Blog
/
/
September 19, 2021

Defending Tokyo Olympics: AI Neutralizes IoT Attack

Learn how Darktrace autonomously thwarted a cyber-attack on a national sporting body before the Tokyo Olympics in this detailed breakdown.
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
Oakley Cox
Director of Product
Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
19
Sep 2021

One of the greatest issues in security is how to deal with high-stress scenarios when there is a significant breach, and there is too much to do in too little time. The nightmare scenario for any CISO is when this happens during a critical moment for the organization: an important acquisition, a crucial news announcement, or in this case, a global sporting event attracting an audience of millions.

Threat actors often exploit the pressure of these events to cause disruption or extract hefty sums. Sporting occasions, especially Formula 1 races, the Super Bowl, and the Olympics, attract a great deal of criminal interest.

The games begin

There have been several recorded attacks and data breaches at the Olympics this year, including an incident when a volleyball commentator asked his colleague for his computer password – not realizing he was still on air.

In a more nefarious case discovered by Darktrace, a Raspberry Pi device was covertly implanted into a national sporting body directly involved in the Olympics, in an attempt to exfiltrate sensitive data. The events took place one week before the start of the Games, and a data breach at this time would have had significant ramifications for the reputation of the organization, the confidentiality of their plans, and potentially the safety of their athletes.

Darktrace AI recognized this activity as malicious given its evolving understanding of ‘self’ for the organization, and Antigena – Darktrace’s autonomous response capability – took action at machine speed to interrupt the threat, affording the human security team the critical time they needed to catch up and neutralize the attack.

In what follows, we break down the attack.

Figure 1: The overall dwell time was three days.

Breaking down the attack

July 15, 14:09 — Initial intrusion

An unauthorized Raspberry Pi device connected to the organization’s digital environment – disguised and named in a way which mimicked the corporate naming convention. As a small IoT device, Raspberry Pis can be easily hidden and are difficult to locate physically in large environments. They have been used in various high-profile hacks in the past including the 2018 NASA breach.

IoT devices – from printers to fish tanks – pose a serious risk to security, as they can be exploited to gather information, move laterally, and escalate privileges.

July 15, 15:25 — External VPN activity

Anomalous UDP connections were made to an external endpoint over port 1194 (Open VPN activity). URIs showed that the device downloaded data potentially associated with Open VPN configuration files. This could represent an attempt to establish a secure channel for malicious activity such as data exfiltration.

By establishing an outgoing VPN, the attacker obfuscated their activity and bypassed the organization’s signature-based security, which could not detect the encrypted traffic. Antigena immediately blocked the suspicious connectivity, regardless of the encryption, identifying that the activity was a deviation from the ‘pattern of life’ for new devices.

July 15, 16:04 — Possible C2 activity

The Raspberry Pi soon began making repeated HTTP connections to a new external endpoint and downloaded octet streams — arbitrary binary data. It seems the activity was initiated by a standalone software process as opposed to a web browser.

Darktrace revealed that the device was performing an unusual external data transfer to the same endpoint, uploading 7.5 MB which likely contained call home data about the new location and name of the device.

July 15, 16:41 — Internal reconnaissance

The device engaged in TCP scanning across three unique internal IP addresses over a wide range of ports. Although the network scan only targeted three internal servers, the activity was identified by Darktrace as a suspicious increase in internal connections and failed internal connections.

Antigena instantly stopped the Raspberry Pi from making internal connections over the ports involved in the scanning activity, as well as enforcing the device’s ‘pattern of life’.

Figure 2: Device event log showing the components which enable Darktrace to detect network scanning.

July 15, 18:14 — Multiple internal reconnaissance tactics

The Raspberry Pi then scanned a large number of devices on SMB port 445 and engaged in suspicious use of the outdated SMB version 1 protocol, suggesting more in-depth reconnaissance to find exploitable vulnerabilities.

Reacting to the scanning activity alongside the insecure protocol SMBv1, Antigena blocked connections from the source device to the destination IPs for one hour.

Four minutes later, the device engaged in connections to the open-source vulnerability scanner, Nmap. Nmap can be used legitimately for vulnerability scanning and so often is not alerted to by traditional security tools. However, Darktrace’s AI detected that the use of the tool was highly anomalous, and so blocked all outgoing traffic for ten minutes.

July 15, 22:03 — Final reconnaissance

Three hours later, the Raspberry Pi initiated another network scan across six unique external IPs – this was in preparation for the final data exfiltration. Antigena responded with instant, specific blocks to the external IPs which the device was attempting to connect to – before any data could be exfiltrated.

After 30 minutes, Darktrace detected bruteforcing activity from the Raspberry Pi using the SMB and NTLM authentication protocols. The device made a large number of failed login attempts to a single internal device using over 100 unique user accounts. Antigena blocked the activity, successfully stopping another wave of attempted SMB lateral movement.

By this stage, Antigena had bought the security team enough time to respond. The team applied an Antigena quarantine rule (the most severe action Antigena can take) to the Raspberry Pi, until they were able to find the physical location of the device and unplug it from the network.

How AI Analyst stitched together the incident

Cyber AI Analyst autonomously reported on three key moments of the attack:

  • Unusual External Data Transfer
  • Possible HTTP Command and Control
  • TCP Scanning of Multiple Devices (the attempted data exfiltration)

It tied together activities over the span of multiple days, which could have been easily missed by human analysis. The AI provided crucial pieces of information, including the extent of the scanning activity. Such insights are time-consuming to calculate manually.

Figure 3: A screenshot from Cyber AI Analyst summarizing potential C2 activity.

Autonomous Response

Antigena took targeted action throughout to neutralize the suspicious behavior, while allowing normal business operations to continue unhindered.

Rather than widespread blocking, Antigena implemented a range of nuanced responses depending on the situation, always taking the smallest action necessary to deal with the threat.

Figure 4: Darktrace’s UI reveals the attempted network reconnaissance, and Antigena actions a targeted response. All IP addresses have been randomized.

Raspberry Pi: IoT threats

In an event involving 206 countries and 11,000 athletes, facing attacks from hacktivists, criminal groups, and nation states, with many broadcasters working remotely and millions watching from home, organizations involved in the Olympics needed a security solution which could rise to the occasion.

Even with the largest affairs, threats can come from the smallest places. The ability to detect unauthorized IoT devices and maintain visibility over all activity in your digital estate is essential.

Autonomous Response protects against the unexpected, stopping malicious activity at machine speed without any user input. This is necessary for rapid response and remediation, especially for resource-stretched internal security teams. When it comes to defending systems and outpacing attackers, AI always wins the race.

Thanks to Darktrace analysts Emma Foulger and Greg Chapman for their insights on the above threat find.

Learn how two rogue Raspberry Pi devices infected a healthcare provider

Darktrace model detections:

  • Compromise / Ransomware / Suspicious SMB Activity
  • Tags / New Raspberry Pi Device
  • Device / Network Scan
  • Unusual Activity / Unusual Raspberry Pi Activity
  • Antigena / Network / Insider Threat / Antigena Network Scan Block
  • Device / Suspicious Network Scan Activity
  • Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block
  • Antigena / Network / Significant Anomaly / Antigena Controlled and Model Breach
  • Device / Suspicious SMB Scanning Activity
  • Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block
  • Device / Attack and Recon Tools
  • Device / New Device with Attack Tools
  • Device / Anomalous Nmap Activity
  • Device / External Network Scan
  • Device / SMB Session Bruteforce
  • Antigena / Network / Manual / Block All Outgoing Connections
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
Oakley Cox
Director of Product

More in this series

No items found.

Blog

/

Network

/

June 27, 2025

Patch and Persist: Darktrace’s Detection of Blind Eagle (APT-C-36)

Default blog imageDefault blog image

What is Blind Eagle?

Since 2018, APT-C-36, also known as Blind Eagle, has been observed performing cyber-attacks targeting various sectors across multiple countries in Latin America, with a particular focus on Colombian organizations.

Blind Eagle characteristically targets government institutions, financial organizations, and critical infrastructure [1][2].

Attacks carried out by Blind Eagle actors typically start with a phishing email and the group have been observed utilizing various Remote Access Trojans (RAT) variants, which often have in-built methods for hiding command-and-control (C2) traffic from detection [3].

What we know about Blind Eagle from a recent campaign

Since November 2024, Blind Eagle actors have been conducting an ongoing campaign targeting Colombian organizations [1].

In this campaign, threat actors have been observed using phishing emails to deliver malicious URL links to targeted recipients, similar to the way threat actors have previously been observed exploiting CVE-2024-43451, a vulnerability in Microsoft Windows that allows the disclosure of a user’s NTLMv2 password hash upon minimal interaction with a malicious file [4].

Despite Microsoft patching this vulnerability in November 2024 [1][4], Blind Eagle actors have continued to exploit the minimal interaction mechanism, though no longer with the intent of harvesting NTLMv2 password hashes. Instead, phishing emails are sent to targets containing a malicious URL which, when clicked, initiates the download of a malicious file. This file is then triggered by minimal user interaction.

Clicking on the file triggers a WebDAV request, with a connection being made over HTTP port 80 using the user agent ‘Microsoft-WebDAV-MiniRedir/10.0.19044’. WebDAV is a transmission protocol which allows files or complete directories to be made available through the internet, and to be transmitted to devices [5]. The next stage payload is then downloaded via another WebDAV request and malware is executed on the target device.

Attackers are notified when a recipient downloads the malicious files they send, providing an insight into potential targets [1].

Darktrace’s coverage of Blind Eagle

In late February 2025, Darktrace observed activity assessed with medium confidence to be  associated with Blind Eagle on the network of a customer in Colombia.

Within a period of just five hours, Darktrace / NETWORK detected a device being redirected through a rare external location, downloading multiple executable files, and ultimately exfiltrating data from the customer’s environment.

Since the customer did not have Darktrace’s Autonomous Response capability enabled on their network, no actions were taken to contain the compromise, allowing it to escalate until the customer’s security team responded to the alerts provided by Darktrace.

Darktrace observed a device on the customer’s network being directed over HTTP to a rare external IP, namely 62[.]60[.]226[.]112, which had never previously been seen in this customer’s environment and was geolocated in Germany. Multiple open-source intelligence (OSINT) providers have since linked this endpoint with phishing and malware campaigns [9].

The device then proceeded to download the executable file hxxp://62[.]60[.]226[.]112/file/3601_2042.exe.

Darktrace’s detection of the affected device connecting to an unusual location based in Germany.
Figure 1: Darktrace’s detection of the affected device connecting to an unusual location based in Germany.
Darktrace’s detection of the affected device downloading an executable file from the suspicious endpoint.
Figure 2: Darktrace’s detection of the affected device downloading an executable file from the suspicious endpoint.

The device was then observed making unusual connections to the rare endpoint 21ene.ip-ddns[.]com and performing unusual external data activity.

This dynamic DNS endpoint allows a device to access an endpoint using a domain name in place of a changing IP address. Dynamic DNS services ensure the DNS record of a domain name is automatically updated when the IP address changes. As such, malicious actors can use these services and endpoints to dynamically establish connections to C2 infrastructure [6].

Further investigation into this dynamic endpoint using OSINT revealed multiple associations with previous likely Blind Eagle compromises, as well as Remcos malware, a RAT commonly deployed via phishing campaigns [7][8][10].

Darktrace’s detection of the affected device connecting to the suspicious dynamic DNS endpoint, 21ene.ip-ddns[.]com.
Figure 3: Darktrace’s detection of the affected device connecting to the suspicious dynamic DNS endpoint, 21ene.ip-ddns[.]com.

Shortly after this, Darktrace observed the user agent ‘Microsoft-WebDAV-MiniRedir/10.0.19045’, indicating usage of the aforementioned transmission protocol WebDAV. The device was subsequently observed connected to an endpoint associated with Github and downloading data, suggesting that the device was retrieving a malicious tool or payload. The device then began to communicate to the malicious endpoint diciembrenotasenclub[.]longmusic[.]com over the new TCP port 1512 [11].

Around this time, the device was also observed uploading data to the endpoints 21ene.ip-ddns[.]com and diciembrenotasenclub[.]longmusic[.]com, with transfers of 60 MiB and 5.6 MiB observed respectively.

Figure 4: UI graph showing external data transfer activity.

This chain of activity triggered an Enhanced Monitoring model alert in Darktrace / NETWORK. These high-priority model alerts are designed to trigger in response to higher fidelity indicators of compromise (IoCs), suggesting that a device is performing activity consistent with a compromise.

 Darktrace’s detection of initial attack chain activity.
Figure 5: Darktrace’s detection of initial attack chain activity.

A second Enhanced Monitoring model was also triggered by this device following the download of the aforementioned executable file (hxxp://62[.]60[.]226[.]112/file/3601_2042.exe) and the observed increase in C2 activity.

Following this activity, Darktrace continued to observe the device beaconing to the 21ene.ip-ddns[.]com endpoint.

Darktrace’s Cyber AI Analyst was able to correlate each of the individual detections involved in this compromise, identifying them as part of a broader incident that encompassed C2 connectivity, suspicious downloads, and external data transfers.

Cyber AI Analyst’s investigation into the activity observed on the affected device.
Figure 6: Cyber AI Analyst’s investigation into the activity observed on the affected device.
Figure 7: Cyber AI Analyst’s detection of the affected device’s broader connectivity throughout the course of the attack.

As the affected customer did not have Darktrace’s Autonomous Response configured at the time, the attack was able to progress unabated. Had Darktrace been properly enabled, it would have been able to take a number of actions to halt the escalation of the attack.

For example, the unusual beaconing connections and the download of an unexpected file from an uncommon location would have been shut down by blocking the device from making external connections to the relevant destinations.

Conclusion

The persistence of Blind Eagle and ability to adapt its tactics, even after patches were released, and the speed at which the group were able to continue using pre-established TTPs highlights that timely vulnerability management and patch application, while essential, is not a standalone defense.

Organizations must adopt security solutions that use anomaly-based detection to identify emerging and adapting threats by recognizing deviations in user or device behavior that may indicate malicious activity. Complementing this with an autonomous decision maker that can identify, connect, and contain compromise-like activity is crucial for safeguarding organizational networks against constantly evolving and sophisticated threat actors.

Credit to Charlotte Thompson (Senior Cyber Analyst), Eugene Chua (Principal Cyber Analyst) and Ryan Traill (Analyst Content Lead)

Appendices

IoCs

IoC – Type - Confidence
Microsoft-WebDAV-MiniRedir/10.0.19045 – User Agent

62[.]60[.]226[.]112 – IP – Medium Confidence

hxxp://62[.]60[.]226[.]112/file/3601_2042.exe – Payload Download – Medium Confidence

21ene.ip-ddns[.]com – Dynamic DNS Endpoint – Medium Confidence

diciembrenotasenclub[.]longmusic[.]com  - Hostname – Medium Confidence

Darktrace’s model alert coverage

Anomalous File / Suspicious HTTP Redirect
Anomalous File / EXE from Rare External Location
Anomalous File / Multiple EXE from Rare External Location
Anomalous Server Activity / Outgoing from Server
Unusual Activity / Unusual External Data to New Endpoint
Device / Anomalous Github Download
Anomalous Connection / Multiple Connections to New External TCP Port
Device / Initial Attack Chain Activity
Anomalous Server Activity / Rare External from Server
Compromise / Suspicious File and C2
Compromise / Fast Beaconing to DGA
Compromise / Large Number of Suspicious Failed Connections
Device / Large Number of Model Alert

Mitre Attack Mapping:

Tactic – Technique – Technique Name

Initial Access - T1189 – Drive-by Compromise
Initial Access - T1190 – Exploit Public-Facing Application
Initial Access ICS - T0862 – Supply Chain Compromise
Initial Access ICS - T0865 – Spearphishing Attachment
Initial Access ICS - T0817 - Drive-by Compromise
Resource Development - T1588.001 – Malware
Lateral Movement ICS - T0843 – Program Download
Command and Control - T1105 - Ingress Tool Transfer
Command and Control - T1095 – Non-Application Layer Protocol
Command and Control - T1571 – Non-Standard Port
Command and Control - T1568.002 – Domain Generation Algorithms
Command and Control ICS - T0869 – Standard Application Layer Protocol
Evasion ICS - T0849 – Masquerading
Exfiltration - T1041 – Exfiltration Over C2 Channel
Exfiltration - T1567.002 – Exfiltration to Cloud Storage

References

1)    https://research.checkpoint.com/2025/blind-eagle-and-justice-for-all/

2)    https://assets.kpmg.com/content/dam/kpmgsites/in/pdf/2025/04/kpmg-ctip-blind-eagle-01-apr-2025.pdf.coredownload.inline.pdf

3)    https://www.checkpoint.com/cyber-hub/threat-prevention/what-is-remote-access-trojan/#:~:text=They%20might%20be%20attached%20to,remote%20access%20or%20system%20administration

4)    https://msrc.microsoft.com/update-guide/vulnerability/CVE-2024-43451

5)    https://www.ionos.co.uk/digitalguide/server/know-how/webdav/

6)    https://vercara.digicert.com/resources/dynamic-dns-resolution-as-an-obfuscation-technique

7)    https://threatfox.abuse.ch/ioc/1437795

8)    https://www.checkpoint.com/cyber-hub/threat-prevention/what-is-malware/remcos-malware/

9)    https://www.virustotal.com/gui/url/b3189db6ddc578005cb6986f86e9680e7f71fe69f87f9498fa77ed7b1285e268

10) https://www.virustotal.com/gui/domain/21ene.ip-ddns.com

11) https://www.virustotal.com/gui/domain/diciembrenotasenclub.longmusic.com/community

Continue reading
About the author
Charlotte Thompson
Cyber Analyst

Blog

/

Network

/

June 19, 2025

Customer Case Study: Leading Petrochemical Manufacturer

Default blog imageDefault blog image

Headquartered in Saudi Arabia, this industry leading petrochemical manufacturer serves customers in more than 80 countries across diverse markets throughout Europe, Africa, Latin America, the Middle East, China, and Southeast Asia.

Cyber resiliency critical to growth strategy

This leading petrochemical manufacturer’s vision is to be one of the major global players in the production and marketing of designated petrochemicals and downstream products. The company aims to significantly increase its capacity to up to a million metric tons within the next few years.

With cyber-attacks on critical infrastructure increasing 30% globally last year, cyber resiliency is essential to supporting the company’s strategic business goals of:

  • Maximizing production through efficient asset utilization
  • Maximizing sales by conducting 90% of its business outside Saudi Arabia
  • Optimizing resources and processes by integrating with UN Global Compact principles for sustainability and efficiency
  • Growing its business portfolio by engaging in joint ventures to diversify production and add value to the economy

However, the industry leader faced several challenges in its drive to fortify its cybersecurity defenses.

Visibility gaps delay response time

The company’s existing security setup provided limited visibility to the in-house security team, hindering its ability to detect anomalous network and user activity in real time. This resulted in delayed responses to potential incidents, making proactive issue resolution difficult and any remediation in the event of a successful attack costly and time-consuming.

Manual detection drains resources

Without automated detection and response capabilities, the organization’s security team had to manually monitor for suspicious activity – a time-consuming and inefficient approach that strained resources and left the organization vulnerable. This made it difficult for the team to stay current with training or acquire new skills and certifications, which are core to the ethos of both the company’s owners and the team itself.

Cyber-attacks on critical infrastructure increasing

The petrochemical manufacturer is part of a broader ecosystem of companies, making the protection of its supply chain – both upstream and downstream – critical. With several manufacturing entities and multiple locations, the customer’s internal structure is complex and challenging to secure. As cyber-attacks on critical infrastructure escalate, it needed a more comprehensive approach to safeguard its business and the wider ecosystem.

Keeping and growing skills and focus in-house

To strengthen its cybersecurity strategy, the company considered two options:

  1. Make a significant initial and ongoing investment in a Security Operations Center (SOC), which would involve skills development outside the company and substantial management overhead.
  2. Use a combination of new, automated tools and an outsourced Managed Detection and Response (MDR) service to reduce the burden on internal security specialists and allow the company to invest in upskilling its staff so they can focus on more strategic tasks.

Faced with this choice between entirely outsourcing security and augmenting the security team with new capabilities, the customer chose the second option, selecting Darktrace to automate the company’s monitoring, detection, and response. Today, the petrochemical manufacturer is using:

Extending the SOC with 24/7 expert support

To alleviate the burden on its lean security team, the company augmented its in-house capabilities with Darktrace’s Managed Detection & Response service. This support acts as an extension of its SOC, providing 24/7 monitoring, investigation, and escalation of high-priority threats. With Darktrace’s global SOC managing alert triage and autonomously containing threats, the organization’s internal team can focus on strategic initiatives. The result is a stronger security posture and increased capacity to proactively address evolving cyber risks – without expanding headcount or sacrificing visibility.

A unique approach to AI

In its search for a new security platform, the company’s Director of Information Technology said Darktrace’s autonomous response capability, coupled with Self-Learning AI-driven threat reduction, were two big reasons for selecting Darktrace over competing products and services.

AI was a huge factor – no one else was doing what Darktrace was doing with [AI].”

Demonstrated visibility

Before Darktrace, the customer had no visibility into the network activity to and from remote worker devices. Some employees need the ability to connect to its networks at any time and from any location, including the Director of Information Technology. The trial deployment of Darktrace / ENDPOINT was a success and gave the team peace of mind that, no matter the location or device, high-value remote workers were protected by Darktrace.

Modular architecture  

Darktrace's modular architecture allowed the company to deploy security controls across its complex, multi-entity environment. The company’s different locations run on segregated networks but are still interconnected and need to be protected. Darktrace / NETWORK provides a unified view and coordinated security response across the organization’s entire network infrastructure, including endpoint devices.

Results

The petrochemical manufacturer is using Darktrace across all of its locations and has achieved total visibility across network and user activity. “Darktrace is increasing in value every day,” said the Director of Information Technology.

I don’t have a big team, and Darktrace makes our lives very, very easy, not least the automation of some of the tasks that require constant manual review.”

Time savings frees analysts to focus on proactive security

Darktrace / NETWORK provides continuous, AI-driven monitoring and analysis of the company’s network activity, user behavior, and threat patterns, establishing a baseline of what normal activity looks like, and then alerting analysts to any deviations from normal traffic, activity, and behaviors. Darktrace’s autonomous response capabilities speed up response to detected threats, meaning intervention from the security team is required for fewer incidents and alerts.

In October 2024 alone, Darktrace Cyber AI Analyst saved the team 810 investigation hours, and autonomously responded to 180 anomalous behaviors that were uncovered during the investigations. With Darktrace managing the majority of threat detection and response efforts, the security team has been able to change its day-to-day activity from manual review of traffic and alerts and belated response to activity, to proactively fortifying its detection and response posture and upskilling to meet evolving requirements.  

Layered email protection reduces phishing threats

The company’s email infrastructure posed a challenge due to petrochemical industry regulations requiring on-premises email servers, with some security delivered via Microsoft Azure. By integrating Darktrace / EMAIL into the Azure stack, the organization has reduced the volume of phishing emails its users receive by 5%.

“Now we have one more layer of security related to email – every email goes through two filters. If something is not being caught or traced by Azure, it is being detected by Darktrace,” said the Director of Information Technology. “As a result, we’re now seeing only about 15% to 20% of the phishing emails we used to receive before implementing Darktrace.”

Preparing for a secure future

The time saved using Darktrace has helped the security team take proactive steps, including preparing for new cyber resilience regulations for Saudi Arabia’s Critical National Infrastructure, as mandated by the National Cybersecurity Authority (NCA).

“The team now has ample time to prepare policies and procedures that meet the new NCA regulations and, in some cases, enhance the requirements of the new law,” said the Director of Information Technology. “All of this is possible because they don’t need to keep watch; Darktrace takes on so much of that task for them.”

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