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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。 

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
Elliot Stocker
Product SME

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

Sliver C2: How Darktrace Provided a Sliver of Hope in the Face of an Emerging C2 Framework

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17
Apr 2024

Offensive Security Tools

As organizations globally seek to for ways to bolster their digital defenses and safeguard their networks against ever-changing cyber threats, security teams are increasingly adopting offensive security tools to simulate cyber-attacks and assess the security posture of their networks. These legitimate tools, however, can sometimes be exploited by real threat actors and used as genuine actor vectors.

What is Sliver C2?

Sliver C2 is a legitimate open-source command-and-control (C2) framework that was released in 2020 by the security organization Bishop Fox. Silver C2 was originally intended for security teams and penetration testers to perform security tests on their digital environments [1] [2] [5]. In recent years, however, the Sliver C2 framework has become a popular alternative to Cobalt Strike and Metasploit for many attackers and Advanced Persistence Threat (APT) groups who adopt this C2 framework for unsolicited and ill-intentioned activities.

The use of Sliver C2 has been observed in conjunction with various strains of Rust-based malware, such as KrustyLoader, to provide backdoors enabling lines of communication between attackers and their malicious C2 severs [6]. It is unsurprising, then, that it has also been leveraged to exploit zero-day vulnerabilities, including critical vulnerabilities in the Ivanti Connect Secure and Policy Secure services.

In early 2024, Darktrace observed the malicious use of Sliver C2 during an investigation into post-exploitation activity on customer networks affected by the Ivanti vulnerabilities. Fortunately for affected customers, Darktrace DETECT™ was able to recognize the suspicious network-based connectivity that emerged alongside Sliver C2 usage and promptly brought it to the attention of customer security teams for remediation.

How does Silver C2 work?

Given its open-source nature, the Sliver C2 framework is extremely easy to access and download and is designed to support multiple operating systems (OS), including MacOS, Windows, and Linux [4].

Sliver C2 generates implants (aptly referred to as ‘slivers’) that operate on a client-server architecture [1]. An implant contains malicious code used to remotely control a targeted device [5]. Once a ‘sliver’ is deployed on a compromised device, a line of communication is established between the target device and the central C2 server. These connections can then be managed over Mutual TLS (mTLS), WireGuard, HTTP(S), or DNS [1] [4]. Sliver C2 has a wide-range of features, which include dynamic code generation, compile-time obfuscation, multiplayer-mode, staged and stageless payloads, procedurally generated C2 over HTTP(S) and DNS canary blue team detection [4].

Why Do Attackers Use Sliver C2?

Amidst the multitude of reasons why malicious actors opt for Sliver C2 over its counterparts, one stands out: its relative obscurity. This lack of widespread recognition means that security teams may overlook the threat, failing to actively search for it within their networks [3] [5].

Although the presence of Sliver C2 activity could be representative of authorized and expected penetration testing behavior, it could also be indicative of a threat actor attempting to communicate with its malicious infrastructure, so it is crucial for organizations and their security teams to identify such activity at the earliest possible stage.

Darktrace’s Coverage of Sliver C2 Activity

Darktrace’s anomaly-based approach to threat detection means that it does not explicitly attempt to attribute or distinguish between specific C2 infrastructures. Despite this, Darktrace was able to connect Sliver C2 usage to phases of an ongoing attack chain related to the exploitation of zero-day vulnerabilities in Ivanti Connect Secure VPN appliances in January 2024.

Around the time that the zero-day Ivanti vulnerabilities were disclosed, Darktrace detected an internal server on one customer network deviating from its expected pattern of activity. The device was observed making regular connections to endpoints associated with Pulse Secure Cloud Licensing, indicating it was an Ivanti server. It was observed connecting to a string of anomalous hostnames, including ‘cmjk3d071amc01fu9e10ae5rt9jaatj6b.oast[.]live’ and ‘cmjft14b13vpn5vf9i90xdu6akt5k3pnx.oast[.]pro’, via HTTP using the user agent ‘curl/7.19.7 (i686-redhat-linux-gnu) libcurl/7.63.0 OpenSSL/1.0.2n zlib/1.2.7’.

Darktrace further identified that the URI requested during these connections was ‘/’ and the top-level domains (TLDs) of the endpoints in question were known Out-of-band Application Security Testing (OAST) server provider domains, namely ‘oast[.]live’ and ‘oast[.]pro’. OAST is a testing method that is used to verify the security posture of an application by testing it for vulnerabilities from outside of the network [7]. This activity triggered the DETECT model ‘Compromise / Possible Tunnelling to Bin Services’, which breaches when a device is observed sending DNS requests for, or connecting to, ‘request bin’ services. Malicious actors often abuse such services to tunnel data via DNS or HTTP requests. In this specific incident, only two connections were observed, and the total volume of data transferred was relatively low (2,302 bytes transferred externally). It is likely that the connections to OAST servers represented malicious actors testing whether target devices were vulnerable to the Ivanti exploits.

The device proceeded to make several SSL connections to the IP address 103.13.28[.]40, using the destination port 53, which is typically reserved for DNS requests. Darktrace recognized that this activity was unusual as the offending device had never previously been observed using port 53 for SSL connections.

Model Breach Event Log displaying the ‘Application Protocol on Uncommon Port’ DETECT model breaching in response to the unusual use of port 53.
Figure 1: Model Breach Event Log displaying the ‘Application Protocol on Uncommon Port’ DETECT model breaching in response to the unusual use of port 53.

Figure 2: Model Breach Event Log displaying details pertaining to the ‘Application Protocol on Uncommon Port’ DETECT model breach, including the 100% rarity of the port usage.
Figure 2: Model Breach Event Log displaying details pertaining to the ‘Application Protocol on Uncommon Port’ DETECT model breach, including the 100% rarity of the port usage.

Further investigation into the suspicious IP address revealed that it had been flagged as malicious by multiple open-source intelligence (OSINT) vendors [8]. In addition, OSINT sources also identified that the JARM fingerprint of the service running on this IP and port (00000000000000000043d43d00043de2a97eabb398317329f027c66e4c1b01) was linked to the Sliver C2 framework and the mTLS protocol it is known to use [4] [5].

An Additional Example of Darktrace’s Detection of Sliver C2

However, it was not just during the January 2024 exploitation of Ivanti services that Darktrace observed cases of Sliver C2 usages across its customer base.  In March 2023, for example, Darktrace detected devices on multiple customer accounts making beaconing connections to malicious endpoints linked to Sliver C2 infrastructure, including 18.234.7[.]23 [10] [11] [12] [13].

Darktrace identified that the observed connections to this endpoint contained the unusual URI ‘/NIS-[REDACTED]’ which contained 125 characters, including numbers, lower and upper case letters, and special characters like “_”, “/”, and “-“, as well as various other URIs which suggested attempted data exfiltration:

‘/upload/api.html?c=[REDACTED] &fp=[REDACTED]’

  • ‘/samples.html?mx=[REDACTED] &s=[REDACTED]’
  • ‘/actions/samples.html?l=[REDACTED] &tc=[REDACTED]’
  • ‘/api.html?gf=[REDACTED] &x=[REDACTED]’
  • ‘/samples.html?c=[REDACTED] &zo=[REDACTED]’

This anomalous external connectivity was carried out through multiple destination ports, including the key ports 443 and 8888.

Darktrace additionally observed devices on affected customer networks performing TLS beaconing to the IP address 44.202.135[.]229 with the JA3 hash 19e29534fd49dd27d09234e639c4057e. According to OSINT sources, this JA3 hash is associated with the Golang TLS cipher suites in which the Sliver framework is developed [14].

結論

Despite its relative novelty in the threat landscape and its lesser-known status compared to other C2 frameworks, Darktrace has demonstrated its ability effectively detect malicious use of Sliver C2 across numerous customer environments. This included instances where attackers exploited vulnerabilities in the Ivanti Connect Secure and Policy Secure services.

While human security teams may lack awareness of this framework, and traditional rules and signatured-based security tools might not be fully equipped and updated to detect Sliver C2 activity, Darktrace’s Self Learning AI understands its customer networks, users, and devices. As such, Darktrace is adept at identifying subtle deviations in device behavior that could indicate network compromise, including connections to new or unusual external locations, regardless of whether attackers use established or novel C2 frameworks, providing organizations with a sliver of hope in an ever-evolving threat landscape.

Credit to Natalia Sánchez Rocafort, Cyber Security Analyst, Paul Jennings, Principal Analyst Consultant

付録

DETECT Model Coverage

  • Compromise / Repeating Connections Over 4 Days
  • Anomalous Connection / Application Protocol on Uncommon Port
  • Anomalous Server Activity / Server Activity on New Non-Standard Port
  • Compromise / Sustained TCP Beaconing Activity To Rare Endpoint
  • Compromise / Quick and Regular Windows HTTP Beaconing
  • Compromise / High Volume of Connections with Beacon Score
  • Anomalous Connection / Multiple Failed Connections to Rare Endpoint
  • Compromise / Slow Beaconing Activity To External Rare
  • Compromise / HTTP Beaconing to Rare Destination
  • Compromise / Sustained SSL or HTTP Increase
  • Compromise / Large Number of Suspicious Failed Connections
  • Compromise / SSL or HTTP Beacon
  • Compromise / Possible Malware HTTP Comms
  • Compromise / Possible Tunnelling to Bin Services
  • Anomalous Connection / Low and Slow Exfiltration to IP
  • Device / New User Agent
  • Anomalous Connection / New User Agent to IP Without Hostname
  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Numeric File Download
  • Anomalous Connection / Powershell to Rare External
  • Anomalous Server Activity / New Internet Facing System

侵害指標(IoC)一覧

18.234.7[.]23 - Destination IP - Likely C2 Server

103.13.28[.]40 - Destination IP - Likely C2 Server

44.202.135[.]229 - Destination IP - Likely C2 Server

参考文献

[1] https://bishopfox.com/tools/sliver

[2] https://vk9-sec.com/how-to-set-up-use-c2-sliver/

[3] https://www.scmagazine.com/brief/sliver-c2-framework-gaining-traction-among-threat-actors

[4] https://github[.]com/BishopFox/sliver

[5] https://www.cybereason.com/blog/sliver-c2-leveraged-by-many-threat-actors

[6] https://securityaffairs.com/158393/malware/ivanti-connect-secure-vpn-deliver-krustyloader.html

[7] https://www.xenonstack.com/insights/out-of-band-application-security-testing

[8] https://www.virustotal.com/gui/ip-address/103.13.28.40/detection

[9] https://threatfox.abuse.ch/browse.php?search=ioc%3A107.174.78.227

[10] https://threatfox.abuse.ch/ioc/1074576/

[11] https://threatfox.abuse.ch/ioc/1093887/

[12] https://threatfox.abuse.ch/ioc/846889/

[13] https://threatfox.abuse.ch/ioc/1093889/

[14] https://github.com/projectdiscovery/nuclei/issues/3330

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著者について
Natalia Sánchez Rocafort
Cyber Security Analyst

Blog

Eメール

Looking Beyond Secure Email Gateways with the Latest Innovations to Darktrace/Email

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09
Apr 2024

Organizations Should Demand More from their Email Security

In response to a more intricate threat landscape, organizations should view email security as a critical component of their defense-in-depth strategy, rather than defending the inbox alone with a traditional Secure Email Gateway (SEG). Organizations need more than a traditional gateway – that doubles, instead of replaces, the capabilities provided by native security vendor – and require an equally granular degree of analysis across all messaging, including inbound, outbound, and lateral mail, plus Teams messages.  

Darktrace/Email is the industry’s most advanced cloud email security, powered by Self-Learning AI. It combines AI techniques to exceed the accuracy and efficiency of leading security solutions, and is the only security built to elevate, not duplicate, native email security.  

With its largest update ever, Darktrace/Email introduces the following innovations, finally allowing security teams to look beyond secure email gateways with autonomous AI:

  • AI-augmented data loss prevention to stop the entire spectrum of outbound mail threats
  • an easy way to deploy DMARC quickly with AI
  • major enhancements to streamline SOC workflows and increase the detection of sophisticated phishing links
  • expansion of Darktrace’s leading AI prevention to lateral mail, account compromise and Microsoft Teams

What’s New with Darktrace/Email  

Data Loss Prevention  

Block the entire spectrum of outbound mail threats with advanced data loss prevention that builds on tags in native email to stop unknown, accidental, and malicious data loss

Darktrace understands normal at individual user, group and organization level with a proven AI that detects abnormal user behavior and dynamic content changes. Using this understanding, Darktrace/Email actions outbound emails to stop unknown, accidental and malicious data loss.  

Traditional DLP solutions only take into account classified data, which relies on the manual input of labelling each data piece, or creating rules to catch pattern matches that try to stop data of certain types leaving the organization. But in today’s world of constantly changing data, regular expression and fingerprinting detection are no longer enough.

  • Human error – Because it understands normal for every user, Darktrace/Email can recognize cases of misdirected emails. Even if the data is correctly labelled or insensitive, Darktrace recognizes when the context in which it is being sent could be a case of data loss and warns the user.  
  • Unclassified data – Whereas traditional DLP solutions can only take action on classified data, Darktrace analyzes the range of data that is either pending labels or can’t be labeled with typical capabilities due to its understanding of the content and context of every email.  
  • Insider threat – If a malicious actor has compromised an account, data exfiltration may still be attempted on encrypted, intellectual property, or other forms of unlabelled data to avoid detection. Darktrace analyses user behaviour to catch cases of unusual data exfiltration from individual accounts.

And classification efforts already in place aren’t wasted – Darktrace/Email extends Microsoft Purview policies and sensitivity labels to avoid duplicate workflows for the security team, combining the best of both approaches to ensure organizations maintain control and visibility over their data.

End User and Security Workflows

Achieve more than 60% improvement in the quality of end-user phishing reports and detection of sophisticated malicious weblinks1

Darktrace/Email improves end-user reporting from the ground up to save security team resource. Employees will always be on the front line of email security – while other solutions assume that end-user reporting is automatically of poor quality, Darktrace prioritizes improving users’ security awareness to increase the quality of end-user reporting from day one.  

Users are empowered to assess and report suspicious activity with contextual banners and Cyber AI Analyst generated narratives for potentially suspicious emails, resulting in 60% fewer benign emails reported.  

Out of the higher-quality emails that end up being reported, the next step is to reduce the amount of emails that reach the SOC. Darktrace/Email’s Mailbox Security Assistant automates their triage with secondary analysis combining additional behavioral signals – using x20 more metrics than previously – with advanced link analysis to detect 70% more sophisticated malicious phishing links.2 This directly alleviates the burden of manual triage for security analysts.

For the emails that are received by the SOC, Darktrace/Email uses automation to reduce time spent investigating per incident. With live inbox view, security teams gain access to a centralized platform that combines intuitive search capabilities, Cyber AI Analyst reports, and mobile application access. Analysts can take remediation actions from within Darktrace/Email, eliminating console hopping and accelerating incident response.

Darktrace takes a user-focused and business-centric approach to email security, in contrast to the attack-centric rules and signatures approach of secure email gateways

Microsoft Teams

Detect threats within your Teams environment such as account compromise, phishing, malware and data loss

Around 83% of Fortune 500 companies rely on Microsoft Office products and services, particularly Teams and SharePoint.3

Darktrace now leverages the same behavioral AI techniques for Microsoft customers across 365 and Teams, allowing organizations to detect threats and signals of account compromise within their Teams environment including social engineering, malware and data loss.  

The primary use case for Microsoft Teams protection is as a potential entry vector. While messaging has traditionally been internal only, as organizations open up it is becoming an entry vector which needs to be treated with the same level of caution as email. That’s why we’re bringing our proven AI approach to Microsoft Teams, that understands the user behind the message.  

Anomalous messaging behavior is also a highly relevant indicator of whether a user has been compromised. Unlike other solutions that analyze Microsoft Teams content which focus on payloads, Darktrace goes beyond basic link and sandbox analysis and looks at actual user behavior from both a content and context perspective. This linguistic understanding isn’t bound by the requirement to match a signature to a malicious payload, rather it looks at the context in which the message has been delivered. From this analysis, Darktrace can spot the early symptoms of account compromise such as early-stage social engineering before a payload is delivered.

Lateral Mail Analysis

Detect and respond to internal mailflow with multi-layered AI to prevent account takeover, lateral phishing and data leaks

The industry’s most robust account takeover protection now prevents lateral mail account compromise. Darktrace has always looked at internal mail to inform inbound and outbound decisions, but will now elevate suspicious lateral mail behaviour using the same AI techniques for inbound, outbound and Teams analysis.

Darktrace integrates signals from across the entire mailflow and communication patterns to determine symptoms of account compromise, now including lateral mailflow

Unlike other solutions which only analyze payloads, Darktrace analyzes a whole range of signals to catch lateral movement before a payload is delivered. Contributing yet another layer to the AI behavioral profile for each user, security teams can now use signals from lateral mail to spot the early symptoms of account takeover and take autonomous actions to prevent further compromise.

DMARC

Gain in-depth visibility and control of 3rd parties using your domain with an industry-first AI-assisted DMARC

Darktrace has created the easiest path to brand protection and compliance with the new Darktrace/DMARC. This new capability continuously stops spoofing and phishing from the enterprise domain, while automatically enhancing email security and reducing the attack surface.

Darktrace/DMARC helps to upskill businesses by providing step by step guidance and automated record suggestions provide a clear, efficient road to enforcement. It allows organizations to quickly achieve compliance with requirements from Google, Yahoo, and others, to ensure that their emails are reaching mailboxes.  

Meanwhile, Darktrace/DMARC helps to reduce the overall attack surface by providing visibility over shadow-IT and third-party vendors sending on behalf of an organization’s brand, while informing recipients when emails from their domains are sent from un-authenticated DMARC source.

Darktrace/DMARC integrates with the wider Darktrace product platform, sharing insights to help further secure your business across Email Attack Path and Attack Surface management.

結論

To learn more about the new innovations to Darktrace/Email download the solution brief here.

All of the new updates to Darktrace/Email sit within the new Darktrace ActiveAI Security Platform, creating a feedback loop between email security and the rest of the digital estate for better protection. Click to read more about the Darktrace ActiveAI Security Platform or to hear about the latest innovations to Darktrace/OT, the most comprehensive prevention, detection, and response solution purpose built for critical infrastructures.  

Learn about the intersection of cyber and AI by downloading the State of AI Cyber Security 2024 report to discover global findings that may surprise you, insights from security leaders, and recommendations for addressing today’s top challenges that you may face, too.

参考文献

[1] Internal Darktrace Research

[2] Internal Darktrace Research

[3] Essential Microsoft Office Statistics in 2024

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著者について
Carlos Gray
Product Manager
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