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PREVENT

PREVENT ユースケース:ブランドの乱用に先手を打つ

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13
Nov 2022
13
Nov 2022
Brand abuse involves impersonating an organization's IP to launch an attack or damage its reputation. This blog lays out how this can be pre-empted and prevented with Darktrace.

ブランドの乱用とは、組織のブランドを不正に模倣することを指します。ブランドの不正利用が発覚すると、企業はデータや知的財産の保護だけでなく、企業の評判も危険にさらされていることを思い知らされることになります。しかし、ブランドの模倣は、組織とその周囲の人々に対して直接攻撃を仕掛けるために使われることもあります。 

試用期間中の最初の製品デモを実施中、Darktrace PREVENT は最近、あるウェブサイトが古典的な手口を用いていることを発見しました。「rn」という文字が順番に使われ、社名の「m」を模倣しているのです(例:exarnple-brand.com )。注意深く見ていれば一目瞭然ですが、疑うことを知らない従業員にとっては、これは簡単に気づかないものです。 

このウェブサイトは、PREVENT デモの 2 週間前に攻撃者によって開設されたものです。このウェブサイトは直ちに削除され、このアドレスからメールを受け取った人がいないかどうか、社内で調査するようにとの指示がありました。同社はまた、サプライチェーンにこの攻撃を知らせる情報キャンペーンを展開し、この最後の活動により、サプライヤーの1社が同じメールドメインを通じて詐欺に遭い、メインブランドとは関係のないシェルカンパニーに多額の資金を送金していたことが発覚しました。そのサプライヤーに警告を発したことで、さらなる送金を防ぐことができました。

この例は、業界全体で見られるより広範な傾向の一部です。ZDNETのFraud Trends Reportによると、2021年第2四半期におよそ25万件の攻撃が何らかの形でブランドの乱用に関与していることが判明しました。これらの攻撃は、風評被害を与えたり、不正競争によって金銭的損失を被ったり、サプライチェーン攻撃のようなより大きな脅威の足がかりとなるなど、企業に損害を与えます。

企業は、競合他社と差別化し、消費者との関係を構築するために、ブランドアイデンティティの確立に努めています。しかし、ブランド力が高く、認知度が高ければ高いほど、悪意のある行為者がその成功に乗じてより多くの被害者を出そうとするため、悪用のターゲットにされることが多くなります。また、オンラインでの存在感が大きい企業や、複数のチャネルで国際的に事業を展開している企業も、より高いリスクを抱えています。 

ブランドの不正利用には、さまざまな形態があります。ブランドのものであるかのように見せかけたWebサイトで、Eメールアドレスやパスワードなどの個人情報を収集することもあります。ベンダーから送られてくる請求書の名前にわずかな誤字がある場合もあります。購入者に商品を発送しない、未承認のブランドのウェブショップである可能性もあります。マルウェアを配布する悪質なウェブサイトやフェイクニュースを広めるソーシャルメディアに誘導する偽のアカウントである可能性があります。著作権や商標権の侵害のような単純なものである場合もあります。

図1: 悪意あるアクターがブランド乱用に使用する一般的なパターン

ブランド乱用への対応

ブランドの不正利用が発生した後にブランドの評判を回復するのは、事前に投資してブランドを保護するよりもはるかに困難でコストがかかることが分かっています。リスクの検知と監視には、さまざまな形態のブランド乱用に対応する総合的なアプローチが必要で、模倣品、タイポスクワッター、その他の悪質な流用がないか、インターネットをパトロールする必要があります。 

図 2:図 1 のブランド乱用のステージにマッピングすると、セキュリティチームは、ブランドの乱用を手遅れになる前に食い止めるために、探すべきシグナルと取るべきアクションのセットを確認することができます

ブランドのアイデンティティと外部からのアタックサーフェスを保護することは、セキュリティチームにとって困難な作業に思えるかもしれません。特に、内部システムを監視すること自体が十分な課題であることが証明されている時代においてはなおさらです。さらに、ブランド不正利用の監視は、どの程度の頻度で行えばよいのでしょうか。企業は、6か月ごと、四半期ごと、あるいは1か月ごとに調査を行うことができますが、それでも、脅威アクターが攻撃を開始してからセキュリティチームがそれを発見するまでの間にギャップが生じることになります。このような場合、人間のチームでは不可能なスピードとスケールで動作するAIが非常に大きな味方となります。 

PREVENTの能力

PREVENT/Attack Surface Management は、ブランドの不正利用を自律的かつ継続的に発見し、その結果として引き起こされる可能性のある攻撃に対して、積極的に防御を強化します。 

AIを利用して、企業の外部資産を世界のインターネットから区別することができます。その処理機能は、ロゴやドメイン名などのブランド関連資産を学習します。また、自然言語処理と画像分類のアルゴリズムを活用し、最も曖昧でエラーが発生しやすい資産にも取り組み、模倣品やタイポスクワッターを特定し、阻止することができます。 

PREVENT/ASMは、このような包括的なレベルの監視を継続的に行い、攻撃者が悪意のあるインフラを構築してから、セキュリティチームがそれを特定するまでのギャップを縮めています。PREVENTは、攻撃者が明日の朝、悪意のあるウェブサイトを作成した場合、セキュリティチームも明日の朝、アラートを受け取ることになります。 

PREVENT/ASMは、ブランドの不正使用を特定するだけでなく、通知とテイクダウンの手順をサポートするために必要なすべての関連データを収集するためのチームも支援します。また、Darktraceの他のセキュリティエコシステムと統合し、PREVENT/ASMによって発見された悪意のある資産が攻撃に使われた場合に備えて、サイバー防御を事前に強化することができます。 

例えば、あるブランドになりすましたWebページを特定することは、Eメールセキュリティにとって有用なデータです。PREVENT は、悪意のあるドメインについてDarktrace/Email に警告し、このサイトから送信されたEメールに対する感度を高めます。ネットワークトラフィックやエンドポイントセキュリティに関しても同様です。このホストにアクセスするエンドポイントデバイスは、Darktrace DETECT +Darktrace RESPOND に高い警戒心を持ち、脅威的な活動が発生したときにすぐに無効化できるようになっています。 

これは、Cyber AI Loop の力であり、AIエンジンが継続的に相互にフィードバックし、強化し合う好循環を意味します。

また、PREVENT は、ブランド乱用の事例(シャドーIT、設定ミス、サプライチェーンリスク、その他の脆弱性とともに)を特定するだけでなく、露出度と潜在的な被害や影響に応じて、これらのリスクに優先順位を付けます。PREVENT Darktrace/End-to-End は、組織内のあらゆるデバイスと接続、すべてのユーザーとそのやり取り、可能な限りの攻撃経路を把握し、内部と外部の攻撃対象から得られる知見を組み合わせて、セキュリティチームがサイバーリスクを減らすために最も効果的に時間を使う方法を十分に理解できるようにします。 

このように、PREVENT は、人間のセキュリティチームの能力をはるかに超える範囲と規模でブランドの不正使用を監視するだけでなく、DETECT +RESPOND と統合して企業のサイバーセキュリティを強化することができるのです。 

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Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
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After 2 years in a commercial role helping to deploy Darktrace across a broad range of digital environments, Elliot currently occupies the role of Product Subject Matter Expert, where he helps to articulate the value of Darktrace’s technology to customers around the world. Elliot holds a Masters degree in Data Science and Machine Learning, using this knowledge to communicate concepts around machine learning and AI in an accessible way to different audiences.

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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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著者について
Jeff Cornelius
EVP, Cyber-Physical Security

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

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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。
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