Blog
/
/
May 3, 2021

Understanding Modern-Day Cyber Attacks

Discover how Darktrace detects and mitigates threats in IoT ecosystems and globalized supply chains that are constantly evolving.
No items found.
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.
No items found.
Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
03
May 2021

It’s ten to five on a Friday afternoon. A technician has come in to perform a routine check on an electronic door. She enters the office with no issues – she works for a trusted third-party vendor, employees see her every week. She opens her laptop and connects to the Door Access Control Unit, a small Internet of Things (IoT) device used to operate the smart lock. Minutes later, trojans have been downloaded onto the company network, a crypto-mining operation has begun, and there is evidence of confidential data being exfiltrated. Where did things go wrong?

Threats in a business: A new dawn surfaces

As organizations keep pace with the demands of digital transformation, the attack surface has become broader than ever before. There are numerous points of entry for a cyber-criminal – from vulnerabilities in IoT ecosystems, to blind spots in supply chains, to insiders misusing their access to the business. Darktrace sees these threats every day. Sometimes, like in the real-world example above, which will be examined in this blog, they can occur in the very same attack.

Insider threats can use their familiarity and level of access to a system as a critical advantage when evading detection and launching an attack. But insiders don’t necessarily have to be malicious. Every employee or contractor is a potential threat: clicking on a phishing link or accidentally releasing data often leads to wide-scale breaches.

At the same time, connectivity in the workspace – with each IoT device communicating with the corporate network and the Internet on its own IP address – is an urgent security issue. Access control systems, for example, add a layer of physical security by tracking who enters the office and when. However, these same control systems imperil digital security by introducing a cluster of sensors, locks, alarm systems, and keypads, which hold sensitive user information and connect to company infrastructure.

Furthermore, a significant proportion of IoT devices are built without security in mind. Vendors prioritize time-to-market and often don’t have the resources to invest in baked-in security measures. Consider the number of start-ups which manufacture IoT – over 60% of home automation companies have fewer than ten employees.

Insider threat detected by Cyber AI

In January 2021, a medium-sized North American company suffered a supply chain attack when a third-party vendor connected to the control unit for a smart door.

Figure 1: The attack lasted 3.5 hours in total, commencing 16:50 local time.

The technician from the vendor’s company had come in to perform scheduled maintenance. They had been authorized to connect directly to the Door Access Control Unit, yet were unaware that the laptop they were using, brought in from outside of the organization, had been infected with malware.

As soon as the laptop connected with the control unit, the malware detected an open port, identified the vulnerability, and began moving laterally. Within minutes, the IoT device was seen making highly unusual connections to rare external IP addresses. The connections were made using HTTP and contained suspicious user agents and URIs.

Darktrace then detected that the control unit was attempting to download trojans and other payloads, including upsupx2.exe and 36BB9658.moe. Other connections were used to send base64 encoded strings containing the device name and the organization’s external IP address.

Cryptocurrency mining activity with a Monero (XMR) CPU miner was detected shortly afterwards. The device also utilized an SMB exploit to make external connections on port 445 while searching for vulnerable internal devices using the outdated SMBv1 protocol.

One hour later, the device connected to an endpoint related to the third-party remote access tool TeamViewer. After a few minutes, the device was seen uploading over 15 MB to a 100% rare external IP.

Figure 2: Timeline of the connections made by an example device on the days around an incident (blue). The connections associated with the compromise are a significant deviation from the device’s normal pattern of life, and result in multiple unusual activity events and repeated model breaches (orange).

Security threats in the supply chain

Cyber AI flagged the insider threat to the customer as soon as the control unit had been compromised. The attack had managed to bypass the rest of the organization’s security stack, for the simple reason that it was introduced directly from a trusted external laptop, and the IoT device itself was managed by the third-party vendor, so the customer had little visibility over it.

Traditional security tools are ineffective against supply chain attacks such as this. From the SolarWinds hack to Vendor Email Compromise, 2021 has put the nail in the coffin for signature-based security – proving that we cannot rely on yesterday’s attacks to predict tomorrow’s threats.

International supply chains and the sheer number of different partners and suppliers which modern organizations work with thus pose a serious security dilemma: how can we allow external vendors onto our network and keep an airtight system?

The first answer is zero-trust access. This involves treating every device as malicious, inside and outside the corporate network, and demanding verification at all stages. The second answer is visibility and response. Security products must shed a clear light into cloud and IoT infrastructure, and react autonomously as soon as subtle anomalies emerge across the enterprise.

IoT investigated

Darktrace’s Cyber AI Analyst reported on every stage of the attack, including the download of the first malicious executable file.

Figure 3: Example of Cyber AI Analyst detecting anomalous behavior on a device, including C2 connectivity and suspicious file downloads.

Cyber AI Analyst investigated the C2 connectivity, providing a high-level summary of the activity. The IoT device had accessed suspicious MOE files with randomly generated alphanumeric names.

Figure 4: A Cyber AI Analyst summary of C2 connectivity for a device.

Not only did the AI detect every stage of the activity, but the customer was also alerted via a Proactive Threat Notification following a high scoring model breach at 16:59, just minutes after the attack had commenced.

Stranger danger

Third parties coming in to tweak device settings and adjust the network can have unintended consequences. The hyper-connected world which we’re living in, with the advent of 5G and Industry 4.0, has become a digital playground for cyber-criminals.

In the real-world case study above, the IoT device was unsecured and misconfigured. With rushed creations of IoT ecosystems, intertwining supply chains, and a breadth of individuals and devices connecting to corporate infrastructure, modern-day organizations cannot expect simple security tools which rely on pre-defined rules to stop insider threats and other advanced cyber-attacks.

The organization did not have visibility over the management of the Door Access Control Unit. Despite this, and despite no prior knowledge of the attack type or the vulnerabilities present in the IoT device, Darktrace detected the behavioral anomalies immediately. Without Cyber AI, the infection could have remained on the customer’s environment for weeks or months, escalating privileges, silently crypto-mining, and exfiltrating sensitive company data.

Thanks to Darktrace analyst Grace Carballo for her insights on the above threat find.

Learn more about insider threats

Darktrace model detections:

  • Anomalous File/Anomalous Octet Stream
  • Anomalous Connection/New User Agent to IP Without Hostname
  • Unusual Activity/Unusual External Connectivity
  • Device/Increased External Connectivity
  • Anomalous Server Activity/Outgoing from Server
  • Device/New User Agent and New IP
  • Compliance/Cryptocurrency Mining Activity
  • Compliance/External Windows Connectivity
  • Anomalous File/Multiple EXE from Rare External Locations
  • Anomalous File/EXE from Rare External Location
  • Device/Large Number of Model Breaches
  • Anomalous File/Internet Facing System File Download
  • Device/Initial Breach Chain Compromise
  • Device/SMB Session Bruteforce
  • Device/Network Scan- Low Anomaly Score
  • Device/Large Number of Connections to New Endpoint
  • Anomalous Server Activity/Outgoing from Server
  • Compromise/Beacon to Young Endpoint
  • Anomalous Server Activity/Rare External from Server
  • Device/Multiple C2 Model Breaches
  • Compliance/Remote Management Tool on Server
  • Anomalous Connection/Data Sent to New External Device

No items found.
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.
No items found.

More in this series

No items found.

Blog

/

/

July 1, 2025

Pre-CVE Threat Detection: 8 Examples Identifying Malicious Activity Prior to Public Disclosure of a Vulnerability

Default blog imageDefault blog image

Can you detect cyber threats before the world knows about them?

Every year, tens of thousands of Common Vulnerabilities and Exposures (CVEs) are disclosed, over 40,000 in 2024 alone [1], and a predicted higher number for 2025 by the Forum for Incident Response and Security Teams (FIRST).

However, cybercriminals don't wait for disclosure. They exploit zero-days while defenders remain in the dark.

Traditional, signature-based tools struggle to detect these early-stage threats. That’s why anomaly detection is becoming essential for organizations seeking pre-CVE detection.

Understanding the gap between zero-day attacks and public CVE disclosure

When a vulnerability is discovered, the standard practice is to report it to the vendor or the responsible organization, allowing them to develop and distribute a patch or fix before the details are made public. This is known as responsible disclosure.

The gap between exploitation of a zero-day and the disclosure of the vulnerability can sometimes be considerable, and retroactively attempting to identify successful exploitation on your network can be challenging, particularly if taking a signature-based approach.

However, abnormal behaviors in networks or systems, such as unusual login patterns or data transfers, can indicate attempted cyber-attacks, insider threats, or compromised systems.

Detecting threats without relying on CVE disclosure

Since Darktrace does not rely on rules or signatures, it can detect malicious activity that is anomalous even without full context of the specific device or asset in question.

For example, during the Fortinet exploitation late last year, the Darktrace Threat Research team were investigating a different Fortinet vulnerability, namely CVE 2024-23113, for exploitation when Mandiant released a security advisory around CVE 2024-47575, which aligned closely with Darktrace’s findings.

Retrospective analysis like this is used by Darktrace’s threat researchers to better understand detections across the threat landscape and to add additional context.

Below are eight examples from the past year where Darktrace detected malicious activity days or even weeks before a vulnerability was publicly disclosed.

ten examples from the past year where Darktrace detected malicious activity days or even weeks before a vulnerability was publicly disclosed.

Trends in pre-cve exploitation

The attack vs. patch race

In many cases, the disclosure of an exploited vulnerability can be off the back of an incident response investigation related to a compromise by an advanced threat actor using a zero-day. Once the vulnerability is registered and publicly disclosed as having been exploited, it can kick off a race between the attacker and defender.

Skilled nation-state actors

Nation-state actors, highly skilled with significant resources, are known to use a range of capabilities to achieve their target, including zero-day use. Often, pre-CVE activity is “low and slow”, last for months with high operational security.

After CVE disclosure, the barriers to entry lower, allowing less skilled and less resourced attackers, like some ransomware gangs, to exploit the vulnerability and cause harm. This is why two distinct types of activity are often seen: pre and post disclosure of an exploited vulnerability.

Examples of exploitation

Darktrace saw this consistent story line play out during several of the Fortinet and PAN OS threat actor campaigns highlighted above last year, where nation-state actors were seen exploiting vulnerabilities first, followed by ransomware gangs impacting organizations [2].

The same applies with the recent SAP Netweaver exploitations being tied to a China based threat actor earlier this spring with subsequent ransomware incidents being observed [3].

You spotted the anomaly but did you stop the breach?

Anomaly-based detection offers the benefit of identifying malicious activity even before a CVE is disclosed; however, security teams still need to quickly contain and isolate the activity.

For example, during the Ivanti chaining exploitation in the early part of 2025, a customer had Darktrace’s Autonomous Response capability enabled on their network. As a result, Darktrace was able to contain the compromise and shut down any ongoing suspicious connectivity by blocking internal connections and enforcing a “pattern of life” on the affected device.

This pre-CVE detection and response by Darktrace occurred 11 days before any public disclosure, demonstrating the value of an anomaly-based approach.

In some cases, customers have even reported that Darktrace stopped malicious exploitation of devices several days before a public disclosure of a vulnerability.

For example, During the ConnectWise exploitation, a customer informed the team that Darktrace had detected malicious software being installed via remote access. Upon further investigation, four servers were found to be impacted, while Autonomous Response had blocked outbound connections and enforced patterns of life on impacted devices.

Conclusion

By continuously analyzing behavioral patterns, systems can spot unusual activities and patterns from users, systems, and networks to detect anomalies that could signify a security breach.

Through ongoing monitoring and learning from these behaviors, anomaly-based security systems can detect threats that traditional signature-based solutions might miss, while also providing detailed insights into threat tactics, techniques, and procedures (TTPs). This type of behavioral intelligence supports pre-CVE detection, allows for a more adaptive security posture, and enables systems to evolve with the ever-changing threat landscape.

Credit to Nathaniel Jones (VP, Security & AI Strategy, Field CISO), Emma Fougler (Global Threat Research Operations Lead), Ryan Traill (Analyst Content Lead)

References and further reading:

  1. https://www.first.org/blog/20250607-Vulnerability-Forecast-for-2025
  2. https://cloud.google.com/blog/topics/threat-intelligence/fortimanager-zero-day-exploitation-cve-2024-47575
  3. https://thehackernews.com/2025/05/china-linked-hackers-exploit-sap-and.html

Realted Darktrace blogs:

*Self-reported by customer, confirmed afterwards.

**Updated January 2024 blog now reflects current findings

Continue reading
About the author

Blog

/

Network

/

June 27, 2025

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

login on laptop dual factor authenticationDefault 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
Your data. Our AI.
Elevate your network security with Darktrace AI