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January 30, 2023

Qakbot Resurgence in the Cyber Landscape

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30
Jan 2023
Stay informed on the evolving threat Qakbot. Protect yourself from the Qakbot resurgence! Learn more from our Darktrace AI Cybersecurity experts!

In June 2022, Darktrace observed a surge in Qakbot infections across its client base. The detected Qakbot infections, which in some cases led to the delivery of secondary payloads such as Cobalt Strike and Dark VNC, were initiated through novel delivery methods birthed from Microsoft’s default blocking of XL4 and VBA macros in early 2022 [1]/[2]/[3]/[4] and from the public disclosure in May 2022 [5] of the critical Follina vulnerability (CVE-2022-30190) in Microsoft Support Diagnostic Tool (MSDT). Despite the changes made to Qakbot’s delivery methods, Qakbot infections still inevitably resulted in unusual patterns of network activity. In this blog, we will provide details of these network activities, along with Darktrace/Network’s coverage of them. 

Qakbot Background 

Qakbot emerged in 2007 as a banking trojan designed to steal sensitive data such as banking credentials.  Since then, Qakbot has developed into a highly modular triple-threat powerhouse used to not only steal information, but to also drop malicious payloads and to serve as a backdoor. The malware is also versatile, with its delivery methods regularly changing in response to the changing threat landscape.  

Threat actors deliver Qakbot through email-based delivery methods. In the first half of 2022, Microsoft started rolling out versions of Office which block XL4 and VBA macros by default. Prior to this change, Qakbot email campaigns typically consisted in the spreading of deceitful emails with Office attachments containing malicious macros.  Opening these attachments and then enabling the macros within them would lead users’ devices to install Qakbot.  

Actors who deliver Qakbot onto users’ devices may either sell their access to other actors, or they may leverage Qakbot’s capabilities to pursue their own objectives [6]. A common objective of actors that use Qakbot is to drop Cobalt Strike beacons onto infected systems. Actors will then leverage the interactive access provided by Cobalt Strike to conduct extensive reconnaissance and lateral movement activities in preparation for widespread ransomware deployment. Qakbot’s close ties to ransomware activity, along with its modularity and versatility, make the malware a significant threat to organisations’ digital environments.

Activity Details and Qakbot Delivery Methods

During the month of June, variationsof the following pattern of network activity were observed in several client networks:

1.     User’s device contacts an email service such as outlook.office[.]com or mail.google[.]com

2.     User’s device makes an HTTP GET request to 185.234.247[.]119 with an Office user-agent string and a ‘/123.RES' target URI. The request is responded to with an HTML file containing a exploit for the Follina vulnerability (CVE-2022-30190)

3.     User’s device makes an HTTP GET request with a cURL User-Agent string and a target URI ending in ‘.dat’ to an unusual external endpoint. The request is responded to with a Qakbot DLL sample

4.     User’s device contacts Qakbot Command and Control servers over ports such as 443, 995, 2222, and 32101

In some cases, only steps 1 and 4 were seen, and in other cases, only steps 1, 3, and 4 were seen. The different variations of the pattern correspond to different Qakbot delivery methods.

Figure 1: Geographic distribution of Darktrace clients affected by Qakbot

Qakbot is known to be delivered via malicious email attachments [7]. The Qakbot infections observed across Darktrace’s client base during June were likely initiated through HTML smuggling — a method which consists in embedding malicious code into HTML attachments. Based on open-source reporting [8]-[14] and on observed patterns of network traffic, we assess with moderate to high confidence that the Qakbot infections observed across Darktrace’s client base during June 2022 were initiated via one of the following three methods:

  • User opens HTML attachment which drops a ZIP file on their device. ZIP file contains a LNK file, which when opened, causes the user's device to make an external HTTP GET request with a cURL User-Agent string and a '.dat' target URI. If successful, the HTTP GET request is responded to with a Qakbot DLL.
  • User opens HTML attachment which drops a ZIP file on their device. ZIP file contains a docx file, which when opened, causes the user's device to make an HTTP GET request to 185.234.247[.]119 with an Office user-agent string and a ‘/123.RES' target URI. If successful, the HTTP GET request is responded to with an HTML file containing a Follina exploit. The Follina exploit causes the user's device to make an external HTTP GET with a '.dat' target URI. If successful, the HTTP GET request is responded to with a Qakbot DL.
  • User opens HTML attachment which drops a ZIP file on their device. ZIP file contains a Qakbot DLL and a LNK file, which when opened, causes the DLL to run.

The usage of these delivery methods illustrate how threat actors are adopting to a post-macro world [4], with their malware delivery techniques shifting from usage of macros-embedding Office documents to usage of container files, Windows Shortcut (LNK) files, and exploits for novel vulnerabilities. 

The Qakbot infections observed across Darktrace’s client base did not only vary in terms of their delivery methods — they also differed in terms of their follow-up activities. In some cases, no follow-up activities were observed. In other cases, however, actors were seen leveraging Qakbot to exfiltrate data and to deliver follow-up payloads such as Cobalt Strike and Dark VNC.  These follow-up activities were likely preparation for the deployment of ransomware. Darktrace’s early detection of Qakbot activity within client environments enabled security teams to take actions which likely prevented the deployment of ransomware. 

Darktrace Coverage 

Users’ interactions with malicious email attachments typically resulted in their devices making cURL HTTP GET requests with empty Host headers and target URIs ending in ‘.dat’ (such as as ‘/24736.dat’ and ‘/noFindThem.dat’) to rare, external endpoints. In cases where the Follina vulnerability is believed to have been exploited, users’ devices were seen making HTTP GET requests to 185.234.247[.]119 with a Microsoft Office User-Agent string before making cURL HTTP GET requests. The following Darktrace DETECT/Network models typically breached as a result of these HTTP activities:

  • Device / New User Agent
  • Anomalous Connection / New User Agent to IP Without Hostname
  • Device / New User Agent and New IP
  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Numeric Exe Download 

These DETECT models were able to capture the unusual usage of Office and cURL User-Agent strings on affected devices, as well as the downloads of the Qakbot DLL from rare external endpoints. These models look for unusual activity that falls outside a device’s usual pattern of behavior rather than for activity involving User-Agent strings, URIs, files, and external IPs which are known to be malicious.

When enabled, Darktrace RESPOND/Network autonomously intervened, taking actions such as ‘Enforce group pattern of life’ and ‘Block connections’ to quickly intercept connections to Qakbot infrastructure. 

Figure 2: This ‘New User Agent to IP Without Hostname’ model breach highlights an example of Darktrace’s detection of a device attempting to download a file containing a Follina exploit
Figure 3: This ‘New User Agent to IP Without Hostname’ model breach highlights an example of Darktrace’s detection of a device attempting to download Qakbot
Figure 4: The Event Log for an infected device highlights the moment a connection to the endpoint outlook.office365[.]com was made. This was followed by an executable file transfer detection and use of a new User-Agent, curl/7.9.1

After installing Qakbot, users’ devices started making connections to Command and Control (C2) endpoints over ports such as 443, 22, 990, 995, 1194, 2222, 2078, 32101. Cobalt Strike and Dark VNC may have been delivered over some of these C2 connections, as evidenced by subsequent connections to endpoints associated with Cobalt Strike and Dark VNC. These C2 activities typically caused the following Darktrace DETECT/Network models to breach: 

  • Anomalous Connection / Application Protocol on Uncommon Port
  • Anomalous Connection / Multiple Connections to New External TCP Port
  • Compromise / Suspicious Beaconing Behavior
  • Anomalous Connection / Multiple Failed Connections to Rare Endpoint
  • Compromise / Large Number of Suspicious Successful Connections
  • Compromise / Sustained SSL or HTTP Increase
  • Compromise / SSL or HTTP Beacon
  • Anomalous Connection / Rare External SSL Self-Signed
  • Anomalous Connection / Anomalous SSL without SNI to New External
  • Compromise / SSL Beaconing to Rare Destination
  • Compromise / Suspicious TLS Beaconing To Rare External
  • Compromise / Slow Beaconing Activity To External Rare
Figure 5: This Device Event Log illustrates the Command and Control activity displayed by a Qakbot-infected device

The Darktrace DETECT/Network models which detected these C2 activities do not look for devices making connections to known, malicious endpoints. Rather, they look for devices deviating from their ordinary patterns of activity, making connections to external endpoints which internal devices do not usually connect to, over ports which devices do not normally connect over. 

In some cases, actors were seen exfiltrating data from Qakbot-infected systems and dropping Cobalt Strike in order to conduct extensive discovery. These exfiltration activities typically caused the following models to breach:

  • Anomalous Connection / Data Sent to Rare Domain
  • Unusual Activity / Enhanced Unusual External Data Transfer
  • Anomalous Connection / Uncommon 1 GiB Outbound
  • Anomalous Connection / Low and Slow Exfiltration to IP
  • Unusual Activity / Unusual External Data to New Endpoints

The reconnaissance and brute-force activities carried out by actors typically resulted in breaches of the following models:

  • Device / ICMP Address Scan
  • Device / Network Scan
  • Anomalous Connection / SMB Enumeration
  • Device / New or Uncommon WMI Activity
  •  Unusual Activity / Possible RPC Recon Activity
  • Device / Possible SMB/NTLM Reconnaissance
  •  Device / SMB Lateral Movement
  •  Device / Increase in New RPC Services
  •  Device / Spike in LDAP Activity
  • Device / Possible SMB/NTLM Brute Force
  • Device / SMB Session Brute Force (Non-Admin)
  • Device / SMB Session Brute Force (Admin)
  • Device / Anomalous NTLM Brute Force

Conclusion

June 2022 saw Qakbot swiftly mould itself in response to Microsoft's default blocking of macros and the public disclosure of the Follina vulnerability. The evolution of the threat landscape in the first half of 2022 caused Qakbot to undergo changes in its delivery methods, shifting from delivery via macros-based methods to delivery via HTML smuggling methods. The effectiveness of these novel delivery methods where highlighted in Darktrace's client base, where large volumes of Qakbot infections were seen during June 2022. Leveraging Self-Learning AI, Darktrace DETECT/Network was able to detect the unusual network behaviors which inevitably resulted from these novel Qakbot infections. Given that the actors behind these Qakbot infections were likely seeking to deploy ransomware, these detections, along with Darktrace RESPOND/Network’s autonomous interventions, ultimately helped to protect affected Darktrace clients from significant business disruption.  

Appendices

List of IOCs

References

[1] https://techcommunity.microsoft.com/t5/excel-blog/excel-4-0-xlm-macros-now-restricted-by-default-for-customer/ba-p/3057905

[2] https://techcommunity.microsoft.com/t5/microsoft-365-blog/helping-users-stay-safe-blocking-internet-macros-by-default-in/ba-p/3071805

[3] https://learn.microsoft.com/en-us/deployoffice/security/internet-macros-blocked

[4] https://www.proofpoint.com/uk/blog/threat-insight/how-threat-actors-are-adapting-post-macro-world

[5] https://twitter.com/nao_sec/status/1530196847679401984

[6] https://www.microsoft.com/security/blog/2021/12/09/a-closer-look-at-qakbots-latest-building-blocks-and-how-to-knock-them-down/

[7] https://www.zscaler.com/blogs/security-research/rise-qakbot-attacks-traced-evolving-threat-techniques

[8] https://www.esentire.com/blog/resurgence-in-qakbot-malware-activity

[9] https://www.fortinet.com/blog/threat-research/new-variant-of-qakbot-spread-by-phishing-emails

[10] https://twitter.com/pr0xylife/status/1539320429281615872

[11] https://twitter.com/max_mal_/status/1534220832242819072

[12] https://twitter.com/1zrr4h/status/1534259727059787783?lang=en

[13] https://isc.sans.edu/diary/rss/28728

[14] https://www.fortiguard.com/threat-signal-report/4616/qakbot-delivered-through-cve-2022-30190-follina

Credit to:  Hanah Darley, Cambridge Analyst Team Lead and Head of Threat Research and Sam Lister, Senior Cyber Analyst

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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Nahisha Nobregas
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January 29, 2025

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Inside the SOC

Bytesize Security: Insider Threats in Google Workspace

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What is an insider threat?

An insider threat is a cyber risk originating from within an organization. These threats can involve actions such as an employee inadvertently clicking on a malicious link (e.g., a phishing email) or an employee with malicious intent conducting data exfiltration for corporate sabotage.

Insiders often exploit their knowledge and access to legitimate corporate tools, presenting a continuous risk to organizations. Defenders must protect their digital estate against threats from both within and outside the organization.

For example, in the summer of 2024, Darktrace / IDENTITY successfully detected a user in a customer environment attempting to steal sensitive data from a trusted Google Workspace service. Despite the use of a legitimate and compliant corporate tool, Darktrace identified anomalies in the user’s behavior that indicated malicious intent.

Attack overview: Insider threat

In June 2024, Darktrace detected unusual activity involving the Software-as-a-Service (SaaS) account of a former employee from a customer organization. This individual, who had recently left the company, was observed downloading a significant amount of data in the form of a “.INDD” file (an Adobe InDesign document typically used to create page layouts [1]) from Google Drive.

While the use of Google Drive and other Google Workspace platforms was not unexpected for this employee, Darktrace identified that the user had logged in from an unfamiliar and suspicious IPv6 address before initiating the download. This anomaly triggered a model alert in Darktrace / IDENTITY, flagging the activity as potentially malicious.

A Model Alert in Darktrace / IDENTITY showing the unusual “.INDD” file being downloaded from Google Workspace.
Figure 1: A Model Alert in Darktrace / IDENTITY showing the unusual “.INDD” file being downloaded from Google Workspace.

Following this detection, the customer reached out to Darktrace’s Security Operations Center (SOC) team via the Security Operations Support service for assistance in triaging and investigating the incident further. Darktrace’s SOC team conducted an in-depth investigation, enabling the customer to identify the exact moment of the file download, as well as the contents of the stolen documents. The customer later confirmed that the downloaded files contained sensitive corporate data, including customer details and payment information, likely intended for reuse or sharing with a new employer.

In this particular instance, Darktrace’s Autonomous Response capability was not active, allowing the malicious insider to successfully exfiltrate the files. If Autonomous Response had been enabled, Darktrace would have immediately acted upon detecting the login from an unusual (in this case 100% rare) location by logging out and disabling the SaaS user. This would have provided the customer with the necessary time to review the activity and verify whether the user was authorized to access their SaaS environments.

Conclusion

Insider threats pose a significant challenge for traditional security tools as they involve internal users who are expected to access SaaS platforms. These insiders have preexisting knowledge of the environment, sensitive data, and how to make their activities appear normal, as seen in this case with the use of Google Workspace. This familiarity allows them to avoid having to use more easily detectable intrusion methods like phishing campaigns.

Darktrace’s anomaly detection capabilities, which focus on identifying unusual activity rather than relying on specific rules and signatures, enable it to effectively detect deviations from a user’s expected behavior. For instance, an unusual login from a new location, as in this example, can be flagged even if the subsequent malicious activity appears innocuous due to the use of a trusted application like Google Drive.

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

Appendices

Darktrace Model Detections

SaaS / Resource::Unusual Download Of Externally Shared Google Workspace File

References

[1]https://www.adobe.com/creativecloud/file-types/image/vector/indd-file.html

MITRE ATT&CK Mapping

Technqiue – Tactic – ID

Data from Cloud Storage Object – COLLECTION -T1530

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About the author
Vivek Rajan
Cyber Analyst

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January 28, 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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