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January 31, 2024

How Darktrace Defeated SmokeLoader Malware

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31
Jan 2024
Read how Darktrace's AI identified and neutralized SmokeLoader malware. Gain insights into their proactive approach to cybersecurity.

What is Loader Malware?

Loader malware is a type of malicious software designed primarily to infiltrate a system and then download and execute additional malicious payloads.

In recent years, loader malware has emerged as a significant threat for organizations worldwide. This trend is expected to continue given the widespread availability of many loader strains within the Malware-as-a-Service (MaaS) marketplace. The MaaS marketplace contains a wide variety of innovative strains which are both affordable, with toolkits ranging from USD 400 to USD 1,650 [1], and continuously improving, aiming to avoid traditional detection mechanisms.

SmokeLoader is one such example of a MaaS strain that has been observed in the wild since 2011 and continues to pose a significant threat to organizations and their security teams.

How does SmokeLoader Malware work?

SmokeLoader’s ability to drop an array of different malware strains onto infected systems, from backdoors, ransomware, cryptominers, password stealers, point-of-sale malware and banking trojans, means its a highly versatile loader that has remained consistently popular among threat actors.

In addition to its versatility, it also exhibits advanced evasion strategies that make it difficult for traditional security solutions to detect and remove, and it is easily distributed via methods like spam emails or malicious file downloads.

Between July and August 2023, Darktrace observed an increasing trend in SmokeLoader compromises across its customer base. The anomaly-based threat detection capabilities of Darktrace, coupled with the autonomous response technology, identified and contained the SmokeLoader infections in their initial stages, preventing attackers from causing further disruption by deploying other malicious software or ransomware.

SmokeLoader Malware Attack Details

PROPagate Injection Technique

SmokeLoader utilizes the PROPagate code injection technique, a less common method that inserts malicious code into existing processes in order to appear legitimate and bypass traditional signature-based security measures [2] [3]. In the case of SmokeLoader, this technique exploits the Windows SetWindowsSubclass function, which is typically used to add or change the behavior of Windows Operation System. By manipulating this function, SmokeLoader can inject its code into other running processes, such as the Internet Explorer. This not only helps to disguise  the malware's activity but also allows attackers to leverage the permissions and capabilities of the infected process.

Obfuscation Methods

SmokeLoader is known to employ several obfuscation techniques to evade the detection and analysis of security teams. The techniques include scrambling portable executable files, encrypting its malicious code, obfuscating API functions and packing, and are intended to make the malware’s code appear harmless or unremarkable to antivirus software. This allows attackers to slip past defenses and execute their malicious activities while remaining undetected.

Infection Vector and Communication

SmokeLoader typically spreads via phishing emails that employ social engineering tactics to convince users to unknowingly download malicious payloads and execute the malware. Once installed on target networks, SmokeLoader acts as a backdoor, allowing attackers to control infected systems and download further malicious payloads from command-and-control (C2) servers. SmokeLoader uses fast flux, a DNS technique utilized by botets whereby IP addresses associated with C2 domains are rapidly changed, making it difficult to trace the source of the attack. This technique also boosts the resilience of attack, as taking down one or two malicious IP addresses will not significantly impact the botnet's operation.

Continuous Evolution

As with many MaaS strains, SmokeLoader is continuously evolving, with its developers regularly adding new features and techniques to increase its effectiveness and evasiveness. This includes new obfuscation methods, injection techniques, and communication protocols. This constant evolution makes SmokeLoader a significant threat and underscores the importance of advanced threat detection and response capabilities solution.

Darktrace’s Coverage of SmokeLoader Attack

Between July and August 2023, Darktrace detected one particular SmokeLoader infection at multiple stages of its kill chain on a customer network. This detection was made possible by Darktrace DETECT’s anomaly-based approach and Self-Learning AI that allows it to identify subtle deviations in device behavior.

One of the key components of this process is the classification of endpoint rarity and determining whether an endpoint is new or unusual for any given network. This classification is applied to various aspects of observed endpoints, such as domains, IP addresses, or hostnames within the network. It thereby plays a vital role in identifying SmokeLoader activity, such as the initial infection vector or C2 communication, which typically involve a device contacting a malicious endpoint associated with SmokeLoader.

The First Signs of Infection SmokeLoader Infection

Beginning in July 2023, Darktrace observed a surge in suspicious activities that were assessed with moderate to high confidence to be associated with SmokeLoader malware.

For example on July 30, a device was observed making a successful HTTPS request to humman[.]art, a domain that had never been seen on the network, and therefore classified as 100% rare by DETECT. During this connection, the device in question received a total of 6.0 KiB of data from the unusual endpoint. Open-source intelligence (OSINT) sources reported with high confidence that this domain was associated with the SmokeLoader C2 botnet.

The device was then detected making an HTTP request to another 100% rare external IP, namely 85.208.139[.]35, using a new user agent. This request contained the URI ‘/DefenUpdate.exe’, suggesting a possible download of an executable (.exe) file. This was corroborated by the total amount of data received in this connection, 4.3 MB. Both the file name and its size suggest that the offending device may have downloaded additional malicious tooling from the SmokeLoader C2 endpoint, such as a trojan or information stealer, as reported on OSINT platforms [4].

Figure 1: Device event log showing the moment when a device made its first connection to a SmokeLoader associated domain, and the use of a new user agent. A few seconds later, the DETECT model “Anomalous Connection / New User Agent to IP Without Hostname” breached.

The observed new user agent, “Mozilla/5.0 (Windows NT 10.0; Win64; x64; Trident/7.0; rv:11.0) like Gecko” was identified as suspicious by Darktrace leading to the “Anomalous Connection / New User Agent to IP Without Hostname” DETECT model breach.

As this specific user agent was associated with the Internet Explorer browser running on Windows 10, it may not have appeared suspicious to traditional security tools. However, Darktrace’s anomaly-based detection allows it to identify and mitigate emerging threats, even those that utilize sophisticated evasion techniques.

This is particularly noteworthy in this case because, as discussed earlier, SmokeLoader is known to inject its malicious code into legitimate processes, like Internet Explorer.

Figure 2: Darktrace detecting the affected device leveraging a new user agent and establishing an anomalous HTTP connection with an external IP, which was 100% rare to the network.

C2 Communication

Darktrace continued to observe the device making repeated connections to the humman[.]art endpoint. Over the next few days. On August 7, the device was observed making unusual POST requests to the endpoint using port 80, breaching the ‘Anomalous Connection / Multiple HTTP POSTs to Rare Hostname’ DETECT model. These observed POST requests were observed over a period of around 10 days and consisted of a pattern of 8 requests, each with a ten-minute interval.

Figure 3: Model Breach Event Log highlighting the Darktrace DETECT model breach ‘Anomalous Connection / Multiple HTTP POSTs to Rare Hostname’.

Upon investigating the details of this activity identified by Darktrace DETECT, a particular pattern was observed in these requests: they used the same user-agent, “Mozilla/5.0 (Windows NT 10.0; Win64; x64; Trident/7.0; rv:11.0) like Gecko”, which was previously detected in the initial breach.

Additionally, they the requests had a constantly changing  eferrer header, possibly using randomly generated domain names for each request. Further examination of the packet capture (PCAP) from these requests revealed that the payload in these POST requests contained an RC4 encrypted string, strongly indicating SmokeLoader C2 activity.

Figure4: Advanced Search results display an unusual pattern in the requests made by the device to the hostname humman[.]art. This pattern shows a constant change in the referrer header for each request, indicating anomalous behavior.
Figure 5: The PCAP shows the payload seen in these POST requests contained an RC4 encrypted string strongly indicating SmokeLoader C2 activity.  

Unfortunately in this case, Darktrace RESPOND was not active on the network meaning that the attack was able to progress through its kill chain. Despite this, the timely alerts and detailed incident insights provided by Darktrace DETECT allowed the customer’s security team to begin their remediation process, implementing blocks on their firewall, thus preventing the SmokeLoader malware from continuing its communication with C2 infrastructure.

Darktrace RESPOND Halting Potential Threats from the Initial Stages of Detection

With Darktrace RESPOND, organizations can move beyond threat detection to proactive defense against emerging threats. RESPOND is designed to halt threats as soon as they are identified by DETECT, preventing them from escalating into full-blown compromises. This is achieved through advanced machine learning and Self-Learning AI that is able to understand  the normal ‘pattern of life’ of customer networks, allowing for swift and accurate threat detection and response.

One pertinent example was seen on July 6, when Darktrace detected a separate SmokeLoader case on a customer network with RESPOND enabled in autonomous response mode. Darktrace DETECT initially identified a string of anomalous activity associated with the download of suspicious executable files, triggering the ‘Anomalous File / Multiple EXE from Rare External Locations’ model to breach.

The device was observed downloading an executable file (‘6523.exe’ and ‘/g.exe’) via HTTP over port 80. These downloads originated from endpoints that had never been seen within the customer’s environment, namely ‘hugersi[.]com’ and ‘45.66.230[.]164’, both of which had strongly been linked to SmokeLoader by OSINT sources, likely indicating the initial infection stage of the attack [5].

Figure 6: This figure illustrates Darktrace DETECT observing a device downloading multiple .exe files from rare endpoints and the associated model breach, ‘Anomalous File / Multiple EXE from Rare External Locations’.

Around the same time, Darktrace also observed the same device downloading an unusual file with a numeric file name. Threat actors often employ this tactic in order to avoid using file name patterns that could easily be recognized and blocked by traditional security measures; by frequently changing file names, malicious executables are more likely to remain undetected.

Figure 7: Graph showing the unusually high number of executable files downloaded by the device during the initial infection stage of the attack. The orange and red circles represent the number of model breaches that the device made during the observed activity related to SmokeLoader infection.
Figure 8: This figure illustrates the moment when Darktrace DETECT identified a suspicious download with a numeric file name.

With Darktrace RESPOND active and enabled in autonomous response mode, the SmokeLoader infection was thwarted in the first instance. RESPOND took swift autonomous action by blocking connections to the suspicious endpoints identified by DETECT, blocking all outgoing traffic, and enforcing a pre-established “pattern of life” on offending devices. By enforcing a patten of life on a device, Darktrace RESPOND ensures that it cannot deviate from its ‘normal’ activity to carry out potentially malicious activity, while allowing the device to continue expected business operations.

Figure 9:  A total of 8 RESPOND actions were applied, including blocking connections to suspicious endpoints and domains associated with SmokeLoader.

In addition to the autonomous mitigative actions taken by RESPOND, this customer also received a Proactive Threat Notification (PTN) informing them of potentially malicious activity on their network. This prompted the Darktrace Security Operations Center (SOC) to investigate and document the incident, allowing the customer’s security team to shift their focus to remediating and removing the threat of SmokeLoader.

Conclusion

Ultimately, Darktrace showcased its ability to detect and contain versatile and evasive strains of loader malware, like SmokeLoader. Despite its adeptness at bypassing conventional security tools by frequently changing its C2 infrastructure, utilizing existing processes to infect malicious code, and obfuscating malicious file and domain names, Darktrace’s anomaly-based approach allowed it to recognize such activity as deviations from expected network behavior, regardless of their apparent legitimacy.

Considering SmokeLoader’s wide array of functions, including C2 communication that could be used to facilitate additional attacks like exfiltration, or even the deployment of information-stealers or ransomware, Darktrace proved to be crucial in safeguarding customer networks. By identifying and mitigating SmokeLoader at the earliest possible stage, Darktrace effectively prevented the compromises from escalating into more damaging and disruptive compromises.

With the threat of loader malware expected to continue growing alongside the boom of the MaaS industry, it is paramount for organizations to adopt proactive security solutions, like Darktrace DETECT+RESPOND, that are able to make intelligent decisions to identify and neutralize sophisticated attacks.

Credit to Patrick Anjos, Senior Cyber Analyst, Justin Torres, Cyber Analyst

Appendices

Darktrace DETECT Model Detections

- Anomalous Connection / New User Agent to IP Without Hostname

- Anomalous Connection / Multiple HTTP POSTs to Rare Hostname

- Anomalous File / Multiple EXE from Rare External Locations

- Anomalous File / Numeric File Download

List of IOCs (IOC / Type / Description + Confidence)

- 85.208.139[.]35 / IP / SmokeLoader C2 Endpoint

- 185.174.137[.]109 / IP / SmokeLoader C2 Endpoint

- 45.66.230[.]164 / IP / SmokeLoader C2 Endpoint

- 91.215.85[.]147 / IP / SmokeLoader C2 Endpoint

- tolilolihul[.]net / Hostname / SmokeLoader C2 Endpoint

- bulimu55t[.]net / Hostname / SmokeLoader C2 Endpoint

- potunulit[.]org / Hostname / SmokeLoader C2 Endpoint

- hugersi[.]com / Hostname / SmokeLoader C2 Endpoint

- human[.]art / Hostname / SmokeLoader C2 Endpoint

- 371b0d5c867c2f33ae270faa14946c77f4b0953 / SHA1 / SmokeLoader Executable

References:

[1] https://bazaar.abuse.ch/sample/d7c395ab2b6ef69210221337ea292e204b0f73fef8840b6e64ab88595eda45b3/#intel

[2] https://malpedia.caad.fkie.fraunhofer.de/details/win.smokeloader

[3] https://www.darkreading.com/cyber-risk/breaking-down-the-propagate-code-injection-attack

[4] https://n1ght-w0lf.github.io/malware%20analysis/smokeloader/

[5] https://therecord.media/surge-in-smokeloader-malware-attacks-targeting-ukrainian-financial-gov-orgs

MITRE ATT&CK Mapping

Model: Anomalous Connection / New User Agent to IP Without Hostname

ID: T1071.001

Sub technique: T1071

Tactic: COMMAND AND CONTROL

Technique Name: Web Protocols

Model: Anomalous Connection / Multiple HTTP POSTs to Rare Hostname

ID: T1185

Sub technique: -

Tactic: COLLECTION

Technique Name: Man in the Browser

ID: T1071.001

Sub technique: T1071

Tactic: COMMAND AND CONTROL

Technique Name: Web Protocols

Model: Anomalous File / Multiple EXE from Rare External Locations

ID: T1189

Sub technique: -

Tactic: INITIAL ACCESS

Technique Name: Drive-by Compromise

ID: T1588.001

Sub technique: - T1588

Tactic: RESOURCE DEVELOPMENT

Technique Name: Malware

Model: Anomalous File / Numeric File Download

ID: T1189

Sub technique: -

Tactic: INITIAL ACCESS

Technique Name: Drive-by Compromise

ID: T1588.001

Sub technique: - T1588

Tactic: RESOURCE DEVELOPMENT

Technique Name: Malware

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.
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Patrick Anjos
Senior Cyber Analyst
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November 19, 2024

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Darktrace Leading the Future of Network Detection and Response with Recognition from KuppingerCole

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KuppingerCole has recognized Darktrace as an overall Leader, Product Leader, Market Leader and Innovation Leader in the KuppingerCole Leadership Compass: Network Detection and Response (2024).

With the perimeter all but dissolved, Network Detection and Response (NDR) tools are quickly becoming a critical component of the security stack, as the main tool to span the modern network. NDRs connect on-premises infrastructure to cloud, remote workers, identities, SaaS applications, and IoT/OT – something not available to EDR that requires agents and isolates visibility to individual devices.

KuppingerCole Analysts AG designated Darktrace an ‘Overall Leader’ position because of our continual innovation around user-led security. Self-Learning AI together with automated triage through Cyber AI Analyst and real-time autonomous response actions have been instrumental to security teams in stopping potential threats before they become a breach. With this time saved, Darktrace is leading beyond reactive security to truly harden a network, allowing the team to spend more time in preventive security measures.

Network Detection and Response protects where others fail to reach

NDR solutions operate at the network level, deploying inside or parallel to your network to ingest raw traffic via virtual or physical sensors. This gives them unprecedented potential to identify anomalies and possible breaches in any network - far beyond simple on-prem, into dynamic virtual environments, cloud or hybrid networks, cloud applications, and even remote devices accessing the corporate network via ZTNA or VPN.

Rather than looking at processes level data, NDR can detect the lateral movement of an adversary across multiple assets by analyzing network traffic patterns which endpoint solutions may not be able to identify [1]. In the face of a growing, complex environment, organizations large and small, will benefit from using NDRs either in conjunction, or as the foundation for, their Extended Detection and Response (XDR) for a unified view that improves their overall threat detection, ease of investigation and faster response times.

Today's NDR solutions are expected to include advanced ML and artificial intelligence (AI) algorithms [1]

Traditional IDS & IPS systems are labor intensive, requiring continuous rule creation, outdated signature maintenance, and manual monitoring for false positives or incorrect actions. This is no longer viable against a higher volume and changing landscape, making NDR the natural network tool to level against these evolutions. The role of AI in NDRs is designed to meet this challenge, “to reduce both the labor need for analysis and false positives, as well as add value by improving anomaly detection and overall security posture” .

Celebrating success in leadership and innovation

Darktrace is proud to have been recognized as an NDR “Overall Leader” in KuppingerCole Analyst AG’s Leadership Compass. The report gave further recognition to Darktrace as a ‘Product Leader”, “Innovation Leader” and “Market Leader”.

Maximum scores were received for core product categories, in addition to market presence and financial strength. Particular attention was directed to our innovation. This year has seen several NDR updates via Darktrace’s ActiveAI Security Platform version 6.2 which has enhanced investigation workflows and provided new AI transparency within the toolset.

Positive scores were also received for Darktrace’s deployment ecosystem and surrounding support, minimizing the need for extraneous integrations through a unique platform architecture that connects with over 90 other vendors.

High Scores received in Darktrace’s KuppingerCole Spider Chart across Core NDR capability areas
Figure 1: High Scores received in Darktrace’s KuppingerCole Spider Chart across Core NDR capability areas

Darktrace’s pioneering AI approach sets it apart

Darktrace / NETWORK’s approach is fundamentally different to other NDRs. Continual anomaly-based detection (our Self-Learning AI), understands what is normal across each of your network entities, and then examines deviations from these behaviors rather than needing to apply static rules or ML to adversary techniques. As a result, Darktrace / NETWORK can focus on surfacing the novel threats that cannot be anticipated, whilst our proactive solutions expose gaps that can be exploited and reduce the risk of known threats.    

Across the millions of possible network events that may occur, Darktrace’s Cyber AI Analyst reduces that manual workload for SOC teams by presenting only what is most important in complete collated incidents. This accelerates SOC Level 2 analyses of incidents by 10x2, giving time back, first for any necessary response and then for preventive workflows.

Finally, when incidents begin to escalate, Darktrace can natively (or via third-party) autonomously respond and take precise actions based on a contextual understanding of both the affected assets and incident in question so that threats can be disarmed without impacting wider operations.

Within the KuppingerCole report, several standout strengths were listed:

  • Cyber AI Analyst was celebrated as a core differentiator, enhancing both visibility and investigation into critical network issues and allowing a faster response.
  • Darktrace / NETWORK was singled for its user benefits. Both a clear interface for analysts with advanced filtering and analytical tools, and efficient role-based access control (RBAC) and configuration options for administrators.
  • At the product level, Darktrace was recognized for complete network traffic analysis (NTA) capabilities allowing extensive analysis into components like application use/type, fingerprinting, source/destination communication, in addition to comprehensive protocol support across a range of network device types from IT, OT, IoT and mobiles and detailed MITRE ATT&CK mapping.
  • Finally, at the heart of it, Darktrace’s innovation was highlighted in relation to its intrinsic Self Learning AI, utilizing multiple layers of deep learning, neural networks, LLMs, NLP, Generative AI and more to understand network activity and filter it for what’s critical on an individual customer level.

Going beyond reactive security

Darktrace’s visibility and AI-enabled detection, investigation and response enable security teams to focus on hardening gaps in their network through contextual relevance & priority. Darktrace / NETWORK explicitly gives time back to security teams allowing them to focus on the bigger strategic and governance workflows that sometimes get overlooked. This is enabled through proactive solutions intrinsically connected to our NDR:

  • Darktrace / Proactive Exposure Management, which looks beyond just CVE risks to instead discover, prioritize and validate risks by business impact and how to mobilize against them early, to reduce the number of real threats security teams face.
  • Darktrace / Incident Readiness & Recovery, a solution rather than service-based approach to incident response (IR) that lets teams respond in the best way to each incident and proactively test their familiarity and effectiveness of IR workflows with sophisticated incident simulations involving their own analysts and assets.

Together, these solutions allow Darktrace / NETWORK to go beyond the traditional NDR and shift teams to a more hardened and proactive state.

Putting customers first

Customers continue to sit at the forefront of Darktrace R&D, with their emerging needs and pain points being the direct inspiration for our continued innovation.

This year Darktrace / NETWORK has protected thousands of customers against the latest attacks, from data exfil and destruction, to unapproved privilege escalation and ransomware including strains like Medusa, Qilin and AlphV BlackCat.

In each instance, Darktrace / NETWORK was able to provide a holistic lens of the anomalies present in their traffic, collated those that were important, and either responded or gave teams the ability to take targeted actions against their threats – even when adversaries pivoted. In one example of a Gootloader compromise, Darktrace ensured a SOC went from detection to recovery within 5 days, 92.8% faster than the average containment time of 69 days.

Results like these, focused on user-led security, have secured Darktrace’s position within the latest NDR Leadership Compass.

To find out more about what makes Darktrace / NETWORK special, read the full KuppingerCole report.

References

[1] Osman Celik, KuppingerCole Leadership Compass:Network Detection and Response (2024)

[2] Darktrace's AI Analyst customer fleet data

[3] https://www.ibm.com/reports/data-breach

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Gabriel Few-Wiegratz
Product Marketing Manager

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November 1, 2024

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Inside the SOC

Phishing and Persistence: Darktrace’s Role in Defending Against a Sophisticated Account Takeover

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The exploitation of SaaS platforms

As businesses continue to grow and evolve, the need for sharing ideas through productivity and cloud Software-as-a-Service (SaaS) platforms is becoming increasingly crucial. However, these platforms have also become prime targets for cyber attackers.

Threat actors often exploit these widely-used services to gain unauthorized access, steal sensitive information, and disrupt business operations. The growing reliance on SaaS platforms makes them attractive entry points for cybercriminals, who use sophisticated techniques such as phishing, social engineering, and malware to compromise these systems.

Services like Microsoft 365 are regularly targeted by threat actors looking for an entry point into an organization’s environment to carry out malicious activities. Securing these platforms is crucial to protect business data and ensure operational continuity.

Darktrace / EMAIL detection of the phishing attack

In a recent case, Darktrace observed a customer in the manufacturing sector receiving a phishing email that led to a threat actor logging in and creating an email rule. Threat actors often create email rules to move emails to their inbox, avoiding detection. Additionally, Darktrace detected a spoofed domain registered by the threat actor. Despite already having access to the customer’s SaaS account, the actor seemingly registered this domain to maintain persistence on the network, allowing them to communicate with the spoofed domain and conduct further malicious activity.

Darktrace / EMAIL can help prevent compromises like this one by blocking suspicious emails as soon as they are identified. Darktrace’s AI-driven email detection and response recognizes anomalies that might indicate phishing attempts and applies mitigative actions autonomously to prevent the escalation of an attack.

Unfortunately, in this case, Darktrace was not configured in Autonomous Response mode at the time of the attack, meaning actions had to be manually applied by the customer’s security team. Had it been fully enabled, it would have held the emails, preventing them from reaching the intended recipient and stopping the attack at its inception.

However, Darktrace’s Managed Threat Detection alerted the Security Operations Center (SOC) team to the compromise, enabling them to thoroughly investigate the incident and notify the customer before further damage could occur.

The Managed Threat Detection service continuously monitors customer networks for suspicious activities that may indicate an emerging threat. When such activities are detected, alerts are sent to Darktrace’s expert Cyber Analysts for triage, significantly speeding up the remediation process.

Attack Overview

On May 2, 2024, Darktrace detected a threat actor targeting a customer in the manufacturing sector then an unusual login to their SaaS environment was observed prior to the creation of a new email rule.

Darktrace immediately identified the login as suspicious due to the rarity of the source IP (31.222.254[.]27) and ASN, coupled with the absence of multi-factor authentication (MFA), which was typically required for this account.

The new email rule was intended to mark emails as read and moved to the ‘Conversation History’ folder for inbound emails from a specific domain. The rule was named “….,,,”, likely the attacker attempting to setup their new rule with an unnoteworthy name to ensure it would not be noticed by the account’s legitimate owner. Likewise, by moving emails from a specific domain to ‘Conversation History’, a folder that is rarely used by most users, any phishing emails sent by that domain would remain undetected by the user.

Darktrace’s detection of the unusual SaaS login and subsequent creation of the new email rule “….,,,”.
Figure 1: Darktrace’s detection of the unusual SaaS login and subsequent creation of the new email rule “….,,,”.

The domain in question was identified as being newly registered and an example of a typosquat domain. Typosquatting involves registering new domains with intentional misspelling designed to convince users to visit fake, and often malicious, websites. This technique is often used in phishing campaigns to create a sense of legitimacy and trust and deceive users into providing sensitive information. In this case, the suspicious domain closely resembled several of the customer’s internal domains, indicating an attempt to impersonate the organization’s legitimate internal sites to gain the target’s trust. Furthermore, the creation of this lookalike domain suggests that the attack was highly targeted at this specific customer.

Interestingly, the threat actor registered this spoofed domain despite already having account access. This was likely intended to ensure persistence on the network without having to launch additional phishing attacks. Such use of spoofed domain could allow an attacker to maintain a foothold in their target network and escalate their malicious activities without having to regain access to the account. This persistence can be used for various purposes, including data exfiltration, spreading malware, or launching further attacks.

Following this, Darktrace detected a highly anomalous email being sent to the customer’s account from the same location as the initial unsual SaaS login. Darktrace’s anomaly-based detection is able to identify threats that human security teams and traditional signature-based methods might miss. By analyzing the expected behavior of network users, Darktrace can recognize the subtle deviations from the norm that may indicate malicious activity. Unfortunately, in this instance, without Darktrace’s Autonomous Response capability enabled, the phishing email was able to successfully reach the recipient. While Darktrace / EMAIL did suggest that the email should be held from the recipients inbox, the customer was required to manually approve it.

Despite this, the Darktrace SOC team were still able to support the customer as they were subscribed to the Managed Threat Detection service. Following the detection of the highlight anomalous activity surrounding this compromise, namely the unusual SaaS login followed by a new email rule, an alert was sent to the Darktrace SOC for immediate triage, who then contacted the customer directly urging immediate action.

Conclusion

This case underscores the need to secure SaaS platforms like Microsoft 365 against sophisticated cyber threats. As businesses increasingly rely on these platforms, they become prime targets for attackers seeking unauthorized access and disruption.

Darktrace’s anomaly-based detection and response capabilities are crucial in identifying and mitigating such threats. In this instance, Darktrace detected a phishing email that led to a threat actor logging in and creating a suspicious email rule. The actor also registered a spoofed domain to maintain persistence on the network.

Darktrace / EMAIL, with its AI-driven detection and analysis, can block suspicious emails before they reach the intended recipient, preventing attacks at their inception. Meanwhile, Darktrace’s SOC team promptly investigated the activity and alerted the customer to the compromise, enabling them to take immediate action to remediate the issue and prevent any further damage.

Credit to Vivek Rajan (Cyber Security Analyst) and Ryan Traill (Threat Content Lead).

Appendices

Darktrace Model Detections

  • SaaS / Access / Unusual External Source for SaaS Credential Use
  • SaaS / Compromise / Login From Rare Endpoint While User Is Active
  • SaaS / Resource / Unusual Access to Delegated Resource by Non Owner
  • SaaS / Email Nexus / Unusual Login Location Following Sender Spoof
  • Compliance / Anomalous New Email Rule
  • SaaS / Compromise / Unusual Login and New Email Rule

Indicators of Compromise (IoCs)

IoC - Type - Description + Confidence

31.222.254[.]27 – IP -  Suspicious Login Endpoint

MITRE ATT&CK Mapping

Tactic – Technqiue – Sub-technique of (if applicable)

Cloud Accounts - DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS - T1078.004 - T1078

Cloud Service Dashboard – DISCOVERY - T1538

Compromise Accounts - RESOURCE DEVELOPMENT - T1586

Steal Web Session Cookie - CREDENTIAL ACCESS - T1539

Outlook Rules – PERSISTENCE - T1137.005 - T1137

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About the author
Vivek Rajan
Cyber Analyst
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