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February 9, 2023

Vidar Network: Analyzing a Prolific Info Stealer

Discover the latest insights on the Vidar network-based info stealer from our Darktrace experts and stay informed on cybersecurity 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
Roberto Romeu
Senior SOC Analyst
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09
Feb 2023

In the latter half of 2022, Darktrace observed a rise in Vidar Stealer infections across its client base. These infections consisted in a predictable series of network behaviors, including usage of certain social media platforms for the retrieval of Command and Control (C2) information and usage of certain URI patterns in C2 communications. In the blog post, we will provide details of the pattern of network activity observed in these Vidar Stealer infections, along with details of Darktrace’s coverage of the activity. 

Background on Vidar Stealer

Vidar Stealer, first identified in 2018, is an info-stealer capable of obtaining and then exfiltrating sensitive data from users’ devices. This data includes banking details, saved passwords, IP addresses, browser history, login credentials, and crypto-wallet data [1]. The info-stealer, which is typically delivered via malicious spam emails, cracked software websites, malicious ads, and websites impersonating legitimate brands, is known to access profiles on social media platforms once it is running on a user’s device. The info-stealer does this to retrieve the IP address of its Command and Control (C2) server. After retrieving its main C2 address, the info-stealer, like many other info-stealers, is known to download several third-party Dynamic Link Libraries (DLLs) which it uses to gain access to sensitive data saved on the infected device. The info-stealer then bundles the sensitive data which it obtains and sends it back to the C2 server.  

Details of Attack Chain 

In the second half of 2022, Darktrace observed the following pattern of activity within many client networks:

1. User’s device makes an HTTPS connection to Telegram and/or to a Mastodon server

2. User’s device makes an HTTP GET request with an empty User-Agent header, an empty Host header and a target URI consisting of 4 digits to an unusual, external endpoint

3. User’s device makes an HTTP GET request with an empty User-Agent header, an empty Host header and a target URI consisting of 10 digits followed by ‘.zip’ to the unusual, external endpoint

4. User’s device makes an HTTP POST request with an empty User-Agent header, an empty Host header, and the target URI ‘/’ to the unusual, external endpoint 

Figure 1: The above network logs, taken from Darktrace’s Advanced Search interface, show an infected device contacting Telegram and then making a series of HTTP requests to 168.119.167[.]188
Figure 2:  The above network logs, taken from Darktrace’s Advanced Search interface, show an infected device contacting a Mastadon server and then making a series of HTTP requests to 107.189.31[.]171

Each of these activity chains occurred as the result of a user running Vidar Stealer on their device. No common method was used to trick users into running Vidar Stealer on their devices. Rather, a variety of methods, ranging from malspam to cracked software downloads appear to have been used. 

Once running on a user’s device, Vidar Stealer went on to make an HTTPS connection to either Telegram (https://t[.]me/) or a Mastodon server (https://nerdculture[.]de/ or https://ioc[.]exchange/). Telegram and Mastodon are social media platforms on which users can create profiles. Malicious actors are known to create profiles on these platforms and then to embed C2 information within the profiles’ descriptions [2].  In the Vidar cases observed across Darktrace’s client base, it seems that Vidar contacted Telegram and/or Mastodon servers in order to retrieve the IP address of its C2 server from a profile description. Since social media platforms are typically trusted, this ‘Dead Drop’ method of sharing C2 details with malware samples makes it possible for threat actors to regularly update C2 details without the communication of these changes being blocked. 

Figure 3: A screenshot a profile on the Mastodon server, nerdculture[.]de. The profile’s description contains a C2 address 

After retrieving its C2 address from the description of a Telegram or Mastodon profile, Vidar went on to make an HTTP GET request with an empty User-Agent header, an empty Host header and a target URI consisting of 4 digits to its C2 server. The sequences of digits appearing in these URIs are campaign IDs. The C2 server responded to Vidar’s GET request with configuration details that likely informed Vidar’s subsequent data stealing activities. 

After receiving its configuration details, Vidar went on to make a GET request with an empty User-Agent header, an empty Host header and a target URI consisting of 10 digits followed by ‘.zip’ to the C2 server. This request was responded to with a ZIP file containing legitimate, third-party Dynamic Link Libraries such as ‘vcruntime140.dll’. Vidar used these libraries to gain access to sensitive data saved on the infected host. 

Figure 4: The above PCAP provides an example of the configuration details provided by a C2 server in response to Vidar’s first GET request 
Figure 5: Examples of DLLs included within ZIP files downloaded by Vidar samples

After downloading a ZIP file containing third-party DLLs, Vidar made a POST request containing hundreds of kilobytes of data to the C2 endpoint. This POST request likely represented exfiltration of stolen information. 

Darktrace Coverage

After infecting users’ devices, Vidar contacted either Telegram or Mastodon, and then made a series of HTTP requests to its C2 server. The info-stealer’s usage of social media platforms, along with its usage of ZIP files for tool transfer, complicate the detection of its activities. The info-stealer’s HTTP requests to its C2 server, however, caused the following Darktrace DETECT/Network models to breach:

  • Anomalous File / Zip or Gzip from Rare External Location 
  • Anomalous File / Numeric File Download
  • Anomalous Connection / Posting HTTP to IP Without Hostname

These model breaches did not occur due to users’ devices contacting IP addresses known to be associated with Vidar. In fact, at the time that the reported activities occurred, many of the contacted IP addresses had no OSINT associating them with Vidar activity. The cause of these model breaches was in fact the unusualness of the devices’ HTTP activities. When a Vidar-infected device was observed making HTTP requests to a C2 server, Darktrace recognised that this behavior was highly unusual both for the device and for other devices in the network. Darktrace’s recognition of this unusualness caused the model breaches to occur. 

Vidar Stealer infections move incredibly fast, with the time between initial infection and data theft sometimes being less than a minute. In cases where Darktrace’s Autonomous Response technology was active, Darktrace RESPOND/Network was able to autonomously block Vidar’s connections to its C2 server immediately after the first connection was made. 

Figure 6: The Event Log for an infected device, shows that Darktrace RESPOND/Network autonomously intervened 1 second after the device first contacted the C2 server 95.217.245[.]254

Conclusion 

In the latter half of 2022, a particular pattern of activity was prolific across Darktrace’s client base, with the pattern being seen in the networks of customers across a broad range of industry verticals and sizes. Further investigation revealed that this pattern of network activity was the result of Vidar Stealer infection. These infections moved fast and were effective at evading detection due to their usage of social media platforms for information retrieval and their usage of ZIP files for tool transfer. Since the impact of info-stealer activity typically occurs off-network, long after initial infection, insufficient detection of info-stealer activity leaves victims at risk of attackers operating unbeknownst to them and of powerful attack vectors being available to launch broad compromises. 

Despite the evasion attempts made by the operators of Vidar, Darktrace DETECT/Network was able to detect the unusual HTTP activities which inevitably resulted from Vidar infections. When active, Darktrace RESPOND/Network was able to quickly take inhibitive actions against these unusual activities. Given the prevalence of Vidar Stealer [3] and the speed at which Vidar Stealer infections progress, Autonomous Response technology proves to be vital for protecting organizations from info-stealer activity.  

Thanks to the Threat Research Team for its contributions to this blog.

MITRE ATT&CK Mapping

List of IOCs

107.189.31[.]171 - Vidar C2 Endpoint

168.119.167[.]188 – Vidar C2 Endpoint 

77.91.102[.]51 - Vidar C2 Endpoint

116.202.180[.]202 - Vidar C2 Endpoint

79.124.78[.]208 - Vidar C2 Endpoint

159.69.100[.]194 - Vidar C2 Endpoint

195.201.253[.]5 - Vidar C2 Endpoint

135.181.96[.]153 - Vidar C2 Endpoint

88.198.122[.]116 - Vidar C2 Endpoint

135.181.104[.]248 - Vidar C2 Endpoint

159.69.101[.]102 - Vidar C2 Endpoint

45.8.147[.]145 - Vidar C2 Endpoint

159.69.102[.]192 - Vidar C2 Endpoint

193.43.146[.]42 - Vidar C2 Endpoint

159.69.102[.]19 - Vidar C2 Endpoint

185.53.46[.]199 - Vidar C2 Endpoint

116.202.183[.]206 - Vidar C2 Endpoint

95.217.244[.]216 - Vidar C2 Endpoint

78.46.129[.]14 - Vidar C2 Endpoint

116.203.7[.]175 - Vidar C2 Endpoint

45.159.249[.]3 - Vidar C2 Endpoint

159.69.101[.]170 - Vidar C2 Endpoint

116.202.183[.]213 - Vidar C2 Endpoint

116.202.4[.]170 - Vidar C2 Endpoint

185.252.215[.]142 - Vidar C2 Endpoint

45.8.144[.]62 - Vidar C2 Endpoint

74.119.192[.]157 - Vidar C2 Endpoint

78.47.102[.]252 - Vidar C2 Endpoint

212.23.221[.]231 - Vidar C2 Endpoint

167.235.137[.]244 - Vidar C2 Endpoint

88.198.122[.]116 - Vidar C2 Endpoint

5.252.23[.]169 - Vidar C2 Endpoint

45.89.55[.]70 - Vidar C2 Endpoint

References

[1] https://blog.cyble.com/2021/10/26/vidar-stealer-under-the-lens-a-deep-dive-analysis/

[2] https://asec.ahnlab.com/en/44554/

[3] https://blog.sekoia.io/unveiling-of-a-large-resilient-infrastructure-distributing-information-stealers/

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
Roberto Romeu
Senior SOC Analyst

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January 9, 2026

Under Medusa’s Gaze: How Darktrace Uncovers RMM Abuse in Ransomware Campaigns

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What is Medusa Ransomware in 2025?

In 2025, the Medusa Ransomware-as-a-Service (RaaS) emerged as one of the top 10 most active ransomware threat actors [1]. Its growing impact prompted a joint advisory from the US Cybersecurity and Infrastructure Security Agency (CISA) and the Federal Bureau of Investigation (FBI) [3]. As of January 2026, more than 500 organizations have fallen victim to Medusa ransomware [2].

Darktrace previously investigated Medusa in a 2024 blog, but the group’s rapid expansion and new intelligence released in late 2025 has lead Darktrace’s Threat Research team to  investigate further. Recent findings include Microsoft’s research on Medusa actors exploiting a vulnerability in Fortra’s GoAnywhere MFT License Servlet (CVE-2025-10035)[4] and Zencec’s report on Medusa’s abuse of flaws in SimpleHelp’s remote support software (CVE-2024-57726, CVE-2024-57727, CVE-2024-57728) [5].

Reports vary on when Medusa first appeared in the wild. Some sources mention June 2021 as the earliest sightings, while others point to late 2022, when its developers transitioned to the RaaS model, as the true beginning of its operation [3][11].

Madusa Ransomware history and background

The group behind Medusa is known by several aliases, including Storm-1175 and Spearwing [4] [7]. Like its mythological namesake, Medusa has many “heads,” collaborating with initial access brokers (IABs) and, according to some evidence, affiliating with Big Game Hunting (BGH) groups such as Frozen Spider, as well as the cybercriminal group UNC7885 [3][6][13].

Use of Cyrillic in its scripts, activity on Russian-language cybercrime forums, slang unique to Russian criminal subcultures, and avoidance of targets in Commonwealth of Independent States (CIS) countries suggest that Medusa operates from Russia or an allied state [11][12].

Medusa ransomware should not be confused with other similarly named malware, such as the Medusa Android Banking Trojan, the Medusa Botnet/Medusa Stealer, or MedusaLocker ransomware. It is easily distinguishable from these variants because it appends the extension .MEDUSA to encrypted files and drops the ransom note !!!READ_ME_MEDUSA!!!.txt on compromised systems [8].

Who does Madusa Ransomware target?

The group appears to show little restraint, indiscriminately attacking organizations across all sectors, including healthcare, and is known to employ triple extortion tactics whereby sensitive data is encrypted, victims are threatened with data leaks, and additional pressure is applied through DDoS attacks or contacting the victim’s customers, rather than the more common double extortion model [13].

Madusa Ransomware TTPs

To attain initial access, Medusa actors typically purchase access to already compromised devices or accounts via IABs that employ phishing, credential stuffing, or brute-force attacks, and also target vulnerable or misconfigured Internet-facing systems.

In addition to the GoAnywhere MFT and SimpleHelp RMM flaws, other vulnerabilities exploited in Medusa attacks include ConnectWise ScreenConnect RMM (CVE-2024-1709), Microsoft Exchange Server (CVE-2021-34473, also known as ProxyShell), and Fortinet Enterprise Management Servers (CVE-2023-48788) [18][19][20][21][24][25].

Darktrace’s Coverage of Medusa Ransomware

Between December 2023 and November 2025, Darktrace observed multiple cases of file encryption related to Medusa ransomware across its customer base. When enabled, Darktrace’s Autonomous Response capability intervened early in the attack chain, blocking malicious activity before file encryption could begin.

Some of the affected were based in Europe, the Middle East and Africa (EMEA), others in the Americas (AMS), and the remainder in the Asia-Pacific and Japan region. The most impacted sectors were financial services and the automotive industry, followed by healthcare, and finally organizations in arts, entertainment and recreation, ICT, and manufacturing.

Remote Monitoring and Management (RMM) tool abuse

In most customer environments where Medusa file encryption attempts were observed, and in one case where the compromise was contained before encryption, unusual external HTTP connections associated with JWrapper were also detected. JWrapper is a legitimate tool designed to simplify the packaging, distribution, and management of Java applications, enabling the creation of executables that run across different operating systems. Many of the destination IP addresses involved in this activity were linked to SimpleHelp servers or associated with Atera.

Medusa actors appear to favor RMM tools such as SimpleHelp. Unpatched or misconfigured SimpleHelp RMM servers can serve as an initial access vector to the victims’ infrastructure.  After gaining access to SimpleHelp management servers, the threat actors edit server configuration files to redirect existing SimpleHelp RMM agents to communicate with unauthorized servers under their control.

The SimpleHelp tool is not only used for command-and-control (C2) and enabling persistence but is also observed during lateral movement within the network, downloading additional attack tools, data exfiltration, and even ransomware binary execution. Other legitimate remote access tools abused by Medusa in a similar manner to evade detection include Atera, AnyDesk, ScreenConnect, eHorus, N-able, PDQ Deploy/Inventory, Splashtop, TeamViewer, NinjaOne, Navicat, and MeshAgent [4][5][15][16][17].

Data exfiltration

Another correlation among Darktrace customers affected by Medusa was observed during the data exfiltration phase. In several environments, data was exfiltrated to the endpoints erp.ranasons[.]com or pruebas.pintacuario[.]mx (143.110.243[.]154, 144.217.181[.]205) over ports 443, 445, and 80. erp.ranasons[.]com was seemingly active between November 2024 and September 2025, while pruebas.pintacuario[.]mx was seen from November 2024 to March 2025. Evidence suggests that pruebas.pintacuario[.]mx previously hosted a SimpleHelp server [22][23].

Apart from RMM tools, Medusa is also known to use Rclone and Robocopy for data exfiltration [3][19]. During one Medusa compromise detected in mid-2024, the customer’s data was exfiltrated to external destinations associated with the Ngrok proxy service using an SSH-2.0-rclone client.

Medusa Compromise Leveraging SimpleHelp

In Q4 2025, Darktrace assisted a European company impacted by Medusa ransomware. The organization had partial Darktrace / NETWORK coverage and had configured Darktrace’s Autonomous Response capability to require manual confirmation for all actions. Despite these constraints, data received through the customer’s security integration with CrowdStrike Falcon enabled Darktrace analysts to reconstruct the attack chain, although the initial access vector remains unclear due to limited visibility.

In late September 2025, a device out of the scope of Darktrace's visibility began scanning the network and using RDP, NTLM/SMB, DCE_RPC, and PowerShell for lateral movement.

CrowdStrike “Defense Evasion: Disable or Modify Tools” alerts related to a suspicious driver (c:\windows\[0-9a-b]{4}.exe) and a PDQ Deploy executable (share=\\<device_hostname>\ADMIN$ file=AdminArsenal\PDQDeployRunner\service-1\exec\[0-9a-b]{4}.exe) suggest that the attackers used the Bring Your Own Vulnerable Driver (BYOVD) technique to terminate antivirus processes on network devices, leveraging tools such as KillAV or AbyssWorker along with the PDQ Software Deployment solution [19][26].

A few hours later, Darktrace observed the same device that had scanned the network writing Temp\[a-z]{2}.exe over SMB to another device on the same subnet. According to data from the CrowdStrike alert, this executable was linked to an RMM application located at C:\Users\<compromised_user>\Documents\[a-z]{2}.exe. The same compromised user account later triggered a CrowdStrike “Command and Control: Remote Access Tools” alert when accessing C:\ProgramData\JWrapper-Remote Access\JWrapper-Remote Access Bundle-[0-9]{11}\JWrapperTemp-[0-9]{10}-[0-9]{1}-app\bin\windowslauncher.exe [27].

An executable file associated with the SimpleHelp RMM tool being written to other devices using the SMB protocol, as detected by Darktrace.
Figure 1: An executable file associated with the SimpleHelp RMM tool being written to other devices using the SMB protocol, as detected by Darktrace.

Soon after, the destination device and multiple other network devices began establishing connections to 31.220.45[.]120 and 213.183.63[.]41, both of which hosted malicious SimpleHelp RMM servers. These C2 connections continued for more than 20 days after the initial compromise.

CrowdStrike integration alerts for the execution of robocopy . "c:\windows\\" /COPY:DT /E /XX /R:0 /W:0 /NP /XF RunFileCopy.cmd /IS /IT commands on several Windows servers, suggested that this utility was likely used to stage files in preparation for data exfiltration [19].

Around two hours later, Darktrace detected another device connecting to the attacker’s SimpleHelp RMM servers. This internal server had ‘doc’ in its hostname, indicating it was likely a file server. It was observed downloading documents from another internal server over SMB and uploading approximately 70 GiB of data to erp.ranasons[.]com (143.110.243[.]154:443).

Data uploaded to erp.ranasons[.]com and the number of model alerts from the exfiltrating device, represented by yellow and orange dots.
Figure 2: Data uploaded to erp.ranasons[.]com and the number of model alerts from the exfiltrating device, represented by yellow and orange dots.

Darktrace’s Cyber AI Analyst autonomously investigated the unusual connectivity, correlating the separate C2 and data exfiltration events into a single incident, providing greater visibility into the ongoing attack.

Cyber AI Analyst identified a file server making C2 connections to an attacker-controlled SimpleHelp server (213.183.63[.]41) and exfiltrating data to erp.ranasons[.]com.
Figure 3: Cyber AI Analyst identified a file server making C2 connections to an attacker-controlled SimpleHelp server (213.183.63[.]41) and exfiltrating data to erp.ranasons[.]com.
The same file server that connected to 213.183.63[.]41 and exfiltrated data to erp.ranasons[.]com was also observed attempting to connect to an IP address associated with Moscow, Russia (193.37.69[.]154:7070).
Figure 4: The same file server that connected to 213.183.63[.]41 and exfiltrated data to erp.ranasons[.]com was also observed attempting to connect to an IP address associated with Moscow, Russia (193.37.69[.]154:7070).

One of the devices connecting to the attacker's SimpleHelp RMM servers was also observed downloading 35 MiB from [0-9]{4}.filemail[.]com. Filemail, a legitimate file-sharing service, has reportedly been abused by Medusa actors to deliver additional malicious payloads [11].

A device controlled remotely via SimpleHelp downloading additional tooling from the Filemail file-sharing service.
Figure 5: A device controlled remotely via SimpleHelp downloading additional tooling from the Filemail file-sharing service.

Finally, integration alerts related to the ransomware binary, such as c:\windows\system32\gaze.exe and <device_hostname>\ADMIN$ file=AdminArsenal\PDQDeployRunner\service-1\exec\gaze.exe, along with “!!!READ_ME_MEDUSA!!!.txt” ransom notes were observed on network devices. This indicates that file encryption in this case was most likely carried out directly on the victim hosts rather than via the SMB protocol [3].

Conclusion

Threat actors, including nation-state actors and ransomware groups like Medusa, have long abused legitimate commercial RMM tools, typically used by system administrators for remote monitoring, software deployment, and device configuration, instead of relying on remote access trojans (RATs).

Attackers employ existing authorized RMM tools or install new remote administration software to enable persistence, lateral movement, data exfiltration, and ingress tool transfer. By mimicking legitimate administrative behavior, RMM abuse enables attackers to evade detection, as security software often implicitly trusts these tools, allowing attackers to bypass traditional security controls [28][29][30].

To mitigate such risks, organizations should promptly patch publicly exposed RMM servers and adopt anomaly-based detection solutions, like Darktrace / NETWORK, which can distinguish legitimate administrative activity from malicious behavior, applying rapid response measures through its Autonomous Response capability to stop attacks in their tracks.

Darktrace delivers comprehensive network visibility and Autonomous Response capabilities, enabling real-time detection of anomalous activity and rapid mitigation, even if an organization fall under Medusa’s gaze.

Credit to Signe Zaharka (Principal Cyber Analyst) and Emma Foulger (Global Threat Research Operations Lead

Edited by Ryan Traill (Analyst Content Lead)

Appendices

List of Indicators of Compromise (IoCs)

IoC - Type - Description + Confidence + Time Observed

185.108.129[.]62 IP address Malicious SimpleHelp server observed during Medusa attacks (High confidence) - March 7, 2023

185.126.238[.]119 IP address Malicious SimpleHelp server observed during Medusa attacks (High confidence) - November 26-27, 2024

213.183.63[.]41 IP address Malicious SimpleHelp server observed during Medusa attacks (High confidence) - November 28, 2024 - Sep 30, 2025

213.183.63[.]42 IP address Malicious SimpleHelp server observed during Medusa attacks (High confidence) - July 4 -9 , 2024

31.220.45[.]120 IP address Malicious SimpleHelp server observed during Medusa attacks (High confidence) - September 12 - Oct 20 , 2025

91.92.246[.]110 IP address Malicious SimpleHelp server observed during Medusa attacks (High confidence) - May 24, 2024

45.9.149[.]112:15330 IP address Malicious SimpleHelp server observed during Medusa attacks (High confidence) - June 21, 2024

89.36.161[.]12 IP address Malicious SimpleHelp server observed during Medusa attacks (High confidence) - June 26-28, 2024

193.37.69[.]154:7070 IP address Suspicious RU IP seen on a device being controlled via SimpleHelp and exfiltrating data to a Medusa related endpoint - September 30 - October 20, 2025

erp.ranasons[.]com·143.110.243[.]154 Hostname Data exfiltration destination - November 27, 2024 - September 30, 2025

pruebas.pintacuario[.]mx·144.217.181[.]205 - Hostname Data exfiltration destination - November 27, 2024  -  March 26, 2025

lirdel[.]com · 44.235.83[.]125/a.msi (1b9869a2e862f1e6a59f5d88398463d3962abe51e19a59) File & hash Atera related file downloaded with PowerShell - June 20, 2024

wizarr.manate[.]ch/108.215.180[.]161:8585/$/1dIL5 File Suspicious file observed on one of the devices exhibiting unusual activity during a Medusa compromise - February 28, 2024

!!!READ_ME_MEDUSA!!!.txt" File - Ransom note

*.MEDUSA - File extension        File extension added to encrypted files

gaze.exe – File - Ransomware binary

Darktrace Model Coverage

Darktrace / NETWORK model detections triggered during connections to attacker controlled SimpleHelp servers:

Anomalous Connection/Anomalous SSL without SNI to New External

Anomalous Connection/Multiple Connections to New External UDP Port

Anomalous Connection/New User Agent to IP Without Hostname

Anomalous Connection/Rare External SSL Self-Signed

Anomalous Connection/Suspicious Self-Signed SSL

Anomalous File/EXE from Rare External Location

Anomalous Server Activity/Anomalous External Activity from Critical Network Device

Anomalous Server Activity/New User Agent from Internet Facing System

Anomalous Server Activity/Outgoing from Server

Anomalous Server Activity/Rare External from Server

Compromise/High Volume of Connections with Beacon Score

Compromise/Large Number of Suspicious Failed Connections

Compromise/Ransomware/High Risk File and Unusual SMB

Device/New User Agent

Unusual Activity/Unusual External Data to New Endpoint

Unusual Activity/Unusual External Data Transfer

Darktrace / NETWORK Model Detections during the September/October 2025 Medusa attack:

Anomalous Connection / Data Sent to Rare Domain

Anomalous Connection / Download and Upload

Anomalous Connection / Low and Slow Exfiltration

Anomalous Connection / New User Agent to IP Without Hostname

Anomalous Connection / Uncommon 1 GiB Outbound

Anomalous Connection / Unusual Admin RDP Session

Anomalous Connection / Unusual Incoming Long Remote Desktop Session

Anomalous Connection / Unusual Long SSH Session

Anomalous File / EXE from Rare External Location

Anomalous File / Internal/Unusual Internal EXE File Transfer

Anomalous Server Activity / Anomalous External Activity from Critical Network Device

Anomalous Server Activity / Outgoing from Server

Anomalous Server Activity / Rare External from Server

Compliance / Default Credential Usage

Compliance / High Priority Compliance Model Alert

Compliance / Outgoing NTLM Request from DC

Compliance / Possible Unencrypted Password File On Server

Compliance / Remote Management Tool On Server

Compromise / Large Number of Suspicious Failed Connections

Compromise / Large Number of Suspicious Successful Connections

Compromise / Ransomware/High Risk File and Unusual SMB

Compromise / Suspicious Beaconing Behaviour

Compromise / Suspicious HTTP and Anomalous Activity

Compromise / Sustained SSL or HTTP Increase

Compromise / Sustained TCP Beaconing Activity To Rare Endpoint

Device / ICMP Address Scan

Device / Increase in New RPC Services

Device / Initial Attack Chain Activity

Device / Large Number of Model Alert

Device / Large Number of Model Alerts from Critical Network Device

Device / Lateral Movement and C2 Activity

Device / Multiple C2 Model Alert

Device / Network Scan

Device / Possible SMB/NTLM Reconnaissance

Device / Spike in LDAP Activity

Device / Suspicious Network Scan Activity

Device / Suspicious SMB Scanning Activity

Security Integration / High Severity Integration Incident

Security Integration / Low Severity Integration Incident

Unusual Activity / Enhanced Unusual External Data Transfer

Unusual Activity / Internal Data Transfer

Unusual Activity / Unusual External Activity

Unusual Activity / Unusual External Data to New Endpoint

Unusual Activity / Unusual External Data Transfer

User / New Admin Credentials on Server

Autonomous Response Actions

Antigena / Network/External Threat/Antigena File then New Outbound Block

Antigena / Network/External Threat/Antigena Ransomware Block

Antigena / Network/External Threat/Antigena Suspicious Activity Block

Antigena / Network/External Threat/Antigena Suspicious File Block

Antigena / Network/Insider Threat/Antigena Internal Anomalous File Activity

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

Antigena / Network/Insider Threat/Antigena Large Data Volume Outbound Block

Antigena / Network/Insider Threat/Antigena Network Scan Block

Antigena / Network/Insider Threat/Antigena Unusual Privileged User Activities Block

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

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

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

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

Antigena / Network/Significant Anomaly/Repeated Antigena Alerts

MITRE ATT&CK Mapping

Technique Name, Tactic, ID, Sub-Technique

Application Layer Protocol , COMMAND AND CONTROL , T1071

Automated Collection , COLLECTION , T1119

Automated Exfiltration , EXFILTRATION , T1020

Brute Force , CREDENTIAL ACCESS , T1110

Client Configurations , RECONNAISSANCE , T1592.004 , T1592

Cloud Accounts , DEFENSE EVASION ,  PERSISTENCE ,  PRIVILEGE ESCALATION ,  INITIAL ACCESS , T1078.004 , T1078

Command-Line Interface , EXECUTION ICS , T0807

Credential Stuffing , CREDENTIAL ACCESS , T1110.004 , T1110

Data Encrypted for Impact , IMPACT , T1486

Data from Network Shared Drive , COLLECTION , T1039

Data Obfuscation , COMMAND AND CONTROL , T1001

Data Staged , COLLECTION , T1074

Data Transfer Size Limits , EXFILTRATION , T1030

Default Accounts , DEFENSE EVASION ,  PERSISTENCE ,  PRIVILEGE ESCALATION ,  INITIAL ACCESS , T1078.001 , T1078

Default Credentials , LATERAL MOVEMENT ICS , T0812

Distributed Component Object Model , LATERAL MOVEMENT , T1021.003 , T1021

Drive-by Compromise , INITIAL ACCESS ICS , T0817

Drive-by Compromise , INITIAL ACCESS , T1189

Email Collection , COLLECTION , T1114

Exfiltration Over Alternative Protocol , EXFILTRATION , T1048

Exfiltration Over C2 Channel , EXFILTRATION , T1041

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

Exploit Public-Facing Application , INITIAL ACCESS , T1190

Exploitation for Privilege Escalation , PRIVILEGE ESCALATION , T0890

Exploitation of Remote Services , LATERAL MOVEMENT , T1210

Exploits , RESOURCE DEVELOPMENT , T1588.005 , T1588

File and Directory Discovery , DISCOVERY , T1083

File Deletion , DEFENSE EVASION , T1070.004 , T1070

Graphical User Interface , EXECUTION ICS , T0823

Ingress Tool Transfer , COMMAND AND CONTROL , T1105

Lateral Tool Transfer , LATERAL MOVEMENT , T1570

LLMNR/NBT-NS Poisoning and SMB Relay , CREDENTIAL ACCESS ,  COLLECTION , T1557.001 , T1557

Malware , RESOURCE DEVELOPMENT , T1588.001 , T1588

Network Service Scanning , DISCOVERY , T1046

Network Share Discovery , DISCOVERY , T1135

Non-Application Layer Protocol , COMMAND AND CONTROL , T1095

Non-Standard Port , COMMAND AND CONTROL , T1571

One-Way Communication , COMMAND AND CONTROL , T1102.003 , T1102

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

Password Cracking , CREDENTIAL ACCESS , T1110.002 , T1110

Password Guessing , CREDENTIAL ACCESS , T1110.001 , T1110

Password Spraying , CREDENTIAL ACCESS , T1110.003 , T1110

Program Download , LATERAL MOVEMENT ICS , T0843

Program Upload , COLLECTION ICS , T0845

Remote Access Software , COMMAND AND CONTROL , T1219

Remote Desktop Protocol , LATERAL MOVEMENT , T1021.001 , T1021

Remote System Discovery , DISCOVERY , T1018

Scanning IP Blocks , RECONNAISSANCE , T1595.001 , T1595

Scheduled Transfer , EXFILTRATION , T1029

Spearphishing Attachment , INITIAL ACCESS ICS , T0865

Standard Application Layer Protocol , COMMAND AND CONTROL ICS , T0869

Supply Chain Compromise , INITIAL ACCESS ICS , T0862

User Execution , EXECUTION ICS , T0863

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

Valid Accounts , PERSISTENCE ICS ,  LATERAL MOVEMENT ICS , T0859

Vulnerabilities , RESOURCE DEVELOPMENT , T1588.006 , T1588

Vulnerability Scanning , RECONNAISSANCE , T1595.002 , T1595

Web Protocols , COMMAND AND CONTROL , T1071.001 , T1071

References

1. https://www.intel471.com/blog/threat-hunting-case-study-medusa-ransomware

2. https://www.ransomware.live/group/medusa

3. https://www.cisa.gov/news-events/cybersecurity-advisories/aa25-071a

4. https://www.microsoft.com/en-us/security/blog/2025/10/06/investigating-active-exploitation-of-cve-2025-10035-goanywhere-managed-file-transfer-vulnerability/

5. https://zensec.co.uk/blog/how-rmm-abuse-fuelled-medusa-dragonforce-attacks/

6. https://www.checkpoint.com/cyber-hub/threat-prevention/ransomware/medusa-ransomware-group/

7. https://cyberpress.org/medusa-ransomware-attacks-spike-42/

8. https://blog.barracuda.com/2025/02/25/medusa-ransomware-and-its-cybercrime-ecosystem

10. https://www.cyberdaily.au/security/10021-more-monster-than-myth-unpacking-the-medusa-ransomware-operation

11. https://unit42.paloaltonetworks.com/medusa-ransomware-escalation-new-leak-site/

12. https://www.bitdefender.com/en-us/blog/businessinsights/medusa-ransomware-a-growing-threat-with-a-bold-online-presence

13. https://redpiranha.net/news/medusa-ransomware-everything-you-need-know

14.  https://www.theregister.com/2025/03/13/medusa_ransomware_infects_300_critical/

15. https://www.s-rminform.com/latest-thinking/cyber-threat-advisory-medusa-and-the-simplehelp-vulnerability

16. https://nagomisecurity.com/medusa-ransomware-us-cert-alert

17. https://arcticwolf.com/resources/blog/arctic-wolf-observes-campaign-exploiting-simplehelp-rmm-software-for-initial-access/

18. https://securityboulevard.com/2025/04/medusa-ransomware-inside-the-2025-resurgence-of-one-of-the-internets-most-aggressive-threats/

19. https://thehackernews.com/2025/03/medusa-ransomware-hits-40-victims-in.html

20.  https://www.quorumcyber.com/threat-intelligence/critical-alert-medusa-ransomware-threat-highlighted-by-fbi-cisa-and-ms-isac/

21. https://brandefense.io/blog/stone-gaze-in-depth-analysis-of-medusa-ransomware/

22. https://www.darktrace.com/ja/blog/2025-cyber-threat-landscape-darktraces-mid-year-review

23. https://www.joesandbox.com/analysis/1576447/0/html

24. https://blog.barracuda.com/2025/02/25/medusa-ransomware-and-its-cybercrime-ecosystem

25. https://shassit.mit.edu/news/medusa-ransomware-attacks-on-gmail/

26. https://thehackernews.com/2025/03/medusa-ransomware-uses-malicious-driver.html

27. https://www.cisa.gov/news-events/cybersecurity-advisories/aa25-163a

28. https://www.catonetworks.com/blog/cato-ctrl-investigation-of-rmm-tools/

29. https://redcanary.com/threat-detection-report/trends/rmm-tools/

30. https://www.proofpoint.com/us/blog/threat-insight/remote-monitoring-and-management-rmm-tooling-increasingly-attackers-first-choice

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About the author
Signe Zaharka
Principal Cyber Analyst

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January 8, 2026

How a leading bank is prioritizing risk management to power a resilient future

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As one of the region’s most established financial institutions, this bank sits at the heart of its community’s economic life – powering everything from daily transactions to business growth and long-term wealth planning. Its blend of physical branches and advanced digital services gives customers the convenience they expect and the personal trust they rely on. But as the financial world becomes more interconnected and adversaries more sophisticated, safeguarding that trust requires more than traditional cybersecurity. It demands a resilient, forward-leaning approach that keeps pace with rising threats and tightening regulatory standards.

A complex risk landscape demands a new approach

The bank faced a challenge familiar across the financial sector: too many tools, not enough clarity. Vulnerability scans, pen tests, and risk reports all produced data, yet none worked together to show how exposures connected across systems or what they meant for day-to-day operations. Without a central platform to link and contextualize this data, teams struggled to see how individual findings translated into real exposure across the business.

  • Fragmented risk assessments: Cyber and operational risks were evaluated in silos, often duplicated across teams, and lacked the context needed to prioritize what truly mattered.
  • Limited executive visibility: Leadership struggled to gain a complete, real-time view of trends or progress, making risk ownership difficult to enforce.
  • Emerging compliance pressure: This gap also posed compliance challenges under the EU’s Digital Operational Resilience Act (DORA), which requires financial institutions to demonstrate continuous oversight, effective reporting, and the ability to withstand and recover from cyber and IT disruptions.
“The issue wasn’t the lack of data,” recalls the bank’s Chief Technology Officer. “The challenge was transforming that data into a unified, contextualized picture we could act on quickly and decisively.”

As the bank advanced its digital capabilities and embraced cloud services, its risk environment became more intricate. New pathways for exploitation emerged, human factors grew harder to quantify, and manual processes hindered timely decision-making. To maintain resilience, the security team sought a proactive, AI-powered platform that could consolidate exposures, deliver continuous insight, and ensure high-value risks were addressed before they escalated.

Choosing Darktrace to unlock proactive cyber resilience

To reclaim control over its fragmented risk landscape, the bank selected Darktrace / Proactive Exposure Management™ for cyber risk insight. The solution’s ability to consolidate scanner outputs, pen test results, CVE data, and operational context into one AI-powered view made it the clear choice. Darktrace delivered comprehensive visibility the team had long been missing.

By shifting from a reactive model to proactive security, the bank aimed to:

  • Improve resilience and compliance with DORA
  • Prioritize remediation efforts with greater accuracy
  • Eliminate duplicated work across teams
  • Provide leadership with a complete view of risk, updated continuously
  • Reduce the overall likelihood of attack or disruption

The CTO explains: “We needed a solution that didn’t just list vulnerabilities but showed us what mattered most for our business – how risks connected, how they could be exploited, and what actions would create the biggest reduction in exposure. Darktrace gave us that clarity.”

Targeting the risks that matter most

Darktrace / Proactive Exposure Management offered the bank a new level of visibility and control by continuously analyzing misconfigurations, critical attack paths, human communication patterns, and high-value assets. Its AI-driven risk scoring allowed the team to understand which vulnerabilities had meaningful business impact, not just which were technically severe.

Unifying exposure across architectures

Darktrace aggregates and contextualizes data from across the bank’s security stack, eliminating the need to manually compile or correlate findings. What once required hours of cross-team coordination now appears in a single, continuously updated dashboard.

Revealing an adversarial view of risk

The solution maps multi-stage, complex attack paths across network, cloud, identity systems, email environments, and endpoints – highlighting risks that traditional CVE lists overlook.

Identifying misconfigurations and controlling gaps

Using Self-Learning AI, Darktrace / Proactive Exposure Management spots misconfigurations and prioritizes them based on MITRE adversary techniques, business context, and the bank’s unique digital environment.

Enhancing red-team and pen test effectiveness

By directing testers to the highest-value targets, Darktrace removes guesswork and validates whether defenses hold up against realistic adversarial behavior.

Supporting DORA compliance

From continuous monitoring to executive-ready reporting, the solution provides the transparency and accountability the bank needs to demonstrate operational resilience frameworks.

Proactive security delivers tangible outcomes

Since deploying Darktrace / Proactive Exposure Management, the bank has significantly strengthened its cybersecurity posture while improving operational efficiency.

Greater insight, smarter prioritization, stronger defensee

Security teams are now saving more than four hours per week previously spent aggregating and analyzing risk data. With a unified view of their exposure, they can focus directly on remediation instead of manually correlating multiple reports.

Because risks are now prioritized based on business impact and real-time operational context, they no longer waste time on low-value tasks. Instead, critical issues are identified and resolved sooner, reducing potential windows for exploitation and strengthening the bank’s ongoing resilience against both known and emerging threats.

“Our goal was to move from reactive to proactive security,” the CTO says. “Darktrace didn’t just help us achieve that, it accelerated our roadmap. We now understand our environment with a level of clarity we simply didn’t have before.”

Leadership clarity and stronger governance

Executives and board stakeholders now receive clear, organization-wide visibility into the bank’s risk posture, supported by consistent reporting that highlights trends, progress, and areas requiring attention. This transparency has strengthened confidence in the bank’s cyber resilience and enabled leadership to take true ownership of risk across the institution.

Beyond improved visibility, the bank has also deepened its overall governance maturity. Continuous monitoring and structured oversight allow leaders to make faster, more informed decisions that strategically align security efforts with business priorities. With a more predictable understanding of exposure and risk movement over time, the organization can maintain operational continuity, demonstrate accountability, and adapt more effectively as regulatory expectations evolve.

Trading stress for control

With Darktrace, leaders now have the clarity and confidence they need to report to executives and regulators with accuracy. The ability to see organization-wide risk in context provides assurance that the right issues are being addressed at the right time. That clarity is also empowering security analysts who no longer shoulder the anxiety of wondering which risks matter most or whether something critical has slipped through the cracks. Instead, they’re working with focus and intention, redirecting hours of manual effort into strategic initiatives that strengthen the bank’s overall resilience.

Prioritizing risk to power a resilient future

For this leading financial institution, Darktrace / Proactive Exposure Management has become the foundation for a more unified, data-driven, and resilient cybersecurity program. With clearer, business-relevant priorities, stronger oversight, and measurable efficiency gains, the bank has strengthened its resilience and met demanding regulatory expectations without adding operational strain.

Most importantly, it shifted the bank’s security posture from a reactive stance to a proactive, continuous program. Giving teams the confidence and intelligence to anticipate threats and safeguard the people and services that depend on them.

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About the author
Kelland Goodin
Product Marketing Specialist
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