Blog
/

Thought Leadership

/
June 7, 2021

When Cyber-Attacks Become Ransomware-as-a-Service

Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
07
Jun 2021
Cyber attacks have occurred since the early days of the Internet. They can be extremely unpredictable. Learn about the dangers and unintended consequences!

In 1988, a Harvard graduate began an experiment to see how many computers were connected to the Internet. 24 hours later, 10% of all computers around the world had been taken down and the damages soared into the millions. Robert Tappan Morris had inadvertently created the first ever computer worm.

Once Morris realized the speed at which his program was replicating, he tried to send instructions to the victims to dismantle the worm and curb the attack. But it was too late. He was indicted one year later and faced fines of over $10,000.

Fast forward to the present day, and we’re facing the most recent example of a cyber-threat miscalculation, or a criminal group that simply did not understand the full impact their attack would have. The DarkSide ransomware group most likely only intended to hit the IT system and corporate business operations of Colonial Pipeline and underestimated the full impact the malware would have. The consequences were disastrous, halting the supply of fuel across the East Coast, leading to gas shortages, hoarding, and spikes in gasoline prices around the world.

In an apparent show of social responsibility, the DarkSide group issued a seemingly heartfelt apology for the attack on social media:

We are apolitical, we do not participate in geopolitics, do not need to tie us with a defined government and look for other our motives. From today, we introduce moderation and check each company that our partners want to encrypt to avoid social consequences in the future.

The motivation behind this statement is clear: self-preservation. The aftermath of the attack affected not only Colonial Pipeline but the DarkSide group themselves. They fell into the direct firing line of the full force of the US government, as well as becoming pariahs among other criminal groups for the attention they have drawn. It also appears they lost whatever formal or informal state supervision or protection they may have held.

As a result of the blowback and possible direct actions against them and their operating infrastructure, in less than a week, DarkSide announced that they would close their operations for good. They could however resurface under a different name, or join another group, if allowed in.

Misjudging the impact and collateral damage of a cyber-attack can lead to a range of unintended ramifications, from a cyber-crime group feeling increased heat from law enforcement to a nation state escalating a conflict greater than they intended.

It is for this reason that many ransomware groups historically have tended to keep their affairs under the radar. Over 70% of ransomware attacks target SMBs. Unfortunately, while many cyber-crime groups pledge to avoid larger bodies like hospitals and critical infrastructure, the allure of fast payouts for record-breaking ransoms has led to the healthcare sector, even vaccine efforts, being a heavy target for ransomware actors.

Following the incident at Colonial Pipeline, and no doubt in the fear of moving up the FBI’s Most Wanted list, a major Ransomware-as-a-Service (RaaS) group, REvil, announced the following policy:

  1. Work in the social sector (health care, educational institutions) is prohibited;
  2. It is forbidden to work on the gov-sector (state) of any country.

Organized cyber-crime groups often stress that they are apolitical and motivated solely by financial gain.

But when the boat is pushed too far, attacks can easily spill over into geopolitical tensions, encouraging governments to issue executive orders and pushing cyber-threats into the headlines – all bad business for criminal groups. And if a threat actor gets in over their head, they either need to lay low and rebrand in what is known as an ‘exit scam’, as ransomware groups such as Maze and Jokeroo have done in the past, or they’re shut down completely, as seen in the disruption of the Emotet botnet at the beginning of this year.

The effects of a cyber-attack are becoming increasingly difficult to predict and control. The reason for this is twofold. The first is this idea of interconnectivity. We live in a digitized world which is so interlinked that an attack on one server can have global consequences, whether that’s reverberations down the supply chain, IT converging with OT, or a cyber-threat against one country affecting the world.

More isolated than federal bodies, the private sector will most often take the brunt of this collateral damage. Just take NotPetya – where a targeted attack against Ukrainian infrastructure went into the wild paralyzing factories across the globe and costing shipping company Maersk $300 million.

The second reason is easier access to more sophisticated tools. The commercialization of cyber-crime has enabled less advanced actors to rent state-of-the-art malware and launch campaigns with speed and with ease. In fact, the Colonial Pipeline attack was likely orchestrated by an affiliate who had paid for the DarkSide malware. This makes it far more challenging to monitor who is being targeted. When it comes to RaaS, even the developers probably do not know for certain how their malware will be used.

When preparing any kind of cyber-attack, the intelligence that an actor has going into the target environment is rarely 100%. If the intention is to impact a single component of a bank, for example, but the attacker fails to realize that a nearby hospital relies on that same electrical grid, the situation can escalate very quickly. And when it’s a low-skilled attacker with little regard or understanding of what a high-powered tool can do, miscalculations become alarmingly easy.

As far as we know, DarkSide itself was not a state-sponsored APT, merely a private criminal franchise. Yet they advertised their ransomware as the fastest in the world and managed to pull off one of the most disruptive critical infrastructure cyber-attacks of all time. As history has shown, from the Morris worm to Colonial Pipeline, when malware is fast and designed to propagate, it is unpredictable. It is nearly impossible to put a highly destructive genie back in the bottle.

As automation and AI-powered attacks become a reality, these trends will increase exponentially and transform the threat landscape. Ransomware is no longer a human-scalable problem. Organizational resilience depends not on throwing more people into the mix, or even upskilling existing teams – machine-speed attacks need a machine-speed response which can adapt as fast as an attack propagates. Thwarting ransomware is both a board-level issue and a national security concern. As such, self-learning AI technology proves critical in tackling the unpredictability and speed of the threats of today, and of tomorrow.

Thanks to Lucas Marsden-Smedley for his contributions.

Learn more about how Darktrace can detect attacks like Colonial Pipeline

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.
Author
Marcus Fowler
CEO of Darktrace Federal and SVP of Strategic Engagements and Threats

Marcus Fowler is the CEO of Darktrace Federal, working to help defend the U.S. Department of Defense (DoD), the Intelligence Community (IC), and Federal Civilian Agencies against cyber disruption and strengthen their defenses with complete AI-powered cybersecurity solutions. Marcus is a seasoned cybersecurity professional, with expertise on emerging and next generation cyber threats, trends, and conflicts. Marcus also serves as the SVP of Strategic Engagements and Threats at Darktrace, working closely with senior security leaders across industries on innovative cybersecurity strategy and business resilience.  

Previously, Marcus spent 15 years at the Central Intelligence Agency developing global cyber operations and technical strategies, leading cyber efforts with various US Intelligence Community elements and global partners. Prior to serving at the CIA, Marcus was an officer in the United States Marine Corps. Marcus has an engineering degree from the United States Naval Academy and a master's degree in international security studies from The Fletcher School. He also completed Harvard Business School’s Executive Education Advanced Management Program.

Book a 1-1 meeting with one of our experts
Share this article

More in this series

No items found.

Blog

/

September 24, 2024

/

Inside the SOC

Lifting the Fog: Darktrace’s Investigation into Fog Ransomware

Default blog imageDefault blog image

Introduction to Fog Ransomware

As ransomware attacks continue to be launched at an alarming rate, Darktrace’s Threat Research team has identified that familiar strains like Akira, LockBit, and BlackBasta remain among the most prevalent threats impacting its customers, as reported in the First 6: Half-Year Threat Report 2024. Despite efforts by law agencies, like dismantling the infrastructure of cybercriminals and shutting down their operations [2], these groups continue to adapt and evolve.

As such, it is unsurprising that new ransomware variants are regularly being created and launched to get round law enforcement agencies and increasingly adept security teams. One recent example of this is Fog ransomware.

What is Fog ransomware?

Fog ransomware is strain that first appeared in the wild in early May 2024 and has been observed actively using compromised virtual private network (VPN) credentials to gain access to organization networks in the education sector in the United States.

Darktrace's detection of Fog Ransomware

In June 2024, Darktrace observed instances of Fog ransomware across multiple customer environments. The shortest time observed from initial access to file encryption in these attacks was just 2 hours, underscoring the alarming speed with which these threat actors can achieve their objectives.

Darktrace identified key activities typical of a ransomware kill chain, including enumeration, lateral movement, encryption, and data exfiltration. In most cases, Darktrace was able to successfully halt the progression Fog attacks in their early stages by applying Autonomous Response actions such as quarantining affected devices and blocking suspicious external connections.

To effectively illustrate the typical kill chain of Fog ransomware, this blog focuses on customer environments that did not have Darktrace’s Autonomous Response enabled. In these cases, the attack progressed unchecked and reached its intended objectives until the customer received Darktrace’s alerts and intervened.

Darktrace’s Coverage of Fog Ransomware

Initial Intrusion

After actors had successfully gained initial access into customer networks by exploiting compromised VPN credentials, Darktrace observed a series of suspicious activities, including file shares, enumeration and extensive scanning. In one case, a compromised domain controller was detected making outgoing NTLM authentication attempts to another internal device, which was subsequently used to establish RDP connections to a Windows server running Hyper-V.

Given that the source was a domain controller, the attacker could potentially relay the NTLM hash to obtain a domain admin Kerberos Ticket Granting Ticket (TGT). Additionally, incoming NTLM authentication attempts could be triggered by tools like Responder, and NTLM hashes used to encrypt challenge response authentication could be abused by offline brute-force attacks.

Darktrace also observed the use of a new administrative credential on one affected device, indicating that malicious actors were likely using compromised privileged credentials to conduct relay attacks.

Establish Command-and-Control Communication (C2)

In many instances of Fog ransomware investigated by Darktrace’s Threat Research team, devices were observed making regular connections to the remote access tool AnyDesk. This was exemplified by consistent communication with the endpoint “download[.]anydesk[.]com” via the URI “/AnyDesk.exe”. In other cases, Darktrace identified the use of another remote management tool, namely SplashTop, on customer servers.

In ransomware attacks, threat actors often use such legitimate remote access tools to establish command-and-control (C2) communication. The use of such services not only complicates the identification of malicious activities but also enables attackers to leverage existing infrastructure, rather than having to implement their own.

Internal Reconnaissance

Affected devices were subsequently observed making an unusual number of failed internal connections to other internal locations over ports such as 80 (HTTP), 3389 (RDP), 139 (NetBIOS) and 445 (SMB). This pattern of activity strongly indicated reconnaissance scanning behavior within affected networks. A further investigation into these HTTP connections revealed the URIs “/nice ports”/Trinity.txt.bak”, commonly associated with the use of the Nmap attack and reconnaissance tool.

Simultaneously, some devices were observed engaging in SMB actions targeting the IPC$ share and the named pipe “srvsvc” on internal devices. Such activity aligns with the typical SMB enumeration tactics, whereby attackers query the list of services running on a remote host using a NULL session, a method often employed to gather information on network resources and vulnerabilities.

Lateral Movement

As attackers attempted to move laterally through affected networks, Darktrace observed suspicious RDP activity between infected devices. Multiple RDP connections were established to new clients, using devices as pivots to propagate deeper into the networks, Following this, devices on multiple networks exhibited a high volume of SMB read and write activity, with internal share drive file names being appended with the “.flocked” extension – a clear sign of ransomware encryption. Around the same time, multiple “readme.txt” files were detected being distributed across affected networks, which were later identified as ransom notes.

Further analysis of the ransom note revealed that it contained an introduction to the Fog ransomware group, a summary of the encryption activity that had been carried out, and detailed instructions on how to communicate with the attackers and pay the ransom.

Packet capture (PCAP) of the ransom note file titled “readme.txt”.
Figure 1: Packet capture (PCAP) of the ransom note file titled “readme.txt”.

Data Exfiltration

In one of the cases of Fog ransomware, Darktrace’s Threat Research team observed potential data exfiltration involving the transfer of internal files to an unusual endpoint associated with the MEGA file storage service, “gfs302n515[.]userstorage[.]mega[.]co[.]nz”.

This exfiltration attempt suggests the use of double extortion tactics, where threat actors not only encrypt victim’s data but also exfiltrate it to threaten public exposure unless a ransom is paid. This often increases pressure on organizations as they face the risk of both data loss and reputational damage caused by the release of sensitive information.

Darktrace’s Cyber AI Analyst autonomously investigated what initially appeared to be unrelated events, linking them together to build a full picture of the Fog ransomware attack for customers’ security teams. Specifically, on affected networks Cyber AI Analyst identified and correlated unusual scanning activities, SMB writes, and file appendages that ultimately suggested file encryption.

Cyber AI Analyst’s analysis of encryption activity on one customer network.
Figure 2: Cyber AI Analyst’s analysis of encryption activity on one customer network.
Figure 3: Cyber AI Analysts breakdown of the investigation process between the linked incident events on one customer network.

Conclusion

As novel and fast-moving ransomware variants like Fog persist across the threat landscape, the time taken for from initial compromise to encryption has significantly decreased due to the enhanced skill craft and advanced malware of threat actors. This trend particularly impacts organizations in the education sector, who often have less robust cyber defenses and significant periods of time during which infrastructure is left unmanned, and are therefore more vulnerable to quick-profit attacks.

Traditional security methods may fall short against these sophisticated attacks, where stealthy actors evade detection by human-managed teams and tools. In these scenarios Darktrace’s AI-driven product suite is able to quickly detect and respond to the initial signs of compromise through autonomous analysis of any unusual emerging activity.

When Darktrace’s Autonomous Response capability was active, it swiftly mitigated emerging Fog ransomware threats by quarantining devices exhibiting malicious behavior to contain the attack and blocking the exfiltration of sensitive data, thus preventing customers from falling victim to double extortion attempts.

Credit to Qing Hong Kwa (Senior Cyber Analyst and Deputy Analyst Team Lead, Singapore) and Ryan Traill (Threat Content Lead)

Appendices

Darktrace Model Detections:

- Anomalous Server Activity::Anomalous External Activity from Critical Network Device

- Anomalous Connection::SMB Enumeration

- Anomalous Connection::Suspicious Read Write Ratio and Unusual SMB

- Anomalous Connection::Uncommon 1 GiB Outbound

- Anomalous File::Internal::Additional Extension Appended to SMB File

- Compliance::Possible Cleartext LDAP Authentication

- Compliance::Remote Management Tool On Server

- Compliance::SMB Drive Write

- Compromise::Ransomware::SMB Reads then Writes with Additional Extensions

- Compromise::Ransomware::Possible Ransom Note Write

- Compromise::Ransomware::Ransom or Offensive Words Written to SMB

- Device::Attack and Recon Tools

- User::New Admin Credentials on Client

- Unusual Activity::Anomalous SMB Move & Write

- Unusual Activity::Internal Data Transfer

- Unusual Activity::Unusual External Data Transfer

- Unusual Activity::Enhanced Unusual External Data Transfer

Darktrace Model Detections:

- Antigena::Network::External Threat::Antigena Suspicious File Block

- Antigena::Network::External Threat::Antigena Suspicious File Pattern of Life Block

- Antigena::Network::External Threat::Antigena File then New Outbound Block

- Antigena::Network::External Threat::Antigena Ransomware Block

- Antigena::Network::External Threat::Antigena Suspicious Activity Block

- Antigena::Network::Significant Anomaly::Antigena Controlled and Model Breach

- Antigena::Network::Significant Anomaly::Antigena Enhanced Monitoring from Server Block

- Antigena::Network::Significant Anomaly::Antigena Breaches Over Time Block

- Antigena::Network::Significant Anomaly::Antigena Significant Server Anomaly Block

- Antigena::Network::Insider Threat::Antigena Internal Data Transfer Block

- Antigena::Network::Insider Threat::Antigena Large Data Volume Outbound Block

- Antigena::Network::Insider Threat::Antigena SMB Enumeration Block

AI Analyst Incident Coverage

- Encryption of Files over SMB

- Scanning of Multiple Devices

- SMB Writes of Suspicious Files

MITRE ATT&CK Mapping

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

Data Obfuscation - COMMAND AND CONTROL - T1001

Remote System Discovery - DISCOVERY - T1018

SMB/Windows Admin Shares - LATERAL MOVEMENT - T1021.002 - T1021

Rename System Utilities - DEFENSE EVASION - T1036.003 - T1036

Network Sniffing - CREDENTIAL ACCESS, DISCOVERY - T1040

Exfiltration Over C2 Channel - EXFILTRATION - T1041

Data Staged - COLLECTION - T1074

Valid Accounts - DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS - T1078

Taint Shared Content - LATERAL MOVEMENT - T1080

File and Directory Discovery - DISCOVERY - T1083

Email Collection - COLLECTION - T1114

Automated Collection - COLLECTION - T1119

Network Share Discovery - DISCOVERY - T1135

Exploit Public-Facing Application - INITIAL ACCESS - T1190

Hardware Additions - INITIAL ACCESS - T1200

Remote Access Software - COMMAND AND CONTROL - T1219

Data Encrypted for Impact - IMPACT - T1486

Pass the Hash - DEFENSE EVASION, LATERAL MOVEMENT - T1550.002 - T1550

Exfiltration to Cloud Storage - EXFILTRATION - T1567.002 - T1567

Lateral Tool Transfer - LATERAL MOVEMENT - T1570

List of Indicators of Compromise (IoCs)

IoC – Type – Description

/AnyDesk.exe - Executable File - Remote Access Management Tool

gfs302n515[.]userstorage[.]mega[.]co[.]nz- Domain - Exfiltration Domain

*.flocked - Filename Extension - Fog Ransomware Extension

readme.txt - Text File - Fog Ransom Note

xql562evsy7njcsngacphcerzjfecwotdkobn3m4uxu2gtqh26newid[.]onion - Onion Domain - Threat Actor’s Communication Channel

References

[1] https://arcticwolf.com/resources/blog/lost-in-the-fog-a-new-ransomware-threat/

[2] https://intel471.com/blog/assessing-the-disruptions-of-ransomware-gangs

[3] https://www.pcrisk.com/removal-guides/30167-fog-ransomware

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

Blog

/

September 11, 2024

/

Inside the SOC

Decrypting the Matrix: How Darktrace Uncovered a KOK08 Ransomware Attack

Default blog imageDefault blog image

What is Matrix Ransomware?

Matrix is a ransomware family that first emerged in December 2016, mainly targeting small to medium-sized organizations across the globe in countries including the US, Belgium, Germany, Canada and the UK [1]. Although the reported number of Matrix ransomware attacks has remained relatively low in recent years, it has demonstrated ongoing development and gradual improvements to its tactics, techniques, and procedures (TTPs).

How does Matrix Ransomware work?

In earlier versions, Matrix utilized spam email campaigns, exploited Windows shortcuts, and deployed RIG exploit kits to gain initial access to target networks. However, as the threat landscape changed so did Matrix’s approach. Since 2018, Matrix has primarily shifted to brute-force attacks, targeting weak credentials on Windows machines accessible through firewalls. Attackers often exploit common and default credentials, such as “admin”, “password123”, or other unchanged default settings, particularly on systems with Remote Desktop Protocol (RDP) enabled [2] [3].

Darktrace observation of Matrix Ransomware tactics

In May 2024, Darktrace observed an instance of KOK08 ransomware, a specific strain of the Matrix ransomware family, in which some of these ongoing developments and evolutions were observed. Darktrace detected activity indicative of internal reconnaissance, lateral movement, data encryption and exfiltration, with the affected customer later confirming that credentials used for Virtual Private Network (VPN) access had been compromised and used as the initial attack vector.

Another significant tactic observed by Darktrace in this case was the exfiltration of data following encryption, a hallmark of double extortion. This method is employed by attacks to increase pressure on the targeted organization, demanding ransom not only for the decryption of files but also threatening to release the stolen data if their demands are not met. These stakes are particularly high for public sector entities, like the customer in question, as the exposure of sensitive information could result in severe reputational damage and legal consequences, making the pressure to comply even more intense.

Darktrace’s Coverage of Matrix Ransomware

Internal Reconnaissance and Lateral Movement

On May 23, 2024, Darktrace / NETWORK identified a device on the customer’s network making an unusually large number of internal connections to multiple internal devices. Darktrace recognized that this unusual behavior was indicative of internal scanning activity. The connectivity observed around the time of the incident indicated that the Nmap attack and reconnaissance tool was used, as evidenced by the presence of the URI “/nice ports, /Trinity.txt.bak”.

Although Nmap is a crucial tool for legitimate network administration and troubleshooting, it can also be exploited by malicious actors during the reconnaissance phase of the attack. This is a prime example of a ‘living off the land’ (LOTL) technique, where attackers use legitimate, pre-installed tools to carry out their objectives covertly. Despite this, Darktrace’s Self-Learning AI had been continually monitoring devices across the customers network and was able to identify this activity as a deviation from the device’s typical behavior patterns.

The ‘Device / Attack and Recon Tools’ model alert identifying the active usage of the attack and recon tool, Nmap.
Figure 1: The ‘Device / Attack and Recon Tools’ model alert identifying the active usage of the attack and recon tool, Nmap.
Figure 2: Cyber AI Analyst Investigation into the ‘Scanning of Multiple Devices' incident.

Darktrace subsequently observed a significant number of connection attempts using the RDP protocol on port 3389. As RDP typically requires authentication, multiple connection attempts like this often suggest the use of incorrect username and password combinations.

Given the unusual nature of the observed activity, Darktrace’s Autonomous Response capability would typically have intervened, taking actions such as blocking affected devices from making internal connections on a specific port or restricting connections to a particular device. However, Darktrace was not configured to take autonomous action on the customer’s network, and thus their security team would have had to manually apply any mitigative measures.

Later that day, the same device was observed attempting to connect to another internal location via port 445. This included binding to the server service (srvsvc) endpoint via DCE/RPC with the “NetrShareEnum” operation, which was likely being used to list available SMB shares on a device.

Over the following two days, it became clear that the attackers had compromised additional devices and were actively engaging in lateral movement. Darktrace detected two more devices conducting network scans using Nmap, while other devices were observed making extensive WMI requests to internal systems over DCE/RPC. Darktrace recognized that this activity likely represented a coordinated effort to map the customer’s network and identity further internal devices for exploitation.

Beyond identifying the individual events of the reconnaissance and lateral movement phases of this attack’s kill chain, Darktrace’s Cyber AI Analyst was able to connect and consolidate these activities into one comprehensive incident. This not only provided the customer with an overview of the attack, but also enabled them to track the attack’s progression with clarity.

Furthermore, Cyber AI Analyst added additional incidents and affected devices to the investigation in real-time as the attack unfolded. This dynamic capability ensured that the customer was always informed of the full scope of the attack. The streamlined incident consolidation and real-time updates saved valuable time and resources, enabling quicker, more informed decision-making during a critical response window.

Cyber AI Analyst timeline showing an overview of the scanning related activity, while also connecting the suspicious lateral movement activity.
Figure 3: Cyber AI Analyst timeline showing an overview of the scanning related activity, while also connecting the suspicious lateral movement activity.

File Encryption

On May 28, 2024, another device was observed connecting to another internal location over the SMB filesharing protocol and accessing multiple files with a suspicious extension that had never previously been observed on the network. This activity was a clear sign of ransomware infection, with the ransomware altering the files by adding the “KOK08@QQ[.]COM” email address at the beginning of the filename, followed by a specific pattern of characters. The string consistently followed a pattern of 8 characters (a mix of uppercase and lowercase letters and numbers), followed by a dash, and then another 8 characters. After this, the “.KOK08” extension was appended to each file [1][4].

Cyber AI Analyst Investigation Process for the 'Possible Encryption of Files over SMB' incident.
Figure 4: Cyber AI Analyst Investigation Process for the 'Possible Encryption of Files over SMB' incident.
Cyber AI Analyst Encryption Information identifying the ransomware encryption activity,
Figure 5: Cyber AI Analyst Encryption Information identifying the ransomware encryption activity.

Data Exfiltration

Shortly after the encryption event, another internal device on the network was observed uploading an unusually large amount of data to the rare external endpoint 38.91.107[.]81 via SSH. The timing of this activity strongly suggests that this exfiltration was part of a double extortion strategy. In this scenario, the attacker not only encrypts the target’s files but also threatens to leak the stolen data unless a ransom is paid, leveraging both the need for decryption and the fear of data exposure to maximize pressure on the victim.

The full impact of this double extortion tactic became evident around two months later when a ransomware group claimed possession of the stolen data and threatened to release it publicly. This development suggested that the initial Matrix ransomware attackers may have sold the exfiltrated data to a different group, which was now attempting to monetize it further, highlighting the ongoing risk and potential for exploitation long after the initial attack.

External data being transferred from one of the involved internal devices during and after the encryption took place.
Figure 6: External data being transferred from one of the involved internal devices during and after the encryption took place.

Unfortunately, because Darktrace’s Autonomous Response capability was not enabled at the time, the ransomware attack was able to escalate to the point of data encryption and exfiltration. However, Darktrace’s Security Operations Center (SOC) was still able to support the customer through the Security Operations Support service. This allowed the customer to engage directly with Darktrace’s expert analysts, who provided essential guidance for triaging and investigating the incident. The support from Darktrace’s SOC team not only ensured the customer had the necessary information to remediate the attack but also expedited the entire process, allowing their security team to quickly address the issue without diverting significant resources to the investigation.

Conclusion

In this Matrix ransomware attack on a Darktrace customer in the public sector, malicious actors demonstrated an elevated level of sophistication by leveraging compromised VPN credentials to gain initial access to the target network. Once inside, they exploited trusted tools like Nmap for network scanning and lateral movement to infiltrate deeper into the customer’s environment. The culmination of their efforts was the encryption of files, followed by data exfiltration via SSH, suggesting that Matrix actors were employing double extortion tactics where the attackers not only demanded a ransom for decryption but also threatened to leak sensitive information.

Despite the absence of Darktrace’s Autonomous Response at the time, its anomaly-based approach played a crucial role in detecting the subtle anomalies in device behavior across the network that signalled the compromise, even when malicious activity was disguised as legitimate.  By analyzing these deviations, Darktrace’s Cyber AI Analyst was able to identify and correlate the various stages of the Matrix ransomware attack, constructing a detailed timeline. This enabled the customer to fully understand the extent of the compromise and equipped them with the insights needed to effectively remediate the attack.

Credit to Christina Kreza (Cyber Analyst) and Ryan Traill (Threat Content Lead)

Appendices

Darktrace Model Detections

·       Device / Network Scan

·       Device / Attack and Recon Tools

·       Device / Possible SMB/NTLM Brute Force

·       Device / Suspicious SMB Scanning Activity

·       Device / New or Uncommon SMB Named Pipe

·       Device / Initial Breach Chain Compromise

·       Device / Multiple Lateral Movement Model Breaches

·       Device / Large Number of Model Breaches from Critical Network Device

·       Device / Multiple C2 Model Breaches

·       Device / Lateral Movement and C2 Activity

·       Anomalous Connection / SMB Enumeration

·       Anomalous Connection / New or Uncommon Service Control

·       Anomalous Connection / Multiple Connections to New External TCP Port

·       Anomalous Connection / Data Sent to Rare Domain

·       Anomalous Connection / Uncommon 1 GiB Outbound

·       Unusual Activity / Enhanced Unusual External Data Transfer

·       Unusual Activity / SMB Access Failures

·       Compromise / Ransomware / Suspicious SMB Activity

·       Compromise / Suspicious SSL Activity

List of Indicators of Compromise (IoCs)

·       .KOK08 -  File extension - Extension to encrypted files

·       [KOK08@QQ[.]COM] – Filename pattern – Prefix of the encrypted files

·       38.91.107[.]81 – IP address – Possible exfiltration endpoint

MITRE ATT&CK Mapping

·       Command and control – Application Layer Protocol – T1071

·       Command and control – Web Protocols – T1071.001

·       Credential Access – Password Guessing – T1110.001

·       Discovery – Network Service Scanning – T1046

·       Discovery – File and Directory Discovery – T1083

·       Discovery – Network Share Discovery – T1135

·       Discovery – Remote System Discovery – T1018

·       Exfiltration – Exfiltration Over C2 Channer – T1041

·       Initial Access – Drive-by Compromise – T1189

·       Initial Access – Hardware Additions – T1200

·       Lateral Movement – SMB/Windows Admin Shares – T1021.002

·       Reconnaissance – Scanning IP Blocks – T1595.001

References

[1] https://unit42.paloaltonetworks.com/matrix-ransomware/

[2] https://www.sophos.com/en-us/medialibrary/PDFs/technical-papers/sophoslabs-matrix-report.pdf

[3] https://cyberenso.jp/en/types-of-ransomware/matrix-ransomware/

[4] https://www.pcrisk.com/removal-guides/10728-matrix-ransomware

Continue reading
About the author
Christina Kreza
Cyber Analyst
Your data. Our AI.
Elevate your network security with Darktrace AI