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December 11, 2024

Company Shuts Down Cyber-attacks with “Flawless” Detection and Response from Darktrace

This blog explores how Darktrace shut down a major third-party cyber-attack, preventing the deployment of ransomware. Read more to discover how the security team now spends 80-90% of their time working on more strategic projects vs. manual, low-level tasks.
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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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Dec 2024

Growing pains: Balancing efficiency with risk  

This organization has recently scaled its operations, and numerous acquisitions have significantly boosted the organization’s capabilities and growth. However, this also creates work and high expectations for the organization’s IT and security teams. Within 12 months of an acquisition, the teams must fully integrate each new business onto the company’s platform. “A huge piece of that integration plan is rolling out our security controls,” said the CISO. “While our goal is to connect those facilities up as quickly as possible to drive efficiency, we also need to implement the proper security controls to protect the enterprise.”

Gap beyond the perimeter  

The organization had established strong security measures to safeguard its perimeter; however, the CISO identified a critical gap in real-time network monitoring. If the perimeter were breached, threats were only discovered after an endpoint was compromised and the issue was manually reported.

As digital transformation progresses, the need to adopt advanced technologies is becoming essential, particularly as organizations begin to open up operational environments to greater connectivity. Many processes still rely on traditional methods, and integrating innovative solutions could drive significant improvements in efficiency and productivity. “We’re committed to adopting cutting-edge technologies,” the CISO explained. “But we understood that without more robust network security controls, opening up our operational environments would expose us to heightened risks, including advanced threats like ransomware.”

Building a layered, proactive security strategy with Darktrace  

To close the gap beyond the perimeter, the company embarked on a free trial with Darktrace. The CISO recalls: “The trials were fantastic. It was obvious that Darktrace was exactly what we needed. The Darktrace team was also very knowledgeable and helpful throughout the process, which was impressive.”  

Today, the organization is using a combination of Darktrace solutions for its layered security approach, including:

Detecting unusual behavior with AI  

Darktrace’s use of machine learning and Self-Learning AI is one of the reasons the company chose Darktrace. Instead of teaching an AI system what an ‘attack’ looks like, training it on large data lakes of thousands of organizations’ data, Darktrace AI learns from the company’s own unique data and user activity to learn and create baseline models of what ‘normal’ looks like for their business.

Darktrace can then detect subtle deviations and unusual activity that signals a possible threat. “That fascinated us because what it really means is this technology doesn’t need to know about every single threat because the threat itself isn’t important, it’s the behavior of the activity that’s important. That capability is unique when it when it comes to threat detection,” said the CISO.

Identifying and mitigating high-impact attack paths

The security team appreciated that with Darktrace they could take a more proactive approach to security by exposing high-risk attack paths through modeling and AI risk assessments. Darktrace / Proactive Exposure Management gives them visibility into vulnerable entry points and assets, identifies active risks, and prioritizes the most important security issues to be addressed.

“Specific users and assets within our business have a higher risk of being targeted by a cyber-attack, for example our executives,” said the CISO. “With Darktrace, we get an adversarial view of our risk. We can see the attack path around those potential targets and proactively take measures to mitigate that vulnerability and prevent an attack.”

Driving up productivity while putting the brakes on cyber-attacks  

The security team collaborated with Darktrace to fine tune the models that really fit their business. With Darktrace now automating most of their threat detection and response efforts, productivity has soared, the security team is now focused on delivering greater value to the business and, most importantly, Darktrace proved it could quickly detect and shut down a major cyber-attack–and do so without impacting business operations.

Fueling team productivity with automation and AI

Prior to using Darktrace, the security team had little visibility into potential risks beyond the perimeter. Today, the team has full control and visibility over the network. “My team is now spending 80-90% of their time doing proactive work because Darktrace is managing the vast majority of our detect and response needs. The team really has faith in the Darktrace system,” said the CISO.  

With less time spent on low-level manual tasks, the security team can now focus on higher priority initiatives. For example, they have expanded their internal vulnerability assessments across the entire group. The team couldn’t focus on this additional audit and vulnerability management work if Darktrace wasn’t taking care of most of their security monitoring. “Darktrace has allowed us to move on to these additional kinds of governance projects that we otherwise would have to hire an army of staff to get through”.

Stopping email threats in their tracks

Using Darktrace / EMAIL, the company has identified and blocked a significant percentage of emails that were making it past their native email filters. “Darktrace is especially good at detecting impersonation emails, and we really appreciate its ability to automatically remove suspicious emails directly from a user’s inbox. It adds an extra level of confidence,” said the CISO.

Self-Learning AI understands anomalies within unique communication patterns to stop known and unknown threats. For example, when an employee sent an email to a brand new domain, Darktrace identified the behavior as unusual and inconsistent with baseline models and blocked the email.

Darktrace passes the biggest test of all

In 2024, the company experienced the value of the security system firsthand when attackers exploited a vulnerability in a third-party remote support solution that they was using. This solution provided remote access and tech support capabilities. If successful, the attackers could have infiltrated high-value end points and created their own administrative user, giving them full control over the server.

“We first became aware of the attack when Darktrace notified us of unusual behavior coming from the remote support server,” said the CISO. The attackers were attempting to put backdoors onto the service with the intent of selling access to the highest bidder who would then install ransomware on their servers. It all happened very quickly, as the attackers tried to connect to the internal network and other servers, while also firing off a host of other actions, like PowerShell commands, to escalate their privileges.  

“Darktrace worked flawlessly. There was no chance that ransomware was ever going to come in,” the CISO said. “Even though there was no signature to really look at, Darktrace realized this was not normal behavior for this server, shutting down connections and doing everything it could do to stop the attack.” Within eight hours, the security team identified and stopped the attack, severed its connection to the third-party solution, and completed additional analysis and clean-up. “In addition to our own investigation, third parties like our external SOC and legal department also confirmed that Darktrace performed as expected. We were able to report back to the executive team that there was zero risk that any data or systems were compromised.”

Post-attack, there was no need to make any changes to Darktrace. The team consistently reviews its models and baselines, often collaborating with Darktrace to make adjustments when needed to continuously improve performance. “Because of this relationship and constant engagement with Darktrace’s technical teams, we didn't have to go back and ask: ‘why wasn’t this updated’ or ‘why didn’t this model work.’ The models worked.”

His advice to other organizations facing similar challenges? First, focus on updating, patching, and vulnerability management, and act quickly when vulnerabilities are identified. His second piece of advice: “have an automated detection system like Darktrace in place so you can respond at the speed that these attacks evolve. Humans can no longer keep up with a scripted attack as it moves around and tries to compromise items on your network. You need the right technology to fight these types of attacks.”

Dynamic capabilities for a dynamic future

Real-time playbooks

With a proactive, enterprise-wide security strategy in place, the CISO now has the time to think about future projects and innovations. He’s particularly interested in the idea of generating playbooks on the fly in response to real-time events. He believes cyber-attacks are far too varied for a static playbook to be useful; when an attack strikes, teams need to quickly understand exactly what’s in front of them and how to shut it down. “This fits into our future cybersecurity strategy, and Darktrace is the only company I’ve seen talking about building playbooks dynamically. This kind of technology would really help bring our cybersecurity strategy full circle.”

“Darktrace ’s technology, experience and expertise is helping us staying ahead of cyber-attacks, minimizing our risk and driving greater productivity for our team,” said the CISO. In collaboration with Darktrace, the team have created a security foundation that is both powerful and agile. “While Darktrace is detecting and responding to attacks targeting our business today, we know that it’s always learning, adapting and scaling to ensure we’re protected tomorrow. That gives me peace of mind and the freedom to focus on our future.”

Download the Darktrace / NETWORK Solution Brief

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Protect in real time: Defend against known and emerging threats without relying on historical data or external intelligence.

Full visibility: Gain comprehensive insights across all network environments, including on-premises, cloud, and remote devices.

AI-powered efficiency: Streamline incident response with AI automation, saving time and resources while ensuring minimal disruption to operations.

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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The Darktrace Community

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September 3, 2026

Darktrace Advances Incident Investigation and AI-Agent Security with OpenAI Daybreak Models

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Earlier this year, Darktrace joined OpenAI’s Daybreak Defense Network to explore how their cyber capabilities can be integrated within Darktrace products and services to transform how security teams move from signal to action.

At the heart of this work is Darktrace's behavioral understanding of customer environments and identification of complex security incidents, combined with OpenAI models that can add context to help explain why an incident matters and its potential impact on the business. By bringing these capabilities into defensive workflows security teams already use, the goal is to give defenders not just greater visibility, but the context and guidance they need to act with confidence.

Since joining the program, we've been working with OpenAI to explore how these capabilities can address specific security challenges for defenders.

The problem we're solving

Attackers continue to change how they operate, including by using AI to increase the speed and scale of some techniques. Security teams are already managing a large volume of alerts, and the question isn't just what's happening, but how it could affect the organization. Even when an incident is fully investigated and correlated, technical severity alone doesn't tell a security team how much it actually matters to the business. That same challenge extends to internal AI adoption. As organizations adopt more AI systems and agents, security teams need visibility into their behavior, access and activity, along with the broader business context needed to identify and investigate potential risk.

Darktrace's Adaptive AI™ builds a detailed, organization-specific picture of what's normal for each environment, and uses that picture to investigate threats and identify complex security activity across domains. OpenAI's models can build on Darktrace's correlated, technically prioritized incidents by adding context that can help defenders understand what may be at stake.

What we're building

Our work is focused on two areas: supporting security investigation and response, and helping defenders identify risky behavior across enterprise AI systems and agents.

The first aligns Darktrace's behavioral understanding with OpenAI models to support  security investigation and prioritization. Darktrace's Adaptive AI continuously learns the unique patterns of normal behavior within each customer it protects, creating a deep, organization-specific understanding of its digital estate. When unusual activity emerges, OpenAI's models can draw on that context to help analysts investigate the incident, understand its significance and assess potential business consequences — reducing the need to manually assemble context from fragmented signals.

Second, we are exploring how these capabilities can support AI-agent and runtime security through Darktrace / SECURE AI™. OpenAI’s Daybreak models can build on the detections and visibility Darktrace / SECURE AI provides, connecting signals across a customer's environment and help defenders identify potentially risky behavior involving AI systems and agents. Activity that might appear isolated can instead be connected with related signals, helping defenders investigate the broader context and determine appropriate remediation.

Darktrace brings deep cybersecurity expertise, an evolving understanding of each customer's environment, and AI-driven identification of threats across the digital estate. Through the Daybreak Defense Network, Darktrace is exploring how OpenAI models can augment those capabilities in defensive security workflows — supporting incident investigation and response and improving visibility into AI-agent and runtime risk.

These capabilities are still in development, and we're excited to continue building on this work.

To learn more about how Darktrace continues to innovate to meet today's most pressing security challenges, register for our upcoming launch broadcast here.

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About the author
Dr. Tim Bazalgette
Chief AI Officer, Darktrace

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September 3, 2026

Botnet Behind the Camera: Mirai Katana Activity on a Video Recording Device

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Key takeaways

  • Darktrace identified a camera device infected with the Mirai/Katana botnet in a sports-sector customer environment, showing how exposed IoT devices can become active participants in wider attack chains.
  • The compromise involved suspicious Wget behavior, file downloads from rare external IPs, unusual incoming HTTP connections to video recorder management interfaces, and large outbound data transfers to infrastructure associated with botnet activity.
  • The incident highlights the importance of extending visibility and response beyond traditional endpoints, as unmanaged or overlooked connected devices can be exploited for command-and-control, malware delivery, and data exfiltration.

Mirai and the Katana variant

Mirai is a botnet that first emerged in August 2016 and is well known for launching large-scale distributed-denial-of-service (DDoS) attacks, typically targeting exposed Internet of Things (IoT) devices. It identifies vulnerable IoT devices ,often by abusing default credentials or exposed services, and recruiting them into a remotely controlled botnet that can be used in DDoS campaigns [1].

Katana, one of the many variants that arose after Mirai’s source code was released publicly, was first observed in late 2020 and has been seen using more advanced capabilities, including custom command-and-control (C2), persistence mechanisms, and DDoS functionality [2].

In March 2026, research from the Nokia Deepfield Emergency Response Team (ERT) identified Katana as a Mirai-derived DDoS botnet targeting Android-based TV set-top boxes through exposed Android Debug Bridge (ADB) access.  Observed capabilities included custom C2, runtime domain rotation, multiple DDoS methods, and an on-device compiled kernel rootkit used for persistence and stealth [3].

Darktrace’s detection of Mirai Botnet activity on a camera device

In early 2026, Darktrace identified a Network/Digital Video Recorder (NVR/DVR) on the network of a sports-sector customer that had been infected with the Mirai Katana botnet and subsequently used to exfiltrate data from the customer’s environment. Seemingly related follow-up activity was observed on the same device several months later.

In both instances, the Darktrace Security Operations Centre (SOC) alerted the customer as part of the Managed Threat Detection (MTD) service. However, as Darktrace’s Autonomous Response capability was not fully enabled on the affected device, Darktrace was unable to proactively block the suspicious activity or prevent the compromise from continuing and recurring.

The initial compromise appears to have occurred when the affected device was seen using Wget to download Linux-based Executable and Linkable Format (ELF) files from a rare external IP, 195.177.94[.]105, which had not previously been observed in the customer’s network. Further analysis downloaded file hashes identified files related to the Mirai botnet.

Figure 1: Darktrace’s Real-Time AI Analyst investigation into the unusual outbound connection where the ELF files were downloaded.

Within a few hours, Darktrace detected the device uploading close to 3GB of data to another external IP, 50.7.49[.]4:3017 (ASN AS30058 FDCSERVERS), suggesting that the activity was likely routed via a virtual private server (VPS) hosted by FDC Servers [2]. Attackers often abuse VPS infrastructure from legitimate cloud providers to blend in with legitimate traffic and evade IP reputation and geolocation-based detections.

Figure 2:  Darktrace’s detection of the unusual data upload activity by the affected camera device.

Darktrace continued to observe similar data transfers to multiple rare endpoints  including 171.225.223[.]53, 95.161.128[.]62, 61.7.209[.]88, 95.161.128[.]62, which have been linked to Mirai by open-source intelligence (OSINT).

Figure 3: Darktrace’s detection of spikes in unusual external data transfer activity from the camera device.

Exploitation continued

Several months later, Darktrace identified the same exfiltration pattern on the device again, this time with stronger indications of associations with Mirai Katana botnet infection.

The device received incoming HTTP connections from 129.121.114[.]124, an external IP known to be associated with the Katana botnet IP [3]. The connections targeted the ‘/dvr/cmd’ path using the root username and user agent Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/42.0.2311.135 Safari/537.36 Edge/12.246.

The ‘/dvr/cmd’ path appears to be associated with the affected device’s web management functionality. This API endpoint has historically been targeted by Mirai and other IoT botnets through the exploitation of critical command injection vulnerabilities and automated botnet exploitation [4].

Figure 4: Darktrace’s  detection of HTTP connectivity from the external IP associated with Mirai Katana Botnet.

A few days later, Darktrace observed the Wget utility being used to download ELF files, including “/lil”,  from the IP 129.121.114[.]124. OSINT reporting has since associated this IP address with the Mirai Katana botnet. Notably, the IP observed earlier in the year, 195.177.94[.]105, had also hosted a file named “lil”, indicating a link between the observed activity.

Over the following days, the device received a sudden spike in connections from multiple rare external endpoints, suggesting a possible successful brute force attack. Darktrace also observed the device exfiltrating just under 4GB of data to another Mirai-associated IP address,  66.92.198[.]194, over ports 3344, 954922, and 80. Finally, the device was seen uploading data to the Mirai botnet IP 5.175.249[.]53 over port138 and exhibited an increase in UDP connections to 34.18.28[.]10 over port 9068.

Following both file download events, Darktrace identified spikes in external data transfers and connection attempts to rare destinations. While Darktrace’s Threat Research team could not confirm with high confidence that this to activity was directly associated with Mirai, it may indicate that Mirai Katana includes data exfiltration functionality.

Darktrace’s threat researchers also identified an internet-facing NTP server belonging to a separate customer receiving incoming connection attempts from the same initially observed IP, 195.177.94[.]105,over the port 123. This suggests that Mirai Katana may not exclusively target IoT devices.

Conclusion

This case demonstrates how threat actors can exploit overlooked IoT and OT devices to support broader malicious objectives. Here, a camera device infected with a botnet was used to exfiltrate data from the customer's environment, showing how peripheral assets can become active participants in an attack chain.

This case also reinforces a challenge many organizations face today: extending security visibility beyond traditional endpoints and servers. Cameras, sensors, and other connected devices often operate with limited monitoring and may fall outside established security processes, despite maintaining network connectivity and access to potentially sensitive environments. This is particularly relevant in the sports sector, where growing reliance on connected cameras, smart stadium technologies, and other IoT devices continues to expand the attack surface, as highlighted in Darktrace's Sports Sector Threat Report.

As botnets like Kata and Mirai continue to evolve, defenders need visibility across unmanaged IoT and edge devices, as well as security solutions that can recognize subtle deviations in device behavior that may indicate an emerging compromise.

Credit to Parvatha Ananthakannan (Cyber Analyst), Signe Zaharka (Principal Analyst)

Edited by Ryan Traill (Content Manager)

Appendices

Darktrace Model Detections

·      Anomalous File / EXE from Rare External Location

·      Anomalous File / Multiple EXE from Rare External Locations

·      Device / Initial Attack Chain Activity

·      Unusual Activity / Unusual External Data to New Endpoint

·      Anomalous Connection / Data Sent to Rare Domain

·      Unusual Activity / Enhanced Unusual External Data Transfer

·      Anomalous Connection / Uncommon 1 GiB Outbound

·      Device / Significant UDP Increase

·      Anomalous Connection / Low and Slow Exfiltration to IP

·      Compromise / Large Number of Suspicious Failed Connections

·      Compromise / Large Number of Suspicious Successful Connections

·      Unusual Activity / Unusual External Activity

·      Compliance / SSH to Rare External Destination

·      Unusual Activity / Unusual DNS

·      Device / External Network Scan

·      Device / Suspicious DNS Activity

·      Device / Large Number of Model Alerts

List of Indicators of Compromise (IoCs)

Indicator of Compromise Type Description
195.177.94[.]105 IP C2 endpoint
50.7.49[.]4:30171 IP Possible C2 endpoint
129.121.114[.]124 IP C2 endpoint
hxxp://195.177.94[.]105/n3 URL Likely C2 endpoint
hxxp://195.177.94[.]105/n2 URL Likely C2 endpoint
hxxp://129.121.114[.]124/lil URL Likely C2 endpoint
hxxp://129.121.114[.]124/HHn URL Possible C2 endpoint
hxxp://129.121.114[.]124/JFc URL Possible C2 endpoint
hxxp://129.121.114[.]124/jum URL Likely C2 endpoint
hxxp://129.121.114[.]124/OaSf URL Likely C2 endpoint
hxxp://129.121.114[.]124/OPWg URL Possible C2 endpoint
hxxp://129.121.114[.]124/vHwK URL Possible C2 endpoint
hxxp://129.121.114[.]124/VLv URL Possible C2 endpoint
hxxp://129.121.114[.]124/WbJ URL Possible C2 endpoint
hxxp://129.121.114[.]124/zkR URL Possible C2 endpoint
Ab17883ae4c3bc6afa18c439166eeeb4b03186e3093d984e3a95f573e0fcb7d8 SHA-256 Mirai payload
3d587e809dac49d34a3f717e072fd0aebe5e71db63333e45c81577d6b4266f87 SHA-256 Mirai payload
Bf6e81733a7e209d3dce80d15bf3c5d300752d961fae6b45d90c9bbe7f8c89a2 SHA-256 Possible payload
f25488303813ab1ec0eaa71562938601aac185e8aaf93adb84522557f7cf4dd6 SHA-256 Possible payload
0cb4ff6b71f4423184bfa35c34e9090297637208b0e30205d4b224e56abde2ef SHA-256 Possible payload
19c24cbeaf06b2e7697083f33a85521a9315105c784691bde7420fde4cc69410 SHA-256 Likely Mirai payload
1e74f734fff8df91f4f7172d0de10c421eca78aeb800e8a48e16bc5dbde5d20e SHA-256 Possible payload
6e71f7763d1f29d5712106ebb122e281c32787540aa2342b0fe5351d585d18d7 SHA-256 Possible payload
71f4ff7cdb6d6a7d2673c543c5d2535093afbd707b20a5b9ddf735466c1105c1 SHA-256 Possible payload
76db7ee73ebf15e48a3cb24a074d92248671ef2c6ed3bc3e708377341fb7674d SHA-256 Possible payload
da87a65f7beb438e61f0b61964fed8aa305a380f569042f84c55eca8fa7929b8 SHA-256 Possible payload
e15809eb6ba66477175270d62cfa53e4bf278595f69938708c81c4bc457930fe SHA-256 Mirai payload

MITRE ATT&CK Mapping

Tactic Technique ID Technique / Sub-technique
Initial Access T1659 Content Injection
T1189 Drive-by Compromise
Exfiltration T1041 Exfiltration Over C2 Channel
T1048.003 Exfiltration Over Unencrypted Non-C2 Protocol
Command and Control T1105 Ingress Tool Transfer
T1095 Non-Application Layer Protocol
T1571 Non-Standard Port
Reconnaissance T1595.001 Scanning IP Blocks
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About the author
Parvatha Ananthakannan
Cyber Analyst
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