December 15, 2023

How Darktrace Halted A DarkGate in MS Teams

Discover how Darktrace thwarted DarkGate malware in Microsoft Teams. Stay informed on the latest cybersecurity measures and protect your business.

Written by

Natalia Sánchez Rocafort

Cyber Security 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

Natalia Sánchez Rocafort

Cyber Security Analyst

Dec 2023

Securing Microsoft Teams and SharePoint

Given the prevalence of the Microsoft Teams and Microsoft SharePoint platforms in the workplace in recent years, it is essential that organizations stay vigilant to the threat posed by applications vital to hybrid and remote work and prioritize the security and cyber hygiene of these services. For just as the use of these platforms has increased exponentially with the rise of remote and hybrid working, so too has the malicious use of them to deliver malware to unassuming users.

Researchers across the threat landscape have begun to observe these legitimate services being leveraged by malicious actors as an initial access method. Microsoft Teams can easily be exploited to send targeted phishing messages to individuals within an organization, while appearing legitimate and safe. Although the exact contents of these messages may vary, the messages frequently use social engineering techniques to lure users to click on a SharePoint link embedded into the message. Interacting with the malicious link will then download a payload [1].

Darktrace observed one such malicious attempt to use Microsoft Teams and SharePoint in September 2023, when a device was observed downloading DarkGate, a commercial trojan that is known to deploy other strains of malware, also referred to as a commodity loader [2], after clicking on SharePoint link. Fortunately for the customer, Darktrace’s suite of products was perfectly poised to identify the initial signs of suspicious activity and Darktrace RESPOND™ was able to immediately halt the advancement of the attack.

DarkGate Attack Overview

On September 8, 2023, Darktrace DETECT™ observed around 30 internal devices on a customer network making unusual SSL connections to an external SharePoint site which contained the name of a person, 'XXXXXXXX-my.sharepoint[.]com' (107.136[.]8, 13.107.138[.]8). The organization did not have any employees who went by this name and prior to this activity, no internal devices had been seen contacting the endpoint.

At first glance, this initial attack vector would have appeared subtle and seemingly trustworthy to users. Malicious actors likely sent various users a phishing message via Microsoft Teams that contained the spoofed SharePoint link to the personalized SharePoint link ''XXXXXXXX-my.sharepoint[.]com'.

Figure 1: Advanced Search query showing a sudden spike in connections to ''XXXXXXXX -my.sharepoint[.]com'.

Darktrace observed around 10 devices downloading approximately 1 MB of data during their connections to the Sharepoint endpoint. Darktrace DETECT observed some of the devices making subsequent HTTP GET requests to a range of anomalous URIs. The devices utilized multiple user-agents for these connections, including ‘curl’, a command line tool that allows individuals to request and transfer data from a specific URL. The connections were made to the IP 5.188.87[.]58, an endpoint that has been flagged as an indicator of compromise (IoC) for DarkGate malware by multiple open-source intelligence (OSINT) sources [3], commonly associated with HTTP GET requests:

GET request over port 2351 with the User-Agent header 'Mozilla/4.0 (compatible; Win32; WinHttp.WinHttpRequest.5)' and the target URI '/bfyxraav' to 5.188.87[.]58
GET request over port 2351 with the user-agent header 'curl' and the target URI '/' to 5.188.87[.]58
GET request over port 2351 with the user-agent header 'curl/8.0.1' and the target URI '/msibfyxraav' to 5.188.87[.]58

The HTTP GET requests made with the user-agent header 'curl' and the target URI '/' to 5.188.87[.]58 were responded to with a filename called 'Autoit3.exe'. The other requests received script files with names ending in '.au3, such as 'xkwtvq.au3', 'otxynh.au3', and 'dcthbq.au3'. DarkGate malware has been known to make use of legitimate AutoIt files, and typically runs multiple AutoIt scripts (‘.au3’) [4].

Following these unusual file downloads, the devices proceeded to make hundreds of HTTP POST requests to the target URI '/' using the user-agent header 'Mozilla/4.0 (compatible; Synapse)' to 5.188.87[.]58. The contents of these requests, along with the contents of the responses, appear to be heavily obfuscated.

Figure 2: Example of obfuscated response, as shown in a packet capture downloaded from Darktrace.

While Microsoft’s Safe Attachments and Safe Links settings were unable to detect this camouflaged malicious activity, Darktrace DETECT observed the unusual over-the-network connectivity that occurred. While Darktrace DETECT identified multiple internal devices engaging in this anomalous behavior throughout the course of the compromise, the activity observed on one device in particular best showcases the overall kill chain of this attack.

The device in question was observed using two different user agents (curl/8.0.1 and Mozilla/4.0 (compatible; Win32; WinHttp.WinHttpRequest.5)) when connecting to the endpoint 5.188.87[.]58 and target URI ‘/bfyxraav’. Additionally, Darktrace DETECT recognized that it was unusual for this device to be making these HTTP connections via destination port 2351.

As a result, Darktrace’s Cyber AI Analyst™ launched an autonomous investigation into the suspicious activity and was able to connect the unusual external connections together, viewing them as one beaconing incident as opposed to isolated series of connections.

Figure 3: Cyber AI Analyst investigation summarizing the unusual repeated connections made to 5.188.87[.]58 via destination port 2351.

Darktrace then observed the device downloading the ‘Autoit3.exe’ file. Darktrace RESPOND took swift mitigative action by blocking similar connections to this endpoint, preventing the device from downloading any additional suspicious files.

Figure 4: Suspicious ‘Autoit3.exe’ downloaded by the source device from the malicious external endpoint.

Just one millisecond later, Darktrace observed the device making suspicious HTTP GET requests to URIs including ‘/msibfyxraav’. Darktrace recognized that the device had carried out several suspicious actions within a relatively short period of time, breaching multiple DETECT models, indicating that it may have been compromised. As a result, RESPOND took action against the offending device by preventing it from communicating externally [blocking all outbound connections] for a period of one hour, allowing the customer’s security team precious time to address the issue.

It should be noted that, at this point, had the customer subscribed to Darktrace’s Proactive Threat Notification (PTN) service, the Darktrace Security Operations Center (SOC) would have investigated these incidents in greater detail, and likely would have sent a notification directly to the customer to inform them of the suspicious activity.

Additionally, AI Analyst collated various distinct events and suggested that these stages were linked as part of an attack. This type of augmented understanding of events calculated at machine speed is extremely valuable since it likely would have taken a human analyst hours to link all the facets of the incident together.

Figure 5: AI Analyst investigation showcasing the use of the ‘curl’ user agent to connect to the target URI ‘/msibfyxraav’.

Figure 6: Darktrace RESPOND moved to mitigate any following connections by blocking all outgoing traffic for 1 hour.

Following this, an automated investigation was launched by Microsoft Defender for Endpoint. Darktrace is designed to coordinate with multiple third-party security tools, allowing for information on ongoing incidents to be seamlessly exchanged between Darktrace and other security tools. In this instance, Microsoft Defender identified a ‘low severity’ incident on the device, this automatically triggered a corresponding alert within DETECT, presented on the Darktrace Threat Visuallizer.

The described activity occurred within milliseconds. At each step of the attack, Darktrace RESPOND took action either by enforcing expected patterns of life [normality] on the affected device, blocking connections to suspicious endpoints for a specified amount of time, and/or blocking all outgoing traffic from the device. All the relevant activity was detected and promptly stopped for this device, and other compromised devices, thus containing the compromise and providing the security team invaluable remediation time.

Figure 7: Overview of the compromise activity, all of which took place within a matter of miliseconds.

Darktrace identified similar activity on other devices in this customer’s network, as well as across Darktrace’s fleet around the same time in early September.

On a different customer environment, Darktrace DETECT observed more than 25 ‘.au3’ files being downloaded; this activity can be seen in Figure 9.

Figure 8: High volume of file downloads following GET request and 'curl' commands.

Figure 9 provides more details of this activity, including the source and destination IP addresses (5.188.87[.]58), the destination port, the HTTP method used and the MIME/content-type of the file

Figure 9: Additional information of the anomalous connections.

A compromised server in another customer deployment was seen establishing unusual connections to the external IP address 80.66.88[.]145 – an endpoint that has been associated with DarkGate by OSINT sources [5]. This activity was identified by Darktrace/DETECT as a new connection for the device via an unusual destination port, 2840. As the device in question was a critical server, Darktrace DETECT treated it with suspicion and generated an ‘Anomalous External Activity from Critical Network Device’ model breach.

Figure 10: Model breach and model breach event log for suspicious connections to additional endpoint.

Conclusion

While Microsoft Teams and SharePoint are extremely prominent tools that are essential to the business operations of many organizations, they can also be used to compromise via living off the land, even at initial intrusion. Any Microsoft Teams user within a corporate setting could be targeted by a malicious actor, as such SharePoint links from unknown senders should always be treated with caution and should not automatically be considered as secure or legitimate, even when operating within legitimate Microsoft infrastructure.

Malicious actors can leverage these commonly used platforms as a means to carry out their cyber-attacks, therefore organizations must take appropriate measures to protect and secure their digital environments. As demonstrated here, threat actors can attempt to deploy malware, like DarkGate, by targeting users with spoofed Microsoft Teams messages. By masking malicious links as legitimate SharePoint links, these attempts can easily convince targets and bypass traditional security tools and even Microsoft’s own Safe Links and Safe Attachments security capabilities.

When the chain of events of an attack escalates within milliseconds, organizations must rely on AI-driven tools that can quickly identify and automatically respond to suspicious events without latency. As such, the value of Darktrace DETECT and Darktrace RESPOND cannot be overstated. Given the efficacy and efficiency of Darktrace’s detection and autonomous response capabilities, a more severe network compromise in the form of the DarkGate commodity loader was ultimately averted.

Credit to Natalia Sánchez Rocafort, Cyber Security Analyst, Zoe Tilsiter.

Appendices

Darktrace DETECT Model Detections

[Model Breach: Device / Initial Breach Chain Compromise 100% –– Breach URI: /#modelbreach/114039 ] (Enhanced Monitoring)· [Model Breach: Device / Initial Breach Chain Compromise 100% –– Breach URI: /#modelbreach/114124 ] (Enhanced Monitoring)
[Model Breach: Device / New User Agent and New IP 62% –– Breach URI: /#modelbreach/114030 ]
[Model Breach: Anomalous Connection / Application Protocol on Uncommon Port 46% –– Breach URI: /#modelbreach/114031 ]
[Model Breach: Anomalous Connection / New User Agent to IP Without Hostname 62% –– Breach URI: /#modelbreach/114032 ]
[Model Breach: Device / New User Agent 32% –– Breach URI: /#modelbreach/114035 ]
[Model Breach: Device / Three Or More New User Agents 31% –– Breach URI: /#modelbreach/114036 ]
[Model Breach: Anomalous Server Activity / Anomalous External Activity from Critical Network Device 62% –– Breach URI: /#modelbreach/612173 ]
[Model Breach: Anomalous File / EXE from Rare External Location 61% –– Breach URI: /#modelbreach/114037 ]
[Model Breach: Anomalous Connection / Multiple Connections to New External TCP Port 61% –– Breach URI: /#modelbreach/114042 ]
[Model Breach: Security Integration / Integration Ransomware Detected 100% –– Breach URI: /#modelbreach/114049 ]
[Model Breach: Compromise / Beaconing Activity To External Rare 62% –– Breach URI: /#modelbreach/114059 ]
[Model Breach: Compromise / HTTP Beaconing to New Endpoint 30% –– Breach URI: /#modelbreach/114067 ]
[Model Breach: Security Integration / C2 Activity and Integration Detection 100% –– Breach URI: /#modelbreach/114069 ]
[Model Breach: Anomalous File / EXE from Rare External Location 55% –– Breach URI: /#modelbreach/114077 ]
[Model Breach: Compromise / High Volume of Connections with Beacon Score 66% –– Breach URI: /#modelbreach/114260 ]
[Model Breach: Security Integration / Low Severity Integration Detection 59% –– Breach URI: /#modelbreach/114293 ]
[Model Breach: Security Integration / Low Severity Integration Detection 33% –– Breach URI: /#modelbreach/114462 ]
[Model Breach: Security Integration / Integration Ransomware Detected 100% –– Breach URI: /#modelbreach/114109 ]· [Model Breach: Device / Three Or More New User Agents 31% –– Breach URI: /#modelbreach/114118 ]· [Model Breach: Anomalous Connection / Application Protocol on Uncommon Port 46% –– Breach URI: /#modelbreach/114113 ] · [Model Breach: Anomalous Connection / New User Agent to IP Without Hostname 62% –– Breach URI: /#modelbreach/114114 ]· [Model Breach: Device / New User Agent 32% –– Breach URI: /#modelbreach/114117 ]· [Model Breach: Anomalous File / EXE from Rare External Location 61% –– Breach URI: /#modelbreach/114122 ]· [Model Breach: Security Integration / Low Severity Integration Detection 54% –– Breach URI: /#modelbreach/114310 ]
[Model Breach: Security Integration / Integration Ransomware Detected 65% –– Breach URI: /#modelbreach/114662 ]Darktrace/Respond Model Breaches
[Model Breach: Antigena / Network::External Threat::Antigena Suspicious File Block 61% –– Breach URI: /#modelbreach/114033 ]
[Model Breach: Antigena / Network::External Threat::Antigena File then New Outbound Block 100% –– Breach URI: /#modelbreach/114038 ]
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Enhanced Monitoring from Client Block 100% –– Breach URI: /#modelbreach/114040 ]
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Significant Anomaly from Client Block 87% –– Breach URI: /#modelbreach/114041 ]
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Controlled and Model Breach 87% –– Breach URI: /#modelbreach/114043 ]
[Model Breach: Antigena / Network::External Threat::Antigena Ransomware Block 100% –– Breach URI: /#modelbreach/114052 ]
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Significant Security Integration and Network Activity Block 87% –– Breach URI: /#modelbreach/114070 ]
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Breaches Over Time Block 87% –– Breach URI: /#modelbreach/114071 ]
[Model Breach: Antigena / Network::External Threat::Antigena Suspicious Activity Block 87% –– Breach URI: /#modelbreach/114072 ]
[Model Breach: Antigena / Network::External Threat::Antigena Suspicious File Block 53% –– Breach URI: /#modelbreach/114079 ]
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Breaches Over Time Block 64% –– Breach URI: /#modelbreach/114539 ]
[Model Breach: Antigena / Network::External Threat::Antigena Ransomware Block 66% –– Breach URI: /#modelbreach/114667 ]
[Model Breach: Antigena / Network::External Threat::Antigena Suspicious Activity Block 79% –– Breach URI: /#modelbreach/114684 ]·
[Model Breach: Antigena / Network::External Threat::Antigena Ransomware Block 100% –– Breach URI: /#modelbreach/114110 ]·
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Significant Anomaly from Client Block 87% –– Breach URI: /#modelbreach/114111 ]·
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Controlled and Model Breach 87% –– Breach URI: /#modelbreach/114115 ]·
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Breaches Over Time Block 87% –– Breach URI: /#modelbreach/114116 ]·
[Model Breach: Antigena / Network::External Threat::Antigena Suspicious File Block 61% –– Breach URI: /#modelbreach/114121 ]·
[Model Breach: Antigena / Network::External Threat::Antigena File then New Outbound Block 100% –– Breach URI: /#modelbreach/114123 ]·
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Enhanced Monitoring from Client Block 100% –– Breach URI: /#modelbreach/114125 ]

List of IoCs

IoC - Type - Description + Confidence

5.188.87[.]58 - IP address - C2 endpoint

80.66.88[.]145 - IP address - C2 endpoint

/bfyxraav - URI - Possible C2 endpoint URI

/msibfyxraav - URI - Possible C2 endpoint URI

Mozilla/4.0 (compatible; Win32; WinHttp.WinHttpRequest.5) - User agent - Probable user agent leveraged

curl - User agent - Probable user agent leveraged

curl/8.0.1 - User agent - Probable user agent leveraged

Mozilla/4.0 (compatible; Synapse) - User agent - Probable user agent leveraged

Autoit3.exe - Filename - Exe file

CvUYLoTv.au3

eDVeqcCe.au3

FeLlcFRS.au3

FTEZlGhe.au3

HOrzcEWV.au3

rKlArXHH.au3

SjadeWUz.au3

ZgOLxJQy.au3

zSrxhagw.au3

ALOXitYE.au3

DKRcfZfV.au3

gQZVKzek.au3

JZrvmJXK.au3

kLECCtMw.au3

LEXCjXKl.au3

luqWdAzF.au3

mUBNrGpv.au3

OoCdHeJT.au3

PcEJXfIl.au3

ssElzrDV.au3

TcBwRRnp.au3

TFvAUIgu.au3

xkwtvq.au3

otxynh.au3

dcthbq.au3 - Filenames - Possible exe files delivered in response to curl/8.0.1 GET requests with Target URI '/msibfyxraav

f3a0a85fe2ea4a00b3710ef4833b07a5d766702b263fda88101e0cb804d8c699 - SHA256 file hash - Possible SHA256 hashes of 'Autoit3.exe' files

afa3feea5964846cd436b978faa7d31938e666288ffaa75d6ba75bfe6c12bf61 - SHA256 file hash - Possible SHA256 hashes of 'Autoit3.exe' files

63aeac3b007436fa8b7ea25298362330423b80a4cb9269fd2c3e6ab1b1289208 - SHA256 file hash - Possible SHA256 hashes of 'Autoit3.exe' files

ab6704e836a51555ec32d1ff009a79692fa2d11205f9b4962121bda88ba55486 - SHA256 file hash - Possible SHA256 hashes of 'Autoit3.exe' files

References

1. https://www.truesec.com/hub/blog/darkgate-loader-delivered-via-teams

2. https://feedit.cz/wp-content/uploads/2023/03/YiR2022_onepager_ransomware_loaders.pdf

‍3. https://www.virustotal.com/gui/ip-address/5.188.87[.]58

‍4. https://www.forescout.com/resources/darkgate-loader-malspam-campaign/

‍5. https://otx.alienvault.com/indicator/ip/80.66.88[.]145

Written by

Natalia Sánchez Rocafort

Cyber Security Analyst

Inside the SOC

Written by

Natalia Sánchez Rocafort

Cyber Security Analyst

Chief AI Officer, Darktrace

Watch the NIS2 Webinar

Blog

AI

September 3, 2026

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

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.

About the author

Dr. Tim Bazalgette

Chief AI Officer, Darktrace

Blog

OT

September 3, 2026

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

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
Initial Access	T1189	Drive-by Compromise
Exfiltration	T1041	Exfiltration Over C2 Channel
Exfiltration	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

About the author

Parvatha Ananthakannan

Cyber Analyst

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Conclusion

Appendices

Darktrace DETECT Model Detections

List of IoCs

References

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MITRE ATT&CK Mapping