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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!
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
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26
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.

  1. Darktrace’s detection capabilities highlight the steps taken by exploited Citrix Netscaler devices executing shell commands.
  2. 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

  1. 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.
  2. 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)

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

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Identity

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July 3, 2025

Top Eight Threats to SaaS Security and How to Combat Them

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The latest on the identity security landscape

Following the mass adoption of remote and hybrid working patterns, more critical data than ever resides in cloud applications – from Salesforce and Google Workspace, to Box, Dropbox, and Microsoft 365.

On average, a single organization uses 130 different Software-as-a-Service (SaaS) applications, and 45% of organizations reported experiencing a cybersecurity incident through a SaaS application in the last year.

As SaaS applications look set to remain an integral part of the digital estate, organizations are being forced to rethink how they protect their users and data in this area.

What is SaaS security?

SaaS security is the protection of cloud applications. It includes securing the apps themselves as well as the user identities that engage with them.

Below are the top eight threats that target SaaS security and user identities.

1.  Account Takeover (ATO)

Attackers gain unauthorized access to a user’s SaaS or cloud account by stealing credentials through phishing, brute-force attacks, or credential stuffing. Once inside, they can exfiltrate data, send malicious emails, or escalate privileges to maintain persistent access.

2. Privilege escalation

Cybercriminals exploit misconfigurations, weak access controls, or vulnerabilities to increase their access privileges within a SaaS or cloud environment. Gaining admin or superuser rights allows attackers to disable security settings, create new accounts, or move laterally across the organization.

3. Lateral movement

Once inside a network or SaaS platform, attackers move between accounts, applications, and cloud workloads to expand their foot- hold. Compromised OAuth tokens, session hijacking, or exploited API connections can enable adversaries to escalate access and exfiltrate sensitive data.

4. Multi-Factor Authentication (MFA) bypass and session hijacking

Threat actors bypass MFA through SIM swapping, push bombing, or exploiting session cookies. By stealing an active authentication session, they can access SaaS environments without needing the original credentials or MFA approval.

5. OAuth token abuse

Attackers exploit OAuth authentication mechanisms by stealing or abusing tokens that grant persistent access to SaaS applications. This allows them to maintain access even if the original user resets their password, making detection and mitigation difficult.

6. Insider threats

Malicious or negligent insiders misuse their legitimate access to SaaS applications or cloud platforms to leak data, alter configurations, or assist external attackers. Over-provisioned accounts and poor access control policies make it easier for insiders to exploit SaaS environments.

7. Application Programming Interface (API)-based attacks

SaaS applications rely on APIs for integration and automation, but attackers exploit insecure endpoints, excessive permissions, and unmonitored API calls to gain unauthorized access. API abuse can lead to data exfiltration, privilege escalation, and service disruption.

8. Business Email Compromise (BEC) via SaaS

Adversaries compromise SaaS-based email platforms (e.g., Microsoft 365 and Google Workspace) to send phishing emails, conduct invoice fraud, or steal sensitive communications. BEC attacks often involve financial fraud or data theft by impersonating executives or suppliers.

BEC heavily uses social engineering techniques, tailoring messages for a specific audience and context. And with the growing use of generative AI by threat actors, BEC is becoming even harder to detect. By adding ingenuity and machine speed, generative AI tools give threat actors the ability to create more personalized, targeted, and convincing attacks at scale.

Protecting against these SaaS threats

Traditionally, security leaders relied on tools that were focused on the attack, reliant on threat intelligence, and confined to a single area of the digital estate.

However, these tools have limitations, and often prove inadequate for contemporary situations, environments, and threats. For example, they may lack advanced threat detection, have limited visibility and scope, and struggle to integrate with other tools and infrastructure, especially cloud platforms.

AI-powered SaaS security stays ahead of the threat landscape

New, more effective approaches involve AI-powered defense solutions that understand the digital business, reveal subtle deviations that indicate cyber-threats, and action autonomous, targeted responses.

[related-resource]

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About the author
Carlos Gray
Senior Product Marketing Manager, Email

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Proactive Security

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July 2, 2025

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

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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:

  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

Related Darktrace blogs:

*Self-reported by customer, confirmed afterwards.

**Updated January 2024 blog now reflects current findings

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About the author
Nathaniel Jones
VP, Security & AI Strategy, Field CISO
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