Blog
/
/
February 20, 2020

Insights From a Sodinokibi Ransomware Attack

Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
20
Feb 2020
The power of Darktrace’s self-learning AI comes into play when threat-actors use off-the-shelf tooling, making detection more difficult.

Introduction

Last week, Darktrace detected a targeted Sodinokibi ransomware attack during a 4-week trial with a mid-sized company.

This blog post will go through every stage of the attack lifecycle and detail the attacker’s techniques, tools and procedures used, and how Darktrace detected the attack.

The Sodinokibi group is an innovative threat-actor that is sometimes referred to as a ‘double-threat’, due to their ability to run targeted attacks using ransomware while simultaneously exfiltrating their victim’s data. This enables them to threaten to make the victim’s data publicly available if the ransom is not paid.

While Darktrace’s AI was able to identify the attack in real time as it was emerging, unfortunately the security team didn’t have eyes on the technology and was unable to action the alerts — nor was Antigena set in active mode, which would have slowed down and contained the threat instantaneously.

Timeline

The timeline below provides a rough overview of the major attack phases. Most of the attack took place over the course of a week, with the majority of activity distributed over the last three days.

Technical analysis

Darktrace detected two main devices being hit by the attack: an internet-facing RDP server (‘RDP server’) and a Domain Controller (‘DC’), that also acts as a SMB file server.

In previous attacks, Sodinokibi has used host-level encryption for ransomware activity where the encryption takes place on the compromised host itself — in contrast to network-level encryption where the bulk of the ransomware activity takes place over network protocols such as SMB.

Initial compromise

Over several days, the victim’s external-facing RDP server was receiving successful RDP connections from a rare external IP address located in Ukraine.

Shortly before the initial reconnaissance started, Darktrace saw another RDP connection coming into the RDP server with the same RDP account as seen before. This connection lasted for almost an hour.

It is highly likely that the RDP credential used in this attack had been compromised prior to the attack, either via common brute-force methods, credential stuffing attacks, or phishing.

Thanks to Darktrace’s Deep-Packet Inspection, we can clearly see the connection and all related information.

Suspicious RDP connection information:

Time: 2020-02-10 16:57:06 UTC
Source: 46.150.70[.]86 (Ukraine)
Destination: 192.168.X.X
Destination Port: 64347
Protocol: RDP
Cookie: [REDACTED]
Duration: 00h41m40s
Data out: 8.44 MB
Data in: 1.86 MB

Darktrace detects incoming RDP connections from IP addresses that usually do not connect to the organization.

Attack tools download

Approximately 45 minutes after the suspicious RDP connection from Ukraine, the RDP server connected to the popular file sharing platform, Megaupload, and downloaded close to 300MB from there.

Darktrace’s AI recognized that neither this server, nor its automatically detected peer group, nor, in fact, anyone else on the network commonly utilized Megaupload — and therefore instantly detected this as anomalous behavior, and flagged it as unusual.

As well as the full hostname and actual IP used for the download, Megaupload is 100% rare for this organization.

Later on, we will see over 40GB being uploaded to Megaupload. This initial download of 300MB however is likely additional tooling and C2 implants downloaded by the threat-actor into the victim’s environment.

Internal reconnaissance

Only 3 minutes after the download from Megaupload onto the RDP server, Darktrace alerted on the RDP server doing an anomalous network scan:

The RDP server scanned 9 other internal devices on the same subnet on 7 unique ports: 21, 80, 139, 445, 3389, 4899, 8080
 . Anybody with some offensive security know-how will recognize most of these ports as default ports one would scan for in a Windows environment for lateral movement. Since this RDP server does not usually conduct network scans, Darktrace again identified this activity as highly anomalous.

Later on, we see the threat-actor do more network scanning. They become bolder and use more generic scans — one of them showing that they are using Nmap with a default user agent:

Additional Command and Control traffic

While the initial Command and Control traffic was most likely using predominantly RDP, the threat-actor now wanted to establish more persistence and create more resilient channels for C2.

Shortly after concluding the initial network scans (ca. 19:17 on 10th February 2020), the RDP server starts communicating with unusual external services that are unique and unusual for the victim’s environment.

Communications to Reddcoin

Again, nobody else is using Reddcoin on the network. The combination of application protocol and external port is extremely unusual for the network as well.

The communications also went to the Reddcoin API, indicating the installation of a software agent rather than manual communications. This was detected as Reddcoin was not only rare for the network, but also ‘young’ — i.e. this particular external destination had never been seen to be contacted before on the network until 25 minutes before.

Communications to the Reddcoin API

Communications to Exceptionless[.]io

As we can see, the communications to exceptionalness[.]io were done in a beaconing manner, using a Let’s Encrypt certificate, being rare for the network and using an unusual JA3 client hash. All of this indicates the presence of new software on the device, shortly after the threat-actor downloaded their 300MB of tooling.

While most of the above network activity started directly after the threat-actor dropped their tooling on the RDP server, the exact purpose of interfacing with Reddcoin and Exceptionless is unclear. The attacker seems to favor off-the-shelf tooling (Megaupload, Nmap, …) so they might use these services for C2 or telemetry-gathering purposes.

This concluded most of the activity on February 10.

More Command and Control traffic

Why would an attacker do this? Surely using all this C2 at the same time is much noisier than just using 1 or 2 channels?

Another significant burst of activity was observed on February 12 and 13.

The RDP server started making a lot of highly anomalous and rare connections to external destinations. It is inconclusive if all of the below services, IPs, and domains were used for C2 purposes only, but they are linked with high-confidence to the attacker’s activities:

  • HTTP beaconing to vkmuz[.]net
  • Significant amount of Tor usage
  • RDP connections to 198-0-244-153-static.hfc.comcastbusiness[.]net over non-standard RDP port 29348
  • RDP connections to 92.119.160[.]60 using an administrative account (geo-located in Russia)
  • Continued connections to Megaupload
  • Continued SSL beaconing to Exceptionless[.]io
  • Continued connections to api.reddcoin[.]com
  • SSL beaconing to freevpn[.]zone
  • HTTP beaconing to 31.41.116[.]201 to /index.php using a new User Agent
  • Unusual SSL connections to aj1713[.]online
  • Connections to Pastebin
  • SSL beaconing to www.itjx3no[.]com using an unusual JA3 client hash
  • SSL beaconing to safe-proxy[.]com
  • SSL connection to westchange[.]top without prior DNS hostname lookups (likely machine-driven)

What is significant here is the diversity in (potential) C2 channels: Tor, RDP going to dynamic ISP addresses, VPN solutions and possibly custom / customized off-the-shelf implants (the DGA-looking domains and HTTP to IP addresses to /index.php).

Why would an attacker do this? Surely using all this C2 at the same time is much noisier than just using 1 or 2 channels?

One answer might be that the attacker cared much more about short-term resilience than about stealth. As the overall attack in the network took less than 7 days, with a majority of the activity taking place over 2.5 days, this makes sense. Another possibility might be that various individuals were involved in parallel during this attack — maybe one attacker prefers the comfort of RDP sessions for hacking while another is more skilled and uses a particular post-exploitation framework.

The overall modus operandi in this financially-motivated attack is much more smash-and-grab than in the stealthy, espionage-related incidents observed in Advanced Persistent Threat campaigns (APT).

Data exfiltration

The DC uploaded around 40GB of data to Megaupload over the course of 24 hours.

While all of the above activity was seen on the RDP server (acting as the initial beach-head), the following data exfiltration activity was observed on a Domain Controller (DC) on the same subnet as the RDP server.

The DC uploaded around 40GB of data to Megaupload over the course of 24 hours.

Darktrace detected this data exfiltration while it was in progress — never did the DC (or any similar devices) upload similar amounts of data to the internet. Neither did any client nor server in the victim’s environment use Megaupload:

Ransom notes

Finally, Darktrace observed unusual files being accessed on internal SMB shares on February 13. These files appear to be ransom notes — they follow a similar, randomly-generated naming convention as other victims of the Sodinokibi group have reported:

413x0h8l-readme.txt
4omxa93-readme.txt

Conclusion and observations

The threat-actor seems to be using mostly off-the-shelf tooling which makes attribution harder — while also making detection more difficult.

This attack is representative of many of the current ransomware attacks: financially motivated, fast-acting, and targeted.

The threat-actor seems to be using mostly off-the-shelf tooling (RDP, Nmap, Mega, VPN solutions) which makes attribution harder — while also making detection more difficult. Using this kind of tooling often allows to blend in with regular admin activity — only once anomaly detection is used can this kind of activity be detected.

How can you spot the one anomalous outbound RDP connection amongst the thousands of regular RDP connections leaving your environment? How do you know when the use of Megaupload is malicious — compared to your users’ normal use of it? This is where the power of Darktrace’s self-learning AI comes into play.

Darktrace detected every stage of the visible attack lifecycle without using any threat intelligence or any static signatures.

The graphics below show an overview of detections on both compromised devices. The compromised devices were the highest-scoring assets for the network — even a level 1 analyst with limited previous exposure to Darktrace could detect such an in-progress attack in real time.

RDP Server

Some of the detections on the RDP server include:

  • Compliance / File Storage / Mega — using Megaupload in an unusual way
  • Device / Network Scan — detecting unusual network scans
  • Anomalous Connection / Application Protocol on Uncommon Port — detecting the use of protocols on unusual ports
  • Device / New Failed External Connections — detecting unusual failing C2
  • Compromise / Unusual Connections to Let’s Encrypt — detecting potential C2 over SSL using Let’s Encrypt
  • Compromise / Beacon to Young Endpoint — detecting C2 to new external endpoints for the network
  • Device / Attack and Recon Tools — detecting known offensive security tools like Nmap
  • Compromise / Tor Usage — detecting unusual Tor usage
  • Compromise / SSL Beaconing to Rare Destination — detecting generic SSL C2
  • Compromise / HTTP Beaconing to Rare Destination — detecting generic HTTP C2
  • Device / Long Agent Connection to New Endpoint — detecting unusual services on a device
  • Anomalous Connection / Outbound RDP to Unusual Port — detecting unusual RDP C2

DC

Some of the detections on the DC include:

  • Anomalous Activity / Anomalous External Activity from Critical Device — detecting unusual behaviour on dcs
  • Compliance / File storage / Mega — using Megaupload in an unusual way
  • Anomalous Connection / Data Sent to New External Device — data exfiltration to unusual locations
  • Anomalous Connection / Uncommon 1GB Outbound — large amounts of data leaving to unusual destinations
  • Anomalous Server Activity / Outgoing from Server — likely C2 to unusual endpoint on the internet


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.
Author
Max Heinemeyer
Global Field CISO

Max is a cyber security expert with over a decade of experience in the field, specializing in a wide range of areas such as Penetration Testing, Red-Teaming, SIEM and SOC consulting and hunting Advanced Persistent Threat (APT) groups. At Darktrace, Max is closely involved with Darktrace’s strategic customers & prospects. He works with the R&D team at Darktrace, shaping research into new AI innovations and their various defensive and offensive applications. Max’s insights are regularly featured in international media outlets such as the BBC, Forbes and WIRED. Max holds an MSc from the University of Duisburg-Essen and a BSc from the Cooperative State University Stuttgart in International Business Information Systems.

Book a 1-1 meeting with one of our experts
Share this article

More in this series

No items found.

Blog

/

OT

/

March 25, 2025

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

Default blog imageDefault blog image

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.

Continue reading
About the author
Pallavi Singh
Product Marketing Manager, OT Security & Compliance

Blog

/

AI

/

March 25, 2025

Survey Findings: AI Cybersecurity Priorities and Objectives in 2025

Default blog imageDefault blog image

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.  

Continue reading
About the author
The Darktrace Community
Your data. Our AI.
Elevate your network security with Darktrace AI