How Empowering End Users can Improve Your Email Security and Decrease the Burden on the SOC
08
May 2024
Most email security solutions either assume end-user reporting is of poor quality, so don’t prioritize it, or triage every user-reported email equally without any attempt to improve long-term efficiency. This blog explores how Darktrace aims to improve user reporting from the ground up, reducing the 90% falsely reported phishing and decreasing the load on security teams.
Why do we pay attention to the end user?
Every email security solution filters inbound mail, then typically hands over false positives and false negatives to the security team for manual triage. A crucial problem with this lifecycle is that it ignores the inevitability of end users being at the front line of any organization. Employees may receive point in time security awareness training, but it is rarely engaging or contextualized to their reality. While an employee may report a suspicious-looking email to the security team, they will rarely get to understand the outcome or impact of that decision. This means that the quality of reporting never improves, so the burden on the security team of triaging these emails – of which 90% are falsely reported – persists and grows with the business over time.
At Darktrace, we recognize that employees will always be on the front line of email security. That’s why we aim to improve end-user reporting from the ground up, reducing the overall number of emails needing triage and saving security team resource.
How does Darktrace improve the quality of end-user reporting?
Darktrace prioritizes improving users’ security awareness to increase the quality of end-user reporting from day one. We train users and optimize their experience, which in turn provides better detection.
That starts with training and security awareness. Traditionally, organizations oblige employees to attend point-in-time training sessions which interrupt their daily work schedules. With Darktrace/Email, if a message contains some potentially suspicious markers but is most likely safe, Darktrace takes a specific action to neutralize the risky components and presents it to the user with a simple narrative explaining why certain elements have been held back. The user can then decide whether to report this email to the security team.
The AI narrative gives the user context for why their specific email may carry risk, putting their security awareness training into practice. This creates an element of trust with the security solution, rather than viewing it as outside of daily workflows. Users may also receive a daily or weekly digest of their held emails and make a decision on whether to release or report them.
Whatever the user’s existing workflow is for reporting emails, Darktrace/Email can integrate with it and improve its quality. Our add-in for Outlook gives users a fully optimized experience, allowing them to engage with the narratives for each email, as well as non-productive mail management. However, if teams want to integrate Darktrace into an existing workflow, it can analyze emails reported to an internal SOC mailbox, the native email provider’s 'Report Phish’ button, or the ‘Knowbe4’ button.
By empowering the user with contextual feedback on each unique email, we foster employee engagement and elevate both reporting quality and security awareness. In fact, 60% fewer benign emails are reported because of the extra context supplied by Darktrace to end users. The eventual report is then fed back to the detection algorithm, improving future decision-making.
Reducing the amount of emails that reach the SOC
Out of the higher-quality emails that do end up being reported by users, the next step is to reduce the amount of emails that reach the SOC.
Once a user reports an email, Darktrace will independently determine if the mail should be automatically remediated based on second level triage. Darktrace/Email’s Mailbox Security Assistant automates secondary triage by combining additional behavioral signals and the most advanced link analysis engine we have ever built. It detects 70% more sophisticated malicious phishing links by looking at an additional twenty times more context than at the primary analysis stage, revealing the hidden intent within interactive and dynamic webpages. This directly alleviates the burden of manual triage for security analysts.
Following this secondary triage the emails that are deemed worthy of security team attention are then passed over, resulting in a lower quantity and higher quality of emails for SOC manual triage.
Centralizing and speeding analysis for investigations
For those emails that are received by the SOC, Darktrace also helps to improve triage time for manual remediation.
AI-generated narratives and automated remediation actions empower teams to fast-track manual triage and remediation, while still providing security analysts with the necessary depth. With live inbox view, security teams gain access to a centralized platform that combines intuitive search capabilities, Cyber AI Analyst reports, and mobile application access. With all security workflows consolidated within a unified interface, users can analyze and take remediation actions without the need to navigate multiple tools, such as e-discovery platforms – eliminating console hopping and accelerating incident response.
Our customers tell us that our AI allows them to go in-depth quickly for investigations, versus other solutions that only provide a high-level view.
Conclusion
Unlike our competitors, we believe that improving the quality of users’ experience is not only a nice-to-have, but a fundamental means for improving security. Any modern solution should consider end users as a key source of information as well as an opportunity for defense. Darktrace does both – optimizing the user experience as well as our AI learning from the user to augment detection.
The benefits of empowering users are ultimately felt by the security team, who benefit from improved detection, a reduction in manual triage of benign emails, and faster investigation workflows.
Augmented end user reporting is just one of a range of features new to Darktrace/Email. Check out the latest Innovations to Darktrace/Email in our recent blog.
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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
Carlos Gray
Product Manager
Carlos Gonzalez Gray is a Product Marketing Manager at Darktrace. Based in the Madrid Office, Carlos engages with the global product team to ensure each product supports the company’s overall strategy and goals throughout their entire lifecycle. Previous to his position in the product team, Carlos worked as a Cyber Technology Specialist where he specialized in the OT sector protecting critical infrastructure. His background as a consultant in Spain to IBEX 35 companies led him to become well versed in matters of compliance, auditing and data privacy as well. Carlos holds an Honors BA in Political Science and a Masters in Cybersecurity from IE 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.
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.
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
Senior Cyber Analyst and Deputy Analyst Team Lead, Singapore
Blog
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September 11, 2024
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Inside the SOC
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.
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.
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].
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.
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