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February 29, 2024

Protecting Against AlphV BlackCat Ransomware

Learn how Darktrace AI is combating AlphV BlackCat ransomware, including the details of this ransomware and how to protect yourself from it.
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
Sam Lister
SOC Analyst
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29
Feb 2024

As-a-Service malware trending

Throughout the course of 2023, “as-a-Service” strains of malware remained the most consistently observed threat type to affect Darktrace customers, mirroring their overall prominence across the cyber threat landscape. With this trend expected to continue throughout 2024, organizations and their security teams should be prepared to defend their network against increasingly versatile and tailorable malware-as-a-service (MaaS) and ransomware-as-a-service (RaaS) strains [1].

What is ALPHV ransomware?

The ALPHV ransomware, also known as ‘BlackCat’ or ‘Noberus’, is one example of a RaaS strain that has been prominent across the threat landscape over the last few years.

ALPHV is a ransomware strain coded in the Rust programming language. The ransomware is sold as part of the RaaS economy [2], with samples of the ransomware being provided and sold by a criminal group (the RaaS ‘operator’) to other cybercriminals (the RaaS ‘affiliates’) who then gain entry to organizations' networks with the intention of detonating the ransomware and demanding ransom payments.

ALPHV was likely first used in the wild back in November 2021 [3]. Since then, it has become one of the most prolific ransomware strains, with the Federal Bureau of Investigation (FBI) reporting nearly USD 300 million in ALPHV ransom payments as of September 2023 [4].

In December 2023, the FBI and the US Department of Justice announced a successful disruption campaign against the ALPHV group, which included a takedown of the their data leak site, and the release of a decryption tool for the ransomware strain [5], and in February 2024, the US Department of State announced  a reward of up to USD 10 million for information leading to the identification or location of anyone occupying a key leadership position in the group operating the ALPHV ransomware strain [6].

The disruption campaign against the ransomware group appeared to have been successful, as evidenced by the recent, significant decline in ALPHV attacks, however, it would not be surprising for the group to simply return with new branding, in a similar vein to its apparent predecessors, DarkSide and BlackMatter [7].

How does ALPHV ransomware work?

ALPHV affiliates have been known to employ a variety of methods to progress towards their objective of detonating ALPHV ransomware [4]. In the latter half of 2023, ALPHV affiliates were observed using malicious advertising (i.e, malvertising) to deliver a Python-based backdoor-dropper known as 'Nitrogen' to users' devices [8][12]. These malvertising operations consisted in affiliates setting up malicious search engine adverts for tools such as WinSCP and AnyDesk.

Users' interactions with these adverts led them to sites resembling legitimate software distribution sites. Users' attempts to download software from these spoofed sites resulted in the delivery of a backdoor-dropping malware sample dubbed 'Nitrogen' to their devices. Nitrogen has been observed dropping a variety of command-and-control (C2) implants onto users' devices, including Cobalt Strike Beacon and Sliver C2. ALPHV affiliates often used the backdoor access afforded to them by these C2 implants to conduct reconnaissance and move laterally, in preparation for detonating ALPHV ransomware payloads.

Darktrace Detection of ALPHV Ransomware

During October 2023, Darktrace observed several cases of ALPHV affiliates attempting to infiltrate organizations' networks via the use of malvertising to socially engineer users into downloading and installing Nitrogen from impersonation websites such as 'wireshhark[.]com' and wìnscp[.]net (i.e, xn--wnscp-tsa[.]net).

While the attackers managed to bypass traditional security measures and evade detection by using a device from the customer’s IT team to perform its malicious activity, Darktrace DETECT™ swiftly identified the subtle indicators of compromise (IoCs) in the first instance. This swift detection of ALPHV, along with Cyber AI Analyst™ autonomously investigating the wide array of post-compromise activity, provided the customer with full visibility over the attack enabling them to promptly initiate their remediation and recovery efforts.

Unfortunately, in this incident, Darktrace RESPOND™ was not fully deployed within their environment, hindering its ability to autonomously counter emerging threats. Had RESPOND been fully operational here, it would have effectively contained the attack in its early stages, avoiding the eventual detonation of the ALPHV ransomware.

Figure 1: Timeline of the ALPHV ransomware attack.

In mid-October, a member of the IT team at a US-based Darktrace customer attempted to install the network traffic analysis software, Wireshark, onto their desktop. Due to the customer’s configuration, Darktrace's visibility over this device was limited to its internal traffic, despite this it was still able to identify and alert for a string of suspicious activity conducted by the device.

Initially, Darktrace observed the device making type A DNS requests for 'wiki.wireshark[.]org' immediately before making type A DNS requests for the domain names 'www.googleadservices[.]com', 'allpcsoftware[.]com', and 'wireshhark[.]com' (note the two 'h's). This pattern of activity indicates that the device’s user was redirected to the website, wireshhark[.]com, as a result of the user's interaction with a sponsored Google Search result pointing to allpcsoftware[.]com.

At the time of analysis, navigating to wireshhark[.]com directly from the browser search bar led to a YouTube video of Rick Astley's song "Never Gonna Give You Up". This suggests that the website, wireshhark[.]com, had been configured to redirect users to this video unless they had arrived at the website via the relevant sponsored Google Search result [8].

Although it was not possible to confirm this with certainty, it is highly likely that users who visited the website via the appropriate sponsored Google Search result were led to a fake website (wireshhark[.]com) posing as the legitimate website, wireshark[.]com. It seems that the actors who set up this fake version of wireshark[.]com were inspired by the well-known bait-and-switch technique known as 'rickrolling', where users are presented with a desirable lure (typically a hyperlink of some kind) which unexpectedly leads them to a music video of Rick Astley's "Never Gonna Give You Up".

After being redirected to wireshhark[.]com, the user unintentionally installed a malware sample which dropped what appears to be Cobalt Strike onto their device. The presence of Cobalt Strike on the user's desktop was evidenced by the subsequent type A DNS requests which the device made for the domain name 'pse[.]ac'. These DNS requests were responded to with the likely Cobalt Strike C2 server address, 194.169.175[.]132. Given that Darktrace only had visibility over the device’s internal traffic, it did not observe any C2 connections to this Cobalt Strike endpoint. However, the desktop's subsequent behavior suggests that a malicious actor had gained 'hands-on-keyboard' control of the device via an established C2 channel.

Figure 2: Advanced Search data showing an customer device being tricked into visiting the fake website, wireshhark[.]com.

Since the malicious actor had gained control of an IT member's device, they were able to abuse the privileged account credentials to spread Python payloads across the network via SMB and the Windows Management Instrumentation (WMI) service. The actor was also seen distributing the Windows Sys-Internals tool, PsExec, likely in an attempt to facilitate their lateral movement efforts. It was normal for this IT member's desktop to distribute files across the network via SMB, which meant that this malicious SMB activity was not, at first glance, out of place.

Figure 3: Advanced Search data showing that it was normal for the IT member's device to distribute files over SMB.

However, Darktrace DETECT recognized that the significant spike in file writes being performed here was suspicious, even though, on the surface, it seemed ‘normal’ for the device. Furthermore, Darktrace identified that the executable files being distributed were attempting to masquerade as a different file type, potentially in an attempt to evade the detection of traditional security tools.

Figure 4: Event Log data showing several Model Breaches being created in response to the IT member's DEVICE's SMB writes of Python-based executables.

An addition to DETECT’s identification of this unusual activity, Darktrace’s Cyber AI Analyst launched an autonomous investigation into the ongoing compromise and was able to link the SMB writes and the sharing of the executable Python payloads, viewing the connections as one lateral movement incident rather than a string of isolated events. After completing its investigation, Cyber AI Analyst was able to provide a detailed summary of events on one pane of glass, ensuring the customer could identify the affected device and begin their remediation.

Figure 5: Cyber AI Analyst investigation summary highlighting the IT member's desktop’s lateral movement activities.

C2 Activity

The Python payloads distributed by the IT member’s device were likely related to the Nitrogen malware, as evidenced by the payloads’ names and by the network behaviours which they engendered.  

Figure 6: Advanced Search data showing the affected device reaching out to the C2 endpoint, pse[.]ac, and then distributing Python-based executable files to an internal domain controller.

The internal devices to which these Nitrogen payloads were distributed immediately went on to contact C2 infrastructure associated with Cobalt Strike. These C2 connections were made over SSL on ports 443 and 8443.  Darktrace identified the attacker moving laterally to an internal SQL server and an internal domain controller.

Figure 7: Advanced Search data showing an internal SQL server contacting the Cobalt Strike C2 endpoint, 194.180.48[.]169, after receiving Python payloads from the IT member’s device.
Figure 8: Event Log data showing several DETECT model breaches triggering in response to an internal SQL server’s C2 connections to 194.180.48[.]169.

Once more, Cyber AI Analyst launched its own investigation into this activity and was able to successfully identify a series of separate SSL connections, linking them together into one wider C2 incident.

Figure 9: Cyber AI Analyst investigation summary highlighting C2 connections from the SQL server.

Darktrace observed the attacker using their 'hands-on-keyboard' access to these systems to elevate their privileges, conduct network reconnaissance (primarily port scanning), spread Python payloads further across the network, exfiltrate data from the domain controller and transfer a payload from GitHub to the domain controller.

Figure 10: Cyber AI Analyst investigation summary an IP address scan carried out by an internal domain controller.
Figure 12: Event Log data showing an internal domain controller contacting GitHub around the time that it was in communication with the C2 endpoint, 194.180.48[.]169.
Figure 13: Event Log data showing a DETECT model breach being created in response to an internal domain controller's large data upload to the C2 endpoint, 194.180.48[.]169.

After conducting extensive reconnaissance and lateral movement activities, the attacker was observed detonating ransomware with the organization's VMware environment, resulting in the successful encryption of the customer’s VMware vCenter server and VMware virtual machines. In this case, the attacker took around 24 hours to progress from initial access to ransomware detonation.  

If the targeted organization had been signed up for Darktrace's Proactive Threat Notification (PTN) service, they would have been promptly notified of these suspicious activities by the Darktrace Security Operations Center (SOC) in the first instance, allowing them to quickly identify affected devices and quarantine them before the compromise could escalate.

Additionally, given the quantity of high-severe alerts that triggered in response to this attack, Darktrace RESPOND would, under normal circumstances, have inhibited the attacker's activities as soon as they were identified by DETECT. However, due to RESPOND not being configured to act on server devices within the customer’s network, the attacker was able to seamlessly move laterally through the organization's server environment and eventually detonate the ALPHV ransomware.

Nevertheless, Darktrace was able to successfully weave together multiple Cyber AI Analyst incidents which it generated into a thread representing the chain of behavior that made up this attack. The thread of Incident Events created by Cyber AI Analyst provided a substantial account of the attack and the steps involved in it, which significantly facilitated the customer’s post-incident investigation efforts.  

Figure 14: Darktrace's AI Analyst weaved together 33 of the Incident Events it created together into a thread representing the attacker’s chain of behavior.

Conclusion

It is expected for malicious cyber actors to revise and upgrade their methods to evade organizations’ improving security measures. The continued improvement of email security tools, for example, has likely created a need for attackers to develop new means of Initial Access, such as the use of Microsoft Teams-based malware delivery.

This fast-paced ALPHV ransomware attack serves as a further illustration of this trend, with the actor behind the attack using malvertising to convince an unsuspecting user to download the Python-based malware, Nitrogen, from a fake Wireshark site. Unbeknownst to the user, this stealthy malware dropped a C2 implant onto the user’s device, giving the malicious actor the ‘hands-on-keyboard’ access they needed to move laterally, conduct network reconnaissance, and ultimately detonate ALPHV ransomware.

Despite the non-traditional initial access methods used by this ransomware actor, Darktrace DETECT was still able to identify the unusual patterns of network traffic caused by the attacker’s post-compromise activities. The large volume of alerts created by Darktrace DETECT were autonomously investigated by Darktrace’s Cyber AI Analyst, which was able to weave together related activities of different devices into a comprehensive timeline of the attacker’s operation. Given the volume of DETECT alerts created in response to this ALPHV attack, it is expected that Darktrace RESPOND would have autonomously inhibited the attacker’s operation had the capability been appropriately configured.

As the first post-compromise activities Darktrace observed in this ALPHV attack were seemingly performed by a member of the customer’s IT team, it may have looked normal to a human or traditional signature and rules-based security tools. To Darktrace’s Self-Learning AI, however, the observed activities represented subtle deviations from the device’s normal pattern of life. This attack, and Darktrace’s detection of it, is therefore a prime illustration of the value that Self-Learning AI can bring to the task of detecting anomalies within organizations’ digital estates.

Credit to Sam Lister, Senior Cyber Analyst, Emma Foulger, Principal Cyber Analyst

Appendices

Darktrace DETECT Model Breaches

- Compliance / SMB Drive Write

- Compliance / High Priority Compliance Model Breach

- Anomalous File / Internal / Masqueraded Executable SMB Write

- Device / New or Uncommon WMI Activity

- Anomalous Connection / New or Uncommon Service Control

- Anomalous Connection / High Volume of New or Uncommon Service Control

- Device / New or Uncommon SMB Named Pipe

- Device / Multiple Lateral Movement Model Breaches

- Device / Large Number of Model Breaches  

- SMB Writes of Suspicious Files (Cyber AI Analyst)

- Suspicious Remote WMI Activity (Cyber AI Analyst)

- Suspicious DCE-RPC Activity (Cyber AI Analyst)

- Compromise / Connection to Suspicious SSL Server

- Compromise / High Volume of Connections with Beacon Score

- Anomalous Connection / Suspicious Self-Signed SSL

- Anomalous Connection / Anomalous SSL without SNI to New External

- Compromise / Suspicious TLS Beaconing To Rare External

- Compromise / Beacon to Young Endpoint

- Compromise / SSL or HTTP Beacon

- Compromise / Agent Beacon to New Endpoint

- Device / Long Agent Connection to New Endpoint

- Compromise / SSL Beaconing to Rare Destination

- Compromise / Large Number of Suspicious Successful Connections

- Compromise / Slow Beaconing Activity To External Rare

- Anomalous Server Activity / Outgoing from Server

- Device / Multiple C2 Model Breaches

- Possible SSL Command and Control (Cyber AI Analyst)

- Unusual Repeated Connections (Cyber AI Analyst)

- Device / ICMP Address Scan

- Device / RDP Scan

- Device / Network Scan

- Device / Suspicious Network Scan Activity

- Scanning of Multiple Devices (Cyber AI Analyst)

- ICMP Address Scan (Cyber AI Analyst)

- Device / Anomalous Github Download

- Unusual Activity / Unusual External Data Transfer

- Device / Initial Breach Chain Compromise

MITRE ATT&CK Mapping

Resource Development techniques:

- Acquire Infrastructure: Malvertising (T1583.008)

Initial Access techniques:

- Drive-by Compromise (T1189)

Execution techniques:

- User Execution: Malicious File (T1204.002)

- System Services: Service Execution (T1569.002)

- Windows Management Instrumentation (T1047)

Defence Evasion techniques:

- Masquerading: Match Legitimate Name or Location (T1036.005)

Discovery techniques:

- Remote System Discovery (T1018)

- Network Service Discovery (T1046)

Lateral Movement techniques:

- Remote Services: SMB/Windows Admin Shares

- Lateral Tool Transfer (T1570)

Command and Control techniques:

- Application Layer Protocol: Web Protocols (T1071.001)

- Encrypted Channel: Asymmetric Cryptography (T1573.002)

- Non-Standard Port (T1571)

- Ingress Tool Channel (T1105)

Exfiltration techniques:

- Exfiltration Over C2 Channel (T1041)

Impact techniques:

- Data Encrypted for Impact (T1486)

List of Indicators of Compromise

- allpcsoftware[.]com

- wireshhark[.]com

- pse[.]ac • 194.169.175[.]132

- 194.180.48[.]169

- 193.42.33[.]14

- 141.98.6[.]195

References  

[1] https://darktrace.com/threat-report-2023

[2] https://www.microsoft.com/en-us/security/blog/2022/05/09/ransomware-as-a-service-understanding-the-cybercrime-gig-economy-and-how-to-protect-yourself/

[3] https://www.bleepingcomputer.com/news/security/alphv-blackcat-this-years-most-sophisticated-ransomware/

[4] https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-353a

[5] https://www.justice.gov/opa/pr/justice-department-disrupts-prolific-alphvblackcat-ransomware-variant

[6] https://www.state.gov/u-s-department-of-state-announces-reward-offers-for-criminal-associates-of-the-alphv-blackcat-ransomware-variant/

[7] https://www.bleepingcomputer.com/news/security/blackcat-alphv-ransomware-linked-to-blackmatter-darkside-gangs/

[8] https://www.trendmicro.com/en_us/research/23/f/malvertising-used-as-entry-vector-for-blackcat-actors-also-lever.html

[9] https://news.sophos.com/en-us/2023/07/26/into-the-tank-with-nitrogen/

[10] https://www.esentire.com/blog/persistent-connection-established-nitrogen-campaign-leverages-dll-side-loading-technique-for-c2-communication

[11] https://www.esentire.com/blog/nitrogen-campaign-2-0-reloads-with-enhanced-capabilities-leading-to-alphv-blackcat-ransomware

[12] https://www.esentire.com/blog/the-notorious-alphv-blackcat-ransomware-gang-is-attacking-corporations-and-public-entities-using-google-ads-laced-with-malware-warns-esentire

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
Sam Lister
SOC Analyst

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June 18, 2025

Customer Case Study: Leading Petrochemical Manufacturer

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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.”

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June 18, 2025

Tracking CVE-2025-31324: Darktrace’s detection of SAP Netweaver exploitation before and after disclosure 

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Introduction: Exploiting SAP platforms

Global enterprises depend extensively on SAP platforms, such as SAP NetWeaver and Visual Composer, to run critical business processes worldwide. These systems; however, are increasingly appealing targets for well-resourced adversaries:

What is CVE-2025-31324?

CVE-2025-31324 affects SAP’s NetWeaver Visual Composer, a web-based software modeling tool. SAP NetWeaver is an application server and development platform that runs and connects SAP and non-SAP applications across different technologies [2]. It is commonly used by process specialists to develop application components without coding in government agencies, large enterprises, and by critical infrastructure operators [4].

CVE-2025-31324 affects SAP’s Netweaver Visual Composer Framework 7.1x (all SPS) and above [4]. The vulnerability in a Java Servlet (/irj/servlet_jsp) would enable an unauthorized actor to upload arbitrary files to the /developmentserver/metadatauploader endpoint, potentially resulting in remote code execution (RCE) and full system compromise [3]. The issue stems from an improper authentication and authorization check in the SAP NetWeaver Application Server Java systems [4].

What is the severity rating of CVE-2025-31324?

The vulnerability, first disclosed on April 24, 2025, carries the highest severity rating (CVSS v3 score: 10.0) and could allow remote attackers to upload malicious files without requiring authentication [1][5]. Although SAP released a workaround on April 8, many organizations are hesitant to take their business-critical SAP NetWeaver systems offline, leaving them exposed to potential exploitation [2].

How is CVE-2025-31324 exploited?

The vulnerability is exploitable by sending specifically crafted GET, POST, or HEAD HTTP requests to the /developmentserver/metadatauploader URL using either HTTP or HTTPS. Attackers have been seen uploading malicious files (.jsp, .java, or .class files to paths containing “\irj\servlet_jsp\irj\”), most of them being web shells, to publicly accessible SAP NetWeaver systems.

External researchers observed reconnaissance activity targeting this vulnerability in late January 2025, followed by a surge in exploitation attempts in February. The first confirmed compromise was reported in March [4].

Multiple threat actors have reportedly targeted the vulnerability, including Chinese Advanced Persistent Threats (APTs) groups Chaya_004 [7], UNC5221, UNC5174, and CL-STA-0048 [8], as well as ransomware groups like RansomEXX, also known as Storm-2460, BianLian [4] or Qilin [6] (the latter two share the same indicators of  compromise (IoCs)).

Following the initial workaround published on April 8, SAP released a security update addressing CVE-2025-31324 and subsequently issued a patch on May 13 (Security Note 3604119) to resolve the root cause of the vulnerability [4].

Darktrace’s coverage of CVE-2025-31324 exploitation

Darktrace has observed activity indicative of threat actors exploiting CVE-2025-31324, including one instance detected before the vulnerability was publicly disclosed.

In April 2025, the Darktrace Threat Research team investigated activity related to the CVE-2025-31324 on SAP devices and identified two cases suggesting active exploitation of the vulnerability. One case was detected prior to the public disclosure of the vulnerability, and the other just two days after it was published.

Early detection of CVE 2025-31324 by Darktrace

Figure 1: Timeline of events for an internet-facing system, believed to be a SAP device, exhibiting activity indicative of CVE-2025-31324 exploitation.
Figure 1: Timeline of events for an internet-facing system, believed to be a SAP device, exhibiting activity indicative of CVE-2025-31324 exploitation.

On April 18, six days prior to the public disclosure of CVE-2025-31324, Darktrace began to detect unusual activity on a device belonging to a logistics organization in the Europe, the Middle East and Africa (EMEA) region. Multiple IoCs observed during this incident have since been linked via OSINT to the exploitation of CVE-2025-31324. Notably, however, this reporting was not available at the time of detection, highlighting Darktrace’s ability to detect threats agnostically, without relying on threat intelligence.

The device was observed making  domain name resolution request for the Out-of-Band Application Security Testing (OAST) domain cvvr9gl9namk9u955tsgaxy3upyezhnm6.oast[.]online. OAST is often used by security teams to test if exploitable vulnerabilities exist in a web application but can similarly be used by threat actors for the same purpose [9].

Four days later, on April 22, Darktrace observed the same device, an internet-facing system believed to be a SAP device, downloading multiple executable (.exe) files from several Amazon Simple Storage Service (S3). Darktrace’s Threat Research team later found these files to be associated with the KrustyLoader  malware [23][24][25].

KrustyLoader is known to be associated with the Chinese threat actor UNC5221, also known as UTA0178, which has been reported to aggressively target devices exposed to the internet [10] [14] [15]. It is an initial-stage malware which downloads and launches a second-stage payload – Sliver C2. Sliver is a similar tool to Cobalt Strike (an open-source post-exploitation toolkit). It is used for command-and-control (C2) connections [11][12]13]. After its successful download, KrustyLoader deletes itself to evade detection.  It has been reported that multiple Chinese APT groups have deployed KrustyLoader on SAP Netweaver systems post-compromise [8].

The actors behind KrustyLoader have also been associated with the exploitation of zero-day vulnerabilities in other enterprise systems, including Ivanti devices [12]. Notably, in this case, one of the Amazon S3 domains observed (abode-dashboard-media.s3.ap-south-1.amazonaws[.]com ) had previously been investigated by Darktrace’s Threat Research team as part of their investigation into Ivanti Connect Secure (CS) and Policy Secure (PS) appliances.

In addition to the download of known malicious files, Darktrace also detected new IoCs, including several executable files that could not be attributed to any known malware families or previous attacks, and for which no corresponding OSINT reporting was available.

Post-CVE publication detection

Exploit Validation

Between April 27 and 29, Darktrace observed unusual activity from an SAP device on the network of a manufacturing customer in EMEA.

Darktrace / NETWORK’s detection of an SAP device performing a large volume of suspicious activity between April 27 and April 29.
Figure 2: Darktrace / NETWORK’s detection of an SAP device performing a large volume of suspicious activity between April 27 and April 29.

The device was observed making DNS requests for OAST domains (e.g. aaaaaaaa.d06qqn7pu5a6u25tv9q08p5xhbjzw33ge.oast[.]online and aaaaaaaaaaa.d07j2htekalm3139uk2gowmxuhapkijtp.oast[.]pro), suggesting that a threat actor was testing for exploit validation [9].

Darktrace / NETWORK’s detection of a SAP device making suspicious domain name resolution requests for multiple OAST domains.
Figure 3: Darktrace / NETWORK’s detection of a SAP device making suspicious domain name resolution requests for multiple OAST domains.

Privilege escalation tool download attempt

One day later, Darktrace observed the same device attempting to download an executable file from hxxp://23.95.123[.]5:666/xmrigCCall/s.exe (SHA-1 file hash: e007edd4688c5f94a714fee036590a11684d6a3a).

Darktrace / NETWORK identified the user agents Microsoft-CryptoAPI/10.0 and CertUtil URL Agent during the connections to 23.95.123[.]5. The connections were made over port 666, which is not typically used for HTTP connections.

Multiple open-source intelligence (OSINT) vendors have identified the executable file as either JuicyPotato or SweetPotato, both Windows privilege escalation tools[16][17][18][19]. The file hash and the unusual external endpoint have been associated with the Chinese APT group Gelsemium in the past, however, many threat actors are known to leverage this tool in their attacks [20] [21].

Figure 4: Darktrace’s Cyber AI Analyst’s detection of a SAP device downloading a suspicious executable file from hxxp://23.95.123[.]5:666/xmrigCCall/s.exe on April 28, 2025.

Darktrace deemed this activity highly suspicious and triggered an Enhanced Monitoring model alert, a high-priority security model designed to detect activity likely indicative of compromise. As the customer was subscribed to the Managed Threat Detection service, Darktrace’s Security Operations Centre (SOC) promptly investigated the alert and notified the customer for swift remediation. Additionally, Darktrace’s Autonomous Response capability automatically blocked connections to the suspicious IP, 23.95.123[.]5, effectively containing the compromise in its early stages.

Actions taken by Darktrace’s Autonomous Response to block connections to the suspicious external endpoint 23.95.123[.]5. This event log shows that the connections to 23.95.123[.]5 were made over a rare destination port for the HTTP protocol and that new user agents were used during the connections.
Figure 5: Actions taken by Darktrace’s Autonomous Response to block connections to the suspicious external endpoint 23.95.123[.]5. This event log shows that the connections to 23.95.123[.]5 were made over a rare destination port for the HTTP protocol and that new user agents were used during the connections.

Conclusion

The exploitation of CVE-2025-31324 to compromise SAP NetWeaver systems highlights the persistent threat posed by vulnerabilities in public-facing assets. In this case, threat actors leveraged the flaw to gain an initial foothold, followed by attempts to deploy malware linked to groups affiliated with China [8][20].

Crucially, Darktrace demonstrated its ability to detect and respond to emerging threats even before they are publicly disclosed. Six days prior to the public disclosure of CVE-2025-31324, Darktrace detected unusual activity on a device believed to be a SAP system, which ultimately represented an early detection of the CVE. This detection was made possible through Darktrace’s behavioral analysis and anomaly detection, allowing it to recognize unexpected deviations in device behavior without relying on signatures, rules or known IoCs. Combined with its Autonomous Response capability, this allowed for immediate containment of suspicious activity, giving security teams valuable time to investigate and mitigate the threat.

Credit to Signe Zaharka (Principal Cyber Analyst), Emily Megan Lim, (Senior Cyber Analyst) and Ryan Traill (Analyst Content Lead)

Appendices

List of IoCs

23.95.123[.]5:666/xmrigCCall/s.exe - URL- JuicyPotato/SweetPotato - high confidence

29274ca90e6dcf5ae4762739fcbadf01- MD5 file hash - JuicyPotato/SweetPotato - high confidence

e007edd4688c5f94a714fee036590a11684d6a3a - SHA-1 file hash - JuicyPotato/SweetPotato -high confidence

3268f269371a81dbdce8c4eedffd8817c1ec2eadec9ba4ab043cb779c2f8a5d2 - SHA-256 file hash - JuicyPotato/SweetPotato -high confidence

abode-dashboard-media.s3.ap-south-1.amazonaws[.]com/nVW2lsYsYnv58 - URL- high confidence

applr-malbbal.s3.ap-northeast-2.amazonaws[.]com/7p3ow2ZH - URL- high confidence

applr-malbbal.s3.ap-northeast-2.amazonaws[.]com/UUTICMm - URL- KrustyLoader - high confidence

beansdeals-static.s3.amazonaws[.]com/UsjKy - URL- high confidence

brandnav-cms-storage.s3.amazonaws[.]com/3S1kc - URL- KrustyLoader - high confidence

bringthenoiseappnew.s3.amazonaws[.]com/pp79zE - URL- KrustyLoader - high confidence

f662135bdd8bf792a941ea222e8a1330 - MD5 file hash- KrustyLoader - high confidence

fa645f33c0e3a98436a0161b19342f78683dbd9d - SHA-1 file hash- KrustyLoader - high confidence

1d26fff4232bc64f9ab3c2b09281d932dd6afb84a24f32d772d3f7bc23d99c60 - SHA-256 file hash- KrustyLoader - high confidence

6900e844f887321f22dd606a6f2925ef - MD5 file hash- KrustyLoader - high confidence

da23dab4851df3ef7f6e5952a2fc9a6a57ab6983 - SHA-1 file hash- KrustyLoader - high confidence

1544d9392eedf7ae4205dd45ad54ec67e5ce831d2c61875806ce4c86412a4344 - SHA-256 file hash- KrustyLoader - high confidence

83a797e5b47ce6e89440c47f6e33fa08 - MD5 file hash - high confidence

a29e8f030db8990c432020441c91e4b74d4a4e16 - SHA-1 file hash - high confidence

72afde58a1bed7697c0aa7fa8b4e3b03 - MD5 file hash- high confidence

fe931adc0531fd1cb600af0c01f307da3314c5c9 - SHA-1 file hash- high confidence

b8e56de3792dbd0f4239b54cfaad7ece3bd42affa4fbbdd7668492de548b5df8 - SHA-256 file hash- KrustyLoader - high confidence

17d65a9d8d40375b5b939b60f21eb06eb17054fc - SHA-1 file hash- KrustyLoader - high confidence

8c8681e805e0ae7a7d1a609efc000c84 - MD5 file hash- KrustyLoader - high confidence

29274ca90e6dcf5ae4762739fcbadf01 - MD5 file hash- KrustyLoader - high confidence

Darktrace Model Detections

Anomalous Connection / CertUtil Requesting Non Certificate

Anomalous Connection / CertUtil to Rare Destination

Anomalous Connection / Powershell to Rare External

Anomalous File / EXE from Rare External Location

Anomalous File / Multiple EXE from Rare External Locations

Anomalous File / Internet Facing System File Download

Anomalous File / Masqueraded File Transfer (Enhanced Monitoring)

Anomalous Server Activity / New User Agent from Internet Facing System

Compliance / CertUtil External Connection

Compromise / High Priority Tunnelling to Bin Services (Enhanced Monitoring)

Compromise / Possible Tunnelling to Bin Services

Device / Initial Attack Chain Activity (Enhanced Monitoring)

Device / Suspicious Domain

Device / Internet Facing Device with High Priority Alert

Device / Large Number of Model Alerts

Device / Large Number of Model Alerts from Critical Network Device (Enhanced Monitoring)

Device / New PowerShell User Agent

Device / New User Agent

Autonomous Response Model Alerts

Antigena / Network / External Threat / Antigena Suspicious File Block

Antigena / Network / Significant Anomaly / Antigena Controlled and Model Alert

Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Server Block

Antigena / Network / Significant Anomaly / Antigena Significant Server Anomaly Block

Antigena/ Network / External Threat / Antigena Suspicious File Block

Antigena/ Network / External Threat / Antigena Suspicious File Pattern of Life Block

Antigena/ Network / Significant Anomaly / Antigena Alerts Over Time Block

Antigena/ Network / Significant Anomaly / Antigena Controlled and Model Alert

Antigena/ Network / Significant Anomaly / Antigena Enhanced Monitoring from Server Block

Antigena/ Network / Significant Anomaly / Antigena Significant Server Anomaly Block

Cyber AI Analyst Incidents

Possible HTTP Command and Control

Suspicious File Download

MITRE ATT&CK Mapping

Malware - RESOURCE DEVELOPMENT - T1588.001

PowerShell - EXECUTION - T1059.001

Drive-by Compromise - INITIAL ACCESS - T1189

Ingress Tool Transfer - COMMAND AND CONTROL - T1105

Application Layer Protocol - COMMAND AND CONTROL - T1071

Exploitation of Remote Services - LATERAL MOVEMENT - T1210

Exfiltration Over Unencrypted/Obfuscated Non-C2 Protocol - EXFILTRATION - T1048.003

References

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About the author
Signe Zaharka
Senior Cyber Security Analyst
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