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July 11, 2023

Detecting and Responding to Vendor Email Compromises (VEC)

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11
Jul 2023
Learn how Darktrace detected and responded to a March 2023 Vendor Email Compromise (VEC) attacks on customer in the energy industry. Read more here!

Threat Trends: Email Landscape

As organizations and security teams around the world continue to improve their cyber hygiene and strengthen the defenses of their digital environments, threat actors are being forced to adapt and employ more advanced, sophisticated attack methods to achieve their goals.

Vendor Email Compromise (VEC) is one such elaborate and sophisticated type of Business Email Compromise (BEC) attack which exploits pre-existing trusted business relationships to impersonate vendors, with the goal of launching a targeted attack on the vendor’s customers [1].  

In March 2023, Darktrace/Email™ detected an example of a VEC attack on the network of a customer in the energy sector. Darktrace’s Self-Learning AI worked to successfully neutralize the VEC attack before it was able to take hold, by blocking the malicious emails so that they did not reach the inboxes of the intended recipients.

Business Email Compromise (BEC)

BEC is the practice of using deceitful emails to trick an organization into transferring funds or divulging sensitive information to a malicious actor. BEC attacks can have devastating financial consequences for organizations, with the FBI reporting a total of USD 2.7 billion in losses from BEC attacks in 2022 [2].  Along with ransomware attacks, BEC attacks are one of the greatest cyber threats facing organizations.

Vendor Email Compromise (VEC)

VEC represents a “new milestone in the evolution of BEC attacks” having taken BEC attacks “to a whole new level of sophistication” [3]. Traditional BEC attacks involve the impersonation of an upper or middle-management employee by a cybercriminal, who attempts to trick a senior executive or employee with access to the company’s finances into transferring funds [4]. Thus, they are crafted to target a specific individual within an organization.

On the other hand, VEC attack campaigns take this attack style even further as they tend to require a greater understanding of existing vendor-customer business relationships. A cyber-criminal gains access to a legitimate vendor account, the process of which may take months to design and fully implement, and uses the account to spread malicious emails to the vendor’s customers. VEC attacks are complex and difficult to detect, however they share some common features [1,3]:

1. Reconnaissance on the vendor and their customer base – the threat actor conducts in-depth research in an attempt to be as convincing as possible in their impersonation efforts. This process may take weeks or months to complete.

2. Credential stealing through phishing campaigns – the threat actor tricks the vendor’s employees into revealing confidential data or corporate credentials in order to gain access to one of the email accounts belonging to the vendor.

3. Account takeover - once the attacker has gained access to one of the vendor’s email accounts, they will create mailbox rules which forward emails meeting certain conditions (such as having ‘Invoice’ in their subject line) to the threat actor’s inbox. This is typically a lengthy process and requires the malicious actors to harvest as much sensitive information as they need in order to successfully masquerade as vendor employees.

4. Deceitful emails are sent to the vendor’s customers – the attacker crafts and sends a highly sophisticated and difficult to detect email campaign to targeted individuals amongst the vendor’s customers. These emails, which may be embedded into existing email threads, will typically contain instructions on how to wire money to the bank account of an attacker.

There have been many high-profile cases of BEC attacks over the years, one of the most famous being the vendor-impersonating BEC attacks carried out between 2013 and 2015 [5]. This BEC campaign resulted in victim companies transferring a total of USD 120 million to bank accounts under the attacker’s control. As the threat of BEC, and in particular VEC, attacks continue to rise, so too does the importance of being able to detect and respond to them.

Observed VEC Attack  

In March 2023, Darktrace/Email observed a VEC attack on an energy company. Email communication between this customer and one of their third-party vendors was common and took place as part of expected business activity, earning previous emails tags such as “Known Domain Relationship”, “Known Correspondent”, and “Established Domain Relationship”. These tags identify the sender relationship as trusted, causing Darktrace’s AI to typically attribute an anomaly score of 0% to emails from this third-party sender.

Just fifty minutes after the above legitimate email was observed, a group of suspicious emails were sent from the same domain, indicating that the trusted third-party had been compromised. Darktrace’s AI picked up on the peculiarity of these emails straight away, detecting elements of the mails which were out of character compared to the sender’s usual pattern of life, and as a result attributing these emails a 100% anomaly score despite the trusted relationship between the customer and sender domain. These suspicious emails were part of a targeted phishing attack, sent to high value individuals such as the company’s CTO and various company directors.  

Figure 1: Darktrace/Email's interface highlighting tags indicating the trusted relationship between the third-party domain and the customer.

Using methods outside of Darktrace’s visibility, a malicious actor managed to hijack the corporate account of a senior employee of this vendor company. The actor abused this email account to send deceitful emails to multiple employees at the energy company, including senior executives.

Figure 2: This screenshot shows Darktrace/Email’s assessment of emails from the vendor account pre-compromise and post-compromise.

Each of the emails sent by the attacker contained a link to a malicious file hosted inside a SharePoint repository associated with a university that had no association with the energy company. The malicious actor therefore appears to have leveraged a previously hijacked SharePoint repository to host their payload.

Cyber-criminals frequently use legitimate file storage domains to host malicious payloads as traditional gateways often fail to defend against them using reputation checks. The SharePoint file which the attacker sought to distribute to employees of the energy company likely provided wire transfer or bank account update instructions. If the attacker had succeeded in delivering these emails to these employees’ mailboxes, then the employees may have been tricked into performing actions resulting in the transfer of funds to a malicious actor. However, the attacker’s attempts to deliver these emails were thwarted by Darktrace/Email.

Darktrace Coverage

Despite the malicious actor sending their deceitful emails from a trusted vendor account, a range of anomalies were detected by Darktrace’s AI, causing the malicious emails to be given a 100% anomaly score and thus held from their recipients’ mailboxes. Such abnormalities, which represented a deviation in normal behavior, included:

  • The presence of an unexpected, out of character file storage link (known to be used for hosting malicious content)
  • The geographical source of the email
  • The anomalous linguistic structure and content of the email body, which earned the emails a high inducement score
Figure 3: Darktrace/Email’s overview of one of the malicious VEC emails it observed.

Darktrace has a series of models designed to trigger when anomalous features, such as those described above, are detected. The emails which made up this particular VEC attack breached a number of notable Darktrace/Email models. The presence of the suspicious link in the emails caused multiple link-related models to breach, which in turn elicited Darktrace RESPOND™ to perform its ‘double lock link’ action – an action which ensures that a user who has clicked on it cannot follow it to its original source. Models which breached due to the suspicious SharePoint link include:

Link / Link To File Storage

  • Link / Low Link Association
  • Link / New Unknown Link
  • Link / Outlook Hijack
  • Link / Relative Sender Anomaly + New Unknown Link
  • Link / Unknown Storage Service
  • Link / Visually Prominent Link Unexpected for Sender
  • Unusual / Unusual Login Location + Unknown Link

The out-of-character and suspicious linguistic aspects of the emails caused the following Darktrace/Email models to breach:

  • High Anomaly Sender
  • Proximity / Phishing
  • Proximity / Phishing and New Activity
  • Unusual / Inducement Shift High
  • Unusual / Undisclosed Recipients
  • Unusual / Unusual Login Location
  • Unusual / Off Topic

Due to the combination of suspicious features that were detected, tags such as ‘Phishing Link’ and ‘Out of Character’ were also added to these emails by Darktrace/Email. Darktrace’s coverage of these emails’ anomalous features ultimately led Darktrace RESPOND to perform its most severe inhibitive action, ‘hold message’. Applying this action stopped the emails from entering their recipients’ mailboxes. By detecting deviations from the sender’s normal email behavior, Darktrace/Email was able to completely neutralize the emails, and prevent them from potentially leading to significant financial harm.

Conclusion

Despite bypassing the customer’s other security measures, Darktrace/Email successfully identified and held these malicious emails, blocking them from reaching the inboxes of the intended recipients and thus preventing a successful targeted VEC attack. The elaborate and sophisticated nature of VEC attacks makes them particularly perilous to customers, and they can be hard to detect due to their exploitation of trusted relationships, and in this case, their use of legitimate services to host malicious files.

Darktrace’s anomaly-based approach to threat detection means it is uniquely placed to identify deviations in common email behavior, while its autonomous response capabilities allow it to take preventative action against emerging threats without latency.

Credits to: Sam Lister, Senior Analyst, for his contributions to this blog.

Appendices

MITRE ATT&CK Mapping

Tactic - Techniques

Resource Development

  • T1586.002 – Compromise Accounts: Email Accounts
  • T1584.006 – Compromise Infrastructure: Web Services
  • T1608.005 – Stage Capabilities: Link Target

Initial Access

  • T1195 – Supply Chain Compromise
  • T1566.002 – Phishing : Spearphishing Link

References

[1] https://www.cloudflare.com/en-gb/learning/email-security/what-is-vendor-email-compromise/

[2] https://www.ic3.gov/Media/PDF/AnnualReport/2022_IC3Report.pdf

[3] https://heimdalsecurity.com/blog/vendor-email-compromise-vec/

[4] https://www.ncsc.gov.uk/files/Business-email-compromise-infographic.pdf  

[5] https://www.justice.gov/usao-sdny/pr/lithuanian-man-sentenced-5-years-prison-theft-over-120-million-fraudulent-business

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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Tiana Kelly
Deputy Team Lead, London & Cyber Analyst
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January 16, 2025

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Reimagining Your SOC: How to Achieve Proactive Network Security

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Introduction: Challenges and solutions to SOC efficiency

For Security Operation Centers (SOCs), reliance on signature or rule-based tools – solutions that are always chasing the latest update to prevent only what is already known – creates an excess of false positives. SOC analysts are therefore overwhelmed by a high volume of context-lacking alerts, with human analysts able to address only about 10% due to time and resource constraints. This forces many teams to accept the risks of addressing only a fraction of the alerts while novel threats go completely missed.

74% of practitioners are already grappling with the impact of an AI-powered threat landscape, which amplifies challenges like tool sprawl, alert fatigue, and burnout. Thus, achieving a resilient network, where SOC teams can spend most of their time getting proactive and stopping threats before they occur, feels like an unrealistic goal as attacks are growing more frequent.

Despite advancements in security technology (advanced detection systems with AI, XDR tools, SIEM aggregators, etc...), practitioners are still facing the same issues of inefficiency in their SOC, stopping them from becoming proactive. How can they select security solutions that help them achieve a proactive state without dedicating more human hours and resources to managing and triaging alerts, tuning rules, investigating false positives, and creating reports?

To overcome these obstacles, organizations must leverage security technology that is able to augment and support their teams. This can happen in the following ways:

  1. Full visibility across the modern network expanding into hybrid environments
  2. Have tools that identifies and stops novel threats autonomously, without causing downtime
  3. Apply AI-led analysis to reduce time spent on manual triage and investigation

Your current solutions might be holding you back

Traditional cybersecurity point solutions are reliant on using global threat intelligence to pattern match, determine signatures, and consequently are chasing the latest update to prevent only what is known. This means that unknown threats will evade detection until a patient zero is identified. This legacy approach to threat detection means that at least one organization needs to be ‘patient zero’, or the first victim of a novel attack before it is formally identified.

Even the point solutions that claim to use AI to enhance threat detection rely on a combination of supervised machine learning, deep learning, and transformers to

train and inform their systems. This entails shipping your company’s data out to a large data lake housed somewhere in the cloud where it gets blended with attack data from thousands of other organizations. The resulting homogenized dataset gets used to train AI systems — yours and everyone else’s — to recognize patterns of attack based on previously encountered threats.

While using AI in this way reduces the workload of security teams who would traditionally input this data by hand, it emanates the same risk – namely, that AI systems trained on known threats cannot deal with the threats of tomorrow. Ultimately, it is the unknown threats that bring down an organization.

The promise and pitfalls of XDR in today's threat landscape

Enter Extended Detection and Response (XDR): a platform approach aimed at unifying threat detection across the digital environment. XDR was developed to address the limitations of traditional, fragmented tools by stitching together data across domains, providing SOC teams with a more cohesive, enterprise-wide view of threats. This unified approach allows for improved detection of suspicious activities that might otherwise be missed in siloed systems.

However, XDR solutions still face key challenges: they often depend heavily on human validation, which can aggravate the already alarmingly high alert fatigue security analysts experience, and they remain largely reactive, focusing on detecting and responding to threats rather than helping prevent them. Additionally, XDR frequently lacks full domain coverage, relying on EDR as a foundation and are insufficient in providing native NDR capabilities and visibility, leaving critical gaps that attackers can exploit. This is reflected in the current security market, with 57% of organizations reporting that they plan to integrate network security products into their current XDR toolset[1].

Why settling is risky and how to unlock SOC efficiency

The result of these shortcomings within the security solutions market is an acceptance of inevitable risk. From false positives driving the barrage of alerts, to the siloed tooling that requires manual integration, and the lack of multi-domain visibility requiring human intervention for business context, security teams have accepted that not all alerts can be triaged or investigated.

While prioritization and processes have improved, the SOC is operating under a model that is overrun with alerts that lack context, meaning that not all of them can be investigated because there is simply too much for humans to parse through. Thus, teams accept the risk of leaving many alerts uninvestigated, rather than finding a solution to eliminate that risk altogether.

Darktrace / NETWORK is designed for your Security Operations Center to eliminate alert triage with AI-led investigations , and rapidly detect and respond to known and unknown threats. This includes the ability to scale into other environments in your infrastructure including cloud, OT, and more.

Beyond global threat intelligence: Self-Learning AI enables novel threat detection & response

Darktrace does not rely on known malware signatures, external threat intelligence, historical attack data, nor does it rely on threat trained machine learning to identify threats.

Darktrace’s unique Self-learning AI deeply understands your business environment by analyzing trillions of real-time events that understands your normal ‘pattern of life’, unique to your business. By connecting isolated incidents across your business, including third party alerts and telemetry, Darktrace / NETWORK uses anomaly chains to identify deviations from normal activity.

The benefit to this is that when we are not predefining what we are looking for, we can spot new threats, allowing end users to identify both known threats and subtle, never-before-seen indicators of malicious activity that traditional solutions may miss if they are only looking at historical attack data.

AI-led investigations empower your SOC to prioritize what matters

Anomaly detection is often criticized for yielding high false positives, as it flags deviations from expected patterns that may not necessarily indicate a real threat or issues. However, Darktrace applies an investigation engine to automate alert triage and address alert fatigue.

Darktrace’s Cyber AI Analyst revolutionizes security operations by conducting continuous, full investigations across Darktrace and third-party alerts, transforming the alert triage process. Instead of addressing only a fraction of the thousands of daily alerts, Cyber AI Analyst automatically investigates every relevant alert, freeing up your team to focus on high-priority incidents and close security gaps.

Powered by advanced machine-learning techniques, including unsupervised learning, models trained by expert analysts, and tailored security language models, Cyber AI Analyst emulates human investigation skills, testing hypotheses, analyzing data, and drawing conclusions. According to Darktrace Internal Research, Cyber AI Analyst typically provides a SOC with up to  50,000 additional hours of Level 2 analysis and written reporting annually, enriching security operations by producing high level incident alerts with full details so that human analysts can focus on Level 3 tasks.

Containing threats with Autonomous Response

Simply quarantining a device is rarely the best course of action - organizations need to be able to maintain normal operations in the face of threats and choose the right course of action. Different organizations also require tailored response functions because they have different standards and protocols across a variety of unique devices. Ultimately, a ‘one size fits all’ approach to automated response actions puts organizations at risk of disrupting business operations.

Darktrace’s Autonomous Response tailors its actions to contain abnormal behavior across users and digital assets by understanding what is normal and stopping only what is not. Unlike blanket quarantines, it delivers a bespoke approach, blocking malicious activities that deviate from regular patterns while ensuring legitimate business operations remain uninterrupted.

Darktrace offers fully customizable response actions, seamlessly integrating with your workflows through hundreds of native integrations and an open API. It eliminates the need for costly development, natively disarming threats in seconds while extending capabilities with third-party tools like firewalls, EDR, SOAR, and ITSM solutions.

Unlocking a proactive state of security

Securing the network isn’t just about responding to incidents — it’s about being proactive, adaptive, and prepared for the unexpected. The NIST Cybersecurity Framework (CSF 2.0) emphasizes this by highlighting the need for focused risk management, continuous incident response (IR) refinement, and seamless integration of these processes with your detection and response capabilities.

Despite advancements in security technology, achieving a proactive posture is still a challenge to overcome because SOC teams face inefficiencies from reliance on pattern-matching tools, which generate excessive false positives and leave many alerts unaddressed, while novel threats go undetected. If SOC teams are spending all their time investigating alerts then there is no time spent getting ahead of attacks.

Achieving proactive network resilience — a state where organizations can confidently address challenges at every stage of their security posture — requires strategically aligned solutions that work seamlessly together across the attack lifecycle.

References

1.       Market Guide for Extended Detection and Response, Gartner, 17thAugust 2023 - ID G00761828

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About the author
Mikey Anderson
Product Marketing Manager, Network Detection & Response

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January 15, 2025

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Ransomware

RansomHub Ransomware: Darktrace’s Investigation of the Newest Tool in ShadowSyndicate's Arsenal

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What is ShadowSyndicate?

ShadowSyndicate, also known as Infra Storm, is a threat actor reportedly active since July 2022, working with various ransomware groups and affiliates of ransomware programs, such as Quantum, Nokoyawa, and ALPHV. This threat actor employs tools like Cobalt Strike, Sliver, IcedID, and Matanbuchus malware in its attacks. ShadowSyndicate utilizes the same SSH fingerprint (1ca4cbac895fc3bd12417b77fc6ed31d) on many of their servers—85 as of September 2023. At least 52 of these servers have been linked to the Cobalt Strike command and control (C2) framework [1].

What is RansomHub?

First observed following the FBI's takedown of ALPHV/BlackCat in December 2023, RansomHub quickly gained notoriety as a Ransomware-as-a-Service (RaaS) operator. RansomHub capitalized on the law enforcement’s disruption of the LockBit group’s operations in February 2024 to market themselves to potential affiliates who had previously relied on LockBit’s encryptors. RansomHub's success can be largely attributed to their aggressive recruitment on underground forums, leading to the absorption of ex-ALPHV and ex-LockBit affiliates. They were one of the most active ransomware operators in 2024, with approximately 500 victims reported since February, according to their Dedicated Leak Site (DLS) [2].

ShadowSyndicate and RansomHub

External researchers have reported that ShadowSyndicate had as many as seven different ransomware families in their arsenal between July 2022, and September 2023. Now, ShadowSyndicate appears to have added RansomHub’s their formidable stockpile, becoming an affiliate of the RaaS provider [1].

Darktrace’s analysis of ShadowSyndicate across its customer base indicates that the group has been leveraging RansomHub ransomware in multiple attacks in September and October 2024. ShadowSyndicate likely shifted to using RansomHub due to the lucrative rates offered by this RaaS provider, with affiliates receiving up to 90% of the ransom—significantly higher than the general market rate of 70-80% [3].

In many instances where encryption was observed, ransom notes with the naming pattern “README_[a-zA-Z0-9]{6}.txt” were written to affected devices. The content of these ransom notes threatened to release stolen confidential data via RansomHub’s DLS unless a ransom was paid. During these attacks, data exfiltration activity to external endpoints using the SSH protocol was observed. The external endpoints to which the data was transferred were found to coincide with servers previously associated with ShadowSyndicate activity.

Darktrace’s coverage of ShadowSyndicate and RansomHub

Darktrace’s Threat Research team identified high-confidence indicators of compromise (IoCs) linked to the ShadowSyndicate group deploying RansomHub. The investigation revealed four separate incidents impacting Darktrace customers across various sectors, including education, manufacturing, and social services. In the investigated cases, multiple stages of the kill chain were observed, starting with initial internal reconnaissance and leading to eventual file encryption and data exfiltration.

Attack Overview

Timeline attack overview of ransomhub ransomware

Internal Reconnaissance

The first observed stage of ShadowSyndicate attacks involved devices making multiple internal connection attempts to other internal devices over key ports, suggesting network scanning and enumeration activity. In this initial phase of the attack, the threat actor gathers critical details and information by scanning the network for open ports that might be potentially exploitable. In cases observed by Darktrace affected devices were typically seen attempting to connect to other internal locations over TCP ports including 22, 445 and 3389.

C2 Communication and Data Exfiltration

In most of the RansomHub cases investigated by Darktrace, unusual connections to endpoints associated with Splashtop, a remote desktop access software, were observed briefly before outbound SSH connections were identified.

Following this, Darktrace detected outbound SSH connections to the external IP address 46.161.27[.]151 using WinSCP, an open-source SSH client for Windows used for secure file transfer. The Cybersecurity and Infrastructure Security Agency (CISA) identified this IP address as malicious and associated it with ShadowSyndicate’s C2 infrastructure [4]. During connections to this IP, multiple gigabytes of data were exfiltrated from customer networks via SSH.

Data exfiltration attempts were consistent across investigated cases; however, the method of egress varied from one attack to another, as one would expect with a RaaS strain being employed by different affiliates. In addition to transfers to ShadowSyndicate’s infrastructure, threat actors were also observed transferring data to the cloud storage and file transfer service, MEGA, via HTTP connections using the ‘rclone’ user agent – a command-line program used to manage files on cloud storage. In another case, data exfiltration activity occurred over port 443, utilizing SSL connections.

Lateral Movement

In investigated incidents, lateral movement activity began shortly after C2 communications were established. In one case, Darktrace identified the unusual use of a new administrative credential which was quickly followed up with multiple suspicious executable file writes to other internal devices on the network.

The filenames for this executable followed the regex naming convention “[a-zA-Z]{6}.exe”, with two observed examples being “bWqQUx.exe” and “sdtMfs.exe”.

Cyber AI Analyst Investigation Process for the SMB Writes of Suspicious Files to Multiple Devices' incident.
Figure 1: Cyber AI Analyst Investigation Process for the SMB Writes of Suspicious Files to Multiple Devices' incident.

Additionally, script files such as “Defeat-Defender2.bat”, “Share.bat”, and “def.bat” were also seen written over SMB, suggesting that threat actors were trying to evade network defenses and detection by antivirus software like Microsoft Defender.

File Encryption

Among the three cases where file encryption activity was observed, file names were changed by adding an extension following the regex format “.[a-zA-Z0-9]{6}”. Ransom notes with a similar naming convention, “README_[a-zA-Z0-9]{6}.txt”, were written to each share. While the content of the ransom notes differed slightly in each case, most contained similar text. Clear indicators in the body of the ransom notes pointed to the use of RansomHub ransomware in these attacks. As is increasingly the case, threat actors employed double extortion tactics, threatening to leak confidential data if the ransom was not paid. Like most ransomware, RansomHub included TOR site links for communication between its "customer service team" and the target.

Figure 2: The graph shows the behavior of a device with encryption activity, using the “SMB Sustained Mimetype Conversion” and “Unusual Activity Events” metrics over three weeks.

Since Darktrace’s Autonomous Response capability was not enabled during the compromise, the ransomware attack succeeded in its objective. However, Darktrace’s Cyber AI Analyst provided comprehensive coverage of the kill chain, enabling the customer to quickly identify affected devices and initiate remediation.

Figure 3: Cyber AI Analyst panel showing the critical incidents of the affected device from one of the cases investigated.

In lieu of Autonomous Response being active on the networks, Darktrace was able to suggest a variety of manual response actions intended to contain the compromise and prevent further malicious activity. Had Autonomous Response been enabled at the time of the attack, these actions would have been quickly applied without any human interaction, potentially halting the ransomware attack earlier in the kill chain.

Figure 4: A list of suggested Autonomous Response actions on the affected devices."

Conclusion

The Darktrace Threat Research team has noted a surge in attacks by the ShadowSyndicate group using RansomHub’s RaaS of late. RaaS has become increasingly popular across the threat landscape due to its ease of access to malware and script execution. As more individual threat actors adopt RaaS, security teams are struggling to defend against the increasing number of opportunistic attacks.

For customers subscribed to Darktrace’s Security Operations Center (SOC) services, the Analyst team promptly investigated detections of the aforementioned unusual and anomalous activities in the initial infection phases. Multiple alerts were raised via Darktrace’s Managed Threat Detection to warn customers of active ransomware incidents. By emphasizing anomaly-based detection and response, Darktrace can effectively identify devices affected by ransomware and take action against emerging activity, minimizing disruption and impact on customer networks.

Credit to Kwa Qing Hong (Senior Cyber Analyst and Deputy Analyst Team Lead, Singapore) and Signe Zahark (Principal Cyber Analyst, Japan)

Appendices

Darktrace Model Detections

Antigena Models / Autonomous Response:

Antigena / Network / Insider Threat / Antigena Network Scan Block

Antigena / Network / Insider Threat / Antigena SMB Enumeration Block

Antigena / Network / Insider Threat / Antigena Internal Anomalous File Activity

Antigena / Network / Insider Threat / Antigena Large Data Volume Outbound Block

Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block

Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block

Antigena / Network / Significant Anomaly / Antigena Controlled and Model Breach

Antigena / Network / Significant Anomaly / Antigena Significant Server Anomaly Block

Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Server Block

Antigena / Network / External Threat / Antigena Suspicious Activity Block

Antigena / Network / External Threat / Antigena Suspicious File Pattern of Life Block

Antigena / Network / External Threat / Antigena File then New Outbound Block


Network Reconnaissance:

Device / Network Scan

Device / ICMP Address Scan

Device / RDP Scan
Device / Anomalous LDAP Root Searches
Anomalous Connection / SMB Enumeration
Device / Spike in LDAP Activity

C2:

Enhanced Monitoring - Device / Lateral Movement and C2 Activity

Enhanced Monitoring - Device / Initial Breach Chain Compromise

Enhanced Monitoring - Compromise / Suspicious File and C2

Compliance / Remote Management Tool On Server

Anomalous Connection / Outbound SSH to Unusual Port


External Data Transfer:

Enhanced Monitoring - Unusual Activity / Enhanced Unusual External Data Transfer

Unusual Activity / Unusual External Data Transfer

Anomalous Connection / Data Sent to Rare Domain

Unusual Activity / Unusual External Data to New Endpoint

Compliance / SSH to Rare External Destination

Anomalous Connection / Application Protocol on Uncommon Port

Enhanced Monitoring - Anomalous File / Numeric File Download

Anomalous File / New User Agent Followed By Numeric File Download

Anomalous Server Activity / Outgoing from Server

Device / Large Number of Connections to New Endpoints

Anomalous Connection / Multiple HTTP POSTs to Rare Hostname

Anomalous Connection / Uncommon 1 GiB Outbound

Lateral Movement:

User / New Admin Credentials on Server

Anomalous Connection / New or Uncommon Service Control

Anomalous Connection / High Volume of New or Uncommon Service Control

Anomalous File / Internal / Executable Uploaded to DC

Anomalous Connection / Suspicious Activity On High Risk Device

File Encryption:

Compliance / SMB Drive Write

Anomalous File / Internal / Additional Extension Appended to SMB File

Compromise / Ransomware / Possible Ransom Note Write

Anomalous Connection / Suspicious Read Write Ratio

List of Indicators of Compromise (IoCs)

IoC - Type - Description + Confidence

83.97.73[.]198 - IP - Data exfiltration endpoint

108.181.182[.]143 - IP - Data exfiltration endpoint

46.161.27[.]151 - IP - Data exfiltration endpoint

185.65.212[.]164 - IP - Data exfiltration endpoint

66[.]203.125.21 - IP - MEGA endpoint used for data exfiltration

89[.]44.168.207 - IP - MEGA endpoint used for data exfiltration

185[.]206.24.31 - IP - MEGA endpoint used for data exfiltration

31[.]216.148.33 - IP - MEGA endpoint used for data exfiltration

104.226.39[.]18 - IP - C2 endpoint

103.253.40[.]87 - IP - C2 endpoint

*.relay.splashtop[.]com - Hostname - C2 & data exfiltration endpoint

gfs***n***.userstorage.mega[.]co.nz - Hostname - MEGA endpoint used for data exfiltration

w.api.mega[.]co.nz - Hostname - MEGA endpoint used for data exfiltration

ams-rb9a-ss.ams.efscloud[.]net - Hostname - Data exfiltration endpoint

MITRE ATT&CK Mapping

Tactic - Technqiue

RECONNAISSANCE – T1592.004 Client Configurations

RECONNAISSANCE – T1590.005 IP Addresses

RECONNAISSANCE – T1595.001 Scanning IP Blocks

RECONNAISSANCE – T1595.002 Vulnerability Scanning

DISCOVERY – T1046 Network Service Scanning

DISCOVERY – T1018 Remote System Discovery

DISCOVERY – T1083 File and Directory Discovery
INITIAL ACCESS - T1189 Drive-by Compromise

INITIAL ACCESS - T1190 Exploit Public-Facing Application

COMMAND AND CONTROL - T1001 Data Obfuscation

COMMAND AND CONTROL - T1071 Application Layer Protocol

COMMAND AND CONTROL - T1071.001 Web Protocols

COMMAND AND CONTROL - T1573.001 Symmetric Cryptography

COMMAND AND CONTROL - T1571 Non-Standard Port

DEFENSE EVASION – T1078 Valid Accounts

DEFENSE EVASION – T1550.002 Pass the Hash

LATERAL MOVEMENT - T1021.004 SSH

LATERAL MOVEMENT – T1080 Taint Shared Content

LATERAL MOVEMENT – T1570 Lateral Tool Transfer

LATERAL MOVEMENT – T1021.002 SMB/Windows Admin Shares

COLLECTION - T1185 Man in the Browser

EXFILTRATION - T1041 Exfiltration Over C2 Channel

EXFILTRATION - T1567.002 Exfiltration to Cloud Storage

EXFILTRATION - T1029 Scheduled Transfer

IMPACT – T1486 Data Encrypted for Impact

References

1.     https://www.group-ib.com/blog/shadowsyndicate-raas/

2.     https://www.techtarget.com/searchsecurity/news/366617096/ESET-RansomHub-most-active-ransomware-group-in-H2-2024

3.     https://cyberint.com/blog/research/ransomhub-the-new-kid-on-the-block-to-know/

4.     https://www.cisa.gov/sites/default/files/2024-05/AA24-131A.stix_.xml

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About the author
Qing Hong Kwa
Senior Cyber Analyst and Deputy Analyst Team Lead, Singapore
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