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二重恐喝ビジネス:ランサムウェアギャングContiが見つけ出した新たな交渉方法

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07
2021年12月
07
2021年12月
By constantly shifting tactics, the Conti Ransomware Gang have maintained one of the largest stakes in the increasingly profitable ransomware industry. Discover how Darktrace was able to detect one of their crippling double extortion attacks at its earliest stages.

前回のブログでは、ロシアのハッカーグループ ‘Wizard Spider’ が開発したRyukランサムウェアが、末端のサイバー犯罪者達の手にも渡っていることを紹介しました。

Wizard Spider はロシア政府の支援を受けて活動しているとされ、FBIとインターポールによる捜査対象となっていますが、彼らは2020年に Ryuk ランサムウェアの後継種 ‘Conti’ を採用しています。Conti はすべてのWindowsオペレーティングシステムに影響し、400件以上のインシデントに関与しています。Wizard Spider はその後ほどなく ‘Conti Ransomware Gang’ という名前にブランドを変更しました。ただしこのグループは必ずしも自身を「ギャング」とは見ていません。彼らはむしろ自らを「ビジネス」であるとしています。

ランサムウェアバブル

ランサムウェアは数十億ドル規模の産業となっています。そしてConti Ransomware Gangは2020年にその15%を占めたと報告されています。このような規模の収入を持つようになるとContiのようなグループも一般のビジネス慣行の真似事を一部取り入れるようになります。この偽企業は彼らの標的を「カスタマー」、彼らの脅迫を「ネゴシエーション」、彼らの犯罪者仲間を「アフィリエイト」と呼んでいるのです。果ては専用のDark Webサイトで「プレスリリース」を発表する有様です。

彼らのRansomware-as-a-Service「ビジネスモデル」は、アフィリエイトを採用し、Contiランサムウェアの展開と管理をトレーニングし、彼らの利益の30%を回収するという方法です。しかし、具体的な利益はマルウェア作成者のみが知りアフィリエイトには知られていないため、多くの場合Contiの取り分は彼らが主張する30%よりもずっと大きいのです。

サイバー地下世界では詐欺に対するチェックや規制はないかもしれませんが、Conti が免れることのできなかったビジネス上の問題の1つは、不満を持った従業員でした。

上司の不当な扱いに不満を持った低賃金のアフィリエイトは2021年8月、Conti Ransomware Gangのトレーニング教材と彼らのCobalt Strike C2サーバーのIPアドレスを公開し、「やつらはカモを集めて働かせ自分たちでカネを分け合っている」と主張したのです。

当時、米国政府もConti Ransomware Gangのようなグループの収益構造を中断させるため、ランサムウェアの取引に利用されていると見られている暗号通貨取引所に対して制裁を課すなどの厳しい措置を取っていました。しかし、このようなリークや規制はContiを破滅させるには程遠いことが証明されました。

現実には、これらのアクションによってConti Ransomware Gangがいわゆる「カスタマー」を失うことはなく、カスタマーのあるところには、利益もついてくるのです。サイバーセキュリティを従来のルールベースの手段に頼っているあらゆる個人や組織は彼らのターゲット市場です。

DarktraceのAIは最近、8月にリークされた手法の1つによって実行されたConti攻撃を検知しました。標的となった組織は米国の運輸会社でした。この会社はDarktraceのトライアル利用中でしたが、Darktraceの自動遮断技術をアクティブモードに設定していなかったため、攻撃の進行を許してしまいました。しかし、その進行の様子を精査すると、このような二重恐喝ランサムウェア攻撃がどれほど大きな脅威となるかがわかるとともに、Darktraceによって攻撃の各ステージでこれを効果的に阻止することが可能だということが明らかになります。

図1: 攻撃のタイムライン

Conti Ransomware Gangはランサムウェアのプレイブックを多様化

たった1つのMicrosoftパッチをインストールしなかったために、標的となった組織は危険なProxyShell脆弱性を抱えることになりました。Contiはこの脆弱性につけこみ、この会社のサーバーに対してリモートでExchange PowerShellコマンドを実行する権利を獲得し、着実にそのプレゼンスをデジタル環境内に広げていきました。これは、これまでフィッシング攻撃やファイアウォールのエクスプロイトに頼ってきたConti Ransomware Gangにとっては比較的新しいアプローチです。アプローチを多様化させることによって、パッチやインテリジェンスに先回りしているのです。

最初の侵入から2週間後、フィンランドにある不審なエンドポイントに対してC2接続が行われました。これは一見無害に見えるもののこの組織にとって100%未知のSSLクライアントを使って行われていました。もし自律遮断技術がアクティブモードに設定されていれば、Darktraceがこの非常に早い段階で接続をシャットダウンしていたでしょう。

この疑わしいエンドポイントのIPアドレスは後にConti IoC(Indicator of Compromise)として特定され、ルールベースのセキュリティソリューションにも組み込むことが可能になりました。しかしこの会社はこのインテリジェンスが入手可能になる何週間も前に侵入されていたため、これはほとんど意味がありませんでした。

Contiは内部偵察を継続し、この会社のデジタル環境内を水平移動しましたが、Darktraceはさらなる不審なアクティビティを検知していました。フィンランドにある疑わしいエンドポイントが新しい‘Living off the Land’ (環境に寄生する) テクニックを使って、通常であれば正当なツールである AnyDesk および Cobalt Strike を環境内のさまざまな場所にインストールしたのです。

一連のSSL接続がAnyDeskエンドポイントおよび外部ホストに対して行われ、そのうちの1つは95時間継続していました。これはConti傘下の何者かがアクティブなリモートセッションを行っていたことを表しています。この段階で、Darktraceは攻撃が差し迫っていることを疑う10個の明確な理由を提示していました。

Conti News: 二重恐喝ランサムウェアで取引を成立させる

二重恐喝はConti Ransomware Gangの新たなお気に入りの販売戦術となりました。身代金の支払いを拒否すれば、Contiはあなたの会社の最も重要なファイルを奪うだけではなく、それを専用の ‘Conti News’ ウェブサイトを使って公開し、あるいは競合他社に直接売ることもあります。

この運輸会社のネットワーク全体に存在を拡大すると、攻撃者はこの会社の大量のデータを抜き出しContiが好んで使うクラウドストレージサイト、MEGAに対して急速に転送し始めました。4日間に渡り、3TBを超える量のデータがアップロードされ、次いで暗号化されました。

人間のセキュリティチームによる検知を逃れるため、暗号化は真夜中近くになって開始されました。Contiの「営業」は営業時間に関係なく行われるのです。この会社のセキュリティチームが翌日出社すると、脅迫状が残されていました。

この攻撃が進行してしまったのは、Darktraceがまだトライアル運用中であり脅威の検知はできたもののそれらに対するアクションを取ることが許可されていなかったためです。自動遮断技術がアクティブモードで運用されていれば、このランサムウェア攻撃は非常に速い段階で、Darktraceが最初に疑わしい接続を検知した時に終了していたはずです。

それでも、Cyber AI Analystが自動的に調査を行い、これらの点と点をつなぎ合わせることができたので、このように部分的なDarktraceの運用であっても、これがなかった場合と比較して修正のための作業は大幅に短縮され、かつ簡単に行うことができました。

図2:Cyber AI Analystはデータ抜き出し発生後インシデントレポートを生成

Conti Ransomware Gangはサイバーインテリジェンスをどのように回避するか

脅威を検知するのにヒューマンインテリジェンスに依存しているセキュリティシステムは、Contiが理想とする顧客プロファイルに完璧に一致しています。RyukからContiへ、そしてスピアフィッシングやファイアウォールのエクスプロイトからProxyShellアプローチへと手口を適応させ多様化することにより、Contiは各種規制をすり抜け彼らの脆弱な顧客ベースをしっかりと把握しています。

Conti Ransomware Gangが内部リークや法規制により壊滅したとしても、この違法な利益を狙って他のグループが台頭し、市場の隙間を埋めるでしょう。こうしたグループを本当に阻止するには、利益が得られないようにしなければなりません。

米国政府は身代金を支払った側に罰金を科すことでこれを実現しようとしましたが、それでも多くの企業はデータを復旧できないことによる損失はあまりにも大きすぎると考えています。前述の通り、問われるべきなのは「支払うべきか支払わないべきか」ではありません。

もし支払うべきか支払わないべきかを考えているならば、あなたは既に深みにはまっているのです。DarktraceはContiのようなグループと最初に遭遇した時点で阻止します。この事例でも明らかになったように、Darktraceの自己学習型AIは人間のアナリストや脅威インテリジェンスが検知できるようになる何週間も前に脅威を識別し、自律遮断技術により攻撃のあらゆる段階でこれらを無害化することができます。

この脅威についての考察はDarktraceアナリストSam Lister が協力しました。

Darktraceによるモデル検知:

  • Device / Long Agent Connection to New Endpoint
  • Device / ICMP Address Scan
  • Anomalous Connection / SMB Enumeration
  • Anomalous Server Activity / Outgoing from Server
  • Compromise / Beacon to Young Endpoint
  • Anomalous Server Activity / Rare External from Server
  • Compromise / Fast Beaconing to DGA
  • Compromise / SSL or HTTP Beacon
  • Compromise / Sustained SSL or HTTP Increase
  • Compromise / Beacon for 4 Days
  • Anomalous Connection / Multiple HTTP POSTs to Rare Hostname
  • Unusual Activity / Enhanced Unusual External Data Transfer
  • Anomalous Connection / Data Sent to Rare Domain
  • Anomalous Connection / Uncommon 1 GiB Outbound
  • Compliance / SMB Drive Write
  • Anomalous File / Internal / Additional Extension Appended to SMB File
  • Anomalous Connection / Suspicious Read Write Ratio
  • Anomalous Connection / Suspicious Read Write Ratio and Unusual SMB
  • Anomalous Connection / Sustained MIME Type Conversion
  • Unusual Activity / Anomalous SMB Move & Write
  • Unusual Activity / Unusual Internal Data Volume as Client or Server
  • Device / Suspicious File Writes to Multiple Hidden SMB Shares
  • Compromise / Ransomware / Suspicious SMB Activity
  • Anomalous File / Internal / Unusual SMB Script Write
  • Anomalous File / Internal / Masqueraded Executable SMB Write
  • Device / SMB Lateral Movement
  • Device / Multiple Lateral Movement Model Breaches

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
Justin Fier
SVP, Red Team Operations

Justin is one of the US’s leading cyber intelligence experts, and holds the position of SVP, Red Team Operations at Darktrace. His insights on cyber security and artificial intelligence have been widely reported in leading media outlets, including the Wall Street Journal, CNN, The Washington Post, and VICELAND. With over 10 years’ experience in cyber defense, Justin has supported various elements in the US intelligence community, holding mission-critical security roles with Lockheed Martin, Northrop Grumman Mission Systems and Abraxas. Justin is also a highly-skilled technical specialist, and works with Darktrace’s strategic global customers on threat analysis, defensive cyber operations, protecting IoT, and machine learning.

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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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著者について
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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