September 18, 2024

FortiClient EMS Exploited: Attack Chain & Post Exploitation Tactics

Read about the methods used to exploit FortiClient EMS and the critical post-exploitation tactics that affect cybersecurity defenses.

Written by

Emily Megan Lim

Cyber Analyst

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

Emily Megan Lim

Cyber Analyst

Sep 2024

Cyber attacks on internet-facing systems

In the first half of 2024, the Darktrace Threat Research team observed multiple campaigns of threat actors targeting vulnerabilities in internet-facing systems, including Ivanti CS/PS appliances, Palo Alto firewall devices, and TeamCity on-premises.

These systems, which are exposed to the internet, are often targeted by threat actors to gain initial access to a network. They are constantly being scanned for vulnerabilities, known or unknown, by opportunistic actors hoping to exploit gaps in security. Unfortunately, this exposure remains a significant blind spot for many security teams, as monitoring edge infrastructure can be particularly challenging due to its distributed nature and the sheer volume of external traffic it processes.

In this blog, we discuss a vulnerability that was exploited in Fortinet’s FortiClient Endpoint Management Server (EMS) and the post-exploitation activity that Darktrace observed across multiple customer environments.

What is FortiClient EMS?

FortiClient is typically used for endpoint security, providing features such as virtual private networks (VPN), malware protection, and web filtering. The FortiClient EMS is a centralized platform used by administrators to enforce security policies and manage endpoint compliance. As endpoints are remote and distributed across various locations, the EMS needs to be accessible over the internet.

However, being exposed to the internet presents significant security risks, and exploiting vulnerabilities in the system may give an attacker unauthorized access. From there, they could conduct further malicious activities such as reconnaissance, establishing command-and-control (C2), moving laterally across the network, and accessing sensitive data.

CVE-2023-48788

CVE-2023-48788 is a critical SQL injection vulnerability in FortiClient EMS that can allow an attacker to gain unauthorized access to the system. It stems from improper neutralization of special elements used in SQL commands, which allows attackers to exploit the system through specially crafted requests, potentially leading to Remote Code Execution (RCE) [1]. This critical vulnerability was given a CVSS score of 9.8 and can be exploited without authentication.

The affected versions of FortiClient EMS include:

FortiClient EMS 7.2.0 to 7.2.2 (fixed in 7.2.3)
FortiClient EMS 7.0.1 to 7.0.10 (fixed in 7.0.11)

The vulnerability was publicly disclosed on March 12, 2024, and an exploit proof of concept was released by Horizon3.ai on March 21 [2]. Starting from March 24, almost two weeks after the initial disclosure, Darktrace began to observe at least six instances where the FortiClient EMS vulnerability had likely been exploited on customer networks. Seemingly exploited devices in multiple customer environments were observed performing anomalous activities, including the installation of Remote Monitoring and Management (RMM) tools, which was also reported by other security vendors around the same time [3].

Darktrace’s Coverage

Initial Access

To understand how the vulnerability can be exploited to gain initial access, we first need to explain some components of the FortiClient EMS:

The service FmcDaemon.exe is used for communication between the EMS and enrolled endpoint clients. It listens on port 8013 for incoming client connections.
Incoming requests are then sent to FCTDas.exe, which translates requests from other server components into SQL requests. This service interacts with the Microsoft SQL database.
Endpoint clients communicate with the FmcDaemon on the server on port 8013 by default.

Therefore, an SQL injection attack can be performed by crafting a malicious payload and sending it over port 8013 to the server. To carry out RCE, an attacker may send further SQL statements to enable and use the xp_cmdshell functionality of the Microsoft SQL server [2].

Shortly before post-exploitation activity began, Darktrace had observed incoming connections to some of the FortiClient EMS devices over port 8013 from the external IPs 77.246.103[.]110, 88.130.150[.]101, and 45.155.141[.]219. This likely represented the threat actors sending an SQL injection payload over port 8013 to the EMS device to validate the exploit.

Establish C2

After exploiting the vulnerability and gaining access to an EMS device on one customer network, two additional devices were seen with HTTP POST requests to 77.246.103[.]110 and 212.113.106[.]100 with a new PowerShell user agent.

Interestingly, the IP 212.113.106[.]100 has been observed in various other campaigns where threat actors have also targeted internet-facing systems and exploited other vulnerabilities. Open-source intelligence (OSINT) suggests that this indicator of compromise (IoC) is related to the Sliver C2 framework and has been used by threat actors such as APT28 (Fancy Bear) and APT29 (Cozy Bear) [4].

Unusual file downloads were also observed on four devices, including:

“SETUP.MSI” from 212.32.243[.]25 and 89.149.200[.]91 with a cURL user agent
“setup.msi” from 212.113.106[.]100 with a Windows Installer user agent
“run.zip” from 95.181.173[.]172 with a PowerShell user agent

The .msi files would typically contain the RMM tools Atera or ScreenConnect [5]. By installing RMM tools for C2, attackers can leverage their wide range of functionalities to carry out various tasks, such as file transfers, without the need to install additional tools. As RMM tools are designed to maintain a stable connection to remote systems, they may also allow the attackers to ensure persistent access to the compromised systems.

A scan of the endpoint 95.181.173[.]172 shows various other files such as “RunSchedulerTask.ps1” and “anydesk.exe” being hosted.

Figure 1: Screenshot of the endpoint 95.181.173[.]172 hosting various files [6].

Shortly after these unusual file downloads, many of the devices were also seen with usage of RMM tools such as Splashtop, Atera, and AnyDesk. The devices were seen connecting to the following endpoints:

*[.]relay.splashtop[.]com
agent-api[.]atera[.]com
api[.]playanext[.]com with user agent AnyDesk/8.0.9

RMM tools have a wide range of legitimate capabilities that allow IT administrators to remotely manage endpoints. However, they can also be repurposed for malicious activities, allowing threat actors to maintain persistent access to systems, execute commands remotely, and even exfiltrate data. As the use of RMM tools can be legitimate, they offer threat actors a way to perform malicious activities while blending into normal business operations, which could evade detection by human analysts or traditional security tools.

One device was also seen making repeated SSL connections to a self-signed endpoint “azure-documents[.]com” (104.168.140[.]84) and further HTTP POSTs to “serv1[.]api[.]9hits[.]com/we/session” (128.199.207[.]131). Although the contents of these connections were encrypted, they were likely additional infrastructure used for C2 in addition to the RMM tools that were used. Self-signed certificates may also be used by an attacker to encrypt C2 communications.

Internal Reconnaissance

Following the exploit, two of the compromised devices then started to conduct internal reconnaissance activity. The following figure shows a spike in the number of internal connections made by one of the compromised devices on the customer’s environment, which typically indicates a network scan.

Figure 2: Advanced Search results of internal connections made an affected device.

Reconnaissance tools such as Advanced Port Scanner (“www[.]advanced-port-scanner[.]com”) and Nmap were also seen being used by one of the devices to conduct scanning activities. Nmap is a network scanning tool commonly used by security teams for legitimate purposes like network diagnostics and vulnerability scanning. However, it can also be abused by threat actors to perform network reconnaissance, a technique known as Living off the Land (LotL). This not only reduces the need for custom or external tools but also reduces the risk of exposure, as the use of a legitimate tool in the network is unlikely to raise suspicion.

Privilege Escalation

In another affected customer network, the threat actor’s attempt to escalate their privileges was also observed, as a FortiClient EMS device was seen with an unusually large number of SMB/NTLM login failures, indicative of brute force activity. This attempt was successful, and the device was later seen authenticating with the credential “administrator”.

Figure 3: Advanced Search results of NTLM (top) and SMB (bottom) login failures.

Lateral Movement

After escalating privileges, attempts to move laterally throughout the same network were seen. One device was seen transferring the file “PSEXESVC.exe” to another device over SMB. This file is associated with PsExec, a command-line tool that allows for remote execution on other systems.

The threat actor was also observed leveraging the DCE-RPC protocol to move laterally within the network. Devices were seen with activity such as an increase in new RPC services, unusual requests to the SVCCTL endpoint, and the execution of WMI commands. The DCE-RPC protocol is typically used to facilitate communication between services on different systems and can allow one system to request services or execute commands on another.

These are further examples of LotL techniques used by threat actors exploiting CVE-2023-48788, as PsExec and the DCE-RPC protocol are often also used for legitimate administrative operations.

Accomplish Mission

In most cases, the threat actor’s end goal was not clearly observed. However, Darktrace did detect one instance where an unusually large volume of data had been uploaded to “put[.]io”, a cloud storage service, indicating that the end goal of the threat actor had been to steal potentially sensitive data.

In a recent investigation of a Medusa ransomware incident that took place in July 2024, Darktrace’s Threat Research team found that initial access to the environment had likely been gained through a FortiClient EMS device. An incoming connection from 209.15.71[.]121 over port 8013 was seen, suggesting that CVE-2023-48788 had been exploited. The device had been compromised almost three weeks before the ransomware was actually deployed, eventually resulting in the encryption of files.

Mitigating risk with proactive exposure management and real-time detection

Threat actors have continued to exploit unpatched vulnerabilities in internet-facing systems to gain initial access to a network. This highlights the importance of addressing and patching vulnerabilities as soon as they are disclosed and a fix is released. However, due to the rapid nature of exploitation, this may not always be enough. Furthermore, threat actors may even be exploiting vulnerabilities that are not yet publicly known.

As the end goals for a threat actor can differ – from data exfiltration to deploying ransomware – the post-exploitation behavior can also vary from actor to actor. However, AI security tools such as Darktrace / NETWORK can help identify and alert for post-exploitation behavior based on abnormal activity seen in the network environment.

Despite CVE-2023-48788 having been publicly disclosed and fixed in March, it appears that multiple threat actors, such as the Medusa ransomware group, have continued to exploit the vulnerability on unpatched systems. With new vulnerabilities being disclosed almost every other day, security teams may find it challenging continuously patch their systems.

As such, Darktrace / Proactive Exposure Management could also alleviate the workload of security teams by helping them identify and prioritize the most critical vulnerabilities in their network.

Insights from Darktrace’s First 6: Half-year threat report for 2024

First 6: half year threat report darktrace screenshot

Darktrace’s First 6: Half-Year Threat Report 2024 highlights the latest attack trends and key threats observed by the Darktrace Threat Research team in the first six months of 2024.

Focuses on anomaly detection and behavioral analysis to identify threats
Maps mitigated cases to known, publicly attributed threats for deeper context
Offers guidance on improving security posture to defend against persistent threats

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Appendices

Credit to Emily Megan Lim (Cyber Security Analyst) and Ryan Traill (Threat Content Lead)

References

[1] https://nvd.nist.gov/vuln/detail/CVE-2023-48788

[2] https://www.horizon3.ai/attack-research/attack-blogs/cve-2023-48788-fortinet-forticlientems-sql-injection-deep-dive/

[3] https://redcanary.com/blog/threat-intelligence/cve-2023-48788/

[4] https://www.fortinet.com/blog/threat-research/teamcity-intrusion-saga-apt29-suspected-exploiting-cve-2023-42793

[5] https://redcanary.com/blog/threat-intelligence/cve-2023-48788/

[6] https://urlscan.io/result/3678b9e2-ad61-4719-bcef-b19cadcdd929/

List of IoCs

IoC - Type - Description + Confidence

212.32.243[.]25/SETUP.MSI - URL - Payload
89.149.200[.]9/SETUP.MSI - URL - Payload
212.113.106[.]100/setup.msi - URL - Payload
95.181.173[.]172/run.zip - URL - Payload
serv1[.]api[.]9hits[.]com - Domain - Likely C2 endpoint
128.199.207[.]131 - IP - Likely C2 endpoint
azure-documents[.]com - Domain - C2 endpoint
104.168.140[.]84 - IP - C2 endpoint
77.246.103[.]110 - IP - Likely C2 endpoint
212.113.106[.]100 - IP - C2 endpoint

Darktrace Model Detections

Anomalous Connection / Callback on Web Facing Device

Anomalous Connection / Multiple HTTP POSTs to Rare Hostname

Anomalous Connection / New User Agent to IP Without Hostname

Anomalous Connection / Posting HTTP to IP Without Hostname

Anomalous Connection / Powershell to Rare External

Anomalous Connection / Rare External SSL Self-Signed

Anomalous Connection / Suspicious Self-Signed SSL

Anomalous Server Activity / Rare External from Server

Anomalous Server Activity / New User Agent from Internet Facing System

Anomalous Server Activity / Server Activity on New Non-Standard Port - External

Compliance / Remote Management Tool On Server

Device / New User Agent

Device / New PowerShell User Agent

Device / Attack and Recon Tools

Device / ICMP Address Scan

Device / Network Range Scan

Device / Network Scan

Device / RDP Scan

Device / Suspicious SMB Scanning Activity

Anomalous Connection / Multiple SMB Admin Session

Anomalous Connection / New or Uncommon Service Control

Anomalous Connection / Unusual Admin SMB Session

Device / Increase in New RPC Services

Device / Multiple Lateral Movement Breaches

Device / New or Uncommon WMI Activity

Device / New or Unusual Remote Command Execution

Device / SMB Lateral Movement

Device / Possible SMB/NTLM Brute Force

Unusual Activity / Successful Admin Brute-Force Activity

User / New Admin Credentials on Server

Unusual Activity / Enhanced Unusual External Data Transfer

Unusual Activity / Unusual External Data Transfer

Unusual Activity / Unusual External Data to New Endpoint

Device / Large Number of Model Breaches

Device / Large Number of Model Breaches from Critical Network Device

MITRE ATT&CK Mapping

Tactic – ID: Technique

Initial Access – T1190: Exploit Public-Facing Application

Resource Development – T1587.003: Develop Capabilities: Digital Certificates

Resource Development – T1608.003: Stage Capabilities: Install Digital Certificate

Command and Control – T1071.001: Application Layer Protocol: Web Protocols

Command and Control – T1219: Remote Access Software

Execution – T1059.001: Command and Scripting Interpreter: PowerShell

Reconnaissance – T1595: Active Scanning

Reconnaissance – T1590.005: Gather Victim Network Information: IP Addresses

Discovery – T1046: Network Service Discovery

Credential Access – T1110: Brute Force

Defense Evasion,Initial Access,Persistence,Privilege Escalation – T1078: Valid Accounts

Lateral Movement – T1021.002: Remote Services: SMB/Windows Admin Shares

Lateral Movement – T1021.003: Remote Services: Distributed Component Object Model

Execution – T1569.002: System Services: Service Execution

Execution – T1047: Windows Management Instrumentation

Exfiltration – T1041: Exfiltration Over C2 Channel

Exfiltration – T1567.002: Exfiltration Over Web Service: Exfiltration to Cloud Storage

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Written by

Emily Megan Lim

Cyber Analyst

Inside the SOC

Written by

Emily Megan Lim

Cyber Analyst

Malware Research Lead

Senior Product Executive

Watch the NIS2 Webinar

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October 20, 2026

Why Kubernetes Security Needs A Behavioral Approach

Kubernetes has become a foundational technology for modern cloud-native infrastructure. It can orchestrate everything from customer-facing applications to data pipelines and, increasingly, AI workloads. This is due to the highly scalable nature of Kubernetes, making it cost efficient and reliable.

Gartner projects that by 2028, 95% of new AI deployments will run on Kubernetes, up from less than 30% today¹. However, the same qualities that make Kubernetes powerful also make it uniquely challenging to secure, leaving many organizations with limited visibility into their clusters. This lack of visibility increases risk - it’s difficult to secure what you can’t see.

However, this risk is often looked at as purely a posture management challenge. While Cloud Security Posture Management (CSPM) solutions can tell you how a cluster should be configured, they don’t tell you what it is doing in real time. This requires runtime behavioral monitoring of clusters to detect active threats.

Yet existing approaches to securing Kubernetes by most Cloud Detection and Response (CDR) and Network Detection and Response (NDR) vendors often have limited coverage or require a third-party integration to forward traffic and metadata. This means that capabilities can be limited and detections can lack the context of the wider environment, which slows down triage, investigation and response.

Why Kubernetes is hard to secure

Traditional security tooling was built for persistent, long-term infrastructure such as servers and virtual machines with fixed identities that last months or years. Some elements of Kubernetes environments can have a much shorter lifespan, breaking many assumptions those tools rely on:

Increased complexity
1. Kubernetes environments can be complex in comparison to traditional infrastructure, with many different elements to consider such as nodes, clusters, containers, pods and the workloads themselves.
Ephemeral by design
1. Kubernetes pods can spin up and terminate in seconds. A container that was compromised may no longer exist by the time a deeper investigation is required, leaving no artifact to analyze. This poses a unique challenge for security operations.
Weaker workload boundaries
1. Kubernetes containers use lightweight, shared-kernel isolation rather than separate virtual machines, improving efficiency but reducing separation between workloads and the host. As a result, a compromised container may have a greater potential impact on the node and neighboring workloads than a compromised virtual machine (VM).²
2. Recent vulnerabilities have shown that threat actors can escape a container and gain access to the underlying host.^{3, 4}
Everything is API-driven
1. Dozens or hundreds of microservices communicate over internal APIs, and the Kubernetes control plane itself is an API. This creates a large and dynamic attack surface, making it difficult to distinguish legitimate activity from malicious behavior.
2. Without identity-aware runtime visibility, threat actors can move laterally between pods and exploit misconfigured role-based access controls (RBAC) with little chance of detection.

Rising to the challenge of securing Kubernetes

With the release of Darktrace 7.2, Darktrace / HYBRID NETWORK can extend behavioral security into Kubernetes, delivering visibility, detection and response capabilities across runtime activity. Darktrace addresses the challenges of securing Kubernetes environments in several ways.

Behavioral detection, not static rules

Many Kubernetes runtime tools rely on predefined rules and signatures - a fixed list of “bad” behaviors to match against. That approach struggles with novel attacks and generates noise at scale. Darktrace takes a different approach: our Adaptive AI builds a Unique Behavioral Profile for each organization from the ground up, learning the normal behavior of every workload, node and identity in your cluster. It then uses this understanding to detect meaningful deviations from expected behavior, which serves as the basis for surfacing suspicious and malicious activity.

A pod reaching out to an unfamiliar destination, an unexpected executable launching inside a workload, or an identity performing an action it has never performed, all surface as anomalies without anyone having to write a rule in advance.

Darktrace surfaces unexpected Kubernetes activity that does not align with an organization’s Unique Behavioral Profile

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Visibility across the network, the process, and the control plane

Darktrace monitors Kubernetes at three levels that together provide comprehensive runtime visibility:

Network-layer
1. Traffic between pods, across nodes and out to the internet. This helps to detect lateral movement and unusual connectivity, whether internal or external.
Process-layer
1. What is executing inside your containers. If a process reads a sensitive credential file or spawns an unexpected shell inside a production pod, Darktrace can identify that activity and use it as context for further detections.
Control plane
1. Activity against the Kubernetes API itself: someone executes a command in a running pod, RBAC changes, or unusual administrative actions. Many high-impact security events involve the control plane, an area that is often less visible to solutions that only analyze or scan network-layer telemetry.

Misconfiguration and vulnerability awareness

Runtime detection is strongest when combined with posture and exposure management. Darktrace surfaces risky pod configurations, such as privileged containers, host networking, and over-permissive service accounts as workloads are deployed, and links CVEs from images to the workloads running them. Security teams can go beyond simply knowing that a vulnerability exists and see exactly where it is in the cluster. When combined with behavior-based detections, this provides invaluable context that can help prioritize incidents and proactively identify areas that need further attention. For example, anomalous workload behavior on its own might not be very interesting to a security team at first, but if that same workload is known to host sensitive data, is known to have critical vulnerabilities associated with it, or is publicly accessible, then this narrative becomes much more suspicious and demanding of their attention.

Darktrace highlights Kubernetes misconfigurations such as privileged containers, host networking, and missing security controls, helping teams prioritize runtime alerts with valuable exposure and risk context

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Response, tailored to Kubernetes

Detection is most effective when paired with response. Darktrace can take precise actions on Kubernetes workloads, including blocking a malicious connection at the pod level, helping to safely contain threats while security teams investigate. Response actions can be taken fully autonomously or via a human-in-the-loop process, which is completely configurable depending on the desired level of autonomy and scope. Darktrace is expanding the number of Kubernetes-native response actions to give customers even more flexibility when containing threats.

Forensics that survive the workload

Because containers are so short-lived, evidence disappears fast and this can make it very difficult to answer questions related to the initial detections. Darktrace solves this with Forensic Acquisition & Investigation capabilities that extend to Kubernetes containers, allowing investigations to be triggered manually by an analyst, or automatically from an alert, preserving evidence before the workload is gone.

For incident responders, this addresses a key challenge in container security: being able to answer “what actually happened?” after an ephemeral workload has vanished.

One platform, not another silo

Kubernetes doesn't exist in isolation, and neither should its security. Darktrace correlates cluster activity with the surrounding cloud environment, including AWS, Azure and GCP identities, network activity and cloud assets, allowing analysts to pivot between a Kubernetes workload and its wider context. A single anomalous action can be traced from the control plane to the pod, and from the pod to the cloud identity behind it, all within a single investigation workflow. This can also include alerts from other areas of hybrid infrastructure or third-party sources where relevant, adding more context to investigations and speeding up workflows for human analysts.

Built to deploy easily

Operational complexity can be a barrier to security adoption. Darktrace / HYBRID NETWORK for Kubernetes installs with a single command, and for teams that manage their infrastructure as code, it supports raw manifests so the deployment can live in a Git repository and be managed through existing GitOps workflows. The same deployment approach works across Kubernetes environments in AWS, Azure, Google Cloud, and on-premises infrastructure. Early adopters of Darktrace’s Kubernetes capabilities have highlighted the simplicity of deployment and time to value.

Darktrace can deploy across your Kubernetes environment and wider hybrid infrastructure, while also providing visibility into Kubernetes deployment structure and status

Next steps

Kubernetes environments are dynamic, ephemeral and API-driven in ways that challenge traditional security tooling. With Kubernetes usage increasing due to widespread AI adoption, it is essential to secure Kubernetes environments as part of securing what AI can do. Darktrace / HYBRID NETWORK addresses these challenges by learning normal behavior in Kubernetes environments across network, process and control-plane layers, identifying meaningful threats and enabling targeted response. Combined with the context of wider hybrid infrastructure and forensic investigation capabilities, Darktrace provides visibility into both emerging threats and active incidents.

To see how Darktrace can help secure your Kubernetes environment and your wider hybrid infrastructure, get in touch to arrange your free trial. Existing customers can contact their Darktrace Account Team for more information about deployment options and licensing.

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Sources

[1] Gartner, Container Management research, 2025: "By 2028, 95% of new AI deployments will use Kubernetes, up from less than 30% today." https://www.gartner.com/en/documents/7913109. (quote reproduced under Gartner reprint at https://www.kubermatic.com/magic-quadrant-and-critical-capabilities-for-container-management/)

[2] Palo Alto Networks (Unit 42) – Container Breakouts: Escape Techniques in Cloud Environments. https://unit42.paloaltonetworks.com/container-escape-techniques/

[3] runC container-escape vulnerabilities (CVE-2025-31133, CVE-2025-52565, CVE-2025-52881), disclosed by a SUSE researcher on November 5, 2025. https://www.securityweek.com/runc-vulnerabilities-can-be-exploited-to-escape-containers/

[4] NVIDIAScape (CVE-2025-23266), CVSS 9.0. https://www.wiz.io/blog/nvidia-ai-vulnerability-cve-2025-23266-nvidiascape

[related-resource]

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About the author

Elise Longhurst

Senior Product Executive

Blog

Network

October 15, 2026

CikaBika Bot: Inside a Discord RAT

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Key Takeaways

· Darktrace malware researchers have found an ongoing malware campaign using a document-themed lure containing a malicious LNK file and a PDF with an embedded payload.

· The Nim based loader deploys a Rust-based remote access trojan (RAT), using a UAC bypass and DLL search-order hijacking technique targeting Microsoft Edge.

· The RAT uses Discord for C2, creating dedicated channels to manage infected devices and execute commands.

· CikaBika Bot supports system reconnaissance, remote command execution, screenshot capture, and file transfers.

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Introduction

In a threat landscape where attackers continue to rely on social engineering techniques to deliver malware, legitimate services are increasingly being abused to support malicious operations. Communications platforms like Discord can provide attackers with a ready-made channel for command-and-control (C2), allowing them to manage compromised devices without establishing dedicated infrastructure.

Malware researchers at Darktrace have identified a campaign distributing CikaBika, a Rust-based RAT that uses Discord for C2. The infection chain begins with a disk image and a malicious Windows shortcut. A Nim loader extracts the final payload and attempts to plant it in Microsoft Edge’s installation directory using a PowerShell UAC bypass. Once running, the RAT collects host information, registers the device with Discord, and accepts commands through a dedicated channel.

Technical Analysis

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Figure 1: Contents of Proposition_Projet.img.

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Initial access and PDF payload

The malware is packaged within a disk image named Proposition_Projet.img. Inside are a PDF titled “Presentation_Generale.pdf.pdf” and a Windows shortcut (LNK) disguised as a Word document, “Proposition_Projet_Personnalisable.docx”. The delivery method has not been confirmed; however, the filenames and document-themed lure are consistent with a phishing campaign.

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Figure 2: PowerShell command embedded in the malicious shortcut.

Opening the shortcut launches a hidden PowerShell process while displaying the PDF as a decoy. The French-language document explains how to produce a written summary or contraction of a text. In the background, PowerShell reads the PDF as bytes and uses the value at offset 239 (0x20) as an XOR key to decode an embedded executable. The resulting payload is written to %TEMP%\IfyuUapz.txt and executed using cmd /c.

Nim loader and UAC bypass

“IfyuUapz.txt” is a Nim-based loader that contains two Base64-encoded blobs: a Rust dynamic-link library (DLL) and a PowerShell deployment script. Both are decoded and written to temporary files, referenced to within the loader as “dllFile” and “copyPs1”. The loader runs the script through a hidden PowerShell process using an encoded command, then attempts to load the DLL using Nim’s loadLib function. If loading fails, it invokes regsvr32.exe and retries.

The PowerShell component is responsible for moving the DLL to C:\Program Files (x86)\Microsoft\Edge\Application\dbghelp.dll. It first copies the DLL to C:\Windows\Temp\dbghelp.tmp, then modifies HKCU\Software\Classes\ms-settings\shell\open\command so that launching computerdefaults.exe can trigger a command to move the staged DLL into the protected Edge directory. This is an attempt to bypass User Account Control (UAC), which depends on the target’s Windows configuration.

The script also compiles a small C# helper that calls ShowWindow to hide windows associated with Windows Settings and ApplicationFrameHost. It launches the bypass helper three times, checks for the presence of the destination DLL, and attempts to delete the temporary scripts, intermediate DLL, and associated registry changes.

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Figure 4: Legitimate *msedge.exe* function to load the legitimate *dbghelp.dll*.

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The legitimate msedge.exe has a delay-loaded dependency on dbghelp.dll, and the malicious DLL exports a subset of the functions associated with Microsoft’s debugging library. The attacker appears to be exploiting this dependency through DLL search-order hijacking. However, it does not export every function in Edge’s delay-import table, meaning its compatibility with the host is incomplete. The observed code establishes the intended sideloading route, rather than proving that Edge successfully loaded the planted DLL.

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Rust RAT payload

Figure 5: Discord configuration within the RAT.

The malicious dbghelp.dll (IfyuUapz.txt) is a Rust-based RAT. At startup, the RAT registers the compromised device with Discord and begins collecting information about the host. Its reconnaissance routine gathers system details, runs tasklist to enumerate processes, executes ipconfig to obtain network configuration, and attempts to take a screenshot. The resulting artifacts include tasklist_startup.txt, network_info.txt, and screenshot.png.

Figure 6: Network configuration notification in Discord channel.

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Figure 7: Network configuration output from *network_info.txt*.

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Discord C2

The RAT uses Discord channels to send commands and report results. The operator can send commands to the device’s channel and receive the resulting output in the same conversation. This gives the attacker an interactive command interface without having to operate and maintain a dedicated C2 server.

Figure 8: Commands available in Discord.

The command set includes !shell for remote command execution; !sysinfo and !info for host details; !isOn for status checks; !tasklist and !ps for process enumeration; and !kill for process termination. File-transfer commands include !upload and !download. Additional strings and command handlers reference screenshots (!src), camera access (!camera), streaming (!stream), and broadcasting (!broadcast).

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Figure 9: Device registration in Discord.

During device registration, the malware retrieves the victim’s public IP address using ipify.com. The registration message records the device ID, hostname, registration time, private and public IP addresses, status, uptime, and the Discord channel assigned to that device.

Operator activity and exfiltration

Figure 10: Powershell commands sent through Discord to exfiltrate data.

Once a device is registered, the attacker can issue commands through its dedicated Discord channel. In the observed activity, the attacker compressed a directory into a ZIP and exfiltrated it using ngrok.

Figure 11: Download command to retrieve a document from the target.

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The operator can also use !download to retrieve files from target. The example above displays a request for a specific document on the victim’s desktop. The requested file is then returned through the device’s Discord channel, giving the attacker a direct way to store and access selected data.

Conclusion

CikaBika Bot demonstrates how attackers continue to rely on social engineering techniques to deliver malware. Although the initial distribution method has not been confirmed, the use of a disk image containing a shortcut disguised as a Word document, alongside a legitimate-looking PDF, suggests the campaign was designed for phishing.

While Nim is less commonly encountered than C in Windows malware, it has increasingly appeared in malicious tooling. In this case, Nim is used to unpack and deploy a Rust-based RAT, adding another layer to the infection chain.

Once installed, CikaBika Bot uses Discord as its C2 platform, allowing the attacker to manage compromised devices, execute commands, and retrieve files without maintaining dedicated C2 infrastructure. The observed use of Discord channels for individual victims, alongside additional data exfiltration through ngrok, shows how legitimate services can be repurposed to support malicious operations.

Credit to Tara Gould (Malware Research Lead)

Indicators of Compromise (IoCs)

Presentation_Generale.pdf.pdf - eeb52cb95113a131c2c7713c17872da6

Proposition_Projet_Personnalisable.docx.lnk - 62e3e85eca78a0cd7e6669e9f33d936d

dbghelp.dll - c66858718d883bcfb9ce2c19b59f96c9

IfyuUapz.txt - 2deb724a709b0b892248405323350e9b

MITRE ATTACK

T1204.002 – User Execution: Malicious File
T1036.007 – Masquerading: Double File Extension
T1059.001 – PowerShell
T1027 – Obfuscated Files or Information
T1140 – Deobfuscate/Decode Files or Information
T1548.002 – Bypass User Account Control
T1112 – Modify Registry
T1574.001 – DLL Search Order Hijacking
T1036.005 – Masquerading: Match Legitimate Resource Name or Location
T1082 – System Information Discovery
T1016 – System Network Configuration Discovery
T1057 – Process Discovery
T1113 – Screen Capture
T1059.003 – Command and Scripting Interpreter: Windows Command Shell
T1102.002 – Web Service: Bidirectional Communication
T1560.001 – Archive Collected Data: Archive via Utility
T1567 – Exfiltration Over Web Service
T1070.004 – Indicator Removal: File Deletion
T1218.010 – Regsvr32
T1005 – Data from Local System
T1074.001 – Data Staged: Local Data Staging
T1041 – Exfiltration Over C2 Channel
T1564.003 – Hide Artifacts: Hidden Window
T1027.013 – Encrypted/Encoded File

About the author

Tara Gould

Malware Research Lead

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Check out this article by Darktrace: FortiClient EMS Exploited: Attack Chain & Post Exploitation Tactics

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Cyber attacks on internet-facing systems

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Darktrace’s Coverage

Initial Access

Establish C2

Internal Reconnaissance

Privilege Escalation

Lateral Movement

Accomplish Mission

Mitigating risk with proactive exposure management and real-time detection

Insights from Darktrace’s First 6: Half-year threat report for 2024

Appendices

References

List of IoCs

Darktrace Model Detections

MITRE ATT&CK Mapping

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MITRE ATTACK