RESPOND, companies can stop threats without the need for 24/7 human monitoring. This blog explores a nighttime incident where RESPOND triggered a decisive model breach but was prevented from acting without human input.

サイバー攻撃を受けるベストなタイミングは?

最も思いつく答えは「絶対にない」ですが、今日の脅威の状況では、これは希望的観測に過ぎないことが多いです。次善の答えは「準備ができたら」です。しかし、これでは攻撃を仕掛ける側の意図が考慮されていません。現実には、サイバー攻撃にとって最良のタイミングは、それを止めるために誰も周囲にいないときなのです。

サイバー攻撃はいつ起こるのか?

Mandiantのこれまでの分析によると、ランサムウェアによる侵害の半数以上は勤務時間外に発生しており、この傾向は、Darktrace も過去2年間に目撃しています [1]。これは意図的なもので、オンラインになっている人が少なければ少ないほど、セキュリティチームと連絡を取るのが難しくなり、攻撃者が目的を達成する可能性が高くなるからです。このような状況を踏まえると、自律的な対応がこれまで以上に重要であることは明らかです。人的資源がない場合、自律的なセキュリティは、ITチームが修復を開始するのに十分な時間、そのギャップを埋めることができます。 

このブログでは、あるインシデントについて詳述します。 Darktrace RESPOND によって提供された自律遮断技術が、早朝に発生したにもかかわらず、感染の試みを完全に防ぐことができたインシデントについて説明します。顧客がRESPOND を人間による確認モード(=AIのレスポンスについてまず人間による承認を要する)にしていたため、XorDDoSによる試みは最終的に成功しました。この攻撃が早朝に発生したことを考えると、Darktrace RESPOND のアクションを確認し、攻撃を防ぐことができる人が周囲にいなかった可能性が高いです。

XorDDoS 概要

XorDDoSはボットネットと呼ばれるマルウェアの一種で、特定の行動を実行するためにデバイスを集団で制御する目的で感染します。XorDDoSの場合、デバイスを使用してサービス拒否攻撃を実行するためにデバイスに感染します。今年、Microsoft 社は、Linux ベースのオペレーティングシステムに焦点を当てたこのマルウェアの活動が大幅に増加していることを報告しています [2]。XorDDoSは、SSHのブルートフォースによってシステムに侵入するのが最も一般的で、侵入後はXOR暗号でトラフィックを暗号化します。XorDDoSはまた、バックドアやクリプトマイナーなどの追加ペイロードをダウンロードすることでも知られています。言うまでもなく、これは企業ネットワーク上に存在するものではありません。 

XorDDoSの初期侵入

この事件は、あるデバイスが8月10日に初めてオンラインになったところから始まります。このデバイスはインターネットに接続されているように見え、Darktrace は様々なエンドポイントからこのデバイスへの数百のSSH接続が確認されました。その後、5日間にわたり、デバイスは、OSINTによるとウェブスキャナーに関連すると思われるいくつかのIPアドレスから何千もの失敗したSSH接続を受信しました [3]。成功したSSH接続は、内部IPアドレスと、アジア太平洋地域(顧客の地理的位置)に関連するITソリューションに関連するIPアドレスから確認されました。8月15日の深夜に、ウェブスキャンに関連するIPアドレスから最初のSSH接続が成功しました。この接続は約1時間半続き、外部IPは約3.3MBのデータをクライアントデバイスにアップロードしました。これらのことと、XorDDoSについて業界が知っていることを考慮すると、クライアントデバイスがインターネットに公開されたSSHを持ち、最初のアクセスのためにブルートフォースされた可能性が高いと思われます。 

デバイスがイラクのミラーサイト、mirror[.]earthlink[.]iqからZIPファイルをダウンロードするまで、数時間の滞留がありましたが、顧客時間帯の午前6時ごろに確認できました。このエンドポイントは過去に一度しか見たことがなく、ネットワークにとって100%珍しいものでした。この特定のエンドポイントやミラーサイトからダウンロードされたZIPファイルに関するOSINTの情報はなかったため、検知はダウンロードの異常さに基づいて行われました。

これに続いて、Darktrace はデバイスが外部IPアドレス107.148.210[.]218にcurlリクエストを行うのが確認されました。これは、curlに関連するユーザーエージェントが以前にデバイス上で見られなかったことと、ホスト名なしでIPアドレスに直接接続された(接続がスクリプト化されたことを示唆)ことから注目されました。これらのリクエストの URI は '1.txt' と '2.txt' でした。 

URIの拡張子 .txt に惑わされ、両方ともテキストファイルを装った実行ファイルであることが判明しました。両方のハッシュのOSINTにより、このファイルがXorDDoSに関連している可能性が高いことが判明しました。さらに、接続のパケットキャプチャから判断すると、真のファイル拡張子は .ELF のようでした。XorDDoSは主にLinuxデバイスに影響を与えるため、これはペイロードの真の拡張子として理にかなっていると言えます。 

図1:違反端末が行ったcurlリクエストのパケットキャプチャ

C2接続

.ELF のダウンロードの直後、Darktrace はデバイスがC2接続を試みているのが確認しました。これには、1525や8993といった通常とは異なるポートでのDGAのようなドメインへの接続も含まれていました。幸運にも、クライアントのファイアウォールがこれらの接続をブロックしていたようですが、それでもXorDDoSは止まりませんでした。XorDDoSはC2ドメインへの接続を試み続け、SOCから警告を受けた複数のProactive Threat Notification(PTN)を引き起こしました。PTNに続いて、最初の侵入から数時間後に、クライアントはデバイスを手動で隔離しました。この対処の遅れは、お客様の従業員がまだオンラインになっていない早朝のタイミングであったことが原因であると思われます。デバイスが隔離された後も、Darktrace は、XorDDoSがC2接続を試みているのが確認しました。9月7日にデバイスがネットワークから削除されるまで、全部で数十万件のC2接続が検知されました。

図2:AI Analystは、異常なアクティビティを識別し、解析しやすい形式にまとめることができました

代替タイムライン 

最終的に装置は撤去されましたが、RESPOND/Networkが人間確認モードでなければ、この攻撃は完全に防げたはずです。デバイスがイラクのミラーサイトから .ZIPファイルをダウンロードした時点で自律的な対応が開始され、違反デバイスからのすべての発信接続を1時間ブロックしていたことでしょう。

図3: その後のすべての活動を阻止することができたであろうAntigena (RESPOND) の最初の違反のスクリーンショット

図3のモデル違反は、XorDDoS実行可能ファイルのダウンロードを阻止し、その後のC2接続を阻止したことになります。この1時間は、顧客のセキュリティチームのメンバーが、侵害されたデバイスが他の何かを試みた場合にオンラインに戻るのに十分な時間を与えるため、非常に重要であったでしょう。全員が注意を払っていれば、この活動がこれほど長く続いたとは考えにくいです。もし攻撃がさらに進行していたら、感染したデバイスは少なくとも将来のDDoS攻撃の不本意な参加者になっていたでしょう。さらに、デバイスにバックドアが仕込まれ、クリプトジャッカーなどのマルウェアが追加で展開されていた可能性もあります。 

結論 

残念ながら、私たちは自律的な対応がこの一連の出来事を防いでいたという別の時間軸には存在しません。幸いにも、そのような体制にはなっていなかったものの、DarktraceのSOC チームが提供した PTN アラートは、発生時間から考えて発見されることを意図していなかった出来事における修復プロセスを加速させることになりました。異常な時間帯の攻撃はランサムウェアに限ったことではなく、組織にとって最も不都合で、攻撃者にとって最も都合の良い時間帯を想定した対策が必要です。しかし、Darktrace/RESPOND は、これをワンクリックで実現することができます。

Brianna Leddyによる本ブログへの寄稿に感謝します。

付録

Darktraceによるモデル検知

以下は、モデルブリーチの発生順のリストです。Proactive Threat Notification のモデルは太字で表示され、最初の侵害を防ぐことができたであろう最初の Antigena [RESPOND] ブリーチのみが記載されています。また、お客様が修復を開始した時期を示すために、手動検疫のブリーチも追加しています。

  • Compliance / Incoming SSH, August 12th 23:39 GMT +8
  • Anomalous File / Zip or Gzip from Rare External Location, August 15th, 6:07 GMT +8 
  • Antigena / Network / External Threat / Antigena File then New Outbound Block, August 15th 6:36 GMT +8 [part of the RESPOND functionality]
  • Anomalous Connection / New User Agent to IP Without Hostname, August 15th 6:59 GMT +8
  • Anomalous File / Numeric Exe Download, August 15th 6:59 GMT +8
  • Anomalous File / Masqueraded File Transfer, August 15th 6:59 GMT +8
  • Anomalous File / EXE from Rare External Location, August 15th 6:59 GMT +8
  • Device / Internet Facing Device with High Priority Alert, August 15th 6:59 GMT +8
  • Compromise / Rare Domain Pointing to Internal IP, August 15th 6:59 GMT +8
  • Device / Initial Breach Chain Compromise, August 15th 6:59 GMT +8
  • Compromise / Large Number of Suspicious Failed Connections, August 15th 7:01 GMT +8
  • Compromise / High Volume of Connections with Beacon Score, August 15th 7:04 GMT +8
  • Compromise / Fast Beaconing to DGA, August 15th 7:04 GMT +8
  • Compromise / Suspicious File and C2, August 15th 7:04 GMT +8
  • Antigena / Network / Manual / Quarantine Device, August 15th 8:54 GMT +8 [part of the RESPOND functionality]

List of IOCs

MITRE ATT&CK マッピング

参考文献リスト

[1] They Come in the Night: Ransomware Deployment Trends

[2] Rise in XorDdos: A deeper look at the stealthy DDoS malware targeting Linux devices

[3] Alien Vault: Domain Navicatadvvr & https://www.virustotal.com/gui/domain/navicatadvvr.com & https://maltiverse.com/hostname/navicatadvvr.com

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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Steven Sosa
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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
Cyber Security Analyst

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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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