January 26, 2020

How AI Can Detect Bitcoin Mining Attack Via Citrix Flaw

Discover how Darktrace AI stops bitcoin mining attacks via Citrix flaws. Learn about the power of Autonomous Response against cyber threats. Read now!

Written by

Max Heinemeyer

Global Field CISO

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

Max Heinemeyer

Global Field CISO

Jan 2020

Over the last 14 days, Darktrace has detected at least 80 different customers all targeted by the same CVE-2019-19781 vulnerability — affecting the Citrix ADC (Citrix Application Delivery Controller) and Citrix Gateway solution for public cloud. Customers operating Darktrace Antigena in ‘active mode’ have all seen that this attack was neutralized within seconds.

According to the National Cyber Security Centre, the exploitation of this vulnerability allows an ‘unauthenticated attacker to perform arbitrary code execution’. While Citrix has released mitigation advice, patches are just being rolled out. This unfortunately left a critical window of time, during which the attackers could exploit the vulnerabilities. However, Darktrace’s immune system technology can effectively halt the attack and contain the damage.

This blog post outlines the attack lifecycle of a campaign exploiting the Citrix vulnerabilities to download crypto-mining malware. It is interesting to see how quick the cyber-criminals were to weaponize the Citrix exploits with crypto-mining payloads for generating profit. It shows that AI-powered Autonomous Response is pivotal in today’s fast-moving threat landscape, where patches might not be available or might take weeks to install safely.

Breaking down the attack lifecycle

The following description of the observed attack stages demonstrates how Darktrace Antigena’s independent and immediate action stops the attack in its tracks, provides visibility of the complete attack lifecycle, and significantly reduces security teams’ investigation time into this activity.

Darktrace’s detection capabilities highlight the steps taken by exploited Citrix Netscaler devices executing shell commands.
These devices begin by receiving HTTP POST requests to URIs that are vulnerable to directory traversal attacks, for example /vpn/…/vpns/cfg/smb.conf. This is visible in the below details provided by Darktrace.

Figure 1: A screenshot of the requests on a particular device

These POST requests are followed by high confidence alerts created by Darktrace – the attack behavior was very similar in different targeted organizations. The high-confidence alerts were equally similar, regardless of the target, as the attack behavior was the same.
Code execution is triggered, leading to the download of shell scripts and other malware with the end-goal of running crypto-mining malware.

Some of the high-confidence alerts are:

Compromise / High Volume of Connections with Beacon Score – used to identify command and control traffic
Compliance / Pastebin – triggers during suspicious and unusual Pastebin activity
Compliance / Crypto Currency Mining Activity
Anomalous Connection / Multiple Failed Connections to Rare Endpoint – indicating unsuccessful command and control traffic attempts
Anomalous File / Script from Rare External – indicating the download of a script file from a location on the internet that is not commonly visited by the targeted organization (often this is the initial infection or a later-stage payload)

In one example, a gateway device was seen downloading a shell script from a rare external endpoint in Russia, with a /ci.sh URI.

Figure 2: Darktrace’s Threat Visualizer showing an endpoint with 100% rarity

Next, compromised devices have been observed downloading an executable file from Ukraine (http://217.12.221[.]12/netscalerd), containing an ELF:BitCoinMiner Malware, triggering the cryptocurrency mining and command and control beaconing alerts.

Figure 3: The Anomalous File / EXE from Rare External Location alert triggered by C2 traffic

Figure 4: Darktrace showing further details about the downloaded malware

An immediate response

However, Darktrace Antigena kicks in as the machine defender, eliminating the incoming threat by blocking miner file downloads and activity for about a day. This offers the customer ample time to react to this anomalous activity and halts the malware’s spread to other devices. Intervening with surgical precision, Antigena stops the malicious activity while allowing normal business processes to continue.

Figure 5: Chronological sequence (bottom to top) of alerts and Antigena actions on the vulnerable device

Lessons for the future

The exploitation of Citrix ADC’s vulnerability has understandably caused concern across the security community. Based upon the cumulation and nature of alerts triggered, the malware aims to mine cryptocurrency like so many other campaigns these days.

On the other hand, and perhaps more importantly here, this recently discovered vulnerability strengthens the case for Autonomous Response and its proven ability to prevent novel attacks.

At Darktrace we are often asked how we detect zero-day exploits. Every stage in the attack lifecycle – from the execution of Pastebin-sourced commands to performing internal reconnaissance and mining crypto with impunity – involved behavior that in some way deviated from the Enterprise Immune System’s learned ‘pattern of life’. Antigena neutralized these attacks without relying on pre-defined blacklists, and no new detections were created. By leveraging Cyber AI, the Bitcoin malware using the Citrix vulnerabilities was instantly contained – before any damage could be done to the customer.

Indicators of compromise

185.178.45[.]221 (hosting malicious shell scripts)
92.63.99[.]17 (mining pool)
217.12.221[.]12 (hosting malware)

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Written by

Max Heinemeyer

Global Field CISO

Inside the SOC

Written by

Max Heinemeyer

Global Field CISO

The Darktrace Community

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July 2, 2025

Pre-CVE Threat Detection: 10 Examples Identifying Malicious Activity Prior to Public Disclosure of a Vulnerability

‍

Vulnerabilities are weaknesses in a system that can be exploited by malicious actors to gain unauthorized access or to disrupt normal operations. Common Vulnerabilities and Exposures (or CVEs) are a list of publicly disclosed cybersecurity vulnerabilities that can be tracked and mitigated by the security community.

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.

With a record-breaking 40,000 CVEs reported for 2024 and a predicted higher number for 2025 by the Forum for Incident Response and Security Teams (FIRST) [1], anomaly-detection is essential for identifying these potential risks. The gap between exploitation of a zero-day and 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.

Detecting threats without relying on CVE disclosure

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

Often, 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: attack vs patch.

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.

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].

Autonomous Response

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:

Related Darktrace blogs:

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*Self-reported by customer, confirmed afterwards.

**Updated January 2024 blog now reflects current findings

About the author

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Network

June 27, 2025

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

login on laptop dual factor authentication

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.

Figure 1: Darktrace’s detection of the affected device connecting to an unusual location based in Germany.

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].

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.

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.

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