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従業員とEメール:ユーザー体験を考慮したEメールセキュリティの強化方法

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10
Apr 2023
10
Apr 2023
Eメールの実質的な利用者である従業員は、Eメールのセキュリティを設計する際に考慮する必要があります。従業員を意識したセキュリティ対策は、防御力を強化し、生産性を向上させ、データ損失を防ぐことができます。

Eメールのセキュリティを考えるとき、ITチームはこれまで、従業員を完全に排除するか、あるいは排除せず権限を与えすぎて、それを補おうと強制力のない信頼ベースのポリシーを導入するかという選択を迫られてきました。 

しかし、Eメールセキュリティは従業員に頼るべきでないからと言って、従業員を完全に排除する必要はありません。従業員は毎日メールに接しており、その経験や行動からセキュリティに関する貴重な洞察を得ることができ、生産性にも影響を与えることができます。 

AI技術は、このように押し付けがましくないニュアンスで従業員のエンゲージメントをサポートし、Eメールセキュリティの維持だけでなく、その強化も実現します。 

セキュリティ戦略における従業員の参画のバランスの模索

歴史的に、セキュリティソリューションは、従業員の関与に対して「オール・オア・ナッシング」のアプローチを提供してきました。従業員を巻き込んだとしても、彼らは信頼できる存在とは言い切れません。社員が全員、実際の仕事の責任に加えてセキュリティの専門家になることはできませんし、ペースの速い環境ではミスも付きものです。  

セキュリティ意識を高めるための試みは行われていますが、トレーニング用のEメールには文脈や現実味がないため、従業員の理解度が低く、実際には安全なEメールでも報告してしまうことがよくあります。ユーザーが常に受信トレイを整理し、安全なEメールを報告することは、時間の無駄であり、ユーザー自身の生産性だけでなく、セキュリティチームの生産性も低下させます。

その他のかつてから存在する従業員の関与の形も、セキュリティを危険にさらします。例えば、ユーザーはフィードバックを通じて包括的なルールを作成することができ、gmail.comドメインから送られてくるすべてのメールをセーフリスト化するような一般的な問題につながる可能性があります。また、文脈や制限なしにEメールを公開することを従業員が自ら選択し、組織に大きなリスクをもたらす場合もあります。このような行動は、従業員がセキュリティに参加することを意味しますが、これはセキュリティの犠牲の上に成り立っているのです。 

より低いステータスの従業員の関与でも、効果がないことが判明することがあります。例えば、社外の連絡先にEメールを送る際に過剰な警告を出すと、バナー疲れにつながります。従業員が毎回同じ警告メッセージやアラートをメッセージの先頭に表示すると、すぐに慣れてしまい、最終的には免疫ができてしまうのが人間の性です。

一方、従業員がセキュリティから完全に排除されている場合、実際のユーザーに応じてセキュリティを微調整し、Eメールセキュリティソリューションがどの程度機能しているかをフィードバックする機会が失われてしまいます。 

そのため、従来のEメールセキュリティでは、従業員を含むか含まないかのどちらの選択肢も、従業員を効果的に活用できないことが判明しています。最高のEメールセキュリティの実践は、この両極端の間でバランスを取り、日常業務を中断することなくセキュリティを維持する、より微妙なやりとりを可能にするものです。これは、セキュリティを損なうのではなく、セキュリティを高めるために、各従業員に特化したやり取りを調整するAIで実現できます。 

セキュリティ啓発教育を充実させながら誤報を減らす 

人間とAIによるEメールセキュリティは、連携することで同時にレベルアップすることができます。AIが社員に情報を提供し、社員がAIに情報を提供することで、社員とAIのフィードバックループが実現します。  

AIは、すべてのEメールユーザーの「正常な」行動を理解することで、Eメールの異常で危険な構成要素を特定し、リンクの書き換え、添付ファイルのフラット化、迷惑メールへの移行など、Eメールの性質に基づいた的確なアクションを行い、それらを無害化できます。AIはさらに一歩進んで、なぜ特定の行動をとったのかを専門的でない平易な言葉で説明することができ、ユーザーを教育することができます。ポイントインタイムでシミュレーションされたフィッシングメールキャンペーンとは対照的に、ユーザーがEメールに疑問を抱いた瞬間に、AIが組織を取り巻く文脈の中で、リアルタイムに分析を共有できることを意味します。 

従業員とAIのフィードバックループは、従業員が追加のエンリッチメントデータとして機能するように教育します。脅威の検知をユーザーに依存しない一方で、ユーザーに情報を提供し、教えるための適切なレベルを決定します。 

一方、AIはユーザーの受信トレイでの行動を学習し、それを徐々に意思決定に反映させていきます。一人の従業員があるEメールを安全だと判断しても、ビジネス全体がそれを承認することはありません。しかし、時間をかけてパターンを観察し、自律的な意思決定を強化することができます。  

Figure 1: The employee-AI feedback loop increases employee understanding without putting security at risk.

従業員とAIのフィードバックループは、従業員がEメールセキュリティに関与することで得られる潜在的なメリットを最大限に引き出します。他のEメールセキュリティソリューションでは、セキュリティチームのワークフローを強化するだけで、不審なメールを報告する従業員のことは考慮されていません。正しいことをしようとしても、やみくもにEメールを報告する社員は、学習も改善もせず、結局は自分の時間を無駄にすることになります。従業員を考慮し、セキュリティ意識のトレーニングを改善することで、従業員とAIのフィードバックループはユーザーをレベルアップさせることができます。従業員はAIの説明から悪意のあるコンポーネントの識別方法を学ぶことで、報告するEメールの数を減らし、より高い精度で報告するようになります。 

AIプログラムが古典的にブラックボックスのように動作しているのに対し、Darktraceは、組織の実際の従業員という最高のデータに基づいてAIを訓練し、セキュリティチームと従業員の双方がその結論の背後にある理由を見るように誘導します。時間の経過とともに、従業員は安全でないEメールを見分ける方法をよりよく学ぶようになり、自分自身をより信頼するようになるのです。 

AIを活用して生産性向上を実現する

ユニークなのは、AIを活用したEメールセキュリティは、セキュリティ関連以外の分野でも効果を発揮することです。非生産的なEメールを管理することで、時間を節約することができるのです。AIは受信トレイでの従業員の行動を常に学習するため、スパムやグレーメール(必ずしも悪意があるわけではないが、受信トレイを乱して生産性を低下させるメール)を検知するのに非常に効果的です。これは、各従業員がスパム、グレーメール、ニュースレターをどのように扱っているかに応じて、ユーザーごとに行われるものです。AIは、このような混乱を検知して学習し、最終的には受信箱からどれを取り出すべきかを学習し、従業員の時間を節約することができます。これは、セキュリティソリューションが、単に軽いタッチでEメール環境を保護するだけでなく、AIが受信トレイの仕分けなどのタスクを自動化することで生産性向上を促進するところまで踏み込めることを強調しています。

メールの誤送信を防ぐ:ヒューマンエラーに対処する方法

ユーザーの理解と意思決定を向上させても、自然なヒューマンエラーを止めることはできません。特にOutlookが間違った宛先を自動入力する場合、従業員は必ずミスを犯し、簡単に間違った相手にEメールを送信してしまいます。このようなミスは、コンプライアンス、顧客からの信頼、知的財産、データ損失などに大きな影響を及ぼし、恥ずかしいものから重大なものまで、さまざまな影響を及ぼす可能性があります。 

しかし、AIを使えば、誤って間違った相手にメールを送ってしまうケースを減らすことができます。ユーザーがOutlookでメールを送信しようとすると、AIが受信者を分析します。送信者と受信者の間の文脈上の関係、受信者同士の関係、各受信者の名前と履歴が他の既知の連絡先とどれだけ似ているか、添付ファイルの名前などを考慮します。  

AIは、そのEメールがユーザーの典型的な行動から外れていると判断した場合、ユーザーに警告することができます。セキュリティチームは、AIが次に何をするかをカスタマイズできます。Eメールをブロックする、Eメールをブロックするがユーザーがそれを上書きする、何もしないがユーザーに考え直すよう促す、などです。AIは各Eメールを分析するため、これらの警告は、無視されがちな外部受信者についての一貫した包括的な警告よりも効果的なものとなっています。このようにターゲットを絞ったアプローチで、AIはデータ漏えいを防ぎ、サイバーリスクを低減します。 

AIは常時稼働し、継続的に学習するため、社員の変化に自律的に適応することができます。従業員の役割が変化した場合、AIは一般的な行動、受信者、添付ファイル名など、新しい常識を学習します。これにより、AIは、手動でルールを変更したり、従業員のワークフローを中断したりすることなく、ヒューマンエラーの可能性がある事例を効果的に指摘し続けることができるようになります。 

従業員体験に基づくEメールセキュリティ

Eメールの実質的な利用者である従業員は、Eメールのセキュリティを設計する際に考慮する必要があります。従業員を意識したセキュリティ対策は、防御力を強化し、生産性を向上させ、データ損失を防ぐことができます。  

このように、Eメールセキュリティは、従業員とセキュリティチームの双方にメリットをもたらします。従業員は、安全なEメールに関する誤った報告を減らすために、セキュリティ意識向上のためのトレーニングを受けることで、もう一つの防衛層となることができます。また、従業員のEメール行動に対する洞察は、グレーメールの学習と選別によって、従業員の生産性を高めることができます。最後に、従業員とセキュリティの関係を見ることで、セキュリティチームは、誤送信されたEメールにフラグを立て、データ損失を減らすツールを導入することができます。これらの機能により、Darktrace/Email™は、セキュリティチームが従業員のEメールセキュリティへの関与のバランスを最適化することを可能にします。

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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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Based in New York, Dan joined Darktrace’s technical team in 2015, helping customers quickly achieve a complete and granular understanding of Darktrace’s product suite. Dan has a particular focus on Darktrace/Email, ensuring that it is effectively deployed in complex digital environments, and works closely with the development, marketing, sales, and technical teams. Dan holds a Bachelor’s degree in Computer Science from New York University.

Carlos Gray
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Carlos Gonzalez Gray is a Product Marketing Manager at Darktrace. Based in the Madrid Office, Carlos engages with the global product team to ensure each product supports the company’s overall strategy and goals throughout their entire lifecycle. Previous to his position in the product team, Carlos worked as a Cyber Technology Specialist where he specialized in the OT sector protecting critical infrastructure.  His background as a consultant in Spain to IBEX 35 companies led him to become well versed in matters of compliance, auditing and data privacy as well. Carlos holds an Honors BA in Political Science and a Masters in Cybersecurity from IE University.

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Inside the SOC

PurpleFox in a Henhouse: How Darktrace Hunted Down a Persistent and Dynamic Rootkit

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27
Nov 2023

Versatile Malware: PurpleFox

As organizations and security teams across the world move to bolster their digital defenses against cyber threats, threats actors, in turn, are forced to adopt more sophisticated tactics, techniques and procedures (TTPs) to circumvent them. Rather than being static and predictable, malware strains are becoming increasingly versatile and therefore elusive to traditional security tools.

One such example is PurpleFox. First observed in 2018, PurpleFox is a combined fileless rootkit and backdoor trojan known to target Windows machines. PurpleFox is known for consistently adapting its functionalities over time, utilizing different infection vectors including known vulnerabilities (CVEs), fake Telegram installers, and phishing. It is also leveraged by other campaigns to deliver ransomware tools, spyware, and cryptocurrency mining malware. It is also widely known for using Microsoft Software Installer (MSI) files masquerading as other file types.

The Evolution of PurpleFox

The Original Strain

First reported in March 2018, PurpleFox was identified to be a trojan that drops itself onto Windows machines using an MSI installation package that alters registry values to replace a legitimate Windows system file [1]. The initial stage of infection relied on the third-party toolkit RIG Exploit Kit (EK). RIG EK is hosted on compromised or malicious websites and is dropped onto the unsuspecting system when they visit browse that site. The built-in Windows installer (MSIEXEC) is leveraged to run the installation package retrieved from the website. This, in turn, drops two files into the Windows directory – namely a malicious dynamic-link library (DLL) that acts as a loader, and the payload of the malware. After infection, PurpleFox is often used to retrieve and deploy other types of malware.  

Subsequent Variants

Since its initial discovery, PurpleFox has also been observed leveraging PowerShell to enable fileless infection and additional privilege escalation vulnerabilities to increase the likelihood of successful infection [2]. The PowerShell script had also been reported to be masquerading as a .jpg image file. PowerSploit modules are utilized to gain elevated privileges if the current user lacks administrator privileges. Once obtained, the script proceeds to retrieve and execute a malicious MSI package, also masquerading as an image file. As of 2020, PurpleFox no longer relied on the RIG EK for its delivery phase, instead spreading via the exploitation of the SMB protocol [3]. The malware would leverage the compromised systems as hosts for the PurpleFox payloads to facilitate its spread to other systems. This mode of infection can occur without any user action, akin to a worm.

The current iteration of PurpleFox reportedly uses brute-forcing of vulnerable services, such as SMB, to facilitate its spread over the network and escalate privileges. By scanning internet-facing Windows computers, PurpleFox exploits weak passwords for Windows user accounts through SMB, including administrative credentials to facilitate further privilege escalation.

Darktrace detection of PurpleFox

In July 2023, Darktrace observed an example of a PurpleFox infection on the network of a customer in the healthcare sector. This observation was a slightly different method of downloading the PurpleFox payload. An affected device was observed initiating a series of service control requests using DCE-RPC, instructing the device to make connections to a host of servers to download a malicious .PNG file, later confirmed to be the PurpleFox rootkit. The device was then observed carrying out worm-like activity to other external internet-facing servers, as well as scanning related subnets.

Darktrace DETECT™ was able to successfully identify and track this compromise across the cyber kill chain and ensure the customer was able to take swift remedial action to prevent the attack from escalating further.

While the customer in question did have Darktrace RESPOND™, it was configured in human confirmation mode, meaning any mitigative actions had to be manually applied by the customer’s security team. If RESPOND had been enabled in autonomous response mode at the time of the attack, it would have been able to take swift action against the compromise to contain it at the earliest instance.

攻撃の概要

Figure 1: Timeline of PurpleFox malware kill chain.

Initial Scanning over SMB

On July 14, 2023, Darktrace detected the affected device scanning other internal devices on the customer’s network via port 445. The numerous connections were consistent with the aforementioned worm-like activity that has been reported from PurpleFox behavior as it appears to be targeting SMB services looking for open or vulnerable channels to exploit.

This initial scanning activity was detected by Darktrace DETECT, specifically through the model breach ‘Device / Suspicious SMB Scanning Activity’. Darktrace’s Cyber AI Analyst™ then launched an autonomous investigation into these internal connections and tied them into one larger-scale network reconnaissance incident, rather than a series of isolated connections.

Figure 2: Cyber AI Analyst technical details summarizing the initial scanning activity seen with the internal network scan over port 445.

As Darktrace RESPOND was configured in human confirmation mode, it was unable to autonomously block these internal connections. However, it did suggest blocking connections on port 445, which could have been manually applied by the customer’s security team.

Figure 3: The affected device’s Model Breach Event Log showing the initial scanning activity observed by Darktrace DETECT and the corresponding suggested RESPOND action.

特権昇格

The device successfully logged in via NTLM with the credential, ‘administrator’. Darktrace recognized that the endpoint was external to the customer’s environment, indicating that the affected device was now being used to propagate the malware to other networks. Considering the lack of observed brute-force activity up to this point, the credentials for ‘administrator’ had likely been compromised prior to Darktrace’s deployment on the network, or outside of Darktrace’s purview via a phishing attack.

Exploitation

Darktrace then detected a series of service control requests over DCE-RPC using the credential ‘admin’ to make SVCCTL Create Service W Requests. A script was then observed where the controlled device is instructed to launch mshta.exe, a Windows-native binary designed to execute Microsoft HTML Application (HTA) files. This enables the execution of arbitrary script code, VBScript in this case.

Figure 4: PurpleFox remote service control activity captured by a Darktrace DETECT model breach.
Figure 5: The infected device’s Model Breach Event Log showing the anomalous service control activity being picked up by DETECT.

There are a few MSIEXEC flags to note:

  • /i : installs or configures a product
  • /Q : sets the user interface level. In this case, it is set to ‘No UI’, which is used for “quiet” execution, so no user interaction is required

Evidently, this was an attempt to evade detection by endpoint users as it is surreptitiously installed onto the system. This corresponds to the download of the rootkit that has previously been associated with PurpleFox. At this stage, the infected device continues to be leveraged as an attack device and scans SMB services over external endpoints. The device also appeared to attempt brute-forcing over NTLM using the same ‘administrator’ credential to these endpoints. This activity was identified by Darktrace DETECT which, if enabled in autonomous response mode would have instantly blocked similar outbound connections, thus preventing the spread of PurpleFox.

Figure 6: The infected device’s Model Breach Event Log showing the outbound activity corresponding to PurpleFox’s wormlike spread. This was caught by DETECT and the corresponding suggested RESPOND action.

Installation

On August 9, Darktrace observed the device making initial attempts to download a malicious .PNG file. This was a notable change in tactics from previously reported PurpleFox campaigns which had been observed utilizing .MOE files for their payloads [3]. The .MOE payloads are binary files that are more easily detected and blocked by traditional signatured-based security measures as they are not associated with known software. The ubiquity of .PNG files, especially on the web, make identifying and blacklisting the files significantly more difficult.

The first connection was made with the URI ‘/test.png’.  It was noted that the HTTP method here was HEAD, a method similar to GET requests except the server must not return a message-body in the response.

The metainformation contained in the HTTP headers in response to a HEAD request should be identical to the information sent in response to a GET request. This method is often used to test hypertext links for validity and recent modification. This is likely a way of checking if the server hosting the payload is still active. Avoiding connections that could possibly be detected by antivirus solutions can help keep this activity under-the-radar.

Figure 7: Packet Capture from an affected customer device showing the initial HTTP requests to the payload server.
Figure 8: Packet Capture showing the HTTP requests to download the payloads.

The server responds with a status code of 200 before the download begins. The HEAD request could be part of the attacker’s verification that the server is still running, and that the payload is available for download. The ‘/test.png’ HEAD request was sent twice, likely for double confirmation to begin the file transfer.

Figure 9: PCAP from the affected customer device showing the Windows Installer user-agent associated with the .PNG file download.

Subsequent analysis using a Packet Capture (PCAP) tool revealed that this connection used the Windows Installer user agent that has previously been associated with PurpleFox. The device then began to download a payload that was masquerading as a Microsoft Word document. The device was thus able to download the payload twice, from two separate endpoints.

By masquerading as a Microsoft Word file, the threat actor was likely attempting to evade the detection of the endpoint user and traditional security tools by passing off as an innocuous text document. Likewise, using a Windows Installer user agent would enable threat actors to bypass antivirus measures and disguise the malicious installation as legitimate download activity.  

Darktrace DETECT identified that these were masqueraded file downloads by correctly identifying the mismatch between the file extension and the true file type. Subsequently, AI Analyst was able to correctly identify the file type and deduced that this download was indicative of the device having been compromised.

In this case, the device attempted to download the payload from several different endpoints, many of which had low antivirus detection rates or open-source intelligence (OSINT) flags, highlighting the need to move beyond traditional signature-base detections.

Figure 10: Cyber AI Analyst technical details summarizing the downloads of the PurpleFox payload.
Figure 11 (a): The Model Breach generated by the masqueraded file transfer associated with the PurpleFox payload.
Figure 11 (b): The Model Breach generated by the masqueraded file transfer associated with the PurpleFox payload.

If Darktrace RESPOND was enabled in autonomous response mode at the time of the attack it would have acted by blocking connections to these suspicious endpoints, thus preventing the download of malicious files. However, as RESPOND was in human confirmation mode, RESPOND actions required manual application by the customer’s security team which unfortunately did not happen, as such the device was able to download the payloads.

結論

The PurpleFox malware is a particularly dynamic strain known to continually evolve over time, utilizing a blend of old and new approaches to achieve its goals which is likely to muddy expectations on its behavior. By frequently employing new methods of attack, malicious actors are able to bypass traditional security tools that rely on signature-based detections and static lists of indictors of compromise (IoCs), necessitating a more sophisticated approach to threat detection.  

Darktrace DETECT’s Self-Learning AI enables it to confront adaptable and elusive threats like PurpleFox. By learning and understanding customer networks, it is able to discern normal network behavior and patterns of life, distinguishing expected activity from potential deviations. This anomaly-based approach to threat detection allows Darktrace to detect cyber threats as soon as they emerge.  

By combining DETECT with the autonomous response capabilities of RESPOND, Darktrace customers are able to effectively safeguard their digital environments and ensure that emerging threats can be identified and shut down at the earliest stage of the kill chain, regardless of the tactics employed by would-be attackers.

Credit to Piramol Krishnan, Cyber Analyst, Qing Hong Kwa, Senior Cyber Analyst & Deputy Team Lead, Singapore

付録

Darktraceによるモデル検知

  • Device / Increased External Connectivity
  • Device / Large Number of Connections to New Endpoints
  • Device / SMB Session Brute Force (Admin)
  • Compliance / External Windows Communications
  • Anomalous Connection / New or Uncommon Service Control
  • Compromise / Unusual SVCCTL Activity
  • Compromise / Rare Domain Pointing to Internal IP
  • Anomalous File / Masqueraded File Transfer

RESPOND Models

  • Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block
  • Antigena / Network / External Threat / Antigena Suspicious Activity Block
  • Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client 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

IoC一覧

IoC - Type - Description

/C558B828.Png - URI - URI for Purple Fox Rootkit [4]

5b1de649f2bc4eb08f1d83f7ea052de5b8fe141f - File Hash - SHA1 hash of C558B828.Png file (Malware payload)

190.4.210[.]242 - IP - Purple Fox C2 Servers

218.4.170[.]236 - IP - IP for download of .PNG file (Malware payload)

180.169.1[.]220 - IP - IP for download of .PNG file (Malware payload)

103.94.108[.]114:10837 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)

221.199.171[.]174:16543 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)

61.222.155[.]49:14098 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)

178.128.103[.]246:17880 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)

222.134.99[.]132:12539 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)

164.90.152[.]252:18075 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)

198.199.80[.]121:11490 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)

MITRE ATT&CK マッピング

Tactic - Technique

Reconnaissance - Active Scanning T1595, Active Scanning: Scanning IP Blocks T1595.001, Active Scanning: Vulnerability Scanning T1595.002

Resource Development - Obtain Capabilities: Malware T1588.001

Initial Access, Defense Evasion, Persistence, Privilege Escalation - Valid Accounts: Default Accounts T1078.001

Initial Access - Drive-by Compromise T1189

Defense Evasion - Masquerading T1036

Credential Access - Brute Force T1110

Discovery - Network Service Discovery T1046

Command and Control - Proxy: External Proxy T1090.002

参考文献

  1. https://blog.360totalsecurity.com/en/purple-fox-trojan-burst-out-globally-and-infected-more-than-30000-users/
  2. https://www.trendmicro.com/en_us/research/19/i/purple-fox-fileless-malware-with-rookit-component-delivered-by-rig-exploit-kit-now-abuses-powershell.html
  3. https://www.akamai.com/blog/security/purple-fox-rootkit-now-propagates-as-a-worm
  4. https://www.foregenix.com/blog/an-overview-on-purple-fox
  5. https://www.trendmicro.com/en_sg/research/21/j/purplefox-adds-new-backdoor-that-uses-websockets.html
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著者について
Piramol Krishnan
Cyber Security Analyst

$70 Million in Cyber Security Funding for Electric Cooperatives & Utilities

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22
Nov 2023

What is the Bipartisan Infrastructure Deal?

The Bipartisan Infrastructure Law passed by congress in 2021 aimed to upgrade power and infrastructure to deliver clean, reliable energy across the US to achieve zero-emissions. To date, the largest investment in clean energy, the deal will fund new programs to support the development and deployment of clean energy technology.

Why is it relevant to electric municipalities?

Section 40124 of the Bipartisan Infrastructure Law allocates $250 million over a 5-year period to create the Rural and Municipal Utility Cybersecurity (RMUC) Program to help electric cooperative, municipal, and small investor-owned utilities protect against, detect, respond to, and recover from cybersecurity threats.1 This act illuminates the value behind a full life-cycle approach to cyber security. Thus, finding a cyber security solution that can provide all aspects of security in one integrated platform would enhance the overall security posture and ease many of the challenges that arise with adopting multiple point solutions.

On November 16, 2023 the Office of Cybersecurity, Energy Security, and Emergency Response (CESER) released the Advanced Cybersecurity Technology (ACT) for electric utilities offering a $70 million funding opportunity that aims to enhance the cybersecurity posture of electric cooperative, municipal, and small investor-owned utilities.

Funding Details

10 projects will be funded with application submissions due November 29, 2023, 5:00 pm ET with $200,000 each in cash prizes in the following areas:

  1. Direct support for eligible utilities to make investments in cybersecurity technologies, tools, training, and improvements in utility processes and procedures;
  2. Funding to strengthen the peer-to-peer and not-for-profit cybersecurity technical assistance ecosystem currently serving eligible electric utilities; and
  3. Increasing access to cybersecurity technical assistance and training for eligible utilities with limited cybersecurity resources. 2

To submit for this award visit: https://www.herox.com/ACT1Prize

How can electric municipalities utilize the funding?

While the adoption of hybrid working patterns increase cloud and SaaS usage, the number of industrial IoT devices also continues to rise. The result is decrease in visibility for security teams and new entry points for attackers. Particularly for energy and utility organizations.

Electric cooperatives seeking to enhance their cyber security posture can aim to invest in cyber security tools that provide the following:

Compliance support: Consider finding an OT security solution that maps out how its solutions and features help your organization comply with relevant compliance mandates such as NIST, ISA, FERC, TSA, HIPAA, CIS Controls, and more.

Anomaly based detection: Siloed security solutions also fail to detect attacks that span
the entire organization. Anomaly-based detection enhances an organization’s cyber security posture by proactively defending against potential attacks and maintaining a comprehensive view of their attack surface.

Integration capabilities: Implementation of several point solutions that complete individual tasks runs the risk of increasing workloads for operators and creates additional challenges with compliance, budgeting, and technical support. Look for cyber security tools that integrate with your existing technologies.

Passive and active asset tracking: Active Identification offers accurate enumeration, real time updates, vulnerability assessment, asset validation while Passive Identification eliminates the risk of operational disruption, minimizes risk, does not generate additional network traffic. It would be ideal to find a security solution that can do both.

Can secure both IT and OT in unison: Given that most OT cyber-attacks actually start in IT networks before pivoting into OT, a mature security posture for critical infrastructure would include a single solution for both IT and OT. Separate solutions for IT and OT present challenges when defending network boundaries and detecting incidents when an attacker pivots from IT to OT. These independent solutions also significantly increase operator workload and materially diminish risk mitigation efforts.

Darktrace/OT for Electric Cooperatives and Utilities

For smaller teams with just one or two dedicated employees, Darktrace’s Cyber AI Analyst and Investigation features allow end users to spend less time in the platform as it compiles critical incidents into comprehensive actionable event reports. AI Analyst brings all the information into a centralized view with incident reporting in natural language summaries and can be generated for compliance reports specific to regulatory requirements.  

For larger teams, Darktrace alerts can be forwarded to 3rd party platforms such as a SIEM, where security team decision making is augmented. Additionally, executive reports and autonomous response reduce the alert fatigue generally associated with legacy tools. Most importantly, Darktrace’s unique understanding of normal allows security teams to detect zero-days and signatureless attacks regardless of the size of the organization and how alerts are consumed.

Key Benefits of Darktrace/OT

Figure 1: Darktrace/OT stops threats moving from IT to OT by providing a unified view across both systems

参考文献

1. https://www.whitehouse.gov/briefing-room/statements-releases/2021/11/06/fact-sheet-the-bipartisan-infrastructure-deal/

2. https://www.energy.gov/ceser/rural-and-municipal-utility-advanced-cybersecurity-grant-and-technical-assistance-rmuc

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Jeff Cornelius
EVP, Cyber-Physical Security

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