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November 7, 2022

[Part 1] Analysis of a Raccoon Stealer v1 Infection

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07
Nov 2022
Darktrace’s SOC team observed a fast-paced compromise involving Raccoon Stealer v1. See which steps the Raccoon Stealer v1 took to extract company data!

Introduction

Towards the end of March 2022, the operators of Raccoon Stealer announced the closure of the Raccoon Stealer project [1]. In May 2022, Raccoon Stealer v2 was unleashed onto the world, with huge numbers of cases being detected across Darktrace’s client base. In this series of blog posts, we will follow the development of Raccoon Stealer between March and September 2022. We will first shed light on how Raccoon Stealer functioned before its demise, by providing details of a Raccoon Stealer v1 infection which Darktrace’s SOC saw within a client network on the 18th March 2022. In the follow-up post, we will provide details about the surge in Raccoon Stealer v2 cases that Darktrace’s SOC has observed since May 2022.  

What is Raccoon Stealer?

The misuse of stolen account credentials is a primary method used by threat actors to gain initial access to target environments [2]. Threat actors have several means available to them for obtaining account credentials. They may, for example, distribute phishing emails which trick their recipients into divulging account credentials. Alternatively, however, they may install information-stealing malware (i.e, info-stealers) onto users’ devices. The results of credential theft can be devastating. Threat actors may use the credentials to gain access to an organization’s SaaS environment, or they may use them to drain users’ online bank accounts or cryptocurrency wallets. 

Raccoon Stealer is a Malware-as-a-Service (MaaS) info-stealer first publicized in April 2019 on Russian-speaking hacking forums. 

Figure 1: One of the first known mentions of Raccoon Stealer on a Russian-speaking hacking forum named ‘Hack Forums’ on the 13th April 2019

The team of individuals behind Raccoon Stealer provide a variety of services to their customers (known as ‘affiliates’), including access to the info-stealer, an easy-to-use automated backend panel, hosting infrastructure, and 24/7 customer support [3]. 

Once Raccoon Stealer affiliates gain access to the info-stealer, it is up to them to decide how to distribute it. Since 2019, affiliates have been observed distributing the info-stealer via a variety of methods, such as exploit kits, phishing emails, and fake cracked software websites [3]/[4]. Once affiliates succeed in installing Raccoon Stealer onto target systems, the info-stealer will typically seek to obtain sensitive information saved in browsers and cryptocurrency wallets. The info-stealer will then exfiltrate the stolen data to a Command and Control (C2) server. The affiliate can then use the stolen data to conduct harmful follow-up activities. 

Towards the end of March 2022, the team behind Raccoon Stealer publicly announced that they would be suspending their operations after one of their core developers was killed during the Russia-Ukraine conflict [5]. 

Figure 2: Raccoon Stealer resignation post on March 25th 2022

Recent details shared by the US Department of Justice [6]/[7] indicate that it was in fact the arrest, rather than the death, of a key Raccoon Stealer operator which led the Raccoon Stealer team to suspend their operations [8].  

The closure of the Raccoon Stealer project, which ultimately resulted from the FBI-backed dismantling of Raccoon Stealer’s infrastructure in March 2022, did not last long, with the completion of Raccoon Stealer v2 being announced on the Raccoon Stealer Telegram channel on the 17th May 2022 [9]. 

 

Figure 3: Telegram post about new version of Raccoon Stealer

In the second part of this blog series, we will provide details of the recent surge in Raccoon Stealer v2 activity. In this post, however, we will provide insight into how the old version of Raccoon Stealer functioned just before its demise, by providing details of a Raccoon Stealer v1 infection which occurred on the 18th March 2022. 

Attack Details

On the 18th March, at around 13:00 (UTC), a user’s device within a customer’s network was seen contacting several websites providing fake cracked software. 

Figure 4: The above figure — obtained from the Darktrace Event Log for the infected device — highlights its connections to cracked software websites such as ‘licensekeysfree[.]com’ and ‘hdlicense[.]com’ before contacting ‘lion-files[.]xyz’ and ‘www.mediafire[.]com’

The user’s attempt to download cracked software from one of these websites resulted in their device making an HTTP GET request with a URI string containing ‘autodesk-revit-crack-v2022-serial-number-2022’ to an external host named ‘lion-filez[.]xyz’

Figure 5: Screenshot from hdlicense[.]com around the time of the infection shows a “Download” button linking to the ‘lion-filez[.]xyz’ endpoint

The device’s HTTP GET request to lion-filez[.]xyz was immediately followed by an HTTPS connection to the file hosting service, www.mediafire[.]com. Given that threat actors are known to abuse platforms such as MediaFire and Discord CDN to host their malicious payloads, it is likely that the user’s device downloaded the Raccoon Stealer v1 sample over its HTTPS connection to www.mediafire[.]com.  

After installing the info-stealer sample, the user’s device was seen making an HTTP GET request with the URI string ‘/g_shock_casio_easy’ to 194.180.191[.]185. The endpoint responded to the request with data related to a Telegram channel named ‘G-Shock’.

Figure 6: Telegram channel ‘@g_shock_casio_easy’

The returned data included the Telegram channel’s description, which in this case, was a base64 encoded and RC4 encrypted string of characters [10]/[11]. The Raccoon Stealer sample decoded and decrypted this string of characters to obtain its C2 IP address, 188.166.49[.]196. This technique used by Raccoon Stealer v1 closely mirrors the espionage method known as ‘dead drop’ — a method in which an individual leaves a physical object such as papers, cash, or weapons in an agreed hiding spot so that the intended recipient can retrieve the object later on without having to come in to contact with the source. In this case, the operators of Raccoon Stealer ‘left’ the malware’s C2 IP address within the description of a Telegram channel. Usage of this method allowed the operators of Raccoon Stealer to easily change the malware’s C2 infrastructure.  

After obtaining the C2 IP address from the ‘G-Shock’ Telegram channel, the Raccoon Stealer sample made an HTTP POST request with the URI string ‘/’ to the C2 IP address, 188.166.49[.]196. This POST request contained a Windows GUID,  a username, and a configuration ID. These details were RC4 encrypted and base64 encoded [12]. The C2 server responded to this HTTP POST request with JSON-formatted configuration information [13], including an identifier string, URL paths for additional files, along with several other fields. This configuration information was also concealed using RC4 encryption and base64 encoding.  

Figure 7- Fields within the JSON-formatted configuration data [13]

In this case, the server’s response included the identifier string ‘hv4inX8BFBZhxYvKFq3x’, along with the following URL paths:

  • /l/f/hv4inX8BFBZhxYvKFq3x/77d765d8831b4a7d8b5e56950ceb96b7c7b0ed70
  • /l/f/hv4inX8BFBZhxYvKFq3x/0cb4ab70083cf5985b2bac837ca4eacb22e9b711
  • /l/f/hv4inX8BFBZhxYvKFq3x/5e2a950c07979c670b1553b59b3a25c9c2bb899b
  • /l/f/hv4inX8BFBZhxYvKFq3x/2524214eeea6452eaad6ea1135ed69e98bf72979

After retrieving configuration data, the user’s device was seen making HTTP GET requests with the above URI strings to the C2 server. The C2 server responded to these requests with legitimate library files such as sqlite3.dll. Raccoon Stealer uses these libraries to extract data from targeted applications. 

Once the Raccoon Stealer sample had collected relevant data, it made an HTTP POST request with the URI string ‘/’ to the C2 server. This posted data likely included a ZIP file (named with the identifier string) containing stolen credentials [13]. 

The observed infection chain, which lasted around 20 minutes, consisted of the following steps:

1. User’s device installs Raccoon Stealer v1 samples from the user attempting to download cracked software

2. User’s device obtains the info-stealer’s C2 IP address from the description text of a Telegram channel

3. User’s device makes an HTTP POST request with the URI string ‘/’ to the C2 server. The request contains a Windows GUID,  a username, and a configuration ID. The response to the request contains configuration details, including an identifier string and URL paths for additional files

4. User’s device downloads library files from the C2 server

5. User’s device makes an HTTP POST request with the URI string ‘/’ to the C2 server. The request contains stolen data

Darktrace Coverage 

Although RESPOND/Network was not enabled on the customer’s deployment, DETECT picked up on several of the info-stealer’s activities. In particular, the device’s downloads of library files from the C2 server caused the following DETECT/Network models to breach:

  • Anomalous File / Masqueraded File Transfer
  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Zip or Gzip from Rare External Location
  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Multiple EXE from Rare External Locations
Figure 8: Event Log for the infected device shows 'Anomalous File / Masqueraded File Transfer' model breach after the device's download of a library file from the C2 server

Since the customer was subscribed to the Darktrace Proactive Threat Notification (PTN) service, they were proactively notified of the info-stealer’s activities. The quick response by Darktrace’s 24/7 SOC team helped the customer to contain the infection and to prevent further damage from being caused. Having been alerted to the info-stealer activity by the SOC team, the customer would also have been able to change the passwords for the accounts whose credentials were exfiltrated.

If RESPOND/Network had been enabled on the customer’s deployment, then it would have blocked the device’s connections to the C2 server, which would have likely prevented any stolen data from being exfiltrated.

Conclusion

Towards the end of March 2022, the team behind Raccoon Stealer announced that they would be suspending their operations. Recent developments suggest that the arrest of a core Raccoon Stealer developer was responsible for this suspension. Just before the Raccoon Stealer team were forced to shut down, Darktrace’s SOC team observed a Raccoon Stealer infection within a client’s network. In this post, we have provided details of the network-based behaviors displayed by the observed Raccoon Stealer sample. Since these v1 samples are no longer active, the details provided here are only intended to provide historical insight into the development of Raccoon Stealer’s operations and the activities carried out by Raccoon Stealer v1 just before its demise. In the next post of this series, we will discuss and provide details of Raccoon Stealer v2 — the new and highly prolific version of Raccoon Stealer. 

Thanks to Stefan Rowe and the Threat Research Team for their contributions to this blog.

References

[1] https://twitter.com/3xp0rtblog/status/1507312171914461188

[2] https://www.gartner.com/doc/reprints?id=1-29OTFFPI&ct=220411&st=sb

[3] https://www.cybereason.com/blog/research/hunting-raccoon-stealer-the-new-masked-bandit-on-the-block

[4] https://www.cyberark.com/resources/threat-research-blog/raccoon-the-story-of-a-typical-infostealer

[5] https://www.bleepingcomputer.com/news/security/raccoon-stealer-malware-suspends-operations-due-to-war-in-ukraine/

[6] https://www.justice.gov/usao-wdtx/pr/newly-unsealed-indictment-charges-ukrainian-national-international-cybercrime-operation

[7] https://www.youtube.com/watch?v=Fsz6acw-ZJY

[8] https://riskybiznews.substack.com/p/raccoon-stealer-dev-didnt-die-in

[9] https://medium.com/s2wblog/raccoon-stealer-is-back-with-a-new-version-5f436e04b20d

[10] https://blog.cyble.com/2021/10/21/raccoon-stealer-under-the-lens-a-deep-dive-analysis/

[11] https://decoded.avast.io/vladimirmartyanov/raccoon-stealer-trash-panda-abuses-telegram/

[12] https://blogs.blackberry.com/en/2021/09/threat-thursday-raccoon-infostealer

[13] https://cyberint.com/blog/research/raccoon-stealer/

Appendices

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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January 13, 2025

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Cloud

Agent vs. Agentless cloud security: Why deployment methods matter

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The rapid adoption of cloud technologies has brought significant security challenges for organizations of all sizes. According to recent studies, over 70% of enterprises now operate in hybrid or multi-cloud environments, with 93% employing a multi-cloud strategy[1]. This complexity requires robust security tools, but opinions vary on the best deployment method—agent-based, agentless, or a combination of both.

Agent-based and agentless cloud security approaches offer distinct benefits and limitations, and organizations often make deployment choices based on their unique needs depending on the function of the specific assets covered, the types of data stored, and cloud architecture, such as hybrid or multi-cloud deployments.

For example, agentless solutions are increasingly favored for their ease of deployment and ability to provide broad visibility across dynamic cloud environments. These are especially useful for DevOps teams, with 64% of organizations citing faster deployment as a key reason for adopting agentless tools[2].

On the other hand, agent-based solutions remain the preferred choice for environments requiring deep monitoring and granular control, such as securing sensitive high-value workloads in industries like finance and healthcare. In fact, over 50% of enterprises with critical infrastructure report relying on agent-based solutions for their advanced protection capabilities[3].

As the debate continues, many organizations are turning to combined approaches, leveraging the strengths of both agent-based and agentless tools to address the full spectrum of their security needs for comprehensive coverage. Understanding the capabilities and limitations of these methods is critical to building an effective cloud security strategy that adapts to evolving threats and complex infrastructures.

Agent-based cloud security

Agent-based security solutions involve deploying software agents on each device or system that needs protection. Agent-based solutions are great choices when you need in-depth monitoring and protection capabilities. They are ideal for organizations that require deep security controls and real-time active response, particularly in hybrid and on-premises environments.

Key advantages include:

1. Real-time monitoring and protection: Agents detect and block threats like malware, ransomware, and anomalous behaviors in real time, providing ongoing protection and enforcing compliance by continuously monitoring workload activities.  Agents enable full control over workloads for active response such as blocking IP addresses, killing processes, disabling accounts, and isolating infected systems from the network, stopping lateral movement.

2. Deep visibility for hybrid environments: Agent-based approaches allow for full visibility across on-premises, hybrid, and multi-cloud environments by deploying agents on physical and virtual machines. Agents offer detailed insights into system behavior, including processes, files, memory, network connections, and more, detecting subtle anomalies that might indicate security threats. Host-based monitoring tracks vulnerabilities at the system and application level, including unpatched software, rogue processes, and unauthorized network activity.

3. Comprehensive coverage: Agents are very effective in hybrid environments (cloud and on-premises), as they can be installed on both physical and virtual machines.  Agents can function independently on each host device onto which they are installed, which is especially helpful for endpoints that may operate outside of constant network connectivity.

Challenges:

1. Resource-intensive: Agents can consume CPU, memory, and network resources, which may affect performance, especially in environments with large numbers of workloads or ephemeral resources.

2. Challenging in dynamic environments: Managing hundreds or thousands of agents in highly dynamic or ephemeral environments (e.g., containers, serverless functions) can be complex and labor-intensive.

3. Slower deployment: Requires agent installation on each workload or instance, which can be time-consuming, particularly in large or complex environments.  

Agentless cloud security

Agentless security does not require software agents to be installed on each device. Instead, it uses cloud infrastructure and APIs to perform security checks. Agentless solutions are highly scalable with minimal impact on performance, and ideal for cloud-native and highly dynamic environments like serverless and containerized. These solutions are great choices for your cloud-native and multi-cloud environments where rapid deployment, scalability, and minimal impact on performance are critical, but response actions can be handled through external tools or manual processes.

Key advantages include:

1. Scalability and ease of deployment: Because agentless security doesn’t require installation on each individual device, it is much easier to deploy and can quickly scale across a vast number of cloud assets. This approach is ideal for environments where resources are frequently created and destroyed (e.g., serverless, containerized workloads), as there is no need for agent installation or maintenance.

2. Reduced system overhead: Without the need to run local agents, agentless security minimizes the impact on system performance. This is crucial in high-performance environments.

3. Broad visibility: Agentless security connects via API to cloud service providers, offering near-instant visibility and threat detection. It provides a comprehensive view of your cloud environment, making it easier to manage and secure large and complex infrastructures.

Challenges

1. Infrastructure-level monitoring: Agentless solutions rely on cloud service provider logs and API calls, meaning that detection might not be as immediate as agent-based solutions. They collect configuration data and logs, focusing on infrastructure misconfigurations, identity risks, exposed resources, and network traffic, but lack visibility and access to detailed, system-level information such as running processes and host-level vulnerabilities.

2. Cloud-focused: Primarily for cloud environments, although some tools may integrate with on-premises systems through API-based data gathering. For organizations with hybrid cloud environments, this approach fragments visibility and security, leading to blind spots and increasing security risk.

3. Passive remediation: Typically provides alerts and recommendations, but lacks deep control over workloads, requiring manual intervention or orchestration tools (e.g., SOAR platforms) to execute responses. Some agentless tools trigger automated responses via cloud provider APIs (e.g., revoking permissions, adjusting security groups), but with limited scope.

Combined agent-based and agentless approaches

A combined approach leverages the strengths of both agent-based and agentless security for complete coverage. This hybrid strategy helps security teams achieve comprehensive coverage by:

  • Using agent-based solutions for deep, real-time protection and detailed monitoring of critical systems or sensitive workloads.
  • Employing agentless solutions for fast deployment, broader visibility, and easier scalability across all cloud assets, which is particularly useful in dynamic cloud environments where workloads frequently change.

The combined approach has distinct practical applications. For example, imagine a financial services company that deals with sensitive transactions. Its security team might use agent-based security for critical databases to ensure stringent protections are in place. Meanwhile, agentless solutions could be ideal for less critical, transient workloads in the cloud, where rapid scalability and minimal performance impact are priorities. With different data types and infrastructures, the combined approach is best.

Best of both worlds: The benefits of a combined approach

The combined approach not only maximizes security efficacy but also aligns with diverse operational needs. This means that all parts of the cloud environment are secured according to their risk profile and functional requirements. Agent-based deployment provides in-depth monitoring and active protection against threats, suitable for environments requiring tight security controls, such as financial services or healthcare data processing systems. Agentless deployment complements agents by offering broader visibility and easier scalability across diverse and dynamic cloud environments, ideal for rapidly changing cloud resources.

There are three major benefits from combining agent-based and agentless approaches.

1. Building a holistic security posture: By integrating both agent-based and agentless technologies, organizations can ensure that all parts of their cloud environments are covered—from persistent, high-risk endpoints to transient cloud resources. This comprehensive coverage is crucial for detecting and responding to threats promptly and effectively.

2. Reducing overhead while boosting scalability: Agentless systems require no software installation on each device, reducing overhead and eliminating the need to update and maintain agents on a large number of endpoints. This makes it easier to scale security as the organization grows or as the cloud environment changes.

3. Applying targeted protection where needed: Agent-based solutions can be deployed on selected assets that handle sensitive information or are critical to business operations, thus providing focused protection without incurring the costs and complexity of universal deployment.

Use cases for a combined approach

A combined approach gives security teams the flexibility to deploy agent-based and agentless solutions based on the specific security requirements of different assets and environments. As a result, organizations can optimize their security expenditures and operational efforts, allowing for greater adaptability in cloud security use cases.

Let’s take a look at how this could practically play out. In the combined approach, agent-based security can perform the following:

1. Deep monitoring and real-time protection:

  • Workload threat detection: Agent-based solutions monitor individual workloads for suspicious activity, such as unauthorized file changes or unusual resource usage, providing high granularity for detecting threats within critical cloud applications.
  • Behavioral analysis of applications: By deploying agents on virtual machines or containers, organizations can monitor behavior patterns and flag anomalies indicative of insider threats, lateral movement, or Advanced Persistent Threats (APTs).
  • Protecting high-sensitivity environments: Agents provide continuous monitoring and advanced threat protection for environments processing sensitive data, such as payment processing systems or healthcare records, leveraging capabilities like memory protection and file integrity monitoring.

2. Cloud asset protection:

  • Securing critical infrastructure: Agent-based deployments are ideal for assets like databases or storage systems that require real-time defense against exploits and ransomware.
  • Advanced packet inspection: For high-value assets, agents offer deep packet inspection and in-depth logging to detect stealthy attacks such as data exfiltration.
  • Customizable threat response: Agents allow for tailored security rules and automated responses at the workload level, such as shutting down compromised instances or quarantining infected files.

At the same time, agentless cloud security provides complementary benefits such as:

1. Broad visibility and compliance:

  • Asset discovery and management: Agentless systems can quickly scan the entire cloud environment to identify and inventory all assets, a crucial capability for maintaining compliance with regulations like GDPR or HIPAA, which require up-to-date records of data locations and usage.
  • Regulatory compliance auditing and configuration management: Quickly identify gaps in compliance frameworks like PCI DSS or SOC 2 by scanning configurations, permissions, and audit trails without installing agents. Using APIs to check configurations across cloud services ensures that all instances comply with organizational and regulatory standards, an essential aspect for maintaining security hygiene and compliance.
  • Shadow IT Detection: Detect and map unauthorized cloud services or assets that are spun up without security oversight, ensuring full inventory coverage.

2. Rapid environmental assessment:

  • Vulnerability assessment of new deployments: In environments where new code is frequently deployed, agentless security can quickly assess new instances, containers, or workloads in CI/CD pipelines for vulnerabilities and misconfigurations, enabling secure deployments at DevOps speed.
  • Misconfiguration alerts: Detect and alert on common cloud configuration issues, such as exposed storage buckets or overly permissive IAM roles, across cloud providers like AWS, Azure, and GCP.
  • Policy enforcement: Validate that new resources adhere to established security baselines and organizational policies, preventing security drift during rapid cloud scaling.

Combining agent-based and agentless approaches in cloud security not only maximizes the protective capabilities, but also offers flexibility, efficiency, and comprehensive coverage tailored to the diverse and evolving needs of modern cloud environments. This integrated strategy ensures that organizations can protect their assets more effectively while also adapting quickly to new threats and regulatory requirements.

Darktrace offers complementary and flexible deployment options for holistic cloud security

Powered by multilayered AI, Darktrace / CLOUD is a Cloud Detection and Response (CDR) solution that is agentless by default, with optional lightweight, host-based server agents for enhanced real-time actioning and deep inspection. As such, it can deploy in cloud environments in minutes and provide unified visibility and security across hybrid, multi-cloud environments.

With any deployment method, Darktrace supports multi-tenant, hybrid, and serverless cloud environments. Its Self-Learning AI learns the normal behavior across architectures, assets, and users to identify unusual activity that may indicate a threat. With this approach, Darktrace / CLOUD quickly disarms threats, whether they are known, unknown, or completely novel. It then accelerates the investigation process and responds to threats at machine speed.

Learn more about how Darktrace / CLOUD secures multi and hybrid cloud environments in the Solution Brief.

References:

1. Flexera 2023 State of the Cloud Report

2. ESG Research 2023 Report on Cloud-Native Security

3. Gartner, Market Guide for Cloud Workload Protection Platforms, 2023

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About the author
Kellie Regan
Director, Product Marketing - Cloud Security

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January 10, 2025

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Inside the SOC

Detecting and mitigating adversary-in-the-middle phishing attacks with Darktrace Services

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What is an Adversary-in-the-Middle Attack?

Threat actors are increasingly utilizing advanced phishing toolkits and techniques to carry out Adversary-in-the-Middle (AitM) attacks. These attacks involve the use of a proxy to a legitimate service, where the attacker’s webpage mimics the expected site. While the victim believes they are visiting the legitimate site, they are actually interacting with the attacker’s device, allowing the malicious actor to monitor all interactions and control the authenticated session, ultimately gaining access to the user’s account [1][2].

This blog will explore how Darktrace detected AitM techniques being leveraged in a Business Email Compromise (BEC) attack that used the widely used and trusted cloud storage service, Dropbox, for delivery. Dropbox’s popularity has made it a prime target for attackers to exploit in recent years. Threat actors can exploit the service for various malicious activities, including distributing malware and exposing sensitive information.

Attack Overview

In these types of AitM BEC attacks, recipients are often targeted with Dropbox-related emails, featuring subject headings like ‘FirstLast shared "Filename" with you,’ which suggest an individual is sharing an invoice-related attachment. These email subjects are common in such attacks, as threat actors attempt to encourage victims to access Dropbox links by masquerading them as legitimate files.

While higher priority users are, of course, targeted, the scope of these attacks remains broad. For instance, if a lower priority user is targeted by a phishing attack or their token is stolen, an attacker can still attempt BEC for further malicious intent and financial gain.

In October 2024, a Darktrace customer received a phishing email from a seemingly legitimate Dropbox address. This email originated from the IP, 54.240.39[.]219 and contained multiple link payloads to Dropbox-related hostnames were observed, inviting the user to access a file. Based on anomaly indicators and detection by Darktrace / EMAIL, Darktrace recognized that one of the payloads was attempting to abuse a legitimate cloud platform to share files or other unwanted material with the recipient.

Figure 1: Overview of the malicious email in the Darktrace / EMAIL console, highlighting Dropbox associated content/link payloads.

Following the recipient’s engagement with this email, Darktrace / IDENTITY identified a series of suspicious activities within the customer’s environment.

AitM attacks allow threat actors to bypass multi-factor authentication (MFA). Initially, when a user is phished, the malicious infrastructure captures both the user’s credentials and the token. This includes replaying a token issued to user that has already completed the MFA requirement, allowing the threat actor to satisfy the validity of the requirement and gain access to sensitive organizational resources. Darktrace is able to analyze user activity and authentication patterns to determine whether MFA requirements were met. This capability helps verify and indicate token theft via AitM.

Darktrace observed the associated user account making requests over Microsoft 365 from the IP 41.90.175[.]46. Given the unusual nature and rare geolocation based in Kenya, Africa, this activity did not appear indicative of legitimate business operations.

Figure 2: Geographical location of the SaaS user in relation to the source IP 41.90.175[.]46.

Further analysis using open-source intelligence (OSINT) revealed that the endpoint was likely associated with a call-back proxy network [3]. This suggested the presence of a network device capable of re-routing traffic and harvesting information.

Darktrace also detected that the same SaaS user was logging in from two different locations around the same time. One login was from a common, expected location, while the other was from an unusual location. Additionally, the user was observed registering security information using the Microsoft Authenticator app, indicating an attempt by an attacker to maintain access to the account by establishing a new method of MFA. This new MFA method could be used to bypass future MFA requirements, allowing the attacker to access sensitive material or carry out further malicious activities.

Figure 3: External sites summary for the SaaS account in relation to the source IP 13.74.161[.]104, observed with Registering Security Information.

Ultimately, this anomalous behavior was escalated to the Darktrace Security Operations Centre (SOC) via the Managed Detection & Response service for prompt triage and investigation by Darktrace’s SOC Analysts who notified the customer of strong evidence of compromise.

Fortunately, since this customer had Darktrace enabled in Autonomous Response mode, the compromised SaaS account had already been disabled, containing the attack. Darktrace’s SOC elected to extend this action to ensure the malicious activity remained halted until the customer could take further remedial action.

Figure 4: Attack timeline of observed activity, in chronological order; This highlighted anomalous SaaS events such as, MailItemsAccessed’, ‘Use of Unusual Credentials’, ‘User Registered Security Info’ events, and a ‘Disable User’ Autonomous Response action.

Conclusion

AitM attacks can play a crucial role in BEC campaigns. These attacks are often part of multi-staged operations, where an initial AitM attack is leveraged to launch a BEC by delivering a malicious URL through a trusted vendor or service. Attackers often attempt to lay low on their target network, sometimes persisting for extended periods, as they monitor user accounts or network segments to intercept sensitive communications.

In this instance, Darktrace successfully identified and acted against AitM techniques being leveraged in a BEC attack that used Dropbox for delivery. While Dropbox is widely used for legitimate purposes, its popularity has also made it a target for exploitation by threat actors, who have used it for a variety of malicious purposes, including delivering malware and revealing sensitive information.

Darktrace’s Security Operations Support service, combined with its Autonomous Response technology, provided timely and effective mitigation. Dedicated Security Operations Support analysts triaged the incident and implemented preventative measures, ensuring the customer was promptly notified. Meanwhile, Darktrace swiftly disabled the compromised SaaS account, allowing the customer to take further necessary actions, such as resetting the user’s password.

This case highlights the capabilities of Darktrace’s solutions, enabling the customer to resume normal business operations despite the malicious activity.

Credit to Justin Torres (Senior Cyber Analyst), Stefan Rowe (Technical Director, SOC) and Ryan Traill (Analyst Content Lead)

Appendices

References

1.    https://www.proofpoint.com/us/threat-reference/man-in-the-middle-attack-mitm

2.    https://thehackernews.com/2024/08/how-to-stop-aitm-phishing-attack.html

3.    https://spur.us/context/41.90.175.46

Darktrace Model Detections

Darktrace / NETWORK Model Alert(s):

SaaS / Compromise::SaaS Anomaly Following Anomalous Login

SaaS / Unusual Activity::Multiple Unusual SaaS Activities

SaaS / Compromise::Unusual Login and Account Update

SaaS / Compromise::Login From Rare Endpoint While User Is Active

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

SaaS / Email Nexus::Unusual Login Location Following Link to File Storage

SaaS / Access::MailItemsAccessed from Rare Endpoint

Darktrace/Autonomous Response Model Alert(s):

Antigena / SaaS::Antigena Suspicious SaaS Activity Block

List of Indicators of Compromise (IoCs)

(IoC - Type - Description)

41.90.175[.]46 – Source IP Observed with Suspicious Login Behavior

MITRE ATT&CK Mapping

(Technique Name - Tactic - ID - Sub-Technique of)

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

Email Accounts - RESOURCE DEVELOPMENT - T1586.002 - T1586

Cloud Service Dashboard - DISCOVERY - T1538

Compromise Accounts - RESOURCE DEVELOPMENT - T1586

Steal Web Session Cookie - CREDENTIAL ACCESS - T1539

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About the author
Justin Torres
Cyber Analyst
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