Blog
/
Network
/
August 27, 2024

Decrypting the Matrix: How Darktrace Uncovered a KOK08 Ransomware Attack

In May 2024, a Darktrace customer was affected by KOK08, a ransomware strain commonly used by the Matrix ransomware family. Learn more about the tactics used by this ransomware case, including double extortion, and how Darktrace is able to detect and respond to such threats.
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.
Written by
Christina Kreza
Cyber Analyst
Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
27
Aug 2024

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

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.
Written by
Christina Kreza
Cyber Analyst

More in this series

No items found.

Blog

/

Identity

/

July 8, 2025

Defending the Cloud: Stopping Cyber Threats in Azure and AWS with Darktrace

fingerprintDefault blog imageDefault blog image

Real-world intrusions across Azure and AWS

As organizations pursue greater scalability and flexibility, cloud platforms like Microsoft Azure and Amazon Web Services (AWS) have become essential for enabling remote operations and digitalizing corporate environments. However, this shift introduces a new set of security risks, including expanding attack surfaces, misconfigurations, and compromised credentials frequently exploited by threat actors.

This blog dives into three instances of compromise within a Darktrace customer’s Azure and AWS environment which Darktrace.

  1. The first incident took place in early 2024 and involved an attacker compromising a legitimate user account to gain unauthorized access to a customer’s Azure environment.
  2. The other two incidents, taking place in February and March 2025, targeted AWS environments. In these cases, threat actors exfiltrated corporate data, and in one instance, was able to detonate ransomware in a customer’s environment.

Case 1 - Microsoft Azure

Simplified timeline of the attack on a customer’s Azure environment.
Figure 1: Simplified timeline of the attack on a customer’s Azure environment.

In early 2024, Darktrace identified a cloud compromise on the Azure cloud environment of a customer in the Europe, the Middle East and Africa (EMEA) region.

Initial access

In this case, a threat actor gained access to the customer’s cloud environment after stealing access tokens and creating a rogue virtual machine (VM). The malicious actor was found to have stolen access tokens belonging to a third-party external consultant’s account after downloading cracked software.

With these stolen tokens, the attacker was able to authenticate to the customer’s Azure environment and successfully modified a security rule to allow inbound SSH traffic from a specific IP range (i.e., securityRules/AllowCidrBlockSSHInbound). This was likely performed to ensure persistent access to internal cloud resources.

Detection and investigation of the threat

Darktrace / IDENTITY recognized that this activity was highly unusual, triggering the “Repeated Unusual SaaS Resource Creation” alert.

Cyber AI Analyst launched an autonomous investigation into additional suspicious cloud activities occurring around the same time from the same unusual location, correlating the individual events into a broader account hijack incident.

Cyber AI Analyst’s investigation into unusual cloud activity performed by the compromised account.
Figure 2: Cyber AI Analyst’s investigation into unusual cloud activity performed by the compromised account.
Figure 2: Surrounding resource creation events highlighted by Cyber AI Analyst.
Figure 3: Surrounding resource creation events highlighted by Cyber AI Analyst.
Figure 4: Surrounding resource creation events highlighted by Cyber AI Analyst.

“Create resource service limit” events typically indicate the creation or modification of service limits (i.e., quotas) for a specific Azure resource type within a region. Meanwhile, “Registers the Capacity Resource Provider” events refer to the registration of the Microsoft Capacity resource provider within an Azure subscription, responsible for managing capacity-related resources, particularly those related to reservations and service limits. These events suggest that the threat actor was looking to create new cloud resources within the environment.

Around ten minutes later, Darktrace detected the threat actor creating or modifying an Azure disk associated with a virtual machine (VM), suggesting an attempt to create a rogue VM within the environment.

Threat actors can leverage such rogue VMs to hijack computing resources (e.g., by running cryptomining malware), maintain persistent access, move laterally within the cloud environment, communicate with command-and-control (C2) infrastructure, and stealthily deliver and deploy malware.

Persistence

Several weeks later, the compromised account was observed sending an invitation to collaborate to an external free mail (Google Mail) address.

Darktrace deemed this activity as highly anomalous, triggering a compliance alert for the customer to review and investigate further.

The next day, the threat actor further registered new multi-factor authentication (MFA) information. These actions were likely intended to maintain access to the compromised user account. The customer later confirmed this activity by reviewing the corresponding event logs within Darktrace.

Case 2 – Amazon Web Services

Simplified timeline of the attack on a customer’s AWS environment
Figure 5: Simplified timeline of the attack on a customer’s AWS environment

In February 2025, another cloud-based compromised was observed on a UK-based customer subscribed to Darktrace’s Managed Detection and Response (MDR) service.

How the attacker gained access

The threat actor was observed leveraging likely previously compromised credential to access several AWS instances within customer’s Private Cloud environment and collecting and exfiltrating data, likely with the intention of deploying ransomware and holding the data for ransom.

Darktrace alerting to malicious activity

This observed activity triggered a number of alerts in Darktrace, including several high-priority Enhanced Monitoring alerts, which were promptly investigated by Darktrace’s Security Operations Centre (SOC) and raised to the customer’s security team.

The earliest signs of attack observed by Darktrace involved the use of two likely compromised credentials to connect to the customer’s Virtual Private Network (VPN) environment.

Internal reconnaissance

Once inside, the threat actor performed internal reconnaissance activities and staged the Rclone tool “ProgramData\rclone-v1.69.0-windows-amd64.zip”, a command-line program to sync files and directories to and from different cloud storage providers, to an AWS instance whose hostname is associated with a public key infrastructure (PKI) service.

The threat actor was further observed accessing and downloading multiple files hosted on an AWS file server instance, notably finance and investment-related files. This likely represented data gathering prior to exfiltration.

Shortly after, the PKI-related EC2 instance started making SSH connections with the Rclone SSH client “SSH-2.0-rclone/v1.69.0” to a RockHoster Virtual Private Server (VPS) endpoint (193.242.184[.]178), suggesting the threat actor was exfiltrating the gathered data using the Rclone utility they had previously installed. The PKI instance continued to make repeated SSH connections attempts to transfer data to this external destination.

Darktrace’s Autonomous Response

In response to this activity, Darktrace’s Autonomous Response capability intervened, blocking unusual external connectivity to the C2 server via SSH, effectively stopping the exfiltration of data.

This activity was further investigated by Darktrace’s SOC analysts as part of the MDR service. The team elected to extend the autonomously applied actions to ensure the compromise remained contained until the customer could fully remediate the incident.

Continued reconissance

Around the same time, the threat actor continued to conduct network scans using the Nmap tool, operating from both a separate AWS domain controller instance and a newly joined device on the network. These actions were accompanied by further internal data gathering activities, with around 5 GB of data downloaded from an AWS file server.

The two devices involved in reconnaissance activities were investigated and actioned by Darktrace SOC analysts after additional Enhanced Monitoring alerts had triggered.

Lateral movement attempts via RDP connections

Unusual internal RDP connections to a likely AWS printer instance indicated that the threat actor was looking to strengthen their foothold within the environment and/or attempting to pivot to other devices, likely in response to being hindered by Autonomous Response actions.

This triggered multiple scanning, internal data transfer and unusual RDP alerts in Darktrace, as well as additional Autonomous Response actions to block the suspicious activity.

Suspicious outbound SSH communication to known threat infrastructure

Darktrace subsequently observed the AWS printer instance initiating SSH communication with a rare external endpoint associated with the web hosting and VPS provider Host Department (67.217.57[.]252), suggesting that the threat actor was attempting to exfiltrate data to an alternative endpoint after connections to the original destination had been blocked.

Further investigation using open-source intelligence (OSINT) revealed that this IP address had previously been observed in connection with SSH-based data exfiltration activity during an Akira ransomware intrusion [1].

Once again, connections to this IP were blocked by Darktrace’s Autonomous Response and subsequently these blocks were extended by Darktrace’s SOC team.

The above behavior generated multiple Enhanced Monitoring alerts that were investigated by Darktrace SOC analysts as part of the Managed Threat Detection service.

Enhanced Monitoring alerts investigated by SOC analysts as part of the Managed Detection and Response service.
Figure 5: Enhanced Monitoring alerts investigated by SOC analysts as part of the Managed Detection and Response service.

Final containment and collaborative response

Upon investigating the unusual scanning activity, outbound SSH connections, and internal data transfers, Darktrace analysts extended the Autonomous Response actions previously triggered on the compromised devices.

As the threat actor was leveraging these systems for data exfiltration, all outgoing traffic from the affected devices was blocked for an additional 24 hours to provide the customer’s security team with time to investigate and remediate the compromise.

Additional investigative support was provided by Darktrace analysts through the Security Operations Service, after the customer's opened of a ticket related to the unfolding incident.

Simplified timeline of the attack
Figure 8: Simplified timeline of the attack

Around the same time of the compromise in Case 2, Darktrace observed a similar incident on the cloud environment of a different customer.

Initial access

On this occasion, the threat actor appeared to have gained entry into the AWS-based Virtual Private Cloud (VPC) network via a SonicWall SMA 500v EC2 instance allowing inbound traffic on any port.

The instance received HTTPS connections from three rare Vultr VPS endpoints (i.e., 45.32.205[.]52, 207.246.74[.]166, 45.32.90[.]176).

Lateral movement and exfiltration

Around the same time, the EC2 instance started scanning the environment and attempted to pivot to other internal systems via RDP, notably a DC EC2 instance, which also started scanning the network, and another EC2 instance.  

The latter then proceeded to transfer more than 230 GB of data to the rare external GTHost VPS endpoint 23.150.248[.]189, while downloading hundreds of GBs of data over SMB from another EC2 instance.

Cyber AI Analyst incident generated following the unusual scanning and RDP connections from the initial compromised device.
Figure 7: Cyber AI Analyst incident generated following the unusual scanning and RDP connections from the initial compromised device.

The same behavior was replicated across multiple EC2 instances, whereby compromised instances uploaded data over internal RDP connections to other instances, which then started transferring data to the same GTHost VPS endpoint over port 5000, which is typically used for Universal Plug and Play (UPnP).

What Darktrace detected

Darktrace observed the threat actor uploading a total of 718 GB to the external endpoint, after which they detonated ransomware within the compromised VPC networks.

This activity generated nine Enhanced Monitoring alerts in Darktrace, focusing on the scanning and external data activity, with the earliest of those alerts triggering around one hour after the initial intrusion.

Darktrace’s Autonomous Response capability was not configured to act on these devices. Therefore, the malicious activity was not autonomously blocked and escalated to the point of ransomware detonation.

Conclusion

This blog examined three real-world compromises in customer cloud environments each illustrating different stages in the attack lifecycle.

The first case showcased a notable progression from a SaaS compromise to a full cloud intrusion, emphasizing the critical role of anomaly detection when legitimate credentials are abused.

The latter two incidents demonstrated that while early detection is vital, the ability to autonomously block malicious activity at machine speed is often the most effective way to contain threats before they escalate.

Together, these incidents underscore the need for continuous visibility, behavioral analysis, and machine-speed intervention across hybrid environments. Darktrace's AI-driven detection and Autonomous Response capabilities, combined with expert oversight from its Security Operations Center, give defenders the speed and clarity they need to contain threats and reduce operational disruption, before the situation spirals.

Credit to Alexandra Sentenac (Senior Cyber Analyst) and Dylan Evans (Security Research Lead)

References

[1] https://www.virustotal.com/gui/ip-address/67.217.57.252/community

Case 1

Darktrace / IDENTITY model alerts

IaaS / Compliance / Uncommon Azure External User Invite

SaaS / Resource / Repeated Unusual SaaS Resource Creation

IaaS / Compute / Azure Compute Resource Update

Cyber AI Analyst incidents

Possible Unsecured AzureActiveDirectory Resource

Possible Hijack of Office365 Account

Case 2

Darktrace / NETWORK model alerts

Compromise / SSH Beacon

Device / Multiple Lateral Movement Model Alerts

Device / Suspicious SMB Scanning Activity

Device / SMB Lateral Movement

Compliance / SSH to Rare External Destination

Device / Anomalous SMB Followed By Multiple Model Alerts

Device / Anonymous NTLM Logins

Anomalous Connection / SMB Enumeration

Device / New or Uncommon SMB Named Pipe Device / Network Scan

Device / Suspicious Network Scan Activity

Device / New Device with Attack Tools

Device / RDP Scan Device / Attack and Recon Tools

Compliance / High Priority Compliance Model Alert

Compliance / Outgoing NTLM Request from DC

Compromise / Large Number of Suspicious Successful Connections

Device / Large Number of Model Alerts

Anomalous Connection / Multiple Failed Connections to Rare Endpoint

Unusual Activity / Internal Data Transfer

Anomalous Connection / Unusual Internal Connections

Device / Anomalous RDP Followed By Multiple Model Alerts

Unusual Activity / Unusual External Activity

Unusual Activity / Enhanced Unusual External Data Transfer

Unusual Activity / Unusual External Data Transfer

Unusual Activity / Unusual External Data to New Endpoint

Anomalous Connection / Multiple Connections to New External TCP Port

Darktrace / Autonomous Response model alerts

Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Server Block

Antigena / Network / Manual / Quarantine Device

Antigena / MDR / MDR-Quarantined Device

Antigena / MDR / Model Alert on MDR-Actioned Device

Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Client Block

Antigena / Network / Significant Anomaly / Antigena Alerts Over Time Block

Antigena / Network / Insider Threat / Antigena Network Scan Block

Antigena / Network / Significant Anomaly / Antigena Significant Server Anomaly Block

Antigena / Network / Insider Threat / Antigena SMB Enumeration Block

Antigena / Network / Significant Anomaly / Antigena Controlled and Model Alert

Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block

Antigena / Network / External Threat / Antigena Suspicious Activity Block

Antigena / Network / Insider Threat / Antigena Internal Data Transfer Block

Cyber AI Analyst incidents

Possible Application Layer Reconnaissance Activity

Scanning of Multiple Devices

Unusual Repeated Connections

Unusual External Data Transfer

Case 3

Darktrace / NETWORK model alerts

Unusual Activity / Unusual Large Internal Transfer

Compliance / Incoming Remote Desktop

Unusual Activity / High Volume Server Data Transfer

Unusual Activity / Internal Data Transfer

Anomalous Connection / Unusual Internal Remote Desktop

Anomalous Connection / Unusual Incoming Data Volume

Anomalous Server Activity / Domain Controller Initiated to Client

Device / Large Number of Model Alerts

Anomalous Connection / Possible Flow Device Brute Force

Device / RDP Scan

Device / Suspicious Network Scan Activity

Device / Network Scan

Anomalous Server Activity / Anomalous External Activity from Critical Network Device

Anomalous Connection / Download and Upload

Unusual Activity / Unusual External Data Transfer

Unusual Activity / High Volume Client Data Transfer

Unusual Activity / Unusual External Activity

Anomalous Connection / Uncommon 1 GiB Outbound

Device / Increased External Connectivity

Compromise / Large Number of Suspicious Successful Connections

Anomalous Connection / Data Sent to Rare Domain

Anomalous Connection / Low and Slow Exfiltration to IP

Unusual Activity / Enhanced Unusual External Data Transfer

Anomalous Connection / Multiple Connections to New External TCP Port

Anomalous Server Activity / Outgoing from Server

Anomalous Connection / Multiple Connections to New External UDP Port

Anomalous Connection / Possible Data Staging and External Upload

Unusual Activity / Unusual External Data to New Endpoint

Device / Large Number of Model Alerts from Critical Network Device

Compliance / External Windows Communications

Anomalous Connection / Unusual Internal Connections

Cyber AI Analyst incidents

Scanning of Multiple Devices

Extensive Unusual RDP Connections

MITRE ATT&CK mapping

(Technique name – Tactic ID)

Case 1

Defense Evasion - Modify Cloud Compute Infrastructure: Create Cloud Instance

Persistence – Account Manipulation

Case 2

Initial Access - External Remote Services

Execution - Inter-Process Communication

Persistence - External Remote Services

Discovery - System Network Connections Discovery

Discovery - Network Service Discovery

Discovery - Network Share Discovery

Lateral Movement - Remote Desktop Protocol

Lateral Movement - Remote Services: SMB/Windows Admin Shares

Collection - Data from Network Shared Drive

Command and Control - Protocol Tunneling

Exfiltration - Exfiltration Over Asymmetric Encrypted Non-C2 Protocol

Case 3

Initial Access - Exploit Public-Facing Application

Discovery - Remote System Discovery

Discovery - Network Service Discovery

Lateral Movement - Remote Services

Lateral Movement - Remote Desktop Protocol  

Collection - Data from Network Shared Drive

Collection - Data Staged: Remote Data Staging

Exfiltration - Exfiltration Over C2 Channel

Command and Control - Non-Standard Port

Command and Control – Web Service

Impact - Data Encrypted for Impact

List of IoCs

IoC         Type      Description + Probability

193.242.184[.]178 - IP Address - Possible Exfiltration Server  

45.32.205[.]52  - IP Address  - Possible C2 Infrastructure

45.32.90[.]176 - IP Address - Possible C2 Infrastructure

207.246.74[.]166 - IP Address - Likely C2 Infrastructure

67.217.57[.]252 - IP Address - Likely C2 Infrastructure

23.150.248[.]189 - IP Address - Possible Exfiltration Server

Continue reading
About the author
Alexandra Sentenac
Cyber Analyst

Blog

/

Identity

/

July 7, 2025

Top Eight Threats to SaaS Security and How to Combat Them

login screen for mutli factor authentication Default blog imageDefault blog image

The latest on the identity security landscape

Following the mass adoption of remote and hybrid working patterns, more critical data than ever resides in cloud applications – from Salesforce and Google Workspace, to Box, Dropbox, and Microsoft 365.

On average, a single organization uses 130 different Software-as-a-Service (SaaS) applications, and 45% of organizations reported experiencing a cybersecurity incident through a SaaS application in the last year.

As SaaS applications look set to remain an integral part of the digital estate, organizations are being forced to rethink how they protect their users and data in this area.

What is SaaS security?

SaaS security is the protection of cloud applications. It includes securing the apps themselves as well as the user identities that engage with them.

Below are the top eight threats that target SaaS security and user identities.

1.  Account Takeover (ATO)

Attackers gain unauthorized access to a user’s SaaS or cloud account by stealing credentials through phishing, brute-force attacks, or credential stuffing. Once inside, they can exfiltrate data, send malicious emails, or escalate privileges to maintain persistent access.

2. Privilege escalation

Cybercriminals exploit misconfigurations, weak access controls, or vulnerabilities to increase their access privileges within a SaaS or cloud environment. Gaining admin or superuser rights allows attackers to disable security settings, create new accounts, or move laterally across the organization.

3. Lateral movement

Once inside a network or SaaS platform, attackers move between accounts, applications, and cloud workloads to expand their foot- hold. Compromised OAuth tokens, session hijacking, or exploited API connections can enable adversaries to escalate access and exfiltrate sensitive data.

4. Multi-Factor Authentication (MFA) bypass and session hijacking

Threat actors bypass MFA through SIM swapping, push bombing, or exploiting session cookies. By stealing an active authentication session, they can access SaaS environments without needing the original credentials or MFA approval.

5. OAuth token abuse

Attackers exploit OAuth authentication mechanisms by stealing or abusing tokens that grant persistent access to SaaS applications. This allows them to maintain access even if the original user resets their password, making detection and mitigation difficult.

6. Insider threats

Malicious or negligent insiders misuse their legitimate access to SaaS applications or cloud platforms to leak data, alter configurations, or assist external attackers. Over-provisioned accounts and poor access control policies make it easier for insiders to exploit SaaS environments.

7. Application Programming Interface (API)-based attacks

SaaS applications rely on APIs for integration and automation, but attackers exploit insecure endpoints, excessive permissions, and unmonitored API calls to gain unauthorized access. API abuse can lead to data exfiltration, privilege escalation, and service disruption.

8. Business Email Compromise (BEC) via SaaS

Adversaries compromise SaaS-based email platforms (e.g., Microsoft 365 and Google Workspace) to send phishing emails, conduct invoice fraud, or steal sensitive communications. BEC attacks often involve financial fraud or data theft by impersonating executives or suppliers.

BEC heavily uses social engineering techniques, tailoring messages for a specific audience and context. And with the growing use of generative AI by threat actors, BEC is becoming even harder to detect. By adding ingenuity and machine speed, generative AI tools give threat actors the ability to create more personalized, targeted, and convincing attacks at scale.

Protecting against these SaaS threats

Traditionally, security leaders relied on tools that were focused on the attack, reliant on threat intelligence, and confined to a single area of the digital estate.

However, these tools have limitations, and often prove inadequate for contemporary situations, environments, and threats. For example, they may lack advanced threat detection, have limited visibility and scope, and struggle to integrate with other tools and infrastructure, especially cloud platforms.

AI-powered SaaS security stays ahead of the threat landscape

New, more effective approaches involve AI-powered defense solutions that understand the digital business, reveal subtle deviations that indicate cyber-threats, and action autonomous, targeted responses.

[related-resource]

Continue reading
About the author
Carlos Gray
Senior Product Marketing Manager, Email
Your data. Our AI.
Elevate your network security with Darktrace AI