June 20, 2024

Post-Exploitation Activities on PAN-OS Devices: A Network-Based Analysis

This blog investigates the network-based activity detected by Darktrace in compromises stemming from the exploitation of a vulnerability in Palo Alto Networks firewall devices, namely CVE-2024-3400.

Written by

Adam Potter

Senior Cyber Analyst

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

Adam Potter

Senior Cyber Analyst

Jun 2024

Update:
Following the initial publication of this blog detailing exploitation campaigns utilizing the recently disclosed vulnerability, Darktrace analysts expanded the scope of the threat research investigation to identify potential earlier, pre-CVE disclosure, exploitation of CVE 2024-3400. While the majority of PAN-OS exploitation activity seen in the Darktrace customer base occurred after the public release of the CVE, Darktrace did also see tooling activity likely related to CVE-2024-3400 exploitation prior to the vulnerability's disclosure. Unlike the post-CVE-release exploitation activity, which largely reflected indiscriminate, opportunistic targeting of unpatched systems, these pre-CVE release activities likely represented selective targeting by more calculated actors.

Between March 26 and 28, Darktrace identified two Palo Alto firewall devices within the network of a public sector customer making HTTP GET requests utilizing both cURL and wget user agents, versions of which were seen in later compromise activity in April. The devices requested multiple shell script files (.sh) from rare external IP addresses. These IPs are likely associated with an operational relay box (ORB) network^[1]. The connections also occurred without a specified hostname lookup, suggesting the IPs were hardcoded into process code or already cached through unexpected running processes. One of the destination IPs was later confirmed by Palo Alto Network’s Unit 42 as associated with exploitation of the PAN-OS vulnerability^[2]. This observed activity closely resembles post-exploitation activity seen on affected firewall devices in mid-April. However, unlike the more disruptive and noisier follow-on exploitation activity seen in post-CVE-release incidents, the pre-CVE-release case observed by Darktrace appears to have been much more discreet, likely due to the relevant threat actor's desire to remain undetected.

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Introduction

Perimeter devices such as firewalls, virtual private networks (VPNs), and intrusion prevention systems (IPS), have long been the target of adversarial actors attempting to gain access to internal networks. However, recent publications and public service announcements by leading public institutions underscore the increased emphasis threat actors are putting on leveraging such products to initiate compromises.

A blog post by the UK National Cyber Security Center (NCSC) released in early 2024 notes that as improvements are made in the detection of phishing email payloads, threat actors have again begun re-focusing efforts to exploiting network edge devices, many of which are not secure by design, as a means of breach initiation.^[i] As such, it comes as no surprise that new Common Vulnerabilities and Exposures (CVEs) are constantly discovered that exploit such internet-exposed systems.

Darktrace analysts frequently observe the impacts of such CVEs first through their investigations via Darktrace’s Security Operations Center (SOC). Beginning in April 2024, Darktrace’s SOC began handling alerts and customer requests for potential incidents involving Palo Alto Networks firewall devices. Just days prior, external researchers publicly disclosed what would later be classified as PAN-OS CVE-2024-3400, a form of remote command execution vulnerability that affects several versions of Palo Alto Networks’ firewall operating system (PAN-OS), namely PAN-OS 11.1, 11.0 and 10.2. At the time, multiple Darktrace customers were unaware of the recently announced vulnerability.

The increase in observed SOC activity for Palo Alto firewall devices, coupled with the public announcement of the new CVE prompted Darktrace researchers to look for evidence of PAN-OS exploitation on customer networks. Researchers also focused on documenting post-exploitation activity from threat actors leveraging the recently disclosed vulnerability.

As such, this blog highlights the network-based behaviors involved in the CVE-2024-3400 attack chains investigated by Darktrace’s SOC and Threat Research teams. Moreover, this investigation also provides a deeper insight into the post-compromise activities of threat actors leveraging the novel CVE. Such insights will not only prove relevant for cybersecurity teams looking to inhibit compromises in this specific instance, but also highlights general patterns of behavior by threat actors utilizing such CVEs to target internet-facing systems.

CVE-2024-3400

In mid-April 2024, the Darktrace SOC observed an uptick in activity involving recurring patterns of malicious activity from Palo Alto firewall appliances. In response to this trend, Darktrace initiated a Threat Research investigation into such activity to try and identify common factors and indicators across seemingly parallel events. Shortly before the Threat Research team opened their investigation, external researchers provided public details of CVE-2024-3400, a form of remote command execution vulnerability in the GlobalProtect feature on Palo Alto Network firewall devices running PAN-OS versions: 10.2, 11.0, and 11.1.^[ii]

In their proof of concept, security researchers at watchTowr demonstrated how an attacker can pass session ID (SESSID) values to these PAN-OS devices to request files that do not exist. In response, the system creates a zero-byte file with root privileges with the same name.^[iii] Log data is passed on devices running telemetry services to external servers through command line functionality.^[iv] Given this functionality, external actors could then request non-existent files in the SESSID containing command parameters which then be interpreted by the command line functionality.^[v] Although researchers first believed the exploit could only be used against devices running telemetry services, this was later discovered to be untrue.^[vi]

As details of CVE-2024-3400 began to surface, Darktrace’s Threat Research analysts quickly identified distinct overlaps in the observed activity on specific customer deployments and the post-exploitation behavior reported by external researchers. Given the parallels, Darktrace correlated the patterns of activity observed by the SOC team to exploitation of the newly discovered vulnerability in PAN-OS firewall appliances.

Campaign Analysis

Between the April and May 2024, Darktrace identified four main themes of post-exploitation activity involving Palo Alto Network firewall devices likely targeted via CVE-2024-3400: exploitation validation, shell command and tool retrieval, configuration data exfiltration, and ongoing command and control through encrypted channels and application protocols.

1. Exploit Validation and Further Vulnerability Enumeration

Many of the investigated attack chains began with malicious actors using out-of-band application security testing (OAST) services such as Interactsh to validate exploits against Palo Alto firewall appliances. This exploit validation activity typically resulted in devices attempting to contact unusual external endpoints (namely, subdomains of ‘oast[.]pro’, ‘oast[.]live’, ‘oast[.]site’, ‘oast[.]online’, ‘oast[.]fun’, ‘oast[.]me’, and ‘g3n[.]in’) associated with OAST services such as Interactsh. These services can be used by developers to inspect and debug internet traffic, but also have been easily abused by threat actors.

While attempted connections to OAST services do not alone indicate CVE-2024-3400 exploitation, the prevalence of such activities in observed Palo Alto firewall attack chains suggests widespread usage of these OAST services to validate initial access methods and possibly further enumerate systems for additional vulnerabilities.

Figure 1: Model alert log details showcasing a PAN-OS device making DNS queries for Interactsh domain names in what could be exploit validation, and/or further host enumeration.

2. Command and Payload Transmission

The most common feature across analyzed incidents was HTTP GET requests for shell scripts and Linux executable files (ELF) from external IPs associated with exploitation of the CVE. These HTTP requests were frequently initiated using the utilities, cURL and wget. On nearly every device likely targeted by threat actors leveraging the CVE, Darktrace analysts highlighted the retrieval of shell scripts that either featured enumeration commands, the removal of evidence of compromise activity, or commands to retrieve and start binaries on the destination device.

a) Shell Script Retrieval

Investigated devices commonly performed HTTP GET requests to retrieve shell command scripts. Despite this commonality, there was some degree of variety amongst the retrieved payloads and their affiliation with certain command tools. Several distinct types of shell commands and files were identified during the analyzed breaches. For example, some firewall devices were seen requesting .txt files associated with both Sliver C2, whose malicious use has previously been investigated by Darktrace, and Cobalt Strike. The target URIs of devices’ HTTP requests for these files included, “36shr.txt”, “2.txt”, “bin.txt”, and “data.txt”.

More interestingly, though, was the frequency with which analyzed systems requested bash scripts from rare external IP addresses, sometimes over non-standard ports for the HTTP protocol. These bash scripts would feature commands usually for the recipient system to check for certain existing files and or running processes. If the file did not exist, the system would then use cURL or wget to obtain content from external sites, change the permissions of the file, and then execute, sending output to dev/null as a means of likely defense evasion. In some scripts, the system would first make a new folder, and change directories prior to acquiring external content. Additionally, some samples highlighted multiple attempts at enumeration of the host system.

Figure 2: Packet capture (PCAP) data highlighting the incoming shell scripts providing instructions to use cURL to obtain external content, change the permissions of the file to execute, and then run the binary using the credentials and details provided.

Figure 3: PCAP data highlighting a variation of a shell script seen in an HTTP response processed by compromised devices. The script provides instructions to make a directory, retrieve and execute external content, and to hide the output.

Not every retrieved file that was not explicitly a binary featured bash scripts. Model alerts on some deployments also included file masquerading attempts by threat actors, whereby the Palo Alto firewall device would request content with a misleading extension in the URI. In one such instance, the requested URI, and HTTP response header suggests the returned content is an image/png, but the actual body response featured configuration parameters for a new daemon service to be run on the system.

Figure 4: PCAP data indicating configuration details likely for a new daemon on an investigated host. Such HTTP body content differs from the image/png extension within the request URI and declared content type in the HTTP response header.

Bash scripts analyzed across customer deployments also mirrored those identified by external security teams. External researchers previously reported on a series of identifiable shell commands in some cases of CVE-2024-3400 exploitation analyzed by their teams. Commands frequently involved a persistence mechanism they later labeled as the “UPSTYLE” backdoor.^[vii] This python-based program operates by reading commands hidden in error logs generated by 404 requests to the compromised server. The backdoor interprets the requests and writes the output to CSS files on the device. In many cases, Darktrace’s Threat Research team noted clear parallels between shell commands retrieved via HTTP GET request with those directly involving UPSTYLE. There were also matches with some URI patterns identified with the backdoor and requests observed on Darktrace deployments.

Figure 5: HTTP response data containing shell commands potentially relating to the UPSTYLE backdoor.

The presence of these UPSTYLE-related shell commands in response to Palo Alto firewall devices’ HTTP requests provides further evidence for initial exploitation of the CVE. Many bash scripts in examined cases interacted with folders and files likely related to CVE-2024-3400 exploitation. These scripts frequently sought to delete contents of certain folders, such as “/opt/panlogs/tmp/device_telemetry/minute/*” where evidence of exploitation would likely reside. Moreover, recursive removal and copy commands were frequently seen targeting CSS files within the GlobalProtect folder, already noted as the vulnerable element within PAN-OS versions. This evidence is further corroborated by host-based forensic analysis conducted by external researchers.^[viii]

Figure 6: PCAP data from investigated system indicating likely defense evasion by removing content on folders where CVE exploitation occurred.

b) Executable File Retrieval

Typically, following command processing, compromised Palo Alto firewall devices proceeded to make web requests for several unusual and potentially malicious files. Many such executables would be retrieved via processed scripts. While there a fair amount of variety in specific executables and binaries obtained, overall, these executables involved either further command tooling such as Sliver C2 or Cobalt Strike payloads, or unknown executables. Affected systems would also employ uncommon ports for HTTP connections, in a likely attempt to evade detection. Extensions featured within the URI, when visible, frequently noted ‘.elf’ (Linux executable) or ‘.exe’ payloads. While most derived hashes did not feature identifiable open-source intelligence (OSINT) details, some samples did have external information tying the sample to specific malware. For example, one such investigation featured a compromised system requesting a file with a hash identified as the Spark malware (backdoor) while another investigated case included a host requesting a known crypto-miner.

Figure 7: PCAP data highlighting compromised system retrieving ELF content from a rare external server running a simple Python HTTP server.

Figure 8: Darktrace model alert logs highlighting a device labeled “Palo Alto” making a HTTP request on an uncommon port for an executable file following likely CVE exploitation.

3. Configuration Data Exfiltration and Unusual HTTP POST Activity

During Darktrace’s investigations, there were also several instances of sensitive data exfiltration from PAN-OS firewall devices. Specifically, targeted systems were observed making HTTP POST requests via destination port 80 to rare external endpoints that OSINT sources associate with CVE-2024-3400 exploitation and activity. PCAP analysis of such HTTP requests revealed that they often contained sensitive configuration details of the targeted Palo Alto firewall devices, including the IP address, default gateway, domain, users, superusers, and password hashes, to name only a few. Threat actors frequently utilized Target URIs such as “/upload” in their HTTP POST requests of this multi-part boundary form data. Again, the User-Agent headers of these HTTP requests largely involved versions of cURL, typically 7.6.1, and wget.

Figure 9: PCAP datahighlighting Palo Alto Firewall device running vulnerable version of PAN-OSposting configuration details to rare external services via HTTP.

Figure 10: Model alert logs highlighting a Palo Alto firewall device performing HTTP POSTs to a rare external IP, without a prior hostname lookup, on an uncommon port using a URI associated with configuration data exfiltration across analyzed incidents

Figure 11: Examples of TargetURIs of HTTP POST requests involving base64 encoded IPs and potential dataegress.

4. Ongoing C2 and Miscellaneous Activity

Lastly, a smaller number of affected Palo Alto firewall devices were seen engaging in repeated beaconing and/or C2 communication via both encrypted and unencrypted protocols during and following the initial series of kill chain events. Such encrypted channels typically involved protocols such as TLS/SSL and SSH. This activity likely represented ongoing communication of targeted systems with attacker infrastructure. Model alerts typically highlighted unusual levels of repeated external connectivity to rare external IP addresses over varying lengths of time. In some investigated incidents, beaconing activity consisted of hundreds of thousands of connections over several days.

Figure 12: Advanced search details highlighting high levels of ongoing external communication to endpoints associated with C2 infrastructure exploiting CVE-2024-3400.

Some beaconing activity appears to have involved the use of the WebSocket protocol, as indicated by the appearance of “/ws” URIs and validated within packet captures. Such connections were then upgraded to an encrypted connection.

Figure 13: PCAP highlighting use of WebSocket protocol to engage in ongoing external connectivity to likely C2 infrastructure following CVE-2024-3400 compromise.

While not directly visible in all the deployments, some investigations also yielded evidence of attempts at further post-exploitation activity. For example, a handful of the analyzed binaries that were downloaded by examined devices had OSINT information suggesting a relation to crypto-mining malware strains. However, crypto-mining activity was not directly observed at this time. Furthermore, several devices also triggered model alerts relating to brute-forcing activity via several authentication protocols (namely, Keberos and RADIUS) during the time of compromise. This brute-force activity likely represented attempts to move laterally from the affected firewall system to deeper parts of the network.

Figure 14: Model alert logs noting repeated SSL connectivity to a Sliver C2-affiliated endpoint in what likely constitutes C2 connectivity.

Figure 15: Model alert logs featuring repeated RADIUS login failures from a compromised PAN-OS device using generic usernames, suggesting brute-force activity.

Conclusion

Between April and late May 2024, Darktrace’s SOC and Threat Research teams identified several instances of likely PAN-OS CVE-2024-3400 exploitation across the Darktrace customer base. The subsequent investigation yielded four major themes that categorize the observed network-based post-exploitation activity. These major themes were exploit validation activity, retrieval of binaries and shell scripts, data exfiltration via HTTP POST activity, and ongoing C2 communication with rare external endpoints. The insights shared in this article will hopefully contribute to the ongoing discussion within the cybersecurity community about how to handle the likely continued exploitation of this vulnerability. Moreover, this article may also help cybersecurity professionals better respond to future exploitation of not only Palo Alto PAN-OS firewall devices, but also of edge devices more broadly.

Threat actors will continue to discover and leverage new CVEs impacting edge infrastructure. Since it is not yet known which CVEs threat actors will exploit next, relying on rules and signatures for the detection of exploitation of such CVEs is not a viable approach. Darktrace’s anomaly-based approach to threat detection, however, is well positioned to robustly adapt to threat actors’ changing methods, since although threat actors can change the CVEs they exploit, they cannot change the fact that their exploitation of CVEs results in highly unusual patterns of activity.

Credit to Adam Potter, Cyber Analyst, Sam Lister, Senior Cyber Analyst

Appendices ‍

Pre-CVE-Release IoCs

38.54[.]104[.]14/3.sh
154.223[.]16[.]34/1.sh
154.223[.]16[.]34/co.sh
38.54[.]104[.]14/

Indicators of Compromise

Indicator – Type – Description

94.131.120[.]80 IP C2 Endpoint

94.131.120[.]80:53/?src=[REDACTED]=hour=root URL C2/Exfiltration Endpoint

134.213.29[.]14/?src=[REDACTED]min=root URL C2/Exfiltration Endpoint

134.213.29[.]14/grep[.]mips64 URL Payload

134.213.29[.]14/grep[.]x86_64 URL Payload

134.213.29[.]14/?deer URL Payload

134.213.29[.]14/?host=IDS URL Payload

134.213.29[.]14/ldr[.]sh URL Payload

91ebcea4e6d34fd6e22f99713eaf67571b51ab01 SHA1 File Hash Payload

185.243.115[.]250/snmpd2[.]elf URL Payload

23.163.0[.]111/com URL Payload

80.92.205[.]239/upload URL C2/Exfiltration Endpoint

194.36.171[.]43/upload URL C2/Exfiltration Endpoint

update.gl-protect[.]com Hostname C2 Endpoint

update.gl-protect[.]com:63869/snmpgp URL Payload

146.70.87[.]237 IP address C2 Endpoint

146.70.87[.]237:63867/snmpdd URL Payload

393c41b3ceab4beecf365285e8bdf0546f41efad SHA1 File Hash Payload

138.68.44[.]59/app/r URL Payload

138.68.44[.]59/app/clientr URL Payload

138.68.44[.]59/manage URL Payload

72.5.43[.]90/patch URL Payload

217.69.3[.]218 IP C2 Endpoint

5e8387c24b75c778c920f8aa38e4d3882cc6d306 SHA1 File Hash Payload

217.69.3[.]218/snmpd[.]elf URL Payload

958f13da6ccf98fcaa270a6e24f83b1a4832938a SHA1 File Hash Payload

6708dc41b15b892279af2947f143af95fb9efe6e SHA1 File Hash Payload

dc50c0de7f24baf03d4f4c6fdf6c366d2fcfbe6c SHA1 File Hash Payload

109.120.178[.]253:10000/data[.]txt URL Payload

109.120.178[.]253:10000/bin[.]txt URL Payload

bc9dc2e42654e2179210d98f77822723740a5ba6 SHA1 File Hash Payload

109.120.178[.]253:10000/123 URL Payload

65283921da4e8b5eabb926e60ca9ad3d087e67fa SHA1 File Hash Payload

img.dxyjg[.]com/6hiryXjZN0Mx[.]sh URL Payload

149.56.18[.]189/IC4nzNvf7w/2[.]txt URL Payload

228d05fd92ec4d19659d71693198564ae6f6b117 SHA1 File Hash Payload

54b892b8fdab7c07e1e123340d800e7ed0386600 SHA1 File Hash Payload

165.232.121[.]217/rules URL Payload

165.232.121[.]217/app/request URL Payload

938faec77ebdac758587bba999e470785253edaf SHA1 File Hash Payload

165.232.121[.]217/app/request63 URL Payload

165.232.121[.]217:4443/termite/165.232.121[.]217 URL Payload

92.118.112[.]60/snmpd2[.]elf URL Payload

2a90d481a7134d66e8b7886cdfe98d9c1264a386 SHA1 File Hash Payload

92.118.112[.]60/36shr[.]txt URL Payload

d6a33673cedb12811dde03a705e1302464d8227f SHA1 File Hash Payload

c712712a563fe09fa525dfc01ce13564e3d98d67 SHA1 File Hash Payload

091b3b33e0d1b55852167c3069afcdb0af5e5e79 SHA1 File Hash Payload

5eebf7518325e6d3a0fd7da2c53e7d229d7b74b6 SHA1 File Hash Payload

183be7a0c958f5ed4816c781a2d7d5aa8a0bca9f SHA1 File Hash Payload

e7d2f1224546b17d805617d02ade91a9a20e783e SHA1 File Hash Payload

e6137a15df66054e4c97e1f4b8181798985b480d SHA1 File Hash Payload

95.164.7[.]33:53/sea[.]png URL Payload

95.164.7[.]33/rules URL Payload

95.164.7[.]33:53/lb64 URL Payload

c2bc9a7657bea17792048902ccf2d77a2f50d2d7 SHA1 File Hash Payload

923369bbb86b9a9ccf42ba6f0d022b1cd4f33e9d SHA1 File Hash Payload

52972a971a05b842c6b90c581b5c697f740cb5b9 SHA1 File Hash Payload

95d45b455cf62186c272c03d6253fef65227f63a SHA1 File Hash Payload

322ec0942cef33b4c55e5e939407cd02e295973e SHA1 File Hash Payload

6335e08873b4ca3d0eac1ea265f89a9ef29023f2 SHA1 File Hash Payload

134.213.29[.]14 IP C2 Endpoint

185.243.115[.]250 IP C2 Endpoint

80.92.205[.]239 IP C2 Endpoint

194.36.171[.]43 IP C2 Endpoint

92.118.112[.]60 IP C2 Endpoint

109.120.178[.]253 IP C2 Endpoint

23.163.0[.]111 IP C2 Endpoint

72.5.43[.]90 IP C2 Endpoint

165.232.121[.]217 IP C2 Endpoint

8.210.242[.]112 IP C2 Endpoint

149.56.18[.]189 IP C2 Endpoint

95.164.7[.]33 IP C2 Endpoint

138.68.44[.]59 IP C2 Endpoint

Img[.]dxyjg[.]com Hostname C2 Endpoint

Darktrace Model Alert Coverage

· Anomalous Connection / New User Agent to IP Without Hostname

· Device / New User Agent (triggered by pre-CVE-release activity)

· Anomalous File / Script from Rare External Location (triggered by pre-CVE-release activity)

· Anomalous File / Masqueraded File Transfer

· Anomalous File / EXE from Rare External Location

· Anomalous File / Multiple EXE from Rare External Locations

· Anomalous File / Script and EXE from Rare External

· Anomalous File / Suspicious Octet Stream Download

· Anomalous File / Numeric File Download

· Anomalous Connection / Application Protocol on Uncommon Port

· Anomalous Connection / Posting HTTP to IP Without Hostname

· Anomalous Connection / Multiple Failed Connections to Rare Endpoint

· Anomalous Connection / Suspicious Self-Signed SSL

· Anomalous Connection / Anomalous SSL without SNI to New External

· Anomalous Connection / Multiple Connections to New External TCP Port

· Anomalous Connection / Rare External SSL Self-Signed

· Anomalous Server Activity / Outgoing from Server

· Anomalous Server Activity / Rare External from Server

· Compromise / SSH Beacon

· Compromise / Beacon for 4 Days

· Compromise / Sustained TCP Beaconing Activity To Rare Endpoint

· Compromise / High Priority Tunnelling to Bin Services

· Compromise / Sustained SSL or HTTP Increase

· Compromise / Connection to Suspicious SSL Server

· Compromise / Suspicious File and C2

· Compromise / Large Number of Suspicious Successful Connections

· Compromise / Slow Beaconing Activity To External Rare

· Compromise / HTTP Beaconing to New Endpoint

· Compromise / SSL or HTTP Beacon

· Compromise / Suspicious HTTP and Anomalous Activity

· Compromise / Beacon to Young Endpoint

· Compromise / High Volume of Connections with Beacon Score

· Compromise / Suspicious Beaconing Behaviour

· Compliance / SSH to Rare External Destination

· Compromise / HTTP Beaconing to Rare Destination

· Compromise / Beaconing Activity To External Rare

· Device / Initial Breach Chain Compromise

· Device / Multiple C2 Model Breaches

MITRE ATTACK Mapping

Tactic – Technique

Initial Access T1190 – Exploiting Public-Facing Application

Execution T1059.004 – Command and Scripting Interpreter: Unix Shell

Persistence T1543.002 – Create or Modify System Processes: Systemd Service

Defense Evasion T1070.004 – Indicator Removal: File Deletion

Credential Access T1110.001 – Brute Force: Password Guessing

Discovery T1083 – File and System Discovery

T1057 – Process Discovery

Collection T1005 – Data From Local System

Command and Control

T1071.001 – Application Layer Protocol: Web Protocols

T1573.002 – Encrypted Channel: Asymmetric Cryptography

T1571 – Non-Standard Port

T1105 – Ingress Tool Transfer

Exfiltration

T1041 – Exfiltration over C2 Protocol

T1048.002 - Exfiltration Over Alternative Protocol: Exfiltration Over Asymmetric Encrypted Non-C2 Protocol

References

[1] https://cloud.google.com/blog/topics/threat-intelligence/china-nexus-espionage-orb-networks

[2] https://unit42.paloaltonetworks.com/cve-2024-3400/

^[i] https://www.ncsc.gov.uk/blog-post/products-on-your-perimeter

^[ii] https://security.paloaltonetworks.com/CVE-2024-3400

^[iii] https://labs.watchtowr.com/palo-alto-putting-the-protecc-in-globalprotect-cve-2024-3400/

^[iv] https://labs.watchtowr.com/palo-alto-putting-the-protecc-in-globalprotect-cve-2024-3400/

^[v] https://labs.watchtowr.com/palo-alto-putting-the-protecc-in-globalprotect-cve-2024-3400/

^[vi] https://security.paloaltonetworks.com/CVE-2024-3400

^[vii] https://www.volexity.com/blog/2024/04/12/zero-day-exploitation-of-unauthenticated-remote-code-execution-vulnerability-in-globalprotect-cve-2024-3400/

^[viii] https://www.volexity.com/blog/2024/05/15/detecting-compromise-of-cve-2024-3400-on-palo-alto-networks-globalprotect-devices/

‍

Written by

Adam Potter

Senior Cyber Analyst

Inside the SOC

Written by

Adam Potter

Senior Cyber Analyst

Principal Cyber Analyst

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January 8, 2026

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

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].

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).

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.

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.

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].

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

About the author

Signe Zaharka

Principal Cyber Analyst

Blog

Proactive Security

January 8, 2026

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

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.

‍

About the author

Kelland Goodin

Product Marketing Specialist

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Check out this article by Darktrace: Post-Exploitation Activities on PAN-OS Devices: A Network-Based Analysis

Post-Exploitation Activities on PAN-OS Devices: A Network-Based Analysis

Introduction

CVE-2024-3400

Campaign Analysis

1. Exploit Validation and Further Vulnerability Enumeration

2. Command and Payload Transmission

a) Shell Script Retrieval

b) Executable File Retrieval

3. Configuration Data Exfiltration and Unusual HTTP POST Activity

4. Ongoing C2 and Miscellaneous Activity

Conclusion

Appendices ‍

Pre-CVE-Release IoCs

Indicators of Compromise

Darktrace Model Alert Coverage

MITRE ATTACK Mapping

References

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

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

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Network

January 8, 2026

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

What is Medusa Ransomware in 2025?

Madusa Ransomware history and background

Who does Madusa Ransomware target?

Madusa Ransomware TTPs

Darktrace’s Coverage of Medusa Ransomware

Remote Monitoring and Management (RMM) tool abuse

Data exfiltration

Medusa Compromise Leveraging SimpleHelp

Conclusion

Appendices

List of Indicators of Compromise (IoCs)

Darktrace Model Coverage

Autonomous Response Actions

MITRE ATT&CK Mapping

References

Blog

Proactive Security

January 8, 2026

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

A complex risk landscape demands a new approach

Choosing Darktrace to unlock proactive cyber resilience

Targeting the risks that matter most

Unifying exposure across architectures

Revealing an adversarial view of risk

Identifying misconfigurations and controlling gaps

Enhancing red-team and pen test effectiveness

Supporting DORA compliance

Proactive security delivers tangible outcomes

Greater insight, smarter prioritization, stronger defensee

Leadership clarity and stronger governance

Trading stress for control

Prioritizing risk to power a resilient future