Learn how a Mimecast misstep led to a large-scale email compromise and how DarkTrace AI detected the threat. Stay informed and protected against cyber threats.
In the last few years, email attacks have rapidly increased in volume and sophistication, with well-researched and convincing impersonation attacks accompanying rising cases of account takeovers. Their sophistication has particularly accelerated over the course of 2020, with globally pertinent news and more businesses embracing new ways of working proving to be fertile content for email attacks.
In this threat landscape, traditional email tools – which create rules for what ‘bad’ emails look like based on past campaigns – are missing these novel and sophisticated hoax emails.
This blog looks at an Australian logistics company that had Mimecast operating in its Microsoft 365 environment, but moved to an autonomous approach to email security when a malicious email — deemed benign by all other tools — was detected by Darktrace’s AI.
The company was trialling Antigena Email which was installed in passive mode, meaning it wasn’t configured to actively interfere. However, looking into the email dashboard allows us to see what actions the technology would have taken – and the consequences of relying purely on gateways to stop advanced threats.
Without AI taking action, compromising one employee’s email account was all the attacker needed to continue making headway throughout the business. The attacker accessed several sensitive files, gathering details of employees and credit card transactions, and then began communicating with others in the organization, sending out over two hundred further emails to take hold of more employee accounts. This activity was picked up in real time by Darktrace’s Microsoft 365 SaaS Module.
Details of the attack
The company was under sustained attack from a cyber-criminal who had already performed account hijacks on a number of their trusted partners. Abusing their trusted relationships, the attacker sent out several tailored emails from these partners’ accounts to the Australian company. All used the same convention in the subject – RFP for [compromised company’s name] – and all appeared to be credential harvesting.
Figure 1: A sample of the malicious emails from the hijacked accounts; the red icon indicating that Antigena Email would have held these emails back
Each of these emails contained a malicious payload, which was a file storage (SharePoint) link, hidden behind the below text. It’s likely the attacker did this to bypass mail link analysis. Mimecast did rewrite the link for analysis, but it failed to identify it as malicious.
Figure 2: Darktrace surfaces the text behind which the link was hidden
When clicked on, the link took the victim to a fake Microsoft login page for credential harvesting. This was an accurate replica of a genuine login page and sent email and password combinations directly to the attacker for further account compromise.
Figure 3: The fake Microsoft login page
A number of employees read the email, including the CEO; however only one person – a general manager – appeared to get their email account hijacked by the attacker.
Figure 4: An interactive snapshot of Antigena Email’s user interface
About three hours after opening the malicious email, an anomalous SaaS login was detected on the account from an IP address not seen across the business before.
Open source analysis of the IP address showed that it was a high fraud risk ISP, which runs anonymizing VPNs and servers – this may have been how the attacker overcame geofencing rules.
Shortly afterwards, Darktrace detected an anonymous sharing link being created for a password file.
Figure 5: Darktrace’s SaaS Module revealing the anomalous creation of a link
Darktrace revealed that this file was subsequently accessed by the anomalous IP address. Deeper analysis showed that the attacker repeated this methodology, making previously protected resources publicly available, before immediately accessing them publicly via the same IP address. Darktrace AI observed the attacker accessing potentially sensitive information, including a file that appeared to hold information about credit card transactions, as well as a document containing passwords.
Figure 6: Darktrace’s SaaS Console surfaces the unusual activity on the compromised account
Perpetuating the attack
The following day, after the attacker had exhausted all sensitive information they could elicit from the compromised email account, they then used that account to send out further malicious emails to trusted business associates using the same methodology as before – sending fake and targeted RFPs in an attempt to compromise credentials. Darktrace’s SaaS Module identified this anomalous behavior, graphically revealing that the attacker sent out over 1,600 tailored emails over the course of 25 minutes.
Figure 7: A graphical representation of the burst of emails sent over a 25 minute period
Why AI is needed to fight modern email threats
For the logistics company in question, this incident served as a wake-up call. The Managed Security Service Provider (MSSP) running their cloud security was completely unaware of the account takeover, which was detected by Darktrace’s SaaS Module. The organization realised that today’s email security challenge requires best in class technologies that can not only prevent phishing emails from reaching the inbox, but detect account takeovers and malicious outbound emails sent from a compromised account.
This incident caused the organization to deploy Antigena Email in active mode, allowing the technology to stop the most subtle and targeted threats that attempt to enter through the inbox based on its nuanced and contextual understanding of the normal ‘pattern of life’ for every user and device.
The reality is, hundreds of emails like this trick not only humans, but traditional security tools every day. It’s clear that when it comes to the growing email security challenge, the status quo is no longer good enough. With the modern workforce more dispersed and agile than ever, there is a growing need to protect remote users across SaaS collaboration platforms, whilst neutralizing email attacks before they reach the inbox.
Thanks to Darktrace analyst Liam Dermody for his insights on the above threat find.
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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
Dan Fein
VP, Product
Based in New York, Dan joined Darktrace’s technical team in 2015, helping customers quickly achieve a complete and granular understanding of Darktrace’s product suite. Dan has a particular focus on Darktrace/Email, ensuring that it is effectively deployed in complex digital environments, and works closely with the development, marketing, sales, and technical teams. Dan holds a Bachelor’s degree in Computer Science from New York University.
Lifting the Fog: Darktrace’s Investigation into Fog Ransomware
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.
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.
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
Decrypting the Matrix: How Darktrace Uncovered a KOK08 Ransomware Attack
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.
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.
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].
Figure 4: Cyber AI Analyst Investigation Process for the 'Possible Encryption of Files over SMB' incident.
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.
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
