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June 27, 2021

Post-Mortem Analysis of a SQL Server Exploit

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27
Jun 2021
Learn about the post-mortem analysis of a SQL Server exploit. Discover key insights and strategies to enhance your cybersecurity defenses.

While SaaS and IoT devices are increasingly popular vectors of intrusion, server-side attacks remain a serious threat to organizations worldwide. With sophisticated vulnerability scanning tools, attackers can now pinpoint security flaws in seconds, finding points of entry across the attack surface. Human security teams often struggle to keep pace with the constant wave of newly documented vulnerabilities and patches.

Darktrace recently stopped a targeted cyber-attack by an unknown attacker. After the initial entry, the attacker exploited an unpatched vulnerability (CVE-2020-0618), granting a low-privileged credential the ability to remotely execute code. This enabled the attacker to spread laterally and eventually establish a foothold in the system by creating a new user account.

The server-side attack cycle: authenticates user; scans network; infects three servers; downloads malware; c2 traffic; creates new user.

Figure 1: Overview of the server-side attack cycle.

This blog breaks down the intrusion and explores how Darktrace’s Autonomous Response technology took three surgical actions to halt the attacker’s movements.

Unknown threat actors exploit a vulnerability

Initial compromise

At a financial firm in Canada with around 3,000 devices, Cyber AI detected the use of a new credential, ‘parents’. The attacker used this credential to access the company’s internal environment through the VPN. From there, the credential authenticated to a desktop using NT LAN Manager (NTLM). No further suspicious activity was observed.

NTLM is a popular attack vector for cyber-criminals as it is vulnerable to multiple methods of compromise, including brute-force and ‘pass the hash’. The initial access to the credential could have been obtained via phishing before Darktrace had been deployed.

Figure 2: The credential was first observed on the device five days prior to reconnaissance. The attacker performed reconnaissance and lateral movement for two days, until the compromised devices were taken down.

Internal reconnaissance

Five days later, the ‘parents’ credential was seen logging onto the desktop. The desktop began scanning the network – over 80 internal IPs – on Port 443 and 445.

Shortly after the scan, the device used Nmap to attempt to establish SMBv1 sessions to 139 internal IPs, using guest / user credentials. 79 out of the 278 sessions were successful, all using the login.

Figure 3: New failed internal connections performed by an initially infected desktop, in a similar incident. The graph highlights a surge in failed internal connections and model breaches.

The network scan was the first stage after intrusion, enabling the attacker to find out which services were running, before looking for unpatched vulnerabilities.

Nmap has multiple built-in functionalities which are often exploited for reconnaissance and lateral movement. In this case, it was being used to establish the SMBv1 sessions to the domain controller, saving the attacker from having to initiate SMBv1 sessions with each destination one by one. SMBv1 has well-known vulnerabilities and best practice is to disable it where possible.

Lateral movement

The desktop began controlling services (svcctl endpoint) on a SQL server. It was observed both creating and starting services (CreateServiceW, StartServiceW).

The desktop then initiated an unencrypted HTTP connection to a SQL Reporting server. This was the first HTTP connection between the two devices and the first time the user agent had been seen on the device.

A packet capture of the connection reveals a POST that is seen in an exploit of CVE-2020-0613. This vulnerability is a deserialization issue, whereby the server mishandles carefully crafted page requests and allows low-privileged accounts to establish a reverse shell and remotely execute code on the server.

Figure 4: A partial PCAP of the HTTP connection. The traffic matches the CVE-2020-0618 exploit, which enables Remote Code Execution (RCE) in SQL Server Reporting Services (SSRS).

Most movements were seen in East-West traffic, with readily-available remote procedure call (RPC) methods. Such connections are abundant in systems. Without learning an organization’s ‘pattern of life’, it would have been near-impossible to highlight the malicious connections.

Cyber AI detected connections to the svcctl endpoint, via the DCE-RPC endpoint. This is called the 'service control' endpoint and is used to remotely control running processes on a device.

During the lateral movement from the desktop, the HTTP POST request revealed that the desktop was exploiting CVE-2020-0613. The attacker had managed to find and exploit an existing vulnerability which hadn’t been patched.

Darktrace was the only tool which alerted to the HTTP connection, revealing this underlying (and concluding) exploit. The AI determined that the user agent was unusual for the device and for the wider organization, and that the connection was highly anomalous. This connection would have gone otherwise amiss, since HTTP connections are common in most digital environments.

Because the attacker on the desktop used readily-available tools and protocols, such as Nmap, DCE-RPC, and HTTP, the device went undetected by all the other cyber defenses. However, Cyber AI noticed multiple scanning and lateral movement anomalies – triggering high-fidelity detections which would have been alerted to with Proactive Threat Notifications.

Command and control (C2) communication

The next day, the attacker connected to an SNMP server from the VPN. The connection used the ‘parents’ RDP cookie.

Immediately after the RDP connection began, the server connected to Pastebin and downloaded small amounts of encrypted data. Pastebin was likely being used as a vector to drop malicious scripts onto the device.

The SNMP server then started controlling services (svcttl) on the SQL server: again, creating and starting services.

Following this, both the SQL server and the SNMP server made a high volume of SSL connections to a rare external domain. One upload to the destination was around 21 MB, but otherwise the connections were mostly the same packet size. This, among other factors, indicated that the destination was being used as a C2 server.

Figure 5: Example Cyber AI Analyst investigation into beaconing activity by a SQL server.

With just one compromised credential, the attacker was now connecting to the VPN and infecting multiple servers on the company’s internal network.

The attacker dropped scripts onto the host using Pastebin. Darktrace alerted on this because Pastebin is highly rare for the organization. In fact, these connections were the first time it had been seen. Most security tools would miss this, as Pastebin is a legitimate site and would not be blocked by open-source intelligence (OSINT).

Even if a lesser-known Pastebin alternative had been used – say, in an environment where Pastebin was blocked on the firewall but the alternative not — Darktrace would have picked up on it in exactly the same way.

The C2 beaconing endpoint – dropbox16[.]com – has no OSINT information available online. The connections were on Port 443 and nothing about them was notable except from their rarity on the company’s system. Darktrace sent alerts because of its high rarity, rather than relying on known signatures.

Achieve persistence

After another Pastebin pull, the attacker attempted to maintain a greater foothold and escalate privileges by creating a new user using the SamrCreateUser2InDomain operation (endpoint: samr).

To establish persistence, the attacker now created a new user through a specific DCE-RPC command to the domain controller. This was highly unusual activity for the device, and was given a 100% anomaly score for ‘New or Uncommon Occurrence’.

If Darktrace had not alerted on this activity, the attacker would have continued to access files and make further inroads in the company, extracting sensitive data and potentially installing ransomware. This could have led to sensitive data loss, reputational damage, and financial losses for the company.

The value of Autonomous Response

The organization had Antigena in passive mode, so although it was not able to respond autonomously, we have visibility into the actions that it would have taken.

Antigena would have taken three actions on the initially infected desktop, as shown in the table below. The actions would have taken effect immediately in response to the first scan and the first service control requests.

During the two days of reconnaissance and lateral movement activity, these were the only steps Antigena suggested. The steps were all directly relevant to the intrusion – there was no attempt to block anything unrelated to the attack, and no other Antigena actions were triggered during this period.

By surgically blocking connections on specific ports during the scanning activity and enforcing the ‘pattern of life’ on the infected desktop, Antigena would have paralyzed the attacker’s reconnaissance efforts.

Furthermore, unusual service control attempts performed by the device would have been halted, minimizing the damage to the targeted destination.

Antigena would have delivered these blocks directly or via whatever integration was most suitable for the customer, such as firewall integrations or NAC integrations.

Lessons learned

The threat story above demonstrates the importance of controlling the access granted to low-privileged credentials, as well as remaining up-to-date with security patches. Since such attacks take advantage of existing network infrastructure, it is extremely difficult to detect these anomalous connections without the use of AI.

There was a delay of several days between the initial use of the ‘parents’ credentials and the first signs of lateral movement. This dormancy period – between compromise and the start of internal activities – is commonly seen in attacks. It likely indicates that the attacker was checking initially if their access worked, and then re-visiting the victim for further compromise once their schedule allowed for it.

Stopping a server-side attack

This compromise is reflective of many real-life intrusions: attacks cannot be easily attributed and are often conducted by sophisticated, unidentified threat actors.

Nevertheless, Darktrace managed to detect each stage of the attack cycle: initial compromise, reconnaissance, lateral movement, established foothold, and privilege escalation, and had Antigena been in active mode, it would have blocked these connections, and even prevented the initial desktop from ever exploiting the SQL vulnerability, which allowed the attacker to execute code remotely.

One day later, after seeing the power of Autonomous Response, the company decided to deploy Antigena in active mode.

Thanks to Darktrace analyst Isabel Finn for her insights on the above threat find.

Darktrace model detections:

  • Device / Anomalous Nmap SMB Activity
  • Device / Network Scan - Low Anomaly Score
  • Device / Network Scan
  • Device / ICMP Address Scan
  • Device / Suspicious Network Scan Activity
  • Anomalous Connection / New or Uncommon Service Control
  • Device / Multiple Lateral Movement Model Breaches
  • Device / New User Agent To Internal Server
  • Compliance / Pastebin
  • Device / Repeated Unknown RPC Service Bind Errors
  • Anomalous Server Activity / Rare External from Server
  • Compromise / Unusual Connections to Rare Lets Encrypt
  • User / Anomalous Domain User Creation Or Addition To Group


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
Max Heinemeyer
Chief Product Officer

Max is a cyber security expert with over a decade of experience in the field, specializing in a wide range of areas such as Penetration Testing, Red-Teaming, SIEM and SOC consulting and hunting Advanced Persistent Threat (APT) groups. At Darktrace, Max is closely involved with Darktrace’s strategic customers & prospects. He works with the R&D team at Darktrace, shaping research into new AI innovations and their various defensive and offensive applications. Max’s insights are regularly featured in international media outlets such as the BBC, Forbes and WIRED. Max holds an MSc from the University of Duisburg-Essen and a BSc from the Cooperative State University Stuttgart in International Business Information Systems.

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September 24, 2024

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Inside the SOC

Lifting the Fog: Darktrace’s Investigation into Fog Ransomware

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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

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

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September 11, 2024

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Inside the SOC

Decrypting the Matrix: How Darktrace Uncovered a KOK08 Ransomware Attack

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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

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About the author
Christina Kreza
Cyber Analyst
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