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Kaseyaサーバー経由のREvilのインパクトを最小化する

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08
Jul 2021
08
Jul 2021
REvil have exploited IT management software provider Kaseya in one of the most far-reaching ransomware attacks of the year. This blog unpacks a real-world intrusion of REvil ransomware, and demonstrates how Autonomous Response protected customer data from encryption.

米国が独立記念日の週末に向けて準備をしていた頃、ランサムウェアグループであるREvilはKaseyaのソフトウェアの脆弱性を悪用してMSP(Managed Service Providers)およびそれらの顧客に対する攻撃を仕掛けました。少なくとも1,500社が影響を受け、その中にはKaseyaと直接関係のない企業も含まれていました。

本稿執筆時点では、Kaseya VSAサーバーへのアクセスが獲得するためにゼロデイ脆弱性が悪用され、その後これらのVSAサーバーが管理するエンドポイントにランサムウェアが展開されたと見られています。 この手口は、これまでの人間が操作した直接の侵入によるランサムウェア攻撃とは大きく異なっていました。

以下の分析結果は、実際の例に基づいたこの攻撃に対するDarktraceの考察です。自己学習型 AIがどのようにこのランサムウェア攻撃を検知し、RESPONDがネットワーク上の顧客データを暗号化から守ったかを解説します。

ネットワークの視点からREvilランサムウェアを解剖

RESPONDは、暗号化が始まると即座にネットワーク上のランサムウェアの初期の兆候を検知しました。以下の図はSMB共有を使ったランサムウェアによる暗号化の開始を示しています。この画面をキャプチャした時、ランサムウェアが発生中でありそれはこれまでに見たことのないものでした。新しい脅威ではありましたが、Darktraceは静的なシグネチャやルールに依存することなくネットワーク暗号化を停止させました。

図1:Darktraceが感染したデバイスからの暗号化を検知

ランサムウェアは11:08:32にアクションを開始しています。これは感染したラップトップからSMBサーバーへのSMB Delete Successによって示されました。このラップトップはそのSMBサーバー上のファイルを読み取ることはたまにありましたが、このファイル共有からこれらの種類のファイルを削除することはありませんでした。そのためDarktraceはこのアクティビティを新しく通常とは異なるものとして検知しました。

同時に、感染したラップトップは身代金要求文 ‘943860t-readme.txt’を作成しました。このSMBサーバーへのSMB Write Successは新しいアクティビティでした。そして重要な点は、Darktraceは静的な文字列や既知の身代金要求文を探したのではないということです。そうではなく、あらゆるエンティティ、ピアグループ、そしてエンタープライズ全体の「通常の」動作を学習することにより、このアクティビティが組織とデバイスにとって普通ではない新しいものだということを識別したのです。

これらのかすかな異常を検知し相関づけることにより、Darktraceはこれがネットワーク上で発生しているランサムウェア暗号化の最も初期段階であることを特定しRESPONDは即座にアクションを取りました。

図2:RESPONDのアクションを示すスナップショット

RESPONDは精密な2段階の対処を実施しました:

  1. 「生活パターン」を5分間に渡り強制する:これにより感染したラップトップが新しいあるいは通常とは異なる接続を行うのを防ぎます。このケースでは、さらなるSMB暗号化アクティビティが行われるのを防ぐことができました。
  2. デバイスを24時間隔離する:通常、RESPONDはそのような極端なアクションをとらないのですが、このアクティビティはランサムウェアの挙動を強く示していることが明確であったため、RESPONDはネットワーク上でデバイスを完全に隔離しこれ以上の被害が及ばないようにすることを決定しました。

数分間、感染したラップトップはSMBを介して他の内部デバイスに接続し暗号化アクティビティを継続しようとしていました。これはRESPONDによりあらゆる段階でブロックされ、攻撃の拡散を抑えるとともに、ネットワーク暗号化による危険が緩和しました。

図3:攻撃の終わり

技術的レベルで見ると、RESPONDはたとえば既存のファイアウォールなどのネイティブセキュリティコントロールとのインテグレーションを通じて、あるいは自らアクションを取ることにより、ブロッキングメカニズムを提供し、接続を中断しています。

以下の図は感染したラップトップのすべてのネットワーク接続の「生活パターン」を示しています。3つの赤い点がDarktraceによる検知結果を示し、REvilランサムウェアがこのラップトップにインストールされた瞬間をピンポイントで特定しています。この図はAntigenaがデバイスを隔離するとともにすべてのネットワーク接続が突然停止した様子も示しています。

図4:感染したラップトップからのネットワーク接続

攻撃はいつでも侵入する

このインシデントでは、暗号化の一部はDarktraceが可視性を持っていないエンドポイントデバイス上でローカルに発生していました。さらに、最初に侵害を受けたインターネットに接続されていたKaseya VSAサーバーも、Darktraceからは見えないところにありました。

それにも関わらず、自己学習型AIは感染がネットワークに到達すると即座に検知しました。これは、エンタープライズ内で活動中のランサムウェアに対して防御できることの重要性を示しています。1つの防御レイヤーだけに依存して脅威を締め出すことは不可能です。攻撃者は必ず、いつかは、環境に侵入するのです。したがって、防御に対するアプローチも敵が一旦内側に侵入したときの検知と被害の軽減に変更していく必要があります。

多くのサイバー攻撃がエンドポイントコントロールを回避して企業内の環境にアグレッシブに拡散することに成功しているのです。このような場合、Darktraceの自律遮断技術はそのようなケースに対しても、たとえ新手の攻撃や新種のマルウェアであってもレジリエンスを提供できます。

自己学習型AIの力により、REvilの攻撃で使われたランサムウェアはネットワークを介した暗号化を実行することはできず、ネットワーク上のファイルは守られたのです。これには、Kaseyaがインストールされていない、したがって悪意ある更新によって直接ペイロードを受信していない、この組織の重要なファイルサーバーも含まれていました。攻撃の発生に対応して即座にこれを中断させたAntigenaは、ネットワーク共有上の数千のファイルが暗号化されるのを防ぎました。

さらなる観察

データ漏えい

Darktraceが過去に検知した他のREvil の侵入とは対照的に、データ抜き出しは観測されませんでした。多くの企業がバックアップを強化したことを受け、サイバー犯罪者達が身代金要求のためにデータを抜き出すことに重点をおくようになった昨年来の全体的傾向と異なっているのが興味深い点です。

ビットコイン

REvilはビットコインでの総額7,000万ドルの支払いを要求しました。利益の最大化を狙うグループにしては、これは2つの理由で奇妙です:

  1. 影響を受けたかもしれない数千もの組織から1つの事業者が7,000万ドルもどうやって集められると思ったのでしょうか?仮にKaseyaが主体となって資金を集められると考えていたとしても、これには膨大なロジスティクス上の手間がかかることを認識していたはずです。
  2. DarkSideがColonial Pipeline社の身代金のほとんどへのアクセスを失って以来、ランサムウェアグループはビットコインよりもMoneroでの支払いを要求するようになってきました。Moneroはどうやら法執行機関が追跡することがより難しいようです。REvilはより追跡可能な暗号通貨であるビットコインを使用しており、利益の最大化といういつもの目標と相反するように見えます。

サービスとしてのランサムウェア(RaaS)

Darktraceは同じ週末に、より従来型の「大物狙い」のREvil ランサムウェア攻撃が発生していたことを検知しました。これは驚くことではありません。REvil はRaaSモデルで動いているため、Kaseyaサプライチェーン攻撃の実行中に、別の関連グループがいつもの大物狙いの攻撃を継続していたものと見られます。

予測不可能は防御不可能ではない

この独立記念日の週末には、大規模なサプライチェーン攻撃がKaseyaに対するものとは別に、カリフォルニア州にある卸売企業Synnexに対しても発生していました。攻撃は、ゼロデイ、ソーシャルエンジニアリング戦術、およびその他の高度なツールを使ってあらゆる方向から発生しています。

上記の事例は自己学習型テクノロジーがこうした攻撃の検知と被害の最小化に有効であることを示しています。他の防御レイヤー、たとえばエンドポイント保護や脅威インテリジェンスや既知のシグネチャおよびルールなどが未知の脅威を検知できないケースにおいて、自己学習型テクノロジーは多層的防御の重要な一部分を担います。

攻撃はミリ秒の速さで発生し、人間のセキュリティチームが対応できるレベルを超えていました。自律対処技術はこの新世代のマシンスピード攻撃に対抗する上で欠かせないテクノロジーであることが実証されています。世界中の数千の組織を24時間保護し、毎秒攻撃を阻止しているのです。

Darktraceによるモデル検知

  • Compromise / Ransomware / Suspicious SMB Activity
  • Compromise / Ransomware / Suspicious SMB File Extension
  • Compromise / Ransomware / Ransom or Offensive Words Written to SMB
  • Compromise / Ransomware / Ransom or Offensive Words Read from SMB
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
Max Heinemeyer
Chief Product Officer

Max is a cyber security expert with over a decade of experience in the field, specializing in a wide range of areas such as Penetration Testing, Red-Teaming, SIEM and SOC consulting and hunting Advanced Persistent Threat (APT) groups. At Darktrace, Max is closely involved with Darktrace’s strategic customers & prospects. He works with the R&D team at Darktrace, shaping research into new AI innovations and their various defensive and offensive applications. Max’s insights are regularly featured in international media outlets such as the BBC, Forbes and WIRED. Max holds an MSc from the University of Duisburg-Essen and a BSc from the Cooperative State University Stuttgart in International Business Information Systems.

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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
Our ai. Your data.

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