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February 22, 2023

Find High-Impact Attack Paths with Darktrace / Proactive Exposure Management

Understand high-impact attack paths with Darktrace / Proactive Exposure Management. Learn from detailed use cases and improve your cybersecurity measures effectively.
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
Elliot Stocker
Product SME
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22
Feb 2023

What are the people, process, and technology assets that would do the most harm, if compromised by an attacker?

Attack path modeling provides a detailed map of all the roads that lead to an organization's crown jewels, prioritized in order of likelihood and potential impact. CISO's are increasingly looking to this kind of solution to complement their security stack because it highlights risks that are specific to this organization's structure, as well as potentially unexpected relationships between devices or users that would prove catastrophic if they were exploited.  

What makes Darktrace's Attack Path Modeling solution stand out?

  • Data sources are varied and information from the entire digital estate is considered
  • Modeling is real-time and continuously re-evaluated
  • Output does not require expert technical knowledge to be leveraged
  • Valuable as a standalone for vulnerability prioritization
  • As a component of the Darktrace ActiveAI Security Platform, the solution provides immediate value by feeding back into detection and response engines (e.g. tag critical assets for detection) but also provides long term systemic improvements as outcomes are followed up.

Thinking like an attacker

It is anticipated that CISOs will soon move beyond just insurance and checkbox compliance, as underwriters include more and more exclusions for certain types of cyber-attacks and the limits of compliance ticking the protection box rather than bolstering operational assurance become more apparent. They will push their teams to opt for more proactive cyber security measures to maximize ROI in the face of budget cuts, shifting investment into tools and capabilities that continuously improve their cyber resilience and demonstrate cyber risk reduction.

While red teams can provide insight into where effort and resource should be most immediately applied, the exercises themselves are often costly, non-exhaustive and infrequently run.

Hackers are constantly seeking pathways, preferably those of least resistance, to compromise a system by exploiting its vulnerabilities. Attack path modeling enables security teams to look at their environment from the perspective of the attacker. In turn, this helps them eliminate attack paths progressively, reducing the options an attacker would have, should they breach the walls.

A deeper dive into Attack Path Modeling

An attack path is a visual representation of the path that an attacker takes to exploit a weakness in the system. It highlights the series of steps (attack vectors) that a threat actor might take from one of the doors into the organization (attack surface) to access valuable assets.

It is typically unusual for an attacker to have a boulevard straight down to the crown jewels. They will most likely leverage a couple of loopholes, unexpected relationships and blind spots in the security stack to piece together a path to these confidential assets. Attack path modeling can help to highlight the attack vectors that connect, to form this path to compromise.  

Figure 1: The Darktrace / Proactive Exposure Management user interface.

How to model attack paths

Darktrace's proprietary Self-Learning AI models relationships, and graph theory is incorporated to understand the importance of users, documents and relationships between these.

Darktrace's Attack Path Modeling component identifies target nodes (users, accounts, devices), it then calculates the shortest paths to these target nodes and weights the results according to the likelihood of this attack path and the damage caused if the target asset was compromised. This is exactly what an attacker would do when planning an attack, albeit with a significant advantage to Darktrace's AI Engine, which has access to more information than the attacker. For the first time, defenders have the upper hand against attackers.

Avoiding siloed efforts

According to a Gartner survey, 75% of organizations are looking at consolidating security tools, not primarily because of cost, but because it helps drive cyber risk reduction. Ensuring that security efforts are part of a wider security ecosystem, rather than siloed efforts, is crucial to maximize the return on these investments.

Darktrace / Proactive Exposure Management integrates with Darktrace's detection and response to ensure that the organization's security posture is hardened, even if the team doesn't have time to eliminate the attack path.

Defensive superiority is key, and Attack Path Modeling is one way to help security teams gain back an advantage. Find out how you can test it in your own environment.

Attack Path Modeling is an objective, however, and there are a few important questions to consider when assessing the different methods of creating these models.

Are we considering all the relevant data when building my attack paths map?

Consider the case where one of your marketing executives has a close friendship with someone in your development team. How do you model that into your attack paths cartography? Attack paths encompass the full digital estate, so the attack path modeling solution should consider information from various parts, internal and external. This may include data from the Email environment, the Network, Endpoints, SaaS & Cloud, Active Directory, Vulnerability Scanners, etc.  

Cross-data analysis is the only way to understand holistic attack paths.

Are we looking at the most up to date map of attack paths?

Relationships between users, devices and other sensitive assets can evolve on a daily basis, this implies attack paths evolve on a daily basis. Ensuring that the methods or solutions used update their understanding continuously and in real-time is vital if security teams want the most up to date understanding of their organization's risk posture.

To improve our security posture, how do we know which attack paths to start with?

One thing is to map the sum-total of attack paths, another is to prioritize them. Attack path modeling gives you the map but adding a risk-assessment (explored in more depth below) layer on top is how you prioritize. This is where graph theory can be very useful to identify choke points that you may want to strengthen.  

Does this output yield actionable insights?

The prime objective of this solution is not simply to provide an assessment of cyber risk posture, but rather to help drive security efforts in the right direction. To that end, the output needs to be accessible to team members that may not have expert cyber skills. Lowering barriers to entry with usable insights and mitigation advice is key to successfully improve the organization's security posture.

Assessing risk to prioritize attack paths

Darktrace Attack Path Modeling (APM) is a risk-based approach to assessing cyber-attack pathways, thinking like an attacker, and probing the path of least resistance. 'Risk' in this case is defined as the product of two factors: Probability and Impact. By using this information to categorize possible attack paths in the risk matrix below, Darktrace's APM can prioritize attack paths to ensure security team efforts are spent on controlling for the most relevant risks for their organization.

Figure 2: Risk matrix for attack path prioritization

A: Defining Probability

There are two types of probability to consider:

The likelihood of one particular door being chosen by an attacker to infiltrate the organization (among the assets at the attack surface - this could be an internet-facing server, an inbox, a SaaS/Cloud account, etc). And,

The likelihood of one particular node (defined as a device or user account) being compromised next, via lateral movement.

Figure 3: Simplified example of calculating probability of lateral movement from a compromised agent to one of two servers

B: Defining Impact

Impact refers to the overall impact of an asset being compromised and unusable. In the case of an asset (e.g.: a key server), the bigger the disruption if this asset goes down, the higher the impact score. If considering a particular document, restricted access and sensitivity score of users accessing it are some of the variables used to estimate impact.

Figure 4: Diagram showing a simplified example of mapping access volume and sensitivity to estimate document value.

Both variables are calculated by the AI autonomously, without requiring human input. Security teams can of course reinforce the AI's understanding of the organization with their business expertise (by tagging additional sensitive devices for example).

A more in-depth description of how impact is propagated to identify key servers or sensitive documents, as well as other components that comprise the Darktrace Attack Path Modeling module can be found in this white paper.

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
Elliot Stocker
Product SME

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June 19, 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 24, 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

1. https://nvd.nist.gov/vuln/detail/CVE-2025-31324

2. https://www.bleepingcomputer.com/news/security/over-1-200-sap-netweaver-servers-vulnerable-to-actively-exploited-flaw/

3. https://reliaquest.com/blog/threat-spotlight-reliaquest-uncovers-vulnerability-behind-sap-netweaver-compromise/

4. https://onapsis.com/blog/active-exploitation-of-sap-vulnerability-cve-2025-31324/

5. https://www.bleepingcomputer.com/news/security/sap-fixes-suspected-netweaver-zero-day-exploited-in-attacks/

6. https://op-c.net/blog/sap-cve-2025-31324-qilin-breach/

7. https://www.forescout.com/blog/threat-analysis-sap-vulnerability-exploited-in-the-wild-by-chinese-threat-actor/

8. https://blog.eclecticiq.com/china-nexus-nation-state-actors-exploit-sap-netweaver-cve-2025-31324-to-target-critical-infrastructures

9. https://portswigger.net/burp/application-security-testing/oast

10. https://www.picussecurity.com/resource/blog/unc5221-cve-2025-22457-ivanti-connect-secure  

11. https://malpedia.caad.fkie.fraunhofer.de/details/elf.krustyloader

12. https://www.broadcom.com/support/security-center/protection-bulletin/krustyloader-backdoor

13. https://labs.withsecure.com/publications/new-krustyloader-variant-dropped-via-screenconnect-exploit

14. https://blog.eclecticiq.com/china-nexus-threat-actor-actively-exploiting-ivanti-endpoint-manager-mobile-cve-2025-4428-vulnerability

15. https://thehackernews.com/2024/01/chinese-hackers-exploiting-critical-vpn.html

16. https://www.virustotal.com/gui/file/3268f269371a81dbdce8c4eedffd8817c1ec2eadec9ba4ab043cb779c2f8a5d2

17. https://bazaar.abuse.ch/sample/3268f269371a81dbdce8c4eedffd8817c1ec2eadec9ba4ab043cb779c2f8a5d2/

18. https://www.fortinet.com/content/dam/fortinet/assets/analyst-reports/report-juicypotato-hacking-tool-discovered.pdf

19. https://www.manageengine.com/log-management/correlation-rules/detecting-sweetpotato.html

20. https://unit42.paloaltonetworks.com/rare-possible-gelsemium-attack-targets-se-asia/

21. https://assets.kpmg.com/content/dam/kpmg/in/pdf/2023/10/kpmg-ctip-gelsemium-apt-31-oct-2023.pdf

22. https://securityaffairs.com/177522/hacking/experts-warn-of-a-second-wave-of-attacks-targeting-sap-netweaver-bug-cve-2025-31324.html

23. https://www.virustotal.com/gui/file/b8e56de3792dbd0f4239b54cfaad7ece3bd42affa4fbbdd7668492de548b5df8

24. https://www.virustotal.com/gui/file/1d26fff4232bc64f9ab3c2b09281d932dd6afb84a24f32d772d3f7bc23d99c60/detection

25. https://www.virustotal.com/gui/file/1544d9392eedf7ae4205dd45ad54ec67e5ce831d2c61875806ce4c86412a4344/detection

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About the author
Signe Zaharka
Senior Cyber Security Analyst
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