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

‍

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

‍

Written by

Emily Megan Lim

Cyber Analyst

Inside the SOC

Written by

Emily Megan Lim

Cyber Analyst

Product Marketing Manager, OT Security & Compliance

Watch the NIS2 Webinar

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Network

November 26, 2025

CastleLoader & CastleRAT: Behind TAG150’s Modular Malware Delivery System

What is TAG-150?

TAG-150, a relatively new Malware-as-a-Service (MaaS) operator, has been active since March 2025, demonstrating rapid development and an expansive, evolving infrastructure designed to support its malicious operations. The group employs two custom malware families, CastleLoader and CastleRAT, to compromise target systems, with a primary focus on the United States [1]. TAG-150’s infrastructure included numerous victim-facing components, such as IP addresses and domains functioning as command-and-control (C2) servers associated with malware families like SecTopRAT and WarmCookie, in addition to CastleLoader and CastleRAT [2].

As of May 2025, CastleLoader alone had infected a reported 469 devices, underscoring the scale and sophistication of TAG-150’s campaign [1].

What are CastleLoader and CastleRAT?

CastleLoader is a loader malware, primarily designed to download and install additional malware, enabling chain infections across compromised systems [3]. TAG-150 employs a technique known as ClickFix, which uses deceptive domains that mimic document verification systems or browser update notifications to trick victims into executing malicious scripts. Furthermore, CastleLoader leverages fake GitHub repositories that impersonate legitimate tools as a distribution method, luring unsuspecting users into downloading and installing malware on their devices [4].

CastleRAT, meanwhile, is a remote access trojan (RAT) that serves as one of the primary payloads delivered by CastleLoader. Once deployed, CastleRAT grants attackers extensive control over the compromised system, enabling capabilities such as keylogging, screen capturing, and remote shell access.

TAG-150 leverages CastleLoader as its initial delivery mechanism, with CastleRAT acting as the main payload. This two-stage attack strategy enhances the resilience and effectiveness of their operations by separating the initial infection vector from the final payload deployment.

How are they deployed?

Castleloader uses code-obfuscation methods such as dead-code insertion and packing to hinder both static and dynamic analysis. After the payload is unpacked, it connects to its command-and-control server to retrieve and running additional, targeted components.

Its modular architecture enables it to function both as a delivery mechanism and a staging utility, allowing threat actors to decouple the initial infection from payload deployment. CastleLoader typically delivers its payloads as Portable Executables (PEs) containing embedded shellcode. This shellcode activates the loader’s core module, which then connects to the C2 server to retrieve and execute the next-stage malware.[6]

Following this, attackers deploy the ClickFix technique, impersonating legitimate software distribution platforms like Google Meet or browser update notifications. These deceptive sites trick victims into copying and executing PowerShell commands, thereby initiating the infection kill chain. [1]

When a user clicks on a spoofed Cloudflare “Verification Step” prompt, a background request is sent to a PHP script on the distribution domain (e.g., /s.php?an=0). The server’s response is then automatically copied to the user’s clipboard using the ‘unsecuredCopyToClipboard()’ function. [7].

The Python-based variant of CastleRAT, known as “PyNightShade,” has been engineered with stealth in mind, showing minimal detection across antivirus platforms [2]. As illustrated in Figure 1, PyNightShade communicates with the geolocation API service ip-api[.]com, demonstrating both request and response behavior

Figure 1: Packet Capture (PCAP) of PyNightShade, the Python-based variant of CastleRAT, communicating with the geolocation API service ip-api[.]com.

Darktrace Coverage

In mid-2025, Darktrace observed a range of anomalous activities across its customer base that appeared linked to CastleLoader, including the example below from a US based organization.

The activity began on June 26, when a device on the customer’s network was observed connecting to the IP address 173.44.141[.]89, a previously unseen IP for this network along with the use of multiple user agents, which was also rare for the user. It was later determined that the IP address was a known indicator of compromise (IoC) associated with TAG-150’s CastleRAT and CastleLoader operations [2][5].

Figure 2: Darktrace’s detection of a device making unusual connections to the malicious endpoint 173.44.141[.]89.

The device was observed downloading two scripts from this endpoint, namely ‘/service/download/data_5x.bin’ and ‘/service/download/data_6x.bin’, which have both been linked to CastleLoader infections by open-source intelligence (OSINT) [8]. The archives contains embedded shellcode, which enables attackers to execute arbitrary code directly in memory, bypassing disk writes and making detection by endpoint detection and response (EDR) tools significantly more difficult [2].

Figure 3: Darktrace’s detection of two scripts from the malicious endpoint.

In addition to this, the affected device exhibited a high volume of internal connections to a broad range of endpoints, indicating potential scanning activity. Such behavior is often associated with reconnaissance efforts aimed at mapping internal infrastructure.

Darktrace / NETWORK correlated these behaviors and generated an Enhanced Monitoring model, a high-fidelity security model designed to detect activity consistent with the early stages of an attack. These high-priority models are continuously monitored and triaged by Darktrace’s Security Operations Center (SOC) as part of the Managed Threat Detection and Managed Detection & Response services, ensuring that subscribed customers are promptly alerted to emerging threats.

Figure 4: Darktrace detected an unusual ZIP file download alongside the anomalous script, followed by internal connectivity. This activity was correlated under an Enhanced Monitoring model.

Darktrace Autonomous Response

Fortunately, Darktrace’s Autonomous Response capability was fully configured, enabling it to take immediate action against the offending device by blocking any further connections external to the malicious endpoint, 173.44.141[.]89. Additionally, Darktrace enforced a ‘group pattern of life’ on the device, restricting its behavior to match other devices in its peer group, ensuring it could not deviate from expected activity, while also blocking connections over 443, shutting down any unwanted internal scanning.

Figure 5: Actions performed by Darktrace’s Autonomous Response to contain the ongoing attack.

Conclusion

The rise of the MaaS ecosystem, coupled with attackers’ growing ability to customize tools and techniques for specific targets, is making intrusion prevention increasingly challenging for security teams. Many threat actors now leverage modular toolkits, dynamic infrastructure, and tailored payloads to evade static defenses and exploit even minor visibility gaps. In this instance, Darktrace demonstrated its capability to counter these evolving tactics by identifying early-stage attack chain behaviors such as network scanning and the initial infection attempt. Autonomous Response then blocked the CastleLoader IP delivering the malicious ZIP payload, halting the attack before escalation and protecting the organization from a potentially damaging multi-stage compromise

Credit to Ahmed Gardezi (Cyber Analyst) Tyler Rhea (Senior Cyber Analyst)
Edited by Ryan Traill (Analyst Content Lead)

Appendices

Darktrace Model Detections

Anomalous Connection / Unusual Internal Connections
Anomalous File / Zip or Gzip from Rare External Location
Anomalous File / Script from Rare External Location
Initial Attack Chain Activity (Enhanced Monitoring Model)

MITRE ATT&CK Mapping

T15588.001 - Resource Development – Malware
TG1599 – Defence Evasion – Network Boundary Bridging
T1046 – Discovery – Network Service Scanning
T1189 – Initial Access

List of IoCs
IoC - Type - Description + Confidence

173.44.141[.]89 – IP – CastleLoader C2 Infrastructure
173.44.141[.]89/service/download/data_5x.bin – URI – CastleLoader Script
173.44.141[.]89/service/download/data_6x.bin – URI - CastleLoader Script
wsc.zip – ZIP file – Possible Payload

References

[1] - https://blog.polyswarm.io/castleloader

[2] - https://www.recordedfuture.com/research/from-castleloader-to-castlerat-tag-150-advances-operations

[3] - https://www.pcrisk.com/removal-guides/34160-castleloader-malware

[4] - https://www.scworld.com/brief/malware-loader-castleloader-targets-devices-via-fake-github-clickfix-phishing

[5] https://www.virustotal.com/gui/ip-address/173.44.141.89/community

[6] https://thehackernews.com/2025/07/castleloader-malware-infects-469.html

[7] https://www.cryptika.com/new-castleloader-attack-using-cloudflare-themed-clickfix-technique-to-infect-windows-computers/

[8] https://www.cryptika.com/castlebot-malware-as-a-service-deploys-range-of-payloads-linked-to-ransomware-attacks/

About the author

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OT

November 20, 2025

Managing OT Remote Access with Zero Trust Control & AI Driven Detection

managing OT remote access with zero trust control and ai driven detection

The shift toward IT-OT convergence

Recently, industrial environments have become more connected and dependent on external collaboration. As a result, truly air-gapped OT systems have become less of a reality, especially when working with OEM-managed assets, legacy equipment requiring remote diagnostics, or third-party integrators who routinely connect in.

This convergence, whether it’s driven by digital transformation mandates or operational efficiency goals, are making OT environments more connected, more automated, and more intertwined with IT systems. While this convergence opens new possibilities, it also exposes the environment to risks that traditional OT architectures were never designed to withstand.

The modernization gap and why visibility alone isn’t enough

The push toward modernization has introduced new technology into industrial environments, creating convergence between IT and OT environments, and resulting in a lack of visibility. However, regaining that visibility is just a starting point. Visibility only tells you what is connected, not how access should be governed. And this is where the divide between IT and OT becomes unavoidable.

Security strategies that work well in IT often fall short in OT, where even small missteps can lead to environmental risk, safety incidents, or costly disruptions. Add in mounting regulatory pressure to enforce secure access, enforce segmentation, and demonstrate accountability, and it becomes clear: visibility alone is no longer sufficient. What industrial environments need now is precision. They need control. And they need to implement both without interrupting operations. All this requires identity-based access controls, real-time session oversight, and continuous behavioral detection.

The risk of unmonitored remote access

This risk becomes most evident during critical moments, such as when an OEM needs urgent access to troubleshoot a malfunctioning asset.

Under that time pressure, access is often provisioned quickly with minimal verification, bypassing established processes. Once inside, there’s little to no real-time oversight of user actions whether they’re executing commands, changing configurations, or moving laterally across the network. These actions typically go unlogged or unnoticed until something breaks. At that point, teams are stuck piecing together fragmented logs or post-incident forensics, with no clear line of accountability.

In environments where uptime is critical and safety is non-negotiable, this level of uncertainty simply isn’t sustainable.

The visibility gap: Who’s doing what, and when?

The fundamental issue we encounter is the disconnect between who has access and what they are doing with it.

Traditional access management tools may validate credentials and restrict entry points, but they rarely provide real-time visibility into in-session activity. Even fewer can distinguish between expected vendor behavior and subtle signs of compromise, misuse or misconfiguration.

As a result, OT and security teams are often left blind to the most critical part of the puzzle, intent and behavior.

Closing the gaps with zero trust controls and AI‑driven detection

Managing remote access in OT is no longer just about granting a connection, it’s about enforcing strict access parameters while continuously monitoring for abnormal behavior. This requires a two-pronged approach: precision access control, and intelligent, real-time detection.

Zero Trust access controls provide the foundation. By enforcing identity-based, just-in-time permissions, OT environments can ensure that vendors and remote users only access the systems they’re explicitly authorized to interact with, and only for the time they need. These controls should be granular enough to limit access down to specific devices, commands, or functions. By applying these principles consistently across the Purdue Model, organizations can eliminate reliance on catch-all VPN tunnels, jump servers, and brittle firewall exceptions that expose the environment to excess risk.

Access control is only one part of the equation

Darktrace / OT complements zero trust controls with continuous, AI-driven behavioral detection. Rather than relying on static rules or pre-defined signatures, Darktrace uses Self-Learning AI to build a live, evolving understanding of what’s “normal” in the environment, across every device, protocol, and user. This enables real-time detection of subtle misconfigurations, credential misuse, or lateral movement as they happen, not after the fact.

By correlating user identity and session activity with behavioral analytics, Darktrace gives organizations the full picture: who accessed which system, what actions they performed, how those actions compared to historical norms, and whether any deviations occurred. It eliminates guesswork around remote access sessions and replaces it with clear, contextual insight.

Importantly, Darktrace distinguishes between operational noise and true cyber-relevant anomalies. Unlike other tools that lump everything, from CVE alerts to routine activity, into a single stream, Darktrace separates legitimate remote access behavior from potential misuse or abuse. This means organizations can both audit access from a compliance standpoint and be confident that if a session is ever exploited, the misuse will be surfaced as a high-fidelity, cyber-relevant alert. This approach serves as a compensating control, ensuring that even if access is overextended or misused, the behavior is still visible and actionable.

If a session deviates from learned baselines, such as an unusual command sequence, new lateral movement path, or activity outside of scheduled hours, Darktrace can flag it immediately. These insights can be used to trigger manual investigation or automated enforcement actions, such as access revocation or session isolation, depending on policy.

This layered approach enables real-time decision-making, supports uninterrupted operations, and delivers complete accountability for all remote activity, without slowing down critical work or disrupting industrial workflows.

Where Zero Trust Access Meets AI‑Driven Oversight:

Granular Access Enforcement: Role-based, just-in-time access that aligns with Zero Trust principles and meets compliance expectations. ‍
Context-Enriched Threat Detection: Self-Learning AI detects anomalous OT behavior in real time and ties threats to access events and user activity. ‍
Automated Session Oversight: Behavioral anomalies can trigger alerting or automated controls, reducing time-to-contain while preserving uptime. ‍
Full Visibility Across Purdue Layers: Correlated data connects remote access events with device-level behavior, spanning IT and OT layers. ‍
Scalable, Passive Monitoring: Passive behavioral learning enables coverage across legacy systems and air-gapped environments, no signatures, agents, or intrusive scans required.

Complete security without compromise

We no longer have to choose between operational agility and security control, or between visibility and simplicity. A Zero Trust approach, reinforced by real-time AI detection, enables secure remote access that is both permission-aware and behavior-aware, tailored to the realities of industrial operations and scalable across diverse environments.

Because when it comes to protecting critical infrastructure, access without detection is a risk and detection without access control is incomplete.

About the author

Pallavi Singh

Product Marketing Manager, OT Security & Compliance

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

FortiClient EMS Exploited: Attack Chain & Post Exploitation Tactics

Cyber attacks on internet-facing systems

What is FortiClient EMS?

CVE-2023-48788

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

CastleLoader & CastleRAT: Behind TAG150’s Modular Malware Delivery System

Managing OT Remote Access with Zero Trust Control & AI Driven Detection

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November 26, 2025

CastleLoader & CastleRAT: Behind TAG150’s Modular Malware Delivery System

What is TAG-150?

What are CastleLoader and CastleRAT?

How are they deployed?

Darktrace Coverage

Darktrace Autonomous Response

Conclusion

Appendices

References

Blog

OT

November 20, 2025

Managing OT Remote Access with Zero Trust Control & AI Driven Detection

The shift toward IT-OT convergence

The modernization gap and why visibility alone isn’t enough

The risk of unmonitored remote access

The visibility gap: Who’s doing what, and when?

Closing the gaps with zero trust controls and AI‑driven detection

Access control is only one part of the equation

Where Zero Trust Access Meets AI‑Driven Oversight:

Complete security without compromise