Blog
/
Network
/
December 20, 2023

Ivanti Sentry Vulnerability | Analysis & Insights

Darktrace observed a critical vulnerability in Ivanti Sentry's cybersecurity. Learn how this almost become a huge threat and how we stopped it in its tracks.
Written by
Sam Lister
Specialist Security Researcher
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Sam Lister
Specialist Security Researcher
Default blog image
20
Dec 2023

In an increasingly interconnected digital landscape, the prevalence of critical vulnerabilities in internet-facing systems stands as an open invitation to malicious actors. These vulnerabilities serve as a near limitless resource, granting attackers a continually array of entry points into targeted networks.

In the final week of August 2023, Darktrace observed malicious actors validating exploits for one such critical vulnerability, likely the critical RCE vulnerability, CVE-2023-38035, on Ivanti Sentry servers within multiple customer networks. Shortly after these successful tests were carried out, malicious actors were seen delivering crypto-mining and reconnaissance tools onto vulnerable Ivanti Sentry servers.

Fortunately, Darktrace DETECT™ was able to identify this post-exploitation activity on the compromised servers at the earliest possible stage, allowing the customer security teams to take action against affected devices. In environments where Darktrace RESPOND™ was enabled in autonomous response mode, Darktrace was further able inhibit the identified post-exploitation activity and stop malicious actors from progressing towards their end goals.

Exploitation of Vulnerabilities in Ivanti Products

The software provider, Ivanti, offers a variety of widely used endpoint management, service management, and security solutions. In July and August 2023, the Norwegian cybersecurity company, Mnemonic, disclosed three vulnerabilities in Ivanti products [1]/[2]/[3]; two in Ivanti's endpoint management solution, Ivanti Endpoint Manager Mobile (EPMM) (formerly called 'MobileIron Core'), and one in Ivanti’s security gateway solution, Ivanti Sentry (formerly called 'MobileIron Sentry'):

CVE-2023-35078

  • CVSS Score: 10.0
  • Affected Product: Ivanti EPMM
  • Details from Ivanti: [4]/[5]/[6]
  • Vulnerability type: Authentication bypass

CVE-2023-35081

  • CVSS Score: 7.2
  • Affected Product: Ivanti EPMM
  • Details from Ivanti: [7]/[8]/[9]
  • Vulnerability type: Directory traversal

CVE-2023-38035

  • CVSS Score:
  • Affected Product: Ivanti Sentry
  • Details from Ivanti: [10]/[11]/[12]
  • Vulnerability type: Authentication bypass

At the beginning of August 2023, the Cybersecurity and Infrastructure Security Agency (CISA) and the Norwegian National Cyber Security Centre (NCSC-NO) provided details of advanced persistent threat (APT) activity targeting EPMM systems within Norwegian private sector and government networks via exploitation of CVE-2023-35078 combined with suspected exploitation of CVE-2023-35081.

In an article published in August 2023 [12], Ivanti disclosed that a very limited number of their customers had been subjected to exploitation of the Ivanti Sentry vulnerability, CVE-2023-38035, and on the August 22, 2023, CISA added the Ivanti Sentry vulnerability, CVE-2023-38035 to its ‘Known Exploited Vulnerabilities Catalogue’.  CVE-2023-38035 is a critical authentication bypass vulnerability affecting the System Manager Portal of Ivanti Sentry systems. The System Manager Portal, which is accessible by default on port 8433, is used for administration of the Ivanti Sentry system. Through exploitation of CVE-2023-38035, an unauthenticated actor with access to the System Manager Portal can achieve Remote Code Execution (RCE) on the underlying Ivanti Sentry system.

Observed Exploitation of CVE-2023-38035

On August 24, Darktrace observed Ivanti Sentry servers within several customer networks receiving successful SSL connections over port 8433 from the external endpoint, 34.77.65[.]112. The usage of port 8433 indicates that the System Manager Portal was accessed over the connections. Immediately after receiving these successful connections, Ivanti Sentry servers made GET requests over port 4444 to 34.77.65[.]112. The unusual string ‘Wget/1.14 (linux-gnu)’ appeared in the User-Agent headers of these requests, indicating that the command-line utility, wget, was abused to initiate the requests.

Figure 1: Event Log data for an Ivanti Sentry system showing the device breaching a range of DETECT models after contacting 34.77.65[.]112.The suspicious behavior highlighted by DETECT was subsequently investigated by Darktrace’s Cyber AI Analyst™, which was able to weave together these separate behaviors into single incidents representing the whole attack chain.

‍

Figure 2: AI Analyst Incident representing a chain of suspicious activities from an Ivanti Sentry server.

In cases where Darktrace RESPOND was enabled in autonomous response mode, RESPOND was able to automatically enforce the Ivanti Sentry server’s normal pattern of life, thus blocking further exploit testing.

Figure 3: Event Log for an Ivanti Sentry server showing the device receiving a RESPOND action immediately after trying to 34.77.65[.]112.

The GET requests to 34.77.65[.]112 were responded to with the following HTML document:

Figure 4: Snapshot of the HTML document returned by 34.77.65[.]112.

None of the links within this HTML document were functional. Furthermore, the devices’ downloads of these HTML documents do not appear to have elicited further malicious activities. These facts suggest that the observed 34.77.65[.]112 activities were representative of a malicious actor validating exploits (likely for CVE-2023-38035) on Ivanti Sentry systems.

Over the next 24 hours, these Ivanti Sentry systems received successful SSL connections over port 8433 from a variety of suspicious external endpoints, such as 122.161.66[.]161. These connections resulted in Ivanti Sentry systems making HTTP GET requests to subdomains of ‘oast[.]site’ and ‘oast[.]live’. Strings containing ‘curl’ appeared in the User-Agent headers of these requests, indicating that the command-line utility, cURL, was abused to initiate the requests.

These ‘oast[.]site’ and ‘oast[.]live’ domains are used by the out-of-band application security testing (OAST) service, Interactsh. Malicious actors are known to abuse this service to carry out out-of-band (OOB) exploit testing. It, therefore, seems likely that these activities were also representative of a malicious actor validating exploits for CVE-2023-38035 on Ivanti Sentry systems.

Figure 5: Event Log for Ivanti Sentry system showing the device contacting an 'oast[.]site' endpoint after receiving connections from the suspicious, external endpoint 122.161.66[.]161.

The actors seen validating exploits for CVE-2023-38035 may have been conducting such activities in preparation for their own subsequent malicious activities. However, given the variety of attack chains which ensued from these exploit validation activities, it is also possible that they were carried out by Initial Access Brokers (IABs) The activities which ensued from exploit validation activities identified by Darktrace fell into two categories: internal network reconnaissance and cryptocurrency mining.

Reconnaissance Activities

In one of the reconnaissance cases, immediately after receiving successful SSL connections over port 8443 from the external endpoints 190.2.131[.]204 and 45.159.248[.]179, an Ivanti Sentry system was seen making a long SSL connection over port 443 to 23.92.29[.]148, and making wget GET requests over port 4444 with the Target URIs '/ncat' and ‘/TxPortMap’ to the external endpoints, 45.86.162[.]147 and 195.123.240[.]183.  

Figure 6: Event Log data for an Ivanti Sentry system showing the device making connections to the external endpoints, 45.86.162[.]147, 23.92.29[.]148, and 195.123.240[.]183, immediately after receiving connections from rare external endpoints.

The Ivanti Sentry system then went on to scan for open SMB ports on systems within the internal network. This activity likely resulted from an attacker dropping a port scanning utility on the vulnerable Ivanti Sentry system.

Figure 7: Event Log data for an Ivanti Sentry server showing the device breaching several DETECT models after downloading a port scanning tool from 195.123.240[.]183.

In another reconnaissance case, Darktrace observed multiple wget HTTP requests with Target URIs such as ‘/awp.tar.gz’ and ‘/resp.tar.gz’ to a suspicious, external server (78.128.113[.]130).  Shortly after making these requests, the Ivanti Sentry system started to scan for open SMB ports and to respond to LLMNR queries from other internal devices. These behaviors indicate that the server may have installed an LLMNR poisoning tool, such as Responder. The Ivanti Sentry server also went on to conduct further information-gathering activities, such as LDAP reconnaissance, HTTP-based vulnerability scanning, HTTP-based password searching, and RDP port scanning.

Figure 8: Event Log data for an Ivanti Sentry system showing the device making connections to 78.128.113[.]130, scanning for an open SMB port on internal endpoints, and responding to LLMNR queries from internal endpoints.

In cases where Darktrace RESPOND was active, reconnaissance activities resulted in RESPOND enforcing the Ivanti Sentry server’s pattern of life.

Figure 9: Event Log data for an Ivanti Sentry system receiving a RESPOND action as a result of its SMB port scanning activity.
Figure 10: Event Log data for an Ivanti Sentry system receiving a RESPOND action as a result of its LDAP reconnaissance activity.

Crypto-Mining Activities

In one of the cryptomining cases, Darktrace detected an Ivanti Sentry server making SSL connections to aelix[.]xyz and mining pool endpoints after receiving successful SSL connections over port 8443 from the external endpoint, 140.228.24[.]160.

Figure 11: Event Log data for an Ivanti Sentry system showing the device contacting aelix[.]xyz and mining pool endpoints immediately after receiving connections from the external endpoint, 140.228.24[.]160.

In a cryptomining case on another customer’s network, an Ivanti Sentry server was seen making GET requests indicative of Kinsing malware infection. These requests included wget GET requests to 185.122.204[.]197 with the Target URIs ‘/unk.sh’ and ‘/se.sh’ and a combination of GET and POST requests to 185.221.154[.]208 with the User-Agent header ‘Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.51 Safari/537.36’ and the Target URIs, ‘/mg’, ‘/ki’, ‘/get’, ‘/h2’, ‘/ms’, and ‘/mu’. These network-based artefacts have been observed in previous Kinsing infections [13].

Figure 12: Event Log data for an Ivanti Sentry system showing the device displaying likely Kinsing C2 activity.

On customer environments where RESPOND was active, Darktrace was able to take swift autonomous action by blocking cryptomining connection attempts to malicious command-and-control (C2) infrastructure, in this case Kinsing servers.

Figure 13: Event Log data for an Ivanti Sentry server showing the device receiving a RESPOND action after attempting to contact Kinsing C2 infrastructure.

Fortunately, due to Darktrace DETECT+RESPOND prompt identification and targeted actions against these emerging threats, coupled with remediating steps taken by affected customers’ security teams, neither the cryptocurrency mining activities nor the network reconnaissance activities led to significant disruption.  

Figure 14: Timeline of observed malicious activities.

Conclusion The inevitable presence of critical vulnerabilities in internet-facing systems underscores the perpetual challenge of defending against malicious intrusions. The near inexhaustible supply of entry routes into organizations’ networks available to malicious actors necessitates a more proactive and vigilant approach to network security.

While it is, of course, essential for organizations to secure their digital environments through the regular patching of software and keeping abreast of developing vulnerabilities that could impact their network, it is equally important to have a safeguard in place to mitigate against attackers who do manage to exploit newly discovered vulnerabilities.

In the case of Ivanti Sentry, Darktrace observed malicious actors validating exploits against affected servers on customer networks just a few days after the public disclosure of the critical vulnerability.  This activity was followed up by a variety of malicious and disruptive, activities including cryptocurrency mining and internal network reconnaissance.

Darktrace DETECT immediately detected post-exploitation activities on compromised Ivanti Sentry servers, enabling security teams to intervene at the earliest possible stage. Darktrace RESPOND, when active, autonomously inhibited detected post-exploitation activities. These DETECT detections, along with their accompanying RESPOND interventions, prevented malicious actors from being able to progress further towards their likely harmful objectives.

Credit to Sam Lister, Senior Cyber Analyst, and Trent Kessler, SOC Analyst  

‍

Appendices

MITRE ATT&CK Mapping

Initial Access techniques:

  • Exploit Public-Facing Application (T1190)

Credential Access techniques:

  • Unsecured Credentials: Credentials In Files (T1552.001)
  • Adversary-in-the-Middle: LLMNR/NBT-NS Poisoning and SMB Relay (T1557.001)

Discovery

  • Network Service Discovery (T1046)
  • Remote System Discovery (T1018)
  • Account Discovery: Domain Account (T1087.002)

Command and Control techniques:

  • Application Layer Protocol: Web Protocols (T1071.001)
  • Ingress Tool Transfer (T1105)
  • Non-Standard Port (T1571)
  • Encrypted Channel: Asymmetric Cryptography (T1573.002)

Impact techniques

  • Resource Hijacking (T1496)
List of IoCs

Exploit testing IoCs:

·      34.77.65[.]112

·      Wget/1.14 (linux-gnu)

·      cjjovo7mhpt7geo8aqlgxp7ypod6dqaiz.oast[.]site • 178.128.16[.]97

·      curl/7.19.7 (x86_64-redhat-linux-gnu) libcurl/7.19.7 NSS/3.27.1 zlib/1.2.3 libidn/1.18 libssh2/1.4.2

·      cjk45q1chpqflh938kughtrfzgwiofns3.oast[.]site • 178.128.16[.]97

·      curl/7.29.0

Kinsing-related IoCs:

·      185.122.204[.]197

·      /unk.sh

·      /se.sh

·      185.221.154[.]208

·      185.221.154[.]208

·      45.15.158[.]124

·      Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.51 Safari/537.36

·      /mg

·      /ki

·      /get

·      /h2

·      /ms

·      /mu

·      vocaltube[.]ru • 185.154.53[.]140

·      92.255.110[.]4

·      194.87.254[.]160

Responder-related IoCs:

·      78.128.113[.]130

·      78.128.113[.]34

·      /awp.tar.gz

·      /ivanty

·      /resp.tar.gz

Crypto-miner related IoCs:

·      140.228.24[.]160

·      aelix[.]xyz • 104.21.60[.]147 / 172.67.197[.]200

·      c8446f59cca2149cb5f56ced4b448c8d (JA3 client fingerprint)

·      b5eefe582e146aed29a21747a572e11c (JA3 client fingerprint)

·      pool.supportxmr[.]com

·      xmr.2miners[.]com

·      xmr.2miners[.]com

·      monerooceans[.]stream

·      xmr-eu2.nanopool[.]org

Port scanner-related IoCs:

·      122.161.66[.]161

·      192.241.235[.]32

·      45.86.162[.]147

·      /ncat

·      Wget/1.14 (linux-gnu)

·      45.159.248[.]179

·      142.93.115[.]146

·      23.92.29[.]148

·      /TxPortMap

·      195.123.240.183

·      6935a8d379e086ea1aed159b8abcb0bc8acf220bd1cbc0a84fd806f14014bca7 (SHA256 hash of downloaded file)

Darktrace DETECT Model Breaches

·      Anomalous Server Activity / New User Agent from Internet Facing System

·      Device / New User Agent

·      Anomalous Connection / New User Agent to IP Without Hostname

·      Device / New User Agent and New IP

·      Anomalous Connection / Application Protocol on Uncommon Port

·      Anomalous Connection / Callback on Web Facing Device

·      Compromise / High Volume of Connections with Beacon Score

·      Compromise / Large Number of Suspicious Failed Connections

·      Compromise / High Volume of Connections with Beacon Score

·      Compromise / Beacon for 4 Days

·      Compromise / Agent Beacon (Short Period)

·      Device / Large Number of Model Breaches

·      Anomalous Server Activity / Rare External from Server

·      Compromise / Large Number of Suspicious Successful Connections

·      Compromise / Monero Mining

·      Compromise / High Priority Crypto Currency Mining

·      Compromise / Sustained TCP Beaconing Activity To Rare Endpoint

·      Device / Internet Facing Device with High Priority Alert

·      Device / Suspicious SMB Scanning Activity

·      Device / Internet Facing Device with High Priority Alert

·      Device / Network Scan

·      Device / Unusual LDAP Bind and Search Activity

·      Compliance / Vulnerable Name Resolution

·      Device / Anomalous SMB Followed By Multiple Model Breaches

·      Device / New User Agent To Internal Server

·      Anomalous Connection / Suspicious HTTP Activity

·      Anomalous Connection / Unusual Internal Connections

·      Anomalous Connection / Suspicious HTTP Activity

·      Device / RDP Scan

·      Device / Large Number of Model Breaches

·      Compromise / Beaconing Activity To External Rare

·      Compromise / Beacon to Young Endpoint

·      Anomalous Connection / Suspicious HTTP Activity

·      Compromise / Suspicious Internal Use Of Web Protocol

·      Anomalous File / EXE from Rare External Location

·      Anomalous File / Internet Facing System File Download

·      Device / Suspicious SMB Scanning Activity

·      Device / Internet Facing Device with High Priority Alert

·      Device / Network Scan

·      Device / Initial Breach Chain Compromise

References

[1] https://www.mnemonic.io/resources/blog/ivanti-endpoint-manager-mobile-epmm-authentication-bypass-vulnerability/
‍[2] https://www.mnemonic.io/resources/blog/threat-advisory-remote-file-write-vulnerability-in-ivanti-epmm/
‍[3] https://www.mnemonic.io/resources/blog/threat-advisory-remote-code-execution-vulnerability-in-ivanti-sentry/
‍[4] https://www.ivanti.com/blog/cve-2023-35078-new-ivanti-epmm-vulnerability
‍[5] https://forums.ivanti.com/s/article/CVE-2023-35078-Remote-unauthenticated-API-access-vulnerability?language=en_US
‍[6] https://forums.ivanti.com/s/article/KB-Remote-unauthenticated-API-access-vulnerability-CVE-2023-35078?language=en_US
‍[7] https://www.ivanti.com/blog/cve-2023-35081-new-ivanti-epmm-vulnerability
‍[8] https://forums.ivanti.com/s/article/CVE-2023-35081-Arbitrary-File-Write?language=en_US
‍[9] https://forums.ivanti.com/s/article/KB-Arbitrary-File-Write-CVE-2023-35081?language=en_US
‍[10] https://www.ivanti.com/blog/cve-2023-38035-vulnerability-affecting-ivanti-sentry
‍[11] https://forums.ivanti.com/s/article/CVE-2023-38035-API-Authentication-Bypass-on-Sentry-Administrator-Interface?language=en_US
‍[12] https://forums.ivanti.com/s/article/KB-API-Authentication-Bypass-on-Sentry-Administrator-Interface-CVE-2023-38035?language=en_US
‍[13] https://isc.sans.edu/diary/Your+Business+Data+and+Machine+Learning+at+Risk+Attacks+Against+Apache+NiFi/29900

Written by
Sam Lister
Specialist Security Researcher
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Sam Lister
Specialist Security Researcher

From Click to Command: Behavioral Detection of AppleScript-Led MacOS Intrusions

Network
•
June 24, 2026
Justin Torres
Cyber Analyst
Watch the NIS2 Webinar
Trending blogs
1
Prompt Security in Enterprise AI: Strengths, Weaknesses, and Common Approaches
May 20, 2026
2
What the Darktrace Annual Threat Report 2026 Means for Security Leaders
Feb 26, 2026
3
Journey of a Threat: How Multi-Layered AI Works in Darktrace / EMAIL
May 26, 2026
4
How to Evaluate AI Vendors: 5 Key categories for AI Adoption
May 27, 2026
5
Darktrace Unites Human Behavior and Threat Detection Across Email, Slack, Teams, and Zoom
Mar 24, 2026

More in this series

No items found.
Continue reading
Network
•
June 24, 2026

From Click to Command: Behavioral Detection of AppleScript-Led MacOS Intrusions

Darktrace researchers analyze a recurring macOS intrusion pattern leveraging ClickFix-style social engineering and AppleScript post-compromise activity. By correlating weak behavioral signals such as HTTP POST beaconing, rare destinations, and SSL anomalies, defenders can detect and disrupt command-and-control activity before sustained attacker control is established.
Justin Torres
Cyber Analyst
Read more
Network
•
June 15, 2026

Hola VPN Abuse: From Proxy Traffic to Malware and Cryptomining

Darktrace’s analysis of Hola VPN-related activity across multiple environments reveals how peer-to-peer proxy functionality can enable malware delivery, command-and-control traffic, and cryptomining. Darktrace data highlights consistent patterns, suspicious downloads from rare endpoints, and post-compromise behavior, demonstrating how seemingly benign software can obscure threats and facilitate further malicious activity.
Min Kim
Cyber Security Analyst
Read more
Network
•
June 10, 2026

How Attackers Abuse the Chinese Nezha Monitoring Tool

This blog examines how attackers abuse the Chinese-developed Nezha monitoring tool, a legitimate open-source platform with remote access capabilities. Darktrace analysis of a honeypot intrusion highlights malicious deployment via containers, demonstrating how dual-use software enables stealthy operations, trust inversion, and detection challenges in dynamic cloud and enterprise environments modern.
Nathaniel Bill
Malware Research Engineer
Read more

Blog

/

Email

/

June 26, 2026

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

Default blog imageDefault blog image

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.

Continue reading
About the author
Mice Chen
Chief Information Security Officer

Blog

/

AI

/

June 25, 2026

Shadow AI Detection: The First Step Toward Securing AI

shadow aiDefault blog imageDefault blog image

Why shadow AI is emerging  

Imagine you’re an employee under pressure, deadlines stacking up, repetitive tasks piling higher by the day. You find a free AI tool online that promises to automate the work in seconds; no approvals are needed. It feels like a simple win, paste in some data, write a quick prompt, and move faster.

But in that moment, something changed.  

Sensitive customer information is entered into a tool your organization doesn’t monitor, doesn’t govern, and can’t see and suddenly, that data is no longer where it should be, and no one knows where it’s gone.

This is the reality of Shadow AI: employees using unsanctioned AI tools to move faster, while unintentionally creating risk that exists entirely outside visibility and control.  

This is not just a one off case, research across businesses indicate that nearly half of employees report using unsanctioned AI tools, often prioritizing speed and productivity over security. Additionally, 51% of employees report connecting AI tools to work systems or apps without IT approval, creating significant operational risk where the average cost of security incidents in organizations with a high level of shadow AI usage can reach $670k.

While shadow AI is often top of mind for security professionals, it is just one component of how AI use can increase risk. Understanding and managing shadow AI use should be considered as part of a broader, comprehensive risk management strategy that aims to secure AI systems, including human and agent identities, interactions, human-AI partnerships, and behaviors operating across the digital enterprise from visibility and governance through detection, response, and recovery.  

Effective risk management calls for a layered and interdisciplinary strategy. It requires addressing issues across governance and visibility; identity, access and agent control, data security and privacy, secure MLOps / LLMOps, runtime security, behavior-based detection, autonomous response and recovery.  

This blog explores a specific governance and visibility use case linked to shadow AI and reveals the challenges it presents as well as the defensive strategies that security teams can adopt.

Why shadow AI is hard to detect  

When it comes to AI, what organizations can easily see does not always reflect the full scope of AI activity occurring within the tools, applications, and workflows used across an enterprise. As a result, organizations using traditional rule-based methods to flag unusual activity may struggle to distinguish unsanctioned AI usage from legitimate operational behavior, particularly as SaaS applications, APIs, and orchestration layers increasingly have AI embedded into normal business workflows. Identifying threats using previously observed intelligence or depending on hard to maintain allow and block lists does not provide a dynamic enough strategy to manage risk. Also, many organizations are focusing on identifying Shadow AI in their governed infrastructure, like gateways, endpoints, or SASE, which is foundational. But, organizations require visibility and Shadow AI detection across all networked infrastructure from on-prem, hybrid, data centers, and cloud infrastructure that may not have endpoint agent visibility. This uncovers the utilization of MCP, data flows, and autonomous agents across these domains.

For example, employees interact with AI assistants across approved SaaS platforms every day. However, browser extensions and other types of plug-ins can route prompts that include enterprise data to embedded AI services in ways that are not visible to the security team. AI enabled workflows may invoke multiple APIs, orchestration layers, and cloud services behind the scenes, making it difficult for traditional security tooling to determine where data is processed, stored, or retransmitted. Because much of this activity occurs within trusted browser sessions and encrypted SaaS traffic, conventional network monitoring, DLP, and application allowlisting controls often lack the context needed to accurately identify or govern these interactions

Identifying AI tools in the environment is one part of the equation. Understanding the behavior surrounding their use is where the real challenge lies. An AI application is not inherently risky, but the way users or other assets interact with it may be. Sensitive data exposure, abnormal access patterns, and misuse of AI-assisted workflows often appear legitimate in isolation and only become visible through behavioral analysis across the broader environment.  

What Shadow AI visibility does and doesn’t show

Comprehensive Shadow AI visibility allows organizations to answer several important questions:

  • What types of AI are we using? What AI platforms, agents, MCP clients/servers, and services are active across the enterprise?  
  • Who is using AI services? Which users, business units, or systems are interacting with those AI services?  
  • Is our data safe? Is sensitive or regulated data being exposed through prompts, workflows, or integrations?  
  • Are AI systems behaving as expected? Are AI systems behaving anomalously or operating outside approved governance processes?  
  • Are our AI systems under attack? Is an attacker attempting to manipulate prompts, influence agent behavior, or abuse AI-enabled workflows?

Answering these questions is foundational to broader AI governance efforts. However, it is limited to helping teams understand initial interactions and fails to offer insight into dependencies and outcomes that are critical to securing AI across an enterprise.  

Deeper visibility that includes the ability to understand dependencies and outcomes are not always available in AI security point products. Answering the questions below requires understanding runtime behavior and operational outcomes:  

  • What actions did the AI interaction trigger?  
  • What systems, applications, or data did it access? Did the AI operate beyond its intended permissions or scope?  
  • Could a low-risk interaction lead to high-risk outcomes?  
  • What is the risk and context understanding of an anomalous activity to assist in prioritization of analysis and autonomous response action?

The distinction between these two sets of questions offers two different layers of AI security. The first set of questions focuses on discovery and interaction visibility. The second set focuses on providing visibility that includes the context and outcomes that are critical for managing follow-on risks associated with obfuscated downstream activities.  

Together, these layers help organizations move beyond simply identifying AI usage toward understanding how AI behaves operationally across the enterprise.

How organizations are addressing shadow AI

Most organizations still approach shadow AI as an application control problem, relying on policies, browser restrictions, and allow/block lists. However, AI adoption is evolving faster than most governance processes can realistically keep pace with. New assistants, plugins, and embedded AI features appear continuously, creating pressure to enable business productivity while simultaneously containing risk.  

Existing governance processes were designed for a more traditional SaaS adoption cycle, where new applications could be reviewed, approved, and monitored over longer time horizons. AI adoption operates differently. New capabilities can appear overnight inside existing platforms employees already use, making it difficult for security and governance teams to maintain an accurate understanding of enterprise AI exposure. This means that many organizations are experiencing significant operational overhead, particularly in large environments where AI usage is decentralized across teams, departments, and third-party services.  

Where should organizations start when securing their AI systems?

Shadow AI identification is an on-going critical component for AI Risk/Governance Boards as well as security organizations. As organizations seek AI certifications like ISO 42001 AI Management Systems, visibility into all AI adoption from enterprise use to custom innovation and development is crucial. Shadow AI identification provides organizations with the visibility needed to decide whether an AI tool should be brought into governed environments to reduce data loss (DLP) risks or whether policies should be established and enforced to restrict their use.

As organizations rapidly innovate and adopt AI, they are taking on more and more risk. Organizations need to have a strategy in place to mitigate the assumed risk, especially with third-party adoption. Visibility, monitoring, governance enforcement, behavioral-based detection of non-deterministic systems, and autonomous investigation and containment becomes critical to mitigating the risk of AI systems.  

How Darktrace secures AI and shadow AI

Attackers are using AI to move faster, scale tactics, and make threats more adaptive and convincing. Internally, organizations are grappling with new forms of risk created by generative AI, autonomous agents, shadow AI, and increasingly complex digital environments.

Darktrace helps organizations protect both people and AI in a world where AI is now central to how business gets done. Darktrace / SECURE AI helps organizations discover and control shadow AI by surfacing unsanctioned or unexpected AI activity where it appears – including MCP detections, distinguishing misuse of legitimate tools and unapproved services, and applying policy to contain data exposure while guiding users toward sanctioned options.

Stay up to date on AI security

Sign up for the Secure AI Readiness Program here: This gives you exclusive access to the latest news on the latest AI threats, updates on emerging approaches shaping AI security, and insights into the latest innovations, including Darktrace’s ongoing work in this area.

Ready to talk with a Darktrace expert on securing AI? Register here to receive practical guidance on the AI risks that matter most to your business, paired with clarity on where to focus first across governance, visibility, risk reduction, and long-term readiness.  

Continue reading
About the author
Nicole Carignan
SVP, Security & AI Strategy, Field CISO
Your data. Our AI.
Elevate your network security with Darktrace AI