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June 10, 2024

Medusa Ransomware: Looking Cyber Threats in the Eye with Darktrace

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10
Jun 2024
This blog investigates Medusa ransomware, a Ransomware-as-a-Service (RaaS) variant that is known to use living off the land techniques to infect target networks and move towards its ultimate goals, data encryption and exfiltration.

What is Living off the Land attack?

In the face of increasingly vigilant security teams and adept defense tools, attackers are continually looking for new ways to circumvent network security and gain access to their target environments. One common tactic is the leveraging of readily available utilities and services within a target organization’s environment in order to move through the kill chain; a popular method known as living off the land (LotL). Rather than having to leverage known malicious tools or write their own malware, attackers are able to easily exploit the existing infrastructure of their targets.

The Medusa ransomware group in particular are known to extensively employ LotL tactics, techniques and procedures (TTPs) in their attacks, as one Darktrace customer in the US discovered in early 2024.

What is Medusa Ransomware?

Medusa ransomware (not to be confused with MedusaLocker) was first observed in the wild towards the end of 2022 and has been a popular ransomware strain amongst threat actors since 2023 [1]. Medusa functions as a Ransomware-as-a-Service (RaaS) platform, providing would-be attackers, also know as affiliates, with malicious software and infrastructure required to carry out disruptive ransomware attacks. The ransomware is known to target organizations across many different industries and countries around the world, including healthcare, education, manufacturing and retail, with a particular focus on the US [2].

How does Medusa Ransomware work?

Medusa affiliates are known to employ a number of TTPs to propagate their malware, most predominantly gaining initial access by exploiting vulnerable internet-facing assets and targeting valid local and domain accounts that are used for system administration.

The ransomware is typically delivered via phishing and spear phishing campaigns containing malicious attachments [3] [4], but it has also been observed using initial access brokers to access target networks [5]. In terms of the LotL strategies employed in Medusa compromises, affiliates are often observed leveraging legitimate services like the ConnectWise remote monitoring and management (RMM) software and PDQ Deploy, in order to evade the detection of security teams who may be unable to distinguish the activity from normal or expected network traffic [2].

According to researchers, Medusa has a public Telegram channel that is used by threat actors to post any data that may have been stolen, likely in an attempt to extort organizations and demand payment [2].  

Darktrace’s Coverage of Medusa Ransomware

Established Foothold and C2 activity

In March 2024, Darktrace / NETWORK identified over 80 devices, including an internet facing domain controller, on a customer network performing an unusual number of activities that were indicative of an emerging ransomware attack. The suspicious behavior started when devices were observed making HTTP connections to the two unusual endpoints, one of which is “go-sw6-02.adventos[.]de”, with the PowerShell and JWrapperDownloader user agents.

Darktrace’s Cyber AI Analyst™ launched an autonomous investigation into the connections and was able to connect the seemingly separate events into one wider incident spanning multiple different devices. This allowed the customer to visualize the activity in chronological order and gain a better understanding of the scope of the attack.

At this point, given the nature and rarity of the observed activity, Darktrace /NETWORK's autonomous response would have been expected to take autonomous action against affected devices, blocking them from making external connections to suspicious locations. However, autonomous response was not configured to take autonomous action at the time of the attack, meaning any mitigative actions had to be manually approved by the customer’s security team.

Internal Reconnaissance

Following these extensive HTTP connections, between March 1 and 7, Darktrace detected two devices making internal connection attempts to other devices, suggesting network scanning activity. Furthermore, Darktrace identified one of the devices making a connection with the URI “/nice ports, /Trinity.txt.bak”, indicating the use of the Nmap vulnerability scanning tool. While Nmap is primarily used legitimately by security teams to perform security audits and discover vulnerabilities that require addressing, it can also be leveraged by attackers who seek to exploit this information.

Darktrace / NETWORK model alert showing the URI “/nice ports, /Trinity.txt.bak”, indicating the use of Nmap.
Figure 1: Darktrace /NETWORK model alert showing the URI “/nice ports, /Trinity.txt.bak”, indicating the use of Nmap.

Darktrace observed actors using multiple credentials, including “svc-ndscans”, which was also seen alongside DCE-RPC activity that took place on March 1. Affected devices were also observed making ExecQuery and ExecMethod requests for IWbemServices. ExecQuery is commonly utilized to execute WMI Query Language (WQL) queries that allow the retrieval of information from WI, including system information or hardware details, while ExecMethod can be used by attackers to gather detailed information about a targeted system and its running processes, as well as a tool for lateral movement.

Lateral Movement

A few hours after the first observed scanning activity on March 1, Darktrace identified a chain of administrative connections between multiple devices, including the aforementioned internet-facing server.

Cyber AI Analyst was able to connect these administrative connections and separate them into three distinct ‘hops’, i.e. the number of administrative connections made from device A to device B, including any devices leveraged in between. The AI Analyst investigation was also able to link the previously detailed scanning activity to these administrative connections, identifying that the same device was involved in both cases.

Cyber AI Analyst investigation into the chain of lateral movement activity.
Figure 2: Cyber AI Analyst investigation into the chain of lateral movement activity.

On March 7, the internet exposed server was observed transferring suspicious files over SMB to multiple internal devices. This activity was identified as unusual by Darktrace compared to the device's normal SMB activity, with an unusual number of executable (.exe) and srvsvc files transferred targeting the ADMIN$ and IPC$ shares.

Cyber AI Analyst investigation into the suspicious SMB write activity.
Figure 3: Cyber AI Analyst investigation into the suspicious SMB write activity.
Graph highlighting the number of successful SMB writes and the associated model alerts.
Figure 4: Graph highlighting the number of successful SMB writes and the associated model alerts.

The threat actor was also seen writing SQLite3*.dll files over SMB using a another credential this time. These files likely contained the malicious payload that resulted in the customer’s files being encrypted with the extension “.s3db”.

Darktrace’s visibility over an affected device performing successful SMB writes.
Figure 5: Darktrace’s visibility over an affected device performing successful SMB writes.

Encryption of Files

Finally, Darktrace observed the malicious actor beginning to encrypt and delete files on the customer’s environment. More specifically, the actor was observed using credentials previously seen on the network to encrypt files with the aforementioned “.s3db” extension.

Darktrace’s visibility over the encrypted files.
Figure 6: Darktrace’s visibility over the encrypted files.


After that, Darktrace observed the attacker encrypting  files and appending them with the extension “.MEDUSA” while also dropping a ransom note with the file name “!!!Read_me_Medusa!!!.txt”

Darktrace’s detection of threat actors deleting files with the extension “.MEDUSA”.
Figure 7: Darktrace’s detection of threat actors deleting files with the extension “.MEDUSA”.
Darktrace’s detection of the Medusa ransom note.
Figure 8: Darktrace’s detection of the Medusa ransom note.

At the same time as these events, Darktrace observed the attacker utilizing a number of LotL techniques including SSL connections to “services.pdq[.]tools”, “teamviewer[.]com” and “anydesk[.]com”. While the use of these legitimate services may have bypassed traditional security tools, Darktrace’s anomaly-based approach enabled it to detect the activity and distinguish it from ‘normal’ network activity. It is highly likely that these SSL connections represented the attacker attempting to exfiltrate sensitive data from the customer’s network, with a view to using it to extort the customer.

Cyber AI Analyst’s detection of “services.pdq[.]tools” usage.
Figure 9: Cyber AI Analyst’s detection of “services.pdq[.]tools” usage.

If this customer had been subscribed to Darktrace's Proactive Threat Notification (PTN) service at the time of the attack, they would have been promptly notified of these suspicious activities by the Darktrace Security Operation Center (SOC). In this way they could have been aware of the suspicious activities taking place in their infrastructure before the escalation of the compromise. Despite this, they were able to receive assistance through the Ask the Expert service (ATE) whereby Darktrace’s expert analyst team was on hand to assist the customer by triaging and investigating the incident further, ensuring the customer was well equipped to remediate.  

As Darktrace /NETWORK's autonomous response was not enabled in autonomous response mode, this ransomware attack was able to progress to the point of encryption and data exfiltration. Had autonomous response been properly configured to take autonomous action, Darktrace would have blocked all connections by affected devices to both internal and external endpoints, as well as enforcing a previously established “pattern of life” on the device to stop it from deviating from its expected behavior.

Conclusion

The threat actors in this Medusa ransomware attack attempted to utilize LotL techniques in order to bypass human security teams and traditional security tools. By exploiting trusted systems and tools, like Nmap and PDQ Deploy, attackers are able to carry out malicious activity under the guise of legitimate network traffic.

Darktrace’s Self-Learning AI, however, allows it to recognize the subtle deviations in a device’s behavior that tend to be indicative of compromise, regardless of whether it appears legitimate or benign on the surface.

Further to the detection of the individual events that made up this ransomware attack, Darktrace’s Cyber AI Analyst was able to correlate the activity and collate it under one wider incident. This allowed the customer to track the compromise and its attack phases from start to finish, ensuring they could obtain a holistic view of their digital environment and remediate effectively.

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  • Identity-based attacks: How attackers are bypassing traditional defenses
  • Zero-day exploitation: The rise of previously unknown vulnerabilities
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Appendices

Credit to Maria Geronikolou, Cyber Analyst, Ryan Traill, Threat Content Lead

Darktrace DETECT Model Detections

Anomalous Connection / SMB Enumeration

Device / Anomalous SMB Followed By Multiple Model Alerts

Device / Suspicious SMB Scanning Activity

Device / Attack and Recon Tools

Device / Suspicious File Writes to Multiple Hidden SMB Share

Compromise / Ransomware / Ransom or Offensive Words Written to SMB

Device / Internet Facing Device with High Priority Alert

Device / Network Scan

Anomalous Connection / Powershell to Rare External

Device / New PowerShell User Agent

Possible HTTP Command and Control

Extensive Suspicious DCE-RPC Activity

Possible SSL Command and Control to Multiple Endpoints

Suspicious Remote WMI Activity

Scanning of Multiple Devices

Possible Ransom Note Accessed over SMB

List of Indicators of Compromise (IoCs)

IoC – Type – Description + Confidence

207.188.6[.]17      -     IP address   -      C2 Endpoint

172.64.154[.]227 - IP address -        C2 Endpoint

go-sw6-02.adventos[.]de.  Hostname  - C2 Endpoint

.MEDUSA             -        File extension     - Extension to encrypted files

.s3db               -             File extension    -  Created file extension

SQLite3-64.dll    -        File           -               Used tool

!!!Read_me_Medusa!!!.txt - File -   Ransom note

Svc-ndscans         -         Credential     -     Possible compromised credential

Svc-NinjaRMM      -       Credential      -     Possible compromised credential

MITRE ATT&CK Mapping

Discovery  - File and Directory Discovery - T1083

Reconnaissance    -  Scanning IP            -          T1595.001

Reconnaissance -  Vulnerability Scanning -  T1595.002

Lateral Movement -Exploitation of Remote Service -  T1210

Lateral Movement - Exploitation of Remote Service -   T1210

Lateral Movement  -  SMB/Windows Admin Shares     -    T1021.002

Lateral Movement   -  Taint Shared Content          -            T1080

Execution   - PowerShell     - T1059.001

Execution  -   Service Execution   -    T1059.002

Impact   -    Data Encrypted for Impact  -  T1486

References

[1] https://unit42.paloaltonetworks.com

[2] https://thehackernews.com

[3] https://trustwave.com

[4] https://www.sangfor.com

[5] https://thehackernews.com

[6]https://any.run

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.
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Maria Geronikolou
Cyber Analyst
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March 25, 2025

Darktrace Recognized as the Only Visionary in the 2025 Gartner® Magic Quadrant™ for CPS Protection Platforms

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We are thrilled to announce that Darktrace has been named the only Visionary in the inaugural Gartner® Magic Quadrant™ for Cyber-Physical Systems (CPS) Protection Platforms. We feel This recognition highlights Darktrace’s AI-driven approach to securing industrial environments, where conventional security solutions struggle to keep pace with increasing cyber threats.

A milestone for CPS security

It's our opinion that the first-ever Gartner Magic Quadrant for CPS Protection Platforms reflects a growing industry shift toward purpose-built security solutions for critical infrastructure. As organizations integrate IT, OT, and cloud-connected systems, the cyber risk landscape continues to expand. Gartner evaluated 17 vendors based on their Ability to Execute and Completeness of Vision, establishing a benchmark for security leaders looking to enhance cyber resilience in industrial environments.

We believe the Gartner recognition of Darktrace as the only Visionary reaffirms the platform’s ability to proactively defend against cyber risks through AI-driven anomaly detection, autonomous response, and risk-based security strategies. With increasingly sophisticated attacks targeting industrial control systems, organizations need a solution that continuously evolves to defend against both known and unknown threats.

AI-driven security for CPS environments

Securing CPS environments requires an approach that adapts to the dynamic nature of industrial operations. Traditional security tools rely on static signatures and predefined rules, leaving gaps in protection against novel and sophisticated threats. Darktrace / OT takes a different approach, leveraging Self-Learning AI to detect and neutralize threats in real time, even in air-gapped or highly regulated environments.

Darktrace / OT continuously analyzes network behaviors to establish a deep understanding of what is “normal” for each industrial environment. This enables it to autonomously identify deviations that signal potential cyber threats, providing early warning and proactive defense before attacks can disrupt operations. Unlike rule-based security models that require constant manual updates, Darktrace / OT improves with the environment, ensuring long-term resilience against emerging cyber risks.

Bridging the IT-OT security gap

A major challenge for organizations protecting CPS environments is the disconnect between IT and OT security. While IT security has traditionally focused on data

protection and compliance, OT security is driven by operational uptime and safety, leading to siloed security programs that leave critical gaps in visibility and response.

Darktrace / OT eliminates these silos by providing unified visibility across IT, OT, and IoT assets, ensuring that security teams have a complete picture of their attack surface. Its AI-driven approach enables cross-domain threat detection, recognizing risks that move laterally between IT and OT environments. By seamlessly integrating with existing security architectures, Darktrace / OT helps organizations close security gaps without disrupting industrial processes.

Proactive OT risk management and resilience

Beyond detection and response, Darktrace / OT strengthens organizations’ ability to manage cyber risk proactively. By mapping vulnerabilities to real-world attack paths, it prioritizes remediation actions based on actual exploitability and business impact, rather than relying on isolated CVE scores. This risk-based approach enables security teams to focus resources where they matter most, reducing overall exposure to cyber threats.

With autonomous threat response capabilities, Darktrace / OT not only identifies risks but also contains them in real time, preventing attackers from escalating intrusions. Whether mitigating ransomware, insider threats, or sophisticated nation-state attacks, Darktrace / OT ensures that industrial environments remain secure, operational, and resilient, no matter how threats evolve.

AI-powered incident response and SOC automation

Security teams are facing an overwhelming volume of alerts, making it difficult to prioritize threats and respond effectively. Darktrace / OT’s Cyber AI Analyst acts as a force multiplier for security teams by automating threat investigation, alert triage, and response actions. By mimicking the workflow of a human SOC analyst, Cyber AI Analyst provides contextual insights that accelerate incident response and reduce the manual workload on security teams.

With 24/7 autonomous monitoring, Darktrace / OT ensures that threats are continuously detected and investigated in real time. Whether facing ransomware, insider threats, or sophisticated nation-state attacks, organizations can rely on AI-driven security to contain threats before they disrupt operations.

Trusted by customers: Darktrace / OT recognized in Gartner Peer Insights

Source: Gartner Peer Insights (Oct 28th)

Beyond our recognition in the Gartner Magic Quadrant, we feel Darktrace / OT is one of the highest-rated CPS security solutions on Gartner Peer Insights, reflecting strong customer trust and validation. With a 4.9/5 overall rating and the highest "Willingness to Recommend" score among CPS vendors, organizations across critical infrastructure and industrial sectors recognize the impact of our AI-driven security approach. Source: Gartner Peer Insights (Oct 28th)

This strong customer endorsement underscores why leading enterprises trust Darktrace / OT to secure their CPS environments today and in the future.

Redefining the future of CPS security

It's our view that Darktrace’s recognition as the only Visionary in the Gartner Magic Quadrant for CPS Protection Platforms validates its leadership in next-generation industrial security. As cyber threats targeting critical infrastructure continue to rise, organizations must adopt AI-driven security solutions that can adapt, respond, and mitigate risks in real time.

We believe this recognition reinforces our commitment to innovation and our mission to secure the world’s most essential systems. This recognition reinforces our commitment to innovation and our mission to secure the world’s most essential systems.

® Download the full Gartner Magic Quadrant for CPS Protection Platforms

® Request a demo to see Darktrace OT in action.

Gartner, Magic Quadrant for CPS Protection Platforms , Katell Thielemann, Wam Voster, Ruggero Contu 12 February 2025

Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

GARTNER is a registered trademark and service mark of Gartner and Magic Quadrant and Peer Insights are a registered trademark, of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved. Gartner Peer Insights content consists of the opinions of individual end users based on their own experiences with the vendors listed on the platform, should not be construed as statements of fact, nor do they represent the views of Gartner or its affiliates. Gartner does not endorse any vendor, product or service depicted in this content nor makes any warranties, expressed or implied, with respect to this content, about its accuracy or completeness, including any warranties of merchantability or fitness for a particular purpose.

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Pallavi Singh
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March 25, 2025

Survey Findings: AI Cybersecurity Priorities and Objectives in 2025

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AI is changing the cybersecurity field, both on the offensive and defensive sides. We surveyed over 1,500 cybersecurity professionals from around the world to uncover their attitudes, understanding, and priorities when it comes to AI cybersecurity in 2025. Our full report, unearthing some telling trends, is available now.  

Download the full report to explore these findings in depth

It is clear that security professionals know their field is changing fast, and that AI will continue to influence those changes. Our survey results show that they are aware that the rise of AI will require them to adopt new tools and learn to use them effectively. Still, they aren’t always certain about how to plan for the future, or what to invest in.

The top priorities of security stakeholders for improving their defenses against AI-powered threats include augmenting their existing tool stacks with AI-powered solutions and improving integration among their security tools.

Figure 1: Year-over-year changes to the priorities of securitystakeholders.

Increasing cybersecurity staff

As was also the case last year, security stakeholders are less interested in hiring additional staff than in adding new AI-powered tools onto their existing security stacks, with only with 11% (and only 8% of executives) planning to increase cybersecurity staff in 2025.

This suggests that leaders are looking for new methods to overcome talent resource shortages.

Adding AI-powered security tools to supplement existing solutions

Executives are particularly enthusiastic about adopting AI-driven tools. Within that goal, there is consensus about the qualities cyber professionals are looking for when purchasing new security capabilities or replacing existing products.

  • 87% of survey respondents prefer solutions that are part of a broader platform over individual point products

These results are similar to last year’s, where again, almost nine out of ten agreed that a platform-oriented security solution was more effective at stopping cyber threats than a collection of individual products.

  • 88% of survey respondents agree that the use of AI within the security stack is critical to freeing up time for security teams to become more proactive, compared to reactive

AI itself can contribute to this shift from reactive to proactive security, improving risk prioritization and automating preventative strategies like Attack Surface Management (ASM) and proactive exposure management.

  • 84% of survey respondents prefer defensive AI solutions that do not require the organization’s data to be shared externally

This preference may reflect increasing attention to the data privacy and security risks posed by generative AI (gen AI) adoption. It may also reflect growing awareness of data residency requirements and other restrictions that regulators are imposing.

Improving cybersecurity awareness training for end users

Based on the survey results, practitioners in SecOps are more interested in improving security awareness training.

This goal is not necessarily mutually exclusive from the addition of AI tools. For example, teams can leverage AI to build more effective security awareness training programs, and as gen AI tools are adopted, users will need to be taught about data privacy and associated security risks.

Looking towards the future

One conclusion we can draw from the attitudinal shifts from last year’s survey to this year’s: while hiring more security staff might be a nice-to-have, implementing AI-powered tools so that existing employees can work smarter is increasingly viewed as a must-have.

However, trending goals are not just about managing resources, whether headcount or AI investments, to keep up with workloads. Existing end users must also be trained to follow safe practices while using established and newly adopted tools.

Security professionals, including executives, SecOps, and every role in between, continue to shift their identified challenges and priorities as they gear up for the coming year in the Era of AI.

State of AI report

Download the full report to explore these findings in depth

The full report for Darktrace’s State of AI Cybersecurity is out now. Download the paper to dig deeper into these trends, and see how results differ by industry, region, organization size, and job title.  

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