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Minimierung der Auswirkungen von REvil über die Kaseya Server

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08
Juli 2021
08
Juli 2021
REvil hat den IT-Management-Softwareanbieter Kaseya in einem der weitreichendsten Ransomware-Angriffe des Jahres ausgenutzt. In diesem Blog wird ein reales Eindringen von REvil-Ransomware beschrieben und gezeigt, wie Autonomous Response Kundendaten vor der Verschlüsselung geschützt hat.

Während sich die USA auf das Feiertagswochenende um den vierten Juli vorbereiteten, nutzte die Ransomware-Gruppe REvil eine Schwachstelle in der Kaseya Software, um Managed Service Provider (MSPs) und deren Kunden anzugreifen. Mindestens 1.500 Unternehmen scheinen betroffen zu sein, auch solche, die keine direkte Beziehung zu Kaseya haben.

Zum Zeitpunkt der Erstellung dieses Artikels scheint es, dass eine Zero-Day-Schwachstelle genutzt wurde, um Zugang zu den Kaseya VSA-Servern zu erhalten, bevor Ransomware auf den von diesen VSA-Servern verwalteten Endpunkten installiert wurde. Dieser Modus Operandi unterscheidet sich deutlich von früheren Ransomware-Kampagnen, bei denen es sich in der Regel um von Menschen durchgeführte, direkte Kompromittierungen handelte.

Die nachstehende Analyse bietet Darktrace Einblicke in die Kampagne anhand eines Beispiels aus der Praxis. Sie zeigt, wie die selbstlernende KI den Ransomware-Angriff erkannte und wie Antigena die Kundendaten im Netzwerk vor der Verschlüsselung schützte.

Analyse der REvil-Ransomware aus der Netzwerkperspektive

Antigena erkannte die ersten Anzeichen von Ransomware im Netzwerk, sobald die Verschlüsselung begonnen hatte. Die folgende Grafik zeigt den Beginn der Ransomware-Verschlüsselung über SMB-Freigaben. Als die Grafik aufgenommen wurde, fand der Angriff live statt und war noch nie zuvor gesehen worden. Da es sich um eine neuartige Bedrohung handelte, stoppte Darktrace die Netzwerkverschlüsselung ohne statische Signaturen oder Regeln.

Abbildung 1: Darktrace erkennt die Verschlüsselung des infizierten Geräts

Die Ransomware begann um 11:08:32 Uhr zu agieren, was durch die Meldung "SMB Delete Success" (SMB-Löschung erfolgreich) vom infizierten Laptop an einen SMB-Server angezeigt wurde. Während der Laptop manchmal Dateien auf diesem SMB-Server liest, löscht er nie diese Art von Dateien auf dieser speziellen Dateifreigabe, so dass Darktrace diese Aktivität als neu und ungewöhnlich erkannte.

Gleichzeitig erstellte der infizierte Laptop den Erpresserbrief "943860t-readme.txt". Auch hier handelte es sich bei dem "SMB Write Success" auf dem SMB-Server um eine neue Aktivität - und Darktrace suchte nicht nach einer statischen Zeichenfolge oder einem bekannten Erpresserbrief. Stattdessen erkannte es - durch vorheriges Lernen des "normalen" Verhaltens jeder Einheit, Peer Group und des gesamten Unternehmens - dass die Aktivität ungewöhnlich und neu für diese Organisation und dieses Gerät war.

Durch die Erkennung und Korrelation dieser subtilen Anomalien identifizierte Darktrace die frühesten Stadien der Ransomware-Verschlüsselung im Netzwerk und Antigena ergriff sofortige Maßnahmen.

Abbildung 2: Screenshot der Aktionen der Antigena

Antigena machte zwei präzise Schritte:

  1. Erzwingen der gelernten "pattern of life" (Verhaltensmuster) für fünf Minuten: Dadurch wurde verhindert, dass der infizierte Laptop neue oder ungewöhnliche Verbindungen herstellt. In diesem Fall wurde jede weitere neue SMB-Verschlüsselungsaktivität verhindert.
  2. Gerät für 24 Stunden unter Quarantäne stellen: Normalerweise würde Antigena nicht so drastische Maßnahmen ergreifen, aber es war klar, dass diese Aktivität dem Verhalten von Ransomware sehr ähnlich war. Daher beschloss Antigena, das Gerät im Netzwerk vollständig unter Quarantäne zu stellen, um zu verhindern, dass es weiteren Schaden anrichtet.

Mehrere Minuten lang versuchte der infizierte Laptop immer wieder, sich über SMB mit anderen internen Geräten zu verbinden, um die Verschlüsselung fortzusetzen. Dieser Versuch wurde von Antigena in jeder Phase blockiert, wodurch die Ausbreitung des Angriffs begrenzt und der durch die Netzwerkverschlüsselung verursachte Schaden gemindert werden konnte.

Abbildung 3: Ende des Angriffs

Auf technischer Ebene lieferte Antigena die Blockierungsmechanismen über die Integration mit nativen Sicherheitskontrollen, wie z. B. bestehenden Firewalls, oder indem es selbst aktiv wurde, um die Verbindungen zu unterbrechen.

Die folgende Grafik zeigt das "Lebensmuster" für alle Netzwerkverbindungen des infizierten Laptops. Die drei roten Punkte stehen für die Erkennungen von Darktraceund zeigen den genauen Zeitpunkt an, zu dem die Ransomware REvil auf dem Laptop installiert wurde. Die Grafik zeigt auch einen abrupten Stopp der gesamten Netzwerkkommunikation, als Antigena das Gerät unter Quarantäne stellte.

Abbildung 4: Netzwerkverbindungen von dem kompromittierten Laptop

Angriffe werden immer vorkommen

Während des Vorfalls fand ein Teil der Verschlüsselung lokal auf dem Endgerät statt, auf das Darktrace keinen Zugriff hatte. Außerdem war der Kaseya VSA-Server, der ursprünglich kompromittiert wurde, via Internet in diesem Fall für Darktrace nicht sichtbar.

Dennoch erkannte die selbstlernende KI die Infektion, sobald sie das Netzwerk erreichte. Dies zeigt, wie wichtig es ist, sich gegen aktive Ransomware im Unternehmen zu schützen. Unternehmen können sich nicht nur auf eine einzige Verteidigungsschicht verlassen, um Bedrohungen abzuwehren. Ein Angreifer wird immer - irgendwann - in Ihre Umgebung eindringen. Die Verteidigung muss daher ihren Ansatz zur Erkennung und Schadensbegrenzung ändern, sobald ein Angreifer in das Netzwerk eingedrungen ist.

Vielen Cyberangriffen gelingt es, die Endpunktkontrollen zu umgehen und sich aggressiv in Unternehmensumgebungen zu verbreiten. Autonomous Response kann in solchen Fällen selbst bei neuartigen Kampagnen und neuen Malware-Stämmen für Ausfallsicherheit sorgen.

Dank der selbstlernenden KI konnte die Ransomware des REvil-Angriffs keine Verschlüsselung über das Netzwerk durchführen, und die im Netzwerk verfügbaren Dateien wurden gesichert. Dazu gehörten auch die kritischen Dateiserver des Unternehmens, auf denen Kaseya nicht installiert war und die daher die ursprüngliche Nutzlast nicht direkt über das bösartige Update erhielten. Durch die Unterbrechung des Angriffs in dem Moment, in dem er stattfand, verhinderte Antigena, dass Tausende von Dateien auf Netzwerkfreigaben verschlüsselt wurden.

Weitere Beobachtungen

Exfiltration von Daten

Im Gegensatz zu anderen REvil-Angriffen, die Darktrace in der Vergangenheit aufgedeckt hat, wurde keine Datenexfiltration beobachtet. Dies ist interessant, da es sich von dem allgemeinen Trend des letzten Jahres unterscheidet, bei dem sich cyberkriminelle Gruppen im Allgemeinen mehr auf die Exfiltration von Daten konzentrieren, um ihre Opfer zu erpressen, da diese immer bessere Back-up Strukturen aufbauen.

Bitcoin

REvil hat eine Gesamtzahlung von 70 Millionen Dollar in Bitcoin gefordert. Für eine Gruppe, die versucht, ihre Gewinne zu maximieren, erscheint dies aus zwei Gründen seltsam:

  1. Wie soll ein einzelnes Unternehmen 70 Millionen Dollar von potenziell Tausenden von betroffenen Organisationen eintreiben? Sie müssen sich der enormen logistischen Herausforderungen bewusst sein, die damit verbunden sind, auch wenn sie von Kaseya erwarten, dass es als zentrale Anlaufstelle für das Einsammeln des Geldes fungiert.
  2. Seit DarkSide den Zugang zu den meisten Colonial Pipeline Lösegeldern verloren hat, sind Ransomware-Gruppen dazu übergegangen, Zahlungen in Monero statt in Bitcoin zu verlangen. Monero scheint für die Strafverfolgungsbehörden schwieriger zu verfolgen zu sein. Die Tatsache, dass REvil Bitcoin, eine besser verfolgbare Kryptowährung, verwendet, scheint kontraproduktiv für ihr übliches Ziel der Gewinnmaximierung zu sein.

Ransomware-as-a-Service (RaaS)

Darktrace bemerkte auch, dass andere, traditionellere "Großwildjagd"-Ransomware-Operationen von REvil am selben Wochenende stattfanden. Dies ist nicht überraschend, da REvil ein RaaS-Modell betreibt. Daher ist es wahrscheinlich, dass einige Partnergruppen ihre regulären Angriffe fortsetzten, während der Angriff auf die Kaseya-Lieferkette im Gange war.

Unberechenbar ist nicht Unverteidigbar

Am Wochenende des vierten Juli gab es große Angriffe auf die Lieferkette von Kaseya und separat auf den kalifornischen Distributor Synnex. Die Bedrohungen kommen aus allen Richtungen und nutzen Zero-Days, Social-Engineering-Taktiken und andere fortschrittliche Tools.

Die obige Fallstudie zeigt, wie selbstlernende Technologie solche Angriffe erkennt und den Schaden minimiert. Sie fungiert als wichtiger Teil der Tiefenverteidigung, wenn andere Schichten - wie Endpunktschutz, Bedrohungsdaten oder bekannte Signaturen und Regeln - unbekannte Bedrohungen nicht erkennen können.

Der Angriff erfolgte in Millisekunden, schneller als jedes menschliche Sicherheitsteam reagieren konnte. Autonomous Response hat sich als unschätzbar wertvoll erwiesen, wenn es darum geht, diese neue Generation von Bedrohungen in Maschinengeschwindigkeit abzuwehren. Es schützt Tausende von Unternehmen auf der ganzen Welt 24/7 und stoppt jede Sekunde einen Angriff.

Abweichungen von Darktrace Modellen

  • 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
EINBLICKE IN DAS SOC-Team
Darktrace Cyber-Analysten sind erstklassige Experten für Threat Intelligence, Threat Hunting und Incident Response. Sie bieten Tausenden von Darktrace Kunden auf der ganzen Welt rund um die Uhr SOC-Support. Einblicke in das SOC-Team wird ausschließlich von diesen Experten verfasst und bietet Analysen von Cyber-Vorfällen und Bedrohungstrends, die auf praktischen Erfahrungen in diesem Bereich basieren.
AUTOR
ÜBER DEN AUTOR
Max Heinemeyer
Leiter der Produktabteilung

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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Einblicke in das SOC-Team

Detecting Attacks Across Email, SaaS, and Network Environments with Darktrace’s AI Platform Approach

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30
Apr 2024

The State of AI in Cybersecurity

In a recent survey outlined in Darktrace’s State of AI Cyber Security whitepaper, 95% of cyber security professionals agree that AI-powered security solutions will improve their organization’s detection of cyber-threats [1]. Crucially, a combination of multiple AI methods is the most effective to improve cybersecurity; improving threat detection, accelerating threat investigation and response, and providing visibility across an organization’s digital environment.

In March 2024, Darktrace’s AI-led security platform was able to detect suspicious activity affecting a customer’s email, Software-as-a-Service (SaaS), and network environments, whilst its applied supervised learning capability, Cyber AI Analyst, autonomously correlated and connected all of these events together in one single incident, explained concisely using natural language processing.

Attack Overview

Following an initial email attack vector, an attacker logged into a compromised SaaS user account from the Netherlands, changed inbox rules, and leveraged the account to send thousands of phishing emails to internal and external users. Internal users fell victim to the emails by clicking on contained suspicious links that redirected them to newly registered suspicious domains hosted on same IP address as the hijacked SaaS account login. This activity triggered multiple alerts in Darktrace DETECT™ on both the network and SaaS side, all of which were correlated into one Cyber AI Analyst incident.

In this instance, Darktrace RESPOND™ was not active on any of the customer’s environments, meaning the compromise was able to escalate until their security team acted on the alerts raised by DETECT. Had RESPOND been enabled at the time of the attack, it would have been able to apply swift actions to contain the attack by blocking connections to suspicious endpoints on the network side and disabling users deviating from their normal behavior on the customer’s SaaS environment.

Nevertheless, thanks to DETECT and Cyber AI Analyst, Darktrace was able to provide comprehensive visibility across the customer’s three digital estate environments, decreasing both investigation and response time which enabled them to quickly enact remediation during the attack. This highlights the crucial role that Darktrace’s combined AI approach can play in anomaly detection cyber defense

Attack Details & Darktrace Coverage

Attack timeline

1. Email: the initial attack vector  

The initial attack vector was likely email, as on March 18, 2024, Darktrace observed a user device making several connections to the email provider “zixmail[.]net”, shortly before it connected to the first suspicious domain. Darktrace/Email identified multiple unusual inbound emails from an unknown sender that contained a suspicious link. Darktrace recognized these emails as potentially malicious and locked the link, ensuring that recipients could not directly click it.

Suspected initial compromise email from an unknown sender, containing a suspicious link, which was locked by Darktrace/Email.
Figure 1: Suspected initial compromise email from an unknown sender, containing a suspicious link, which was locked by Darktrace/Email.

2. Escalation to Network

Later that day, despite Darktrace/Email having locked the link in the suspicious email, the user proceeded to click on it and was directed to a suspicious external location, namely “rz8js7sjbef[.]latovafineart[.]life”, which triggered the Darktrace/Network DETECT model “Suspicious Domain”. Darktrace/Email was able to identify that this domain had only been registered 4 days before this activity and was hosted on an IP address based in the Netherlands, 193.222.96[.]9.

3. SaaS Account Hijack

Just one minute later, Darktrace/Apps observed the user’s Microsoft 365 account logging into the network from the same IP address. Darktrace understood that this represented unusual SaaS activity for this user, who had only previously logged into the customer’s SaaS environment from the US, triggering the “Unusual External Source for SaaS Credential Use” model.

4. SaaS Account Updates

A day later, Darktrace identified an unusual administrative change on the user’s Microsoft 365 account. After logging into the account, the threat actor was observed setting up a new multi-factor authentication (MFA) method on Microsoft Authenticator, namely requiring a 6-digit code to authenticate. Darktrace understood that this authentication method was different to the methods previously used on this account; this, coupled with the unusual login location, triggered the “Unusual Login and Account Update” DETECT model.

5. Obfuscation Email Rule

On March 20, Darktrace detected the threat actor creating a new email rule, named “…”, on the affected account. Attackers are typically known to use ambiguous or obscure names when creating new email rules in order to evade the detection of security teams and endpoints users.

The parameters for the email rule were:

“AlwaysDeleteOutlookRulesBlob: False, Force: False, MoveToFolder: RSS Feeds, Name: ..., MarkAsRead: True, StopProcessingRules: True.”

This rule was seemingly created with the intention of obfuscating the sending of malicious emails, as the rule would move sent emails to the "RSS Feeds” folder, a commonly used tactic by attackers as the folder is often left unchecked by endpoint users. Interestingly, Darktrace identified that, despite the initial unusual login coming from the Netherlands, the email rule was created from a different destination IP, indicating that the attacker was using a Virtual Private Network (VPN) after gaining a foothold in the network.

Hijacked SaaS account making an anomalous login from the unusual Netherlands-based IP, before creating a new email rule.
Figure 2: Hijacked SaaS account making an anomalous login from the unusual Netherlands-based IP, before creating a new email rule.

6. Outbound Phishing Emails Sent

Later that day, the attacker was observed using the compromised customer account to send out numerous phishing emails to both internal and external recipients. Darktrace/Email detected a significant spike in inbound emails on the compromised account, with the account receiving bounce back emails or replies in response to the phishing emails. Darktrace further identified that the phishing emails contained a malicious DocSend link hidden behind the text “Click Here”, falsely claiming to be a link to the presentation platform Prezi.

Figure 3: Darktrace/Email detected that the DocSend link displayed via text “Click Here”, was embedded in a Prezi link.
Figure 3: Darktrace/Email detected that the DocSend link displayed via text “Click Here”, was embedded in a Prezi link.

7. Suspicious Domains and Redirects

After the phishing emails were sent, multiple other internal users accessed the DocSend link, which directed them to another suspicious domain, “thecalebgroup[.]top”, which had been registered on the same day and was hosted on the aforementioned Netherlands-based IP, 193.222.96[.]91. At the time of the attack, this domain had not been reported by any open-source intelligence (OSINT), but it has since been flagged as malicious by multiple vendors [2].

External Sites Summary showing the suspicious domain that had never previously been seen on the network. A total of 11 “Suspicious Domain” models were triggered in response to this activity.
Figure 4: External Sites Summary showing the suspicious domain that had never previously been seen on the network. A total of 11 “Suspicious Domain” models were triggered in response to this activity.  

8. Cyber AI Analyst’s Investigation

As this attack was unfolding, Darktrace’s Cyber AI Analyst was able to autonomously investigate the events, correlating them into one wider incident and continually adding a total of 14 new events to the incident as more users fell victim to the phishing links.

Cyber AI Analyst successfully weaved together the initial suspicious domain accessed in the initial email attack vector (Figure 5), the hijack of the SaaS account from the Netherlands IP (Figure 6), and the connection to the suspicious redirect link (Figure 7). Cyber AI Analyst was also able to uncover other related activity that took place at the time, including a potential attempt to exfiltrate data out of the customer’s network.

By autonomously analyzing the thousands of connections taking place on a network at any given time, Darktrace’s Cyber AI Analyst is able to detect seemingly separate anomalous events and link them together in one incident. This not only provides organizations with full visibility over potential compromises on their networks, but also saves their security teams precious time ensuring they can quickly scope out the ongoing incident and begin remediation.

Figure 5: Cyber AI Analyst correlated the attack’s sequence, starting with the initial suspicious domain accessed in the initial email attack vector.
Figure 5: Cyber AI Analyst correlated the attack’s sequence, starting with the initial suspicious domain accessed in the initial email attack vector.
Figure 6: As the attack progressed, Cyber AI Analyst correlated and appended additional events to the same incident, including the SaaS account hijack from the Netherlands-based IP.
Figure 6: As the attack progressed, Cyber AI Analyst correlated and appended additional events to the same incident, including the SaaS account hijack from the Netherlands-based IP.
Cyber AI Analyst correlated and appended additional events to the same incident, including additional users connecting to the suspicious redirect link following the outbound phishing emails being sent.
Figure 7: Cyber AI Analyst correlated and appended additional events to the same incident, including additional users connecting to the suspicious redirect link following the outbound phishing emails being sent.

Schlussfolgerung

In this scenario, Darktrace demonstrated its ability to detect and correlate suspicious activities across three critical areas of a customer’s digital environment: email, SaaS, and network.

It is essential that cyber defenders not only adopt AI but use a combination of AI technology capable of learning and understanding the context of an organization’s entire digital infrastructure. Darktrace’s anomaly-based approach to threat detection allows it to identify subtle deviations from the expected behavior in network devices and SaaS users, indicating potential compromise. Meanwhile, Cyber AI Analyst dynamically correlates related events during an ongoing attack, providing organizations and their security teams with the information needed to respond and remediate effectively.

Credit to Zoe Tilsiter, Analyst Consulting Lead (EMEA), Brianna Leddy, Director of Analysis

Appendices

References

[1] https://darktrace.com/state-of-ai-cyber-security

[2] https://www.virustotal.com/gui/domain/thecalebgroup.top

Darktrace DETECT Model Coverage

SaaS Models

- SaaS / Access / Unusual External Source for SaaS Credential Use

- SaaS / Compromise / Unusual Login and Account Update

- SaaS / Compliance / Anomalous New Email Rule

- SaaS / Compromise / Unusual Login and New Email Rule

Network Models

- Device / Suspicious Domain

- Multiple Device Correlations / Multiple Devices Breaching Same Model

Cyber AI Analyst Incidents

- Possible Hijack of Office365 Account

- Possible SSL Command and Control

Indicators of Compromise (IoCs)

IoC – Type – Description

193.222.96[.]91 – IP – Unusual Login Source

thecalebgroup[.]top – Domain – Possible C2 Endpoint

rz8js7sjbef[.]latovafineart[.]life – Domain – Possible C2 Endpoint

https://docsend[.]com/view/vcdmsmjcskw69jh9 - Domain - Phishing Link

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Zoe Tilsiter
Cyber Analyst

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Attack trends: Cloud-Based Cyber-Attacks and the Rise of Alternative Initial Access Methods

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29
Apr 2024

What is the primary entry point for malware attacks?

Phishing attacks targeting employee inboxes are the most common initial access method used by malicious threat actors to deliver malware.

Because email remains the lifeblood of how organizations operate attackers continue to develop new techniques for creating more convincing and sophisticated phishing messages at scale.

What are new entry points cyber attackers are using?

While traditional phishing attacks are very common for attackers, they are not the only method threat actors are using to initiate malware delivery and other malicious campaigns of cyber disruption.

For its End of Year Threat Report, Darktrace analyzed attacks targeting customer environments. While email remains the most common means of attempted initial compromise, the second half of 2023 saw a significant rise in alternative initial access methods.

Much of this is taking advantage of cloud-base applications and collaboration tools including Dropbox, Microsoft Teams, and SharePoint which have become fundamental to how organizations operate in the era of hybrid work.

DarkGate exploits Microsoft Teams

Darktrace analysts have seen threat actors attempting to infect target networks with malware by leveraging Microsoft Teams and SharePoint.  

In one example, Darktrace detected an attacker delivering DarkGate a trojan used to download other malware, by sending messages and attachments in Microsoft Teams and SharePoint.

The External Access functionality in Microsoft Teams allows users to contact people who aren’t in their organization. It’s designed as a tool to aid collaboration, but threat actors have realized they can abuse it for their own gain.  

Users are told to lookout for suspicious email phishing messages, but often this thinking isn’t applied to Microsoft Teams and other collaboration platforms.  

Messages from outside the organization are marked with a note that they are coming from an external source, but a well-designed phishing message with an urgent call to action can persuade the target to ignore this, driving them towards an external SharePoint URL, which tricks the user into downloading and installing malware.

Because this happens outside of the inbox, the activity can be missed by traditional email security solutions. Fortunately, in this case, it was detected by Darktrace DETECT and the activity was contained by Darktrace RESPOND before it could drop any additional malware.  

Dropbox has established itself as a leading cloud storage service by allowing users to share and access files, no matter where they are in the world or what device they’re using. But while this is legitimate and useful for organizations, it has also opened a new avenue for threat actors to exploit.

Dropbox as an attack vector

Darktrace recently detected attackers attempting to leverage Dropbox as an initial access method. Emails from ‘no-reply@dropbox[.]com’ – a legitimate email address – were sent to employees at a Darktrace customer.

The emails contained a link to push users towards to a PDF file hosted on Dropbox, which in turn contained a phishing link which if followed, took users to a convincing looking spoof of a Microsoft 365 login page designed to steal usernames and passwords.

A user fell victim to this campaign, unwittingly entering their Microsoft 365 credentials. Shortly after that, Darktrace/Apps started to see suspicious activity relating to the account, with multiple logins from unusual locations which had never been associated with the account previously.  

While many traditional security solutions successfully detect and disrupt email-based attacks, many struggle with cloud-based apps and services like Dropbox, Microsoft 365 and others.  

There are several reasons for this, including the way in which the use of multiple different cloud services fragments the attack surface, making it hard for network administrators to keep track of everything, alongside the way in which some security solutions don’t take behavior into account in a system which can be accessed from anywhere. That means even from the other side of the world, attackers who have the right cloud credentials could access the network, potentially without being disrupted.  

Why are attackers turning to alternative access methods?

Attackers are turning to alternative methods because delivering malicious links and payloads via cloud-based services potentially bypasses traditional cybersecurity protections. That, combined with how attackers can take legitimate login credentials to access system means attackers actions can’t be easily traced.  

This rise in alternative initial access methods is likely a result of the continued development and enhancement of traditional email security solutions. But in the cat and mouse game of cybersecurity, threat actors continue to evolve new techniques to get by defenses.  

Darktrace’s Self-Learning AI learns the unique digital environment and patterns of each business, meaning it can recognize subtle deviations in activity, even within cloud services, helping to mitigate and neutralize attacks and helping to keep your organization safe from cyber disruption.

Learn more about Darktrace

Join Darktrace LIVE half-day event to understand the reality versus the hype surrounding AI and how to achieve cyber resilience.

For more information on emerging threats read the Darktrace End of Year Threat Report 2023 here.

To learn more about Darktrace’s latest innovations watch the Darktrace Virtual Innovation Launch video here.  

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