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October 30, 2024

Post-Exploitation Activities on Fortinet Devices: A Network-Based Analysis

This blog explores recent findings from Darktrace's Threat Research team on active exploitation campaigns targeting Fortinet appliances. This analysis focuses on the September 2024 exploitation of FortiManager via CVE-2024-47575, alongside related malicious activity observed in June 2024.
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
Adam Potter
Senior Cyber Analyst
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30
Oct 2024

Introduction: Uncovering active exploitation of Fortinet vulnerabilities

As part of the Darktrace Threat Research team's routine analysis of October's Patch Tuesday vulnerabilities, the team began searching for signs of active exploitation of a critical vulnerability (CVE-2024-23113) affecting the FortiGate to FortiManager (FGFM) protocol.[1]

Although the investigation was prompted by an update regarding CVE 2024-23113, results of the inquiry yielded evidence of widespread exploitation of Fortinet devices in both June and September 2024 potentially via multiple vulnerabilities including CVE 2024-47575. Analysts identified two clusters of activity involving overlapping indicators of compromise (IoCs), likely constituting unique campaigns targeting Fortinet appliances.

This blog will first highlight the finding and analysis of the network-based indicators of FortiManager post-exploitation activity in September, likely involving CVE 2024-47575. The article will then briefly detail a similar pattern of malicious activity observed in June 2024 that involved similar IoCs that potentially comprises a distinct campaign targeting Fortinet perimeter devices.

Fortinet CVE Disclosures

FortiManager devices allow network administrators to manage Fortinet devices on organizations’ networks.[2] One such subset of devices managed through this method are Fortinet firewalls known as FortiGate. These manager and firewall devices communicate with each other via a custom protocol known as FortiGate to FortiManager (FGFM), whereby devices can perform reachability tests and configuration-related actions and reporting.[3] By default, FortiManager devices operate this protocol via port 541.[4]

Fortinet Product Security Incident Response Team released multiple announcements revealing vulnerabilities within the daemon responsible for implementing operability of the FGFM service. Specifically, CVE 2024-23113 enables attackers to potentially perform arbitrary remote command execution through the use of a specially crafted format string to a FortiGate device running the “fgfm daemon”.[5][6]  Similarly, the exploitation of CVE 2024-47575  could also allow remote command execution due to a missing authentication mechanism when targeting specifically FortiManager devices.[7][8]  Given how prolific both FortiGate and FortiManager devices are within the global IT security ecosystem, Darktrace analysts hypothesized that there may have been specific targeting of such devices within the customer base using these vulnerabilities throughout mid to late 2024.

Campaign Analysis

In light of these vulnerability disclosures, Darktrace’s Threat Research team began searching for signs of active exploitation by investigating file download, lateral movement or tooling activity from devices that had previously received suspicious connections on port 541. The team first noticed increases in suspicious activity involving Fortinet devices particularly in mid-September 2024. Further analysis revealed a similar series of activities involving some overlapping devices identified in June 2024. Analysis of these activity clusters revealed a pattern of malicious activity against likely FortiManager devices, including initial exploitation, payload retrieval, and exfiltration of probable configuration data.

Below is an overview of malicious activity we have observed by sector and region:

Sector and region affected by malicious activity on fortigate devices
The sectors of affected customers listed above are categorized according to the United Kingdom’s Standard Industrial Classification (SIC).

Initial Exploitation of FortiManager Devices

Across many of the observed cases in September, activity began with the initial exploitation of FortiManager devices via incoming connectivity over TLS/SSL. Such activity was detected due to the rarity of the receiving devices accepting connections from external sources, particularly over destination port 541. Within nearly all investigated incidents, connectivity began with the source IP, 45.32.41[.]202, establishing an SSL session with likely FortiManager devices.  Device types were determined through a combination of the devices’ hostnames and the noted TLS certificate issuer for such encrypted connections.

Due to the encrypted nature of the connection, it was not possible to ascertain the exploit used in the analyzed cases. However, given the similarity of activities targeting FortiManager devices and research conducted by outside firms, attackers likely utilized CVE 2024-47575.[9] For example, the source IP initiating the SSL sessions also has been referenced by Mandiant as engaging in CVE 2024-47575 exploitation. In addition to a consistent source IP for the connections, a similar JA3 hash was noted across multiple examined accounts, suggesting a similarity in source process for the activity.

In most cases observed by Darktrace, the incoming connectivity was followed by an outgoing connection on port 443 to the IP 45.32.41[.]202. Uncommon reception of encrypted connections over port 541, followed by the initiation of outgoing SSL connections to the same endpoint would suggest probable successful exploitation of FortiManager CVEs during this time.

Model alert logs highlighting the incoming connectivity over port 541 to the FortiManager devices followed by outgoing connection to the external IP.
Figure 1: Model alert logs highlighting the incoming connectivity over port 541 to the FortiManager devices followed by outgoing connection to the external IP.

Payload Retrieval

Investigated devices commonly retrieved some form of additional content after incoming connectivity over port 541. Darktrace’s Threat Research team noted how affected devices would make HTTP GET requests to the initial exploitation IP for the URI: /dom.js. This URI, suggestive of JavaScript content retrieval, was then validated by the HTTP response content type. Although Darktrace could see the HTTP content of the connections, usage of destination port 443 featured prominently during these HTTP requests, suggesting an attempt at encryption of the session payload details.

Figure 2: Advanced Search HTTP log to the exploitation IP noting the retrieval of JavaScript content using the curl user agent.

Cyber AI Analyst investigation into the initial exploitation activity. This incident emphasizes the rare external connectivity over port 443 requesting JavaScript content following the incoming connections over port 541.
Figure 3: Cyber AI Analyst investigation into the initial exploitation activity. This incident emphasizes the rare external connectivity over port 443 requesting JavaScript content following the incoming connections over port 541.

The operators of the campaign also appear to have used a consistent user agent for payload retrieval: curl 8.4.0. Usage of an earlier version of the curl (version 7 .86.0) was only observed in one instance. The incorporation of curl utility to establish HTTP connections therefore suggests interaction with command-line utilities on the inspected Fortinet hosts. Command-line interaction also adds validity to the usage of exploits such as CVE 2024-47575 which enable unauthenticated remote command execution. Moreover, given the egress of data seen by the devices receiving this JavaScript content, Darktrace analysts concluded that this payload likely resulted in the configuration aggregation activity noted by external researchers.

Data Exfiltration

Nearly all devices investigated during the September time period performed some form of data exfiltration using the HTTP protocol. Most frequently, devices would initiate these HTTP requests using the same curl user agent already observed during web callback activity.  Again, usage of this tool heavily suggests interaction with the command-line interface and therefore command execution.

The affected device typically made an HTTP POST request to one or both of the following two rare external IPs: 104.238.141[.]143 and 158.247.199[.]37. One of the noted IPs, 104.238.141[.]143, features prominently within external research conducted by Mandiant during this time. These HTTP POST requests nearly always sent data to the /file endpoint on the destination IPs. Analyzed connections frequently noted an HTTP mime type suggestive of compressed archive content. Some investigations also revealed specific filenames for the data sent externally: “.tm”. HTTP POST requests occurred without a specified hostname. This would suggest the IP address may have already been cached locally on the device from a running process or the IP address was hardcoded into the details of unwarranted code running on the system. Moreover, many such POSTs occurred without a GET request, which can indicate exfiltration activity.

Model alert logs noting both the connection to the IP 158.247.199[.]37 over port 443 without a hostname, and the unusual activity metric describing how the request was made without a prior HTTP GET request. Such activity can indicate malicious data exfiltration.
Figure 4: Model alert logs noting both the connection to the IP 158.247.199[.]37 over port 443 without a hostname, and the unusual activity metric describing how the request was made without a prior HTTP GET request. Such activity can indicate malicious data exfiltration.

Interestingly, in many investigations, analysts noticed a lag period between the initial access and exploitation, and the exfiltration of data via HTTP. Such a pause, sometimes over several hours to over a day, could reflect the time needed to aggregate data locally on the host or as a strategic pause in activity to avoid detection. While not present within every compromise activity logs inspected, the delay could represent slight adjustments in behavior during the campaign by the threat actor.

Figure 5: Advanced search logs showing both the payload retrieval and exfiltration activity, emphasizing the gap in time between payload retrieval and exfiltration via HTTP POST request.

HTTP and file identification details identified during this time also directly correspond to research conducted by Mandiant. Not only do we see overlap in IPs identified as receiving the posted data (104.238.141[.]143) we also directly observed an overlap in filenames for the locally aggregated configuration data. Moreover, the gzip mime type identified in multiple customer investigations also corresponds directly to exfiltration activity noted by Mandiant researchers.

Advanced search logs noting the filename and URL of the posted data to one of the exfiltration IPs. The .tm filename corresponds to the locally stored file on affected FortiManager devices analyzed by external researchers.
Figure 6: Advanced search logs noting the filename and URL of the posted data to one of the exfiltration IPs. The .tm filename corresponds to the locally stored file on affected FortiManager devices analyzed by external researchers.

Activity detected in June 2024

Common indicators

Analysts identified a similar pattern of activity between June 23 and June 25. Activity in this period involved incoming connections from the aforementioned IP 45.32.41[.]202 on either port 541 or port 443 followed by an outgoing connection to the source. This behavior was then followed by HTTP POSTs to the previously mentioned IP address 158.247.199[.]37 in addition to the novel IP: 195.85.114[.]78  using same URI ‘/file’ noted above. Given the commonalties in indicators, time period, and observed behaviors, this grouping of exploitation attempts appears to align closely with the campaign described by Mandiant and may represent exploitation of CVE 2024-47575 in June 2024. The customers targeted in June fall into the same regions and sectors as seen those in the September campaign.

Deviations in behavior

Notably, Darktrace detected a different set of actions during the same June timeframe despite featuring the same infrastructure. This activity involved an initial incoming connection from 158.247.199[.]37 to an internal device on either port 541 or port 443. This was then followed by an outgoing HTTP connection to 158.247.199[.]37 on port 443 with a URI containing varying external IPs. Upon further review, analysts noticed the IPs listed may be the public IPs of the targeted victim, suggesting a potential form device registration by the threat actor or exploit validation. While the time period and infrastructure closely align with the previous campaign described, the difference in activity may suggest another threat actor sharing infrastructure or the same threat actor carrying out a different campaign at the same time. Although the IP 45.32.41[.]202 was contacted, paralleling activity seen in September, analysts did notice a different payload received from the external host, a shell script with the filename ver.sh.

Figure 7: AI Analyst timeline noting the suspicious HTTP behavior from a FortiManager device involving the IP 158.247.199[.] 37.

Darktrace's depth of detection and investigation

Darktrace detected spikes in anomalous behavior from Fortinet devices within the customer base between September 22 and 23, 2024. Following an in-depth investigation into affected accounts and hosts, Darktrace identified a clear pattern where one, or multiple, threat actors leveraged CVEs affecting likely FortiManager devices to execute commands on the host, retrieve malicious content, and exfiltrate sensitive data. During this investigation, analysts then identified possibly related activity in June 2024 highlighted above.

The gathering and exfiltration of configuration data from network security management or other perimeter hosts is a technique that can enable future access by threat actors. This parallels activity previously discussed by Darktrace focused on externally facing devices, such as Palo Alto Networks firewall devices.  Malicious entities could utilize stolen configuration data and potentially stored passwords/hashes to gain initial access in the future, irrespective of the state of device patching. This data can also be potentially sold by initial access brokers on illicit sites. Moreover, groups can leverage this information to establish persistence mechanisms within devices and host networks to enable more impactful compromise activity.

Uncover threat pattens before they strike your network

Network and endpoint management services are essential tools for network administrators and will remain a critical part of IT infrastructure. However, these devices are often configured as internet-facing systems, which can unintentionally expose organizations networks' to attacks. Internet exposure provides malicious groups with novel entry routes into target environments. Although threat actors can swap vulnerabilities to access target networks, the exploitation process leaves behind unusual traffic patterns, making their presence detectable with the right network detection tools.

By detecting the unusual patterns of network traffic which inevitably ensue from exploitation of novel vulnerabilities, Darktrace’s anomaly-based detection and response approach can continue to identify and inhibit such intrusion activities irrespective of exploit used. Eulogizing the principle of least privilege, configuration and asset management, and maintaining the CIA Triad across security operations will continue to help security teams boost their defense posture.

See how anomaly-based detection can enhance your security operations—schedule a personalized demo today.

Get a demo button for Darktrace

Credit to Adam Potter (Senior Cyber Analyst), Emma Foulger (Principal Cyber Analyst), Nahisha Nobregas (Senior Cyber Analyst), Hyeongyung Yeom (Principal Cyber Analyst & Analyst Team Lead, East Asia), Sam Lister (Senior Cyber Analyst)

Appendix

Model Alerts

  • Anomalous Connection / Posting HTTP to IP without Hostname
  • Anomalous Connection / Callback on Web Facing Device
  • Anomalous Server Activity / New Internet Facing Server
  • Anomalous Server Activity / Outgoing from Server

Cyber AI Analyst Incidents

  • Possible HTTP Command and Control
  • Possible HTTP Command and Control to Multiple Endpoints

IoCs

Indicator – Type - Description

104.238.141[.]143 -  IP Address  - C2 infrastructure

158.247.199[.]37 - IP Address - C2 infrastructure

45.32.41[.]202 - IP Address - C2 infrastructure

104.238.141[.]143/file – URL - C2 infrastructure

158.247.199[.]37/file  - URL - C2 infrastructure

45.32.41[.]202/dom.js – URL - C2 infrastructure

.tm – Filename - Gzip file

MITRE Attack Framework

  • Initial Access
    T1190 Exploiting Public-Facing Application
  • Execution:
    T1059 Command and Scripting Interpreter  (Sub-Techniques: T1059.004 Unix Shell, T1059.008 Network Device CLI)
  • Discovery:
    T1083 File and System Discovery
    T1057 Process Discovery
  • Collection:
    T1005 Data From Local System
  • Command and Control:
    T1071 Application Layer Protocols (Sub-Technique:
    T1071.001 Web Protocols)
    T1573  Encrypted Channel
    T1573.001  Symmetric Cryptography
    T1571 Non-Standard Port
    T1105 Ingress Tool Transfer
    T1572 Protocol Tunnelling 
  • Exfiltration:
    T1048.003 Exfiltration Over Unencrypted Non-C2 Protocol

References

{1} https://cloud.google.com/blog/topics/threat-intelligence/fortimanager-zero-day-exploitation-cve-2024-47575/

{2} https://docs.fortinet.com/document/fortimanager/6.4.0/ports-and-protocols/606094/fortigate-fortimanager-protocol#:~:text=The%20FortiGate%2DFortiManager%20(FGFM),by%20using%20the%20FGFM%20protocol.

{3)https://docs.fortinet.com/document/fortigate/6.4.0/ports-and-protocols/373486/fgfm-fortigate-to-fortimanager-protocol
{4} https://www.fortiguard.com/psirt/FG-IR-24-029
{5} https://www.fortiguard.com/psirt/FG-IR-24-423
{6}https://www.fortinet.com/content/dam/fortinet/assets/data-sheets/fortimanager.pdf

{7} https://doublepulsar.com/burning-zero-days-fortijump-fortimanager-vulnerability-used-by-nation-state-in-espionage-via-msps-c79abec59773

{8} https://darktrace.com/blog/post-exploitation-activities-on-pan-os-devices-a-network-based-analysis

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
Adam Potter
Senior Cyber Analyst

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June 30, 2026

5 Ways AI is changing traditional security models according to modern CISOs

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The Reality of Securing AI in Motion

Traditional security tools were built for environments defined by fixed rules and predictable workflows. But AI behavior is non-deterministic. The same prompt can produce different outcomes, and risk often emerges gradually as AI behavior adapts, and permissions drift over time. This creates a constantly shifting environment where security teams are working to define control in a system that resists stability. “In AI security, yesterday's priorities can become tomorrow's blind spots. The landscape shifts that fast,” warned the SVP and Head of Technology and Cybersecurity of a real estate investment trust. Conventional approaches, which rely on establishing and maintaining a steady baseline, struggle to keep up with that level of change.

At the same time, AI adoption is accelerating across organizations, often faster than security teams can implement the controls needed to manage it. “The car is being built while it’s already on the road,” explained the CISO of a global private fund administrator. “The threats we're securing against today won't be the threats we're facing tomorrow. What kept us up three months ago looks nothing like what we're dealing with today.”

As businesses move quickly to unlock value from AI, security teams are left closing gaps in real time, while also facing adversaries who are using AI to make their attacks more scalable, adaptive, and difficult to detect. In this recent roundtable discussion of CISOs and security leaders, five themes emerged around AI cyber risk.  

1. AI agents with human access but no human judgment

In Darktrace’s 2026 State of AI Cybersecurity report, 96% of the surveyed security professionals agree that AI significantly improves the speed and efficiency with which they work. Yet, 92% admitted that they’re concerned with the security implications of the use of AI agents across their workforce.

AI agents now operate with human-level permissions across systems, acting at machine speed, orchestrating actions across platforms, and making decisions without the judgment or caution a person would apply. Unlike human users, they cannot be expected to pause and question whether a given action is appropriate.

Their identities are also difficult to inventory, govern, and audit. As agents become easier to deploy than legacy IT systems ever were, organizations are quickly losing track of what is running, what it has access to, and what it is doing. This creates a growing class of highly privileged, autonomous actors operating without the visibility or oversight that traditional identity and access controls were designed to provide.“While AI adoption is critical to running a modern business, AI alone can’t solve all our cybersecurity challenges,” said a global financial sector CISO. “We still need think critically and use human judgement. Those are two things AI can’t do.”

This lack of human judgment becomes especially risky as new architectures, such as Model Context Protocol (MCP), can expand how agents connect to data, tools, and external systems. By design, MCP enables agents to dynamically discover and interact with new resources, increasing flexibility but also introducing new pathways for unintended access, data exposure, or abuse if not properly governed.

The CISO of a fund administrator highlighted one emerging vector as an example: rogue MCP servers. “Our developers want to move quickly and bring value to the business, but technologies like these can unintentionally expose sensitive data in ways that would never have happened before.”

2. Increased digital complexity and expanded attack surface

AI activity rarely stays contained. A single prompt can trigger a chain of actions across networks, email, cloud infrastructure, SaaS platforms, endpoints, identity systems, and development environments, spanning systems that were never designed to be secured as a single, connected flow. This expands both the scale and complexity of what security teams need to monitor and defend.

Yet no single control has visibility across that entire chain. “You can’t defend effectively what you can’t see,” cautioned the private fund administrator CISO. As AI-driven activity moves fluidly across environments, gaps in coverage become inevitable, creating blind spots that attackers can exploit.

Threat actors are already capitalizing on this lack of visibility. “Threat actors have advanced their use of generative AI to launch more convincing phishing campaigns, automate social engineering, and scale attacks with greater precision down to the individual level,” said the SVP of Technology and Cybersecurity for the real estate investment trust. What was once manual and targeted can now be automated and personalized at scale, making attacks harder to detect and easier to execute.

At the same time, the pace of exploitation is accelerating. As a global CISO operating across 40+ countries described it: “Zero-day vulnerabilities are no longer zero day; it’s minus one day. By the time you get to it and address it, it’s already a problem.” By the time risk is identified, it has often already been realized.

The result is a rapidly expanding and increasingly interconnected attack surface that challenges security teams to maintain visibility, context, and control across AI-driven activity.

3. Shadow AI is already everywhere

76% of organizations now cite shadow AI as a problem, one that is spreading through organizations in ways that are hard to track and even harder to control.

Employees are experimenting with publicly available Gen AI tools. Teams are spinning up low-code automations on their own. SaaS providers are quietly embedding AI into existing products. Developers are plugging AI services directly into workflows, often without pausing to consider what that exposure means.

The result is a lack of visibility into:

  • What AI tools are being used
  • What data those tools can access
  • Where prompts and outputs are going
  • Which AI agents are interacting with enterprise systems

The SVP of Cybersecurity at a real estate investment trust described the shift: “Before, I was worried about someone sending data erroneously to their personal email. Now we have all these agents online that people are utilizing, and we’re looking at those vectors as well.” For security teams, this means operating without a complete view of how AI is being used, what it can access, and where risk may already be emerging.

4. Built-in guardrails are not enough

Organizations often assume that native AI guardrails or provider-level controls are sufficient to manage AI risk. But securing AI requires ongoing visibility, oversight, and governance, not just controls configured at deployment. "It’s a misconception that adopting AI is going to solve all your problems,” warns a global financial services CISO.

Security leaders are increasingly recognizing the limitations of these controls as:

  • Fragmented and difficult to enforce consistently across multiple AI systems, workflows, and environments
  • Ambiguous in terms of accountability due to shared responsibility for AI governance between IT, security, developers, business teams, and third-party providers
  • Limited in end-to-end oversight, leaving gaps that stretch from the initial prompt all the way through to the downstream impact of an agent's actions

Securing AI demands more than simple prompt filtering or static policy enforcement. It requires understanding intent, behavior, and context across both human and AI activity.

The next phase of cybersecurity: securing AI

To safely and responsibly adopt AI at scale, organizations need a new operational model for cybersecurity that’s capable of:

• Understanding AI behavior

• Identifying risk in real time

• Maintaining governance without slowing innovation

The CSO of a $10 billion municipal utility organization described the challenge with precision: “We have to move at the speed of innovation and risk, because both are accelerating faster than ever.”

Embrace AI with confidence with Darktrace / SECURE AI

Darktrace has introduced Darktrace / SECURE AI™, a new product within the Darktrace ActiveAI Security Platform™  ,designed to provide enterprise-wide security for AI by applying industry leading behavioral analysis to how prompts, agents, and AI systems are used.

Darktrace / SECURE AITM delivers real-time visibility and control across Enterprise and SaaS GenAI prompts, AI agent identities, development and production environments, and Shadow AI - detecting even subtle misuse, misconfiguration, and drift that traditional, rule-based controls simply do not understand. By interpreting context and intent across humans and machines, Darktrace enables organizations to adopt AI at scale without introducing unmanaged risk

What makes this possible is Darktrace’s decade-long maturity and expertise in behavioral understanding and AI-native cybersecurity. Achieved with Self-Learning AI that has been proven across more than 10,000 organizations, Darktrace understands what “normal” looks like for a business, across its users, systems, and now AI, so that meaningful deviations can be detected and acted on before they become incidents.

With one CISO describing Darktrace’s Self-Learning AI as “a leap forward compared to other tools” and another as a “force multiplier,” the technology can interpret ambiguous interactions, understand how access accumulates over time, and recognize when behavior, human or machine, begins to drift.

“Strategically, we’re looking to gain more visibility into how AI is operating across the environment and achieve greater control over what AI should be allowed to access and do,” shared the CISO at a private fund administrator.  

“What I’ve seen from Darktrace / SECURE AI is extremely promising. I have tremendous confidence in Darktrace’s vision for where this is headed and its ability to execute on this new solution.”

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June 29, 2026

How Darktrace Transformed Cybersecurity at Our Health Center: A CIO’s Perspective

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How Darktrace Transformed Cybersecurity at Our Health Center: A CIO’s Perspective

In my role as CIO, I bring years of experience leading IT for healthcare organizations. I’ve seen firsthand the unique cybersecurity challenges that nonprofit health centers face: limited budgets, small IT teams, and the constant pressure to prioritize patient care over technology investments. Yet, the threat landscape for health is relentless, and the stakes for protecting patient data and ensuring operational continuity have never been higher. It’s a balancing act.

The search for a better solution

Like many nonprofits, organizations I work at start with Microsoft’s security stack. The discounted pricing for nonprofits makes it an obvious choice, and Microsoft Defender provided a solid foundation for endpoint and email security. However, I quickly realized that relying on a single vendor, even one as robust as Microsoft, left gaps in our defenses. Cybersecurity is never one-size-fits-all, which is why my preference was to layer an additional solution on top of our native security to improve our security posture.

Teams needed a solution that could layer seamlessly on top of Microsoft, without adding complexity or draining limited resources. That’s when I found Darktrace. I had heard of their reputation after seeing how other organizations used Darktrace to secure their infrastructure and was impressed by their AI-native, agentless approach and agreed to a proof of value (POV).

Our goal was to elavate Microsoft with an additional layer of intelligence- one that could seamlessly integrate, operate autonomously, and support a small team without increasing overhead. We turned to Darktrace because its AI-native, agentless approach offered a fundamentally different way to detect and respond to threats, learning our environment in real time and filling gaps that traditional tools can miss. With a quick POV, we were able to validate how effectively Darktrace works alongside Microsoft to deliver a more complete and resilient security architecture.

Why Darktrace stood out

From the start, Darktrace differentiated itself in several critical ways:

  • Deep visibility: Unlike other solutions that rely simply on host-based monitoring with endpoint agents, Darktrace operates passively at the network layer and integrates via APIs for email and identity security. This gave full visibility into network traffic that we previously didn’t have, going beyond our existing endpoint-based tools without adding additional maintenance overhead for our small IT team.
  • AI-native from the ground up: Darktrace wasn’t just layering AI on top of an existing product; it was built with AI at its core. Their autonomous detection and response to threats immediately reduced the need for constant human supervision. In a world where cyber-attacks are increasingly sophisticated and subtle, having an AI that learns our environment and adapts in real time is invaluable.
  • Comprehensive coverage: We started with a POV focused on email security, but quickly expanded to full deployment across our entire infrastructure. Darktrace’s products now protect our email, network, and identity layers, providing visibility and defense against lateral movement and abnormal behavior that traditional tools often miss.

Integration and workflow: Smooth and simple

One of the most impressive aspects of Darktrace is how easy it was to integrate into an existing environment. For network security, it was as simple as plugging an appliance into our top-of-rack switch – no downtime, no complex configuration. For email and identity, API integrations meant we could be up and running in hours, not weeks.

This simplicity extended to day-to-day operations. Our IT team received regular security reports, and any time we had questions or needed to adjust policies, Darktrace’s support team was there with white-glove service. Their responsiveness- even in the middle of the night- gave us confidence that we had true partners, not just a vendor.

Real-world impact: Threats stopped, time saved

The results spoke for themselves. During the time with Darktrace, I did not experience any security incidents. The team slept better at night knowing that Darktrace was monitoring for anomalies and proactively blocking suspicious activity, alerting us even before we noticed anything was wrong.

A memorable example was during an Electronic Health Record (EHR) upgrade, when my team forgot to adjust the policy in advance. Darktrace’s autonomous response was so effective that it blocked our upgrade activities- proof that nothing, not even internal changes, could slip by unnoticed. This level of vigilance meant that ransomware, data exfiltration attempts, or insider threats would be detected and contained before causing harm.

While I can’t share specific ROI numbers, the value was clear: we’ve avoided costly breaches, reduced the time spent investigating alerts, and eliminated the performance drag of agent-based tools. With Darktrace layered on top of Microsoft, I’ve hit the right balance of maximum protection with minimal spending. The cost of Darktrace / EMAIL was competitive, especially when factoring in the included Managed Detection and Response (MDR) service, which provides expert human oversight on top of the AI.

Key differentiators over the competition

  • Extending visibility beyond the endpoint: Traditional host-based monitoring solutions, such as EDR, play a critical role in securing individual devices. By adding a network detection and response (NDR) layer, we gained visibility into activity across our wider digital environment, surfacing threats that move laterally, operate between devices, or bypass endpoint controls. Darktrace also stood out for its ability to learn our normal patterns of behavior and identify subtle deviations in real time, not just known indicators of compromise. Because this is delivered through passive, non-disruptive monitoring, we were able to strengthen our defenses without adding complexity or impacting performance.
  • Layered security without complexity: Darktrace elevated our Microsoft foundation without creating conflicts or requiring us to disable existing protections. This layered approach maximized our security posture without adding operational burden.
  • Expert partnership: Beyond technology, Darktrace’s team acted as true partners, guiding us through deployment, providing ongoing support, and helping us interpret findings. This partnership was as valuable as the technology itself.

Advice for other nonprofits

If you’re an IT leader in a nonprofit, my advice is simple: look for solutions that are easy to deploy, intelligent in their response, and cost-effective. Don’t settle for more endpoint based tools that overlap with what you already have. Seek out a layered approach that covers your blind spots – especially at the network and email layers- at a price point that suits your organization.

Most importantly, don’t be afraid to evaluate new solutions. Even if you’re inundated with vendor pitches, you owe it to your organization to explore options that could save you time, money, and sleepless nights.

For organizations I work at, combining Microsoft’s security stack with Darktrace’s AI-native, platform struck the right balance between protection and practicality. We gained enterprise-grade security without sacrificing performance or stretching our budget. In the end, that meant more resources for what matters most: delivering care to our patients. If you’re facing similar challenges, I encourage you to consider how Darktrace could transform your security posture, and give your team the peace of mind they deserve.

For the organization I work in, combining Microsoft with Darktrace delivered a clear step-change in our security posture. Microsoft provided the foundation, while Darktrace’s behavioral intelligence added visibility into the unknown, surfacing emerging threats based on deviations in real-time activity, not just known indicators.

The result was enterprise-grade protection without added overhead, allowing us to stay focused on patient outcomes, not security operations. For organizations facing similar pressures, this layered approach offers a smarter, more efficient path to securing modern environments.

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Mice Chen
Chief Information Security Officer
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