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December 14, 2021

Log4Shell Vulnerability Detection & Response With Darktrace

Learn how Darktrace's AI detects and responds to Log4Shell attacks. Explore real-world examples and see how Darktrace identified and mitigated cyber threats.
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
Max Heinemeyer
Global Field CISO
Written by
Justin Fier
SVP, Red Team Operations
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14
Dec 2021

In this blog, we’ll take a look at the Log4Shell vulnerability and provide real-world examples of how Darktrace detects and responds to attacks attempting to leverage Log4Shell in the wild.

Log4Shell is now the well-known name for CVE-2021-44228 – a severity 10 zero-day exploiting a well-known Java logging utility known as Log4j. Vulnerabilities are discovered daily, and some are more severe than others, but the fact that this open source utility is nested into nearly everything, including the Mars Ingenuity drone, makes this that much more menacing. Details and further updates about Log4Shell are still emerging at the publication date of this blog.

Typically, zero-days with the power to reach this many systems are held close to the chest and only used by nation states for high value targets or operations. This one, however, was first discovered being used against Minecraft gaming servers, shared in chat amongst gamers.

While all steps should be taken to deploy mitigations to the Log4Shell vulnerability, these can take time. As evidenced here, behavioral detection can be used to look for signs of post-exploitation activity such as scanning, coin mining, lateral movement, and other activities.

Darktrace initially detected the Log4Shell vulnerability targeting one of our customers’ Internet-facing servers, as you will see in detail in an actual anonymized threat investigation below. This was highlighted and reported using Cyber AI Analyst, unpacked here by our SOC team. Please take note that this was using pre-existing algorithms without retraining classifiers or adjusting response mechanisms in reaction to Log4Shell cyber-attacks.

How Log4Shell works

The vulnerability works by taking advantage of improper input validation by the Java Naming and Directory Interface (JNDI). A command comes in from an HTTP user-agent, encrypted HTTPS connection, or even a chat room message, and the JNDI sends that to the target system in which it gets executed. Most libraries and applications have checks and protections in place to prevent this from happening, but as seen here, they get missed at times.

Various threat actors have started to leverage the vulnerability in attacks, ranging from indiscriminate crypto-mining campaigns to targeted, more sophisticated attacks.

Real-world example 1: Log4Shell exploited on CVE ID release date

Darktrace saw this first example on December 10, the same day the CVE ID was released. We often see publicly documented vulnerabilities being weaponized within days by threat actors. This attack hit an Internet-facing device in an organization’s demilitarized zone (DMZ). Darktrace had automatically classified the server as an Internet-facing device based on its behavior.

The organization had deployed Darktrace in the on-prem network as one of many coverage areas that include cloud, email and SaaS. In this deployment, Darktrace had good visibility of the DMZ traffic. Antigena was not active in this environment, and Darktrace was in detection-mode only. Despite this fact, the client in question was able to identify and remediate this incident within hours of the initial alert. The attack was automated and had the goal of deploying a crypto-miner known as Kinsing.

In this attack, the attacker made it harder to detect the compromise by encrypting the initial command injection using HTTPS over the more common HTTP seen in the wild. Despite this method being able to bypass traditional rules and signature-based systems Darktrace was able to spot multiple unusual behaviors seconds after the initial connection.

Initial compromise details

Through peer analysis Darktrace had previously learned what this specific DMZ device and its peer group normally do in the environment. During the initial exploitation, Darktrace detected various subtle anomalies that taken together made the attack obvious.

  1. 15:45:32 Inbound HTTPS connection to DMZ server from rare Russian IP — 45.155.205[.]233;
  2. 15:45:38 DMZ server makes new outbound connection to the same rare Russian IP using two new user agents: Java user agent and curl over a port that is unusual to serve HTTP compared to previous behavior;
  3. 15:45:39 DMZ server uses an HTTP connection with another new curl user agent (‘curl/7.47.0’) to the same Russian IP. The URI contains reconnaissance information from the DMZ server.

All this activity was detected not because Darktrace had seen it before, but because it strongly deviated from the regular ‘pattern of life’ for this and similar servers in this specific organization.

This server never reached out to rare IP addresses on the Internet, using user agents it never used before, over protocol and port combinations it never uses. Every point-in-time anomaly itself may have presented slightly unusual behavior – but taken together and analyzed in the context of this particular device and environment, the detections clearly tell a bigger story of an ongoing cyber-attack.

Darktrace detected this activity with various models, for example:

  • Anomalous Connection / New User Agent to IP Without Hostname
  • Anomalous Connection / Callback on Web Facing Device

Further tooling and crypto-miner download

Less than 90 minutes after the initial compromise, the infected server started downloading malicious scripts and executables from a rare Ukrainian IP 80.71.158[.]12.

The following payloads were subsequently downloaded from the Ukrainian IP in order:

  • hXXp://80.71.158[.]12//lh.sh
  • hXXp://80.71.158[.]12/Expl[REDACTED].class
  • hXXp://80.71.158[.]12/kinsing
  • hXXp://80.71.158[.]12//libsystem.so
  • hXXp://80.71.158[.]12/Expl[REDACTED].class

Using no threat intelligence or detections based on static indicators of compromise (IoC) such as IPs, domain names or file hashes, Darktrace detected this next step in the attack in real time.

The DMZ server in question never communicated with this Ukrainian IP address in the past over these uncommon ports. It is also highly unusual for this device and its peers to download scripts or executable files from this type of external destination, in this fashion. Shortly after these downloads, the DMZ server started to conduct crypto-mining.

Darktrace detected this activity with various models, for example:

  • Anomalous File / Script from Rare External Location
  • Anomalous File / Internet Facing System File Download
  • Device / Internet Facing System with High Priority Alert

Surfacing the Log4Shell incident immediately

In addition to Darktrace detecting each individual step of this attack in real time, Darktrace Cyber AI Analyst also surfaced the overarching security incident, containing a cohesive narrative for the overall attack, as the most high-priority incident within a week’s worth of incidents and alerts in Darktrace. This means that this incident was the most obvious and immediate item highlighted to human security teams as it unfolded. Darktrace’s Cyber AI Analyst found each stage of this incident and asked the very questions you would expect of your human SOC analysts. From the natural language report generated by the Cyber AI Analyst, a summary of each stage of the incident followed by the vital data points human analysts need, is presented in an easy to digest format. Each tab signifies a different part of this incident outlining the actual steps taken during each investigative process.

The result of this is no sifting through low-level alerts, no need to triage point-in-time detections, no putting the detections into a bigger incident context, no need to write a report. All of this was automatically completed by the AI Analyst saving human teams valuable time.

The below incident report was automatically created and could be downloaded as a PDF in various languages.

Figure 1: Darktrace’s Cyber AI Analyst surfaces multiple stages of the attack and explains its investigation process

Real-world example 2: Responding to a different attack using Log4Shell

On December 12, another organization’s Internet-facing server was initially compromised via Log4Shell. While the details of the compromise are different – other IoCs are involved – Darktrace detected and surfaced the attack similarly to the first example.

Interestingly, this organization had Darktrace Antigena in autonomous mode on their server, meaning the AI can take autonomous actions to respond to ongoing cyber-attacks. These responses can be delivered via a variety of mechanisms, for instance, API interactions with firewalls, other security tools, or native responses issued by Darktrace.

In this attack the rare external IP 164.52.212[.]196 was used for command and control (C2) communication and malware delivery, using HTTP over port 88, which was highly unusual for this device, peer group and organization.

Antigena reacted in real time in this organization, based on the specific context of the attack, without any human in the loop. Antigena interacted with the organization’s firewall in this case to block any connections to or from the malicious IP address – in this case 164.52.212[.]196 – over port 88 for 2 hours with the option of escalating the block and duration if the attack appears to persist. This is seen in the illustration below:

Figure 2: Antigena’s response

Here comes the trick: thanks to Self-Learning AI, Darktrace knows exactly what the Internet-facing server usually does and does not do, down to each individual data point. Based on the various anomalies, Darktrace is certain that this represents a major cyber-attack.

Antigena now steps in and enforces the regular pattern of life for this server in the DMZ. This means the server can continue doing whatever it normally does – but all the highly anomalous actions are interrupted as they occur in real time, such as speaking to a rare external IP over port 88 serving HTTP to download executables.

Of course the human can change or lift the block at any given time. Antigena can also be configured to be in human confirmation mode, having the human in the loop at certain times during the day (e.g. office hours) or at all times, depending on an organization’s needs and requirements.

Conclusion

This blog illustrates further aspects of cyber-attacks leveraging the Log4Shell vulnerability. It also demonstrates how Darktrace detects and responds to zero-day attacks if Darktrace has visibility of the attacked entities.

While Log4Shell is dominating the IT and security news, similar vulnerabilities have surfaced in the past and will appear in the future. We’ve spoken about our approach to detecting and responding to similar vulnerabilities and surrounding cyber-attacks before, for instance:

As always, companies should aim for a defense-in-depth strategy combining preventative security controls with detection and response mechanisms, as well as strong patch management.

Thanks to Brianna Leddy (Darktrace’s Director of Analysis) for her insights on the above threat find.

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
Max Heinemeyer
Global Field CISO
Written by
Justin Fier
SVP, Red Team Operations

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October 30, 2025

WSUS Exploited: Darktrace’s Analysis of Post-Exploitation Activities Related to CVE-2025-59287

WSUS Exploited: Darktrace’s Analysis of Post-Exploitation Activities Related to CVE-2025-59287Default blog imageDefault blog image

Introduction

On October 14, 2025, Microsoft disclosed a new critical vulnerability affecting the Windows Server Update Service (WSUS), CVE-2025-59287.  Exploitation of the vulnerability could allow an unauthenticated attacker to remotely execute code [1][6].

WSUS allows for centralized distribution of Microsoft product updates [3]; a server running WSUS is likely to have significant privileges within a network making it a valuable target for threat actors. While WSUS servers are not necessarily expected to be open to the internet, open-source intelligence (OSINT) has reported  thousands of publicly exposed instances that may be vulnerable to exploitation [2].

Microsoft’s initial ‘Patch Tuesday’ update for this vulnerability did not fully mitigate the risk, and so an out-of-band update followed on October 23 [4][5] . Widespread exploitation of this vulnerability started to be observed shortly after the security update [6], prompting CISA to add CVE-2025-59287 to its Known Exploited Vulnerability Catalog (KEV) on October 24 [7].

Attack Overview

The Darktrace Threat Research team have recently identified multiple potential cases of CVE-2025-59287 exploitation, with two detailed here. While the likely initial access method is consistent across the cases, the follow-up activities differed, demonstrating the variety in which such a CVE can be exploited to fulfil each attacker’s specific goals.

The first signs of suspicious activity across both customers were detected by Darktrace on October 24, the same day this vulnerability was added to CISA’s KEV. Both cases discussed here involve customers based in the United States.

Case Study 1

The first case, involving a customer in the Information and Communication sector, began with an internet-facing device making an outbound connection to the hostname webhook[.]site. Observed network traffic indicates the device was a WSUS server.

OSINT has reported abuse of the workers[.]dev service in exploitation of CVE-2025-59287, where enumerated network information gathered through running a script on the compromised device was exfiltrated using this service [8].

In this case, the majority of connectivity seen to webhook[.]site involved a PowerShell user agent; however, cURL user agents were also seen with some connections taking the form of HTTP POSTs. This connectivity appears to align closely with OSINT reports of CVE-2025-59287 post-exploitation behaviour [8][9].

Connections to webhook[.]site continued until October 26. A single URI was seen consistently until October 25, after which the connections used a second URI with a similar format.

Later on October 26, an escalation in command-and-control (C2) communication appears to have occurred, with the device starting to make repeated connections to two rare workers[.]dev subdomains (royal-boat-bf05.qgtxtebl.workers[.]dev & chat.hcqhajfv.workers[.]dev), consistent with C2 beaconing. While workers[.]dev is associated with the legitimate Cloudflare Workers service, the service is commonly abused by malicious actors for C2 infrastructure. The anomalous nature of the connections to both webhook[.]site and workers[.]dev led to Darktrace generating multiple alerts including high-fidelity Enhanced Monitoring alerts and alerts for Darktrace’s Autonomous Response.

Infrastructure insight

Hosted on royal-boat-bf05.qgtxtebl.workers[.]dev is a Microsoft Installer file (MSI) named v3.msi.

Screenshot of v3.msi content.
Figure 1: Screenshot of v3.msi content.

Contained in the MSI file is two Cabinet files named “Sample.cab” and “part2.cab”. After extracting the contents of the cab files, a file named “Config” and a binary named “ServiceEXE”. ServiceEXE is the legitimate DFIR tool Velociraptor, and “Config” contains the configuration details, which include chat.hcqhajfv.workers[.]dev as the server_url, suggesting that Velociraptor is being used as a tunnel to the C2. Additionally, the configuration points to version 0.73.4, a version of Velociraptor that is vulnerable to CVE-2025-6264, a privilege escalation vulnerability.

 Screenshot of Config file.
Figure 2: Screenshot of Config file.

Velociraptor, a legitimate security tool maintained by Rapid7, has been used recently in malicious campaigns. A vulnerable version of tool has been used by threat actors for command execution and endpoint takeover, while other campaigns have used Velociraptor to create a tunnel to the C2, similar to what was observed in this case [10] .

The workers[.]dev communication continued into the early hours of October 27. The most recent suspicious behavior observed on the device involved an outbound connection to a new IP for the network - 185.69.24[.]18/singapure - potentially indicating payload retrieval.

The payload retrieved from “/singapure” is a UPX packed Windows binary. After unpacking the binary, it is an open-source Golang stealer named “Skuld Stealer”. Skuld Stealer has the capabilities to steal crypto wallets, files, system information, browser data and tokens. Additionally, it contains anti-debugging and anti-VM logic, along with a UAC bypass [11].

A timeline outlining suspicious activity on the device alerted by Darktrace.
Figure 3: A timeline outlining suspicious activity on the device alerted by Darktrace.

Case Study 2

The second case involved a customer within the Education sector. The affected device was also internet-facing, with network traffic indicating it was a WSUS server

Suspicious activity in this case once again began on October 24, notably only a few seconds after initial signs of compromise were observed in the first case. Initial anomalous behaviour also closely aligned, with outbound PowerShell connections to webhook[.]site, and then later connections, including HTTP POSTs, to the same endpoint with a cURL user agent.

While Darktrace did not observe any anomalous network activity on the device after October 24, the customer’s security integration resulted in an additional alert on October 27 for malicious activity, suggesting that the compromise may have continued locally.

By leveraging Darktrace’s security integrations, customers can investigate activity across different sources in a seamless manner, gaining additional insight and context to an attack.

A timeline outlining suspicious activity on the device alerted by Darktrace.
Figure 4: A timeline outlining suspicious activity on the device alerted by Darktrace.

Conclusion

Exploitation of a CVE can lead to a wide range of outcomes. In some cases, it may be limited to just a single device with a focused objective, such as exfiltration of sensitive data. In others, it could lead to lateral movement and a full network compromise, including ransomware deployment. As the threat of internet-facing exploitation continues to grow, security teams must be prepared to defend against such a possibility, regardless of the attack type or scale.

By focussing on detection of anomalous behaviour rather than relying on signatures associated with a specific CVE exploit, Darktrace is able to alert on post-exploitation activity regardless of the kind of behaviour seen. In addition, leveraging security integrations provides further context on activities beyond the visibility of Darktrace / NETWORKTM, enabling defenders to investigate and respond to attacks more effectively.

With adversaries weaponizing even trusted incident response tools, maintaining broad visibility and rapid response capabilities becomes critical to mitigating post-exploitation risk.

Credit to Emma Foulger (Global Threat Research Operations Lead), Tara Gould (Threat Research Lead), Eugene Chua (Principal Cyber Analyst & Analyst Team Lead), Nathaniel Jones (VP, Security & AI Strategy, Field CISO),

Edited by Ryan Traill (Analyst Content Lead)

Appendices

References

1.        https://nvd.nist.gov/vuln/detail/CVE-2025-59287

2.    https://www.bleepingcomputer.com/news/security/hackers-now-exploiting-critical-windows-server-wsus-flaw-in-attacks/

3.    https://learn.microsoft.com/en-us/windows-server/administration/windows-server-update-services/get-started/windows-server-update-services-wsus

4.    https://www.cisa.gov/news-events/alerts/2025/10/24/microsoft-releases-out-band-security-update-mitigate-windows-server-update-service-vulnerability-cve

5.    https://msrc.microsoft.com/update-guide/vulnerability/CVE-2025-59287

6.    https://thehackernews.com/2025/10/microsoft-issues-emergency-patch-for.html

7.    https://www.cisa.gov/known-exploited-vulnerabilities-catalog

8.    https://www.huntress.com/blog/exploitation-of-windows-server-update-services-remote-code-execution-vulnerability

9.    https://unit42.paloaltonetworks.com/microsoft-cve-2025-59287/

10. https://blog.talosintelligence.com/velociraptor-leveraged-in-ransomware-attacks/

11. https://github.com/hackirby/skuld

Darktrace Model Detections

·       Device / New PowerShell User Agent

·       Anomalous Connection / Powershell to Rare External

·       Compromise / Possible Tunnelling to Bin Services

·       Compromise / High Priority Tunnelling to Bin Services

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

·       Device / New User Agent

·       Device / Internet Facing Device with High Priority Alert

·       Anomalous Connection / Multiple HTTP POSTs to Rare Hostname

·       Anomalous Server Activity / Rare External from Server

·       Compromise / Agent Beacon (Long Period)

·       Device / Large Number of Model Alerts

·       Compromise / Agent Beacon (Medium Period)

·       Device / Long Agent Connection to New Endpoint

·       Compromise / Slow Beaconing Activity To External Rare

·       Security Integration / Low Severity Integration Detection

·       Antigena / Network / Significant Anomaly / Antigena Alerts Over Time Block

·       Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Server Block

·       Antigena / Network / External Threat / Antigena Suspicious Activity Block

·       Antigena / Network / Significant Anomaly / Antigena Significant Server Anomaly Block

List of Indicators of Compromise (IoCs)

IoC - Type - Description + Confidence

o   royal-boat-bf05.qgtxtebl.workers[.]dev – Hostname – Likely C2 Infrastructure

o   royal-boat-bf05.qgtxtebl.workers[.]dev/v3.msi - URI – Likely payload

o   chat.hcqhajfv.workers[.]dev – Hostname – Possible C2 Infrastructure

o   185.69.24[.]18 – IP address – Possible C2 Infrastructure

o   185.69.24[.]18/bin.msi - URI – Likely payload

o   185.69.24[.]18/singapure - URI – Likely payload

The content provided in this blog is published by Darktrace for general informational purposes only and reflects our understanding of cybersecurity topics, trends, incidents, and developments at the time of publication. While we strive to ensure accuracy and relevance, the information is provided “as is” without any representations or warranties, express or implied. Darktrace makes no guarantees regarding the completeness, accuracy, reliability, or timeliness of any information presented and expressly disclaims all warranties.

Nothing in this blog constitutes legal, technical, or professional advice, and readers should consult qualified professionals before acting on any information contained herein. Any references to third-party organizations, technologies, threat actors, or incidents are for informational purposes only and do not imply affiliation, endorsement, or recommendation.

Darktrace, its affiliates, employees, or agents shall not be held liable for any loss, damage, or harm arising from the use of or reliance on the information in this blog.

The cybersecurity landscape evolves rapidly, and blog content may become outdated or superseded. We reserve the right to update, modify, or remove any content

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About the author
Emma Foulger
Global Threat Research Operations Lead

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October 24, 2025

Patch Smarter, Not Harder: Now Empowering Security Teams with Business-Aligned Threat Context Agents

Patch Smarter, Not Harder: Now Empowering Security Teams with Business-Aligned Threat Context Agents Default blog imageDefault blog image

Most risk management programs remain anchored in enumeration: scanning every asset, cataloging every CVE, and drowning in lists that rarely translate into action. Despite expensive scanners, annual pen tests, and countless spreadsheets, prioritization still falters at two critical points.

Context gaps at the device level: It’s hard to know which vulnerabilities actually matter to your business given existing privileges, what software it runs, and what controls already reduce risk.

Business translation: Even when the technical priority is clear, justifying effort and spend in financial terms—especially across many affected devices—can delay action. Especially if it means halting other areas of the business that directly generate revenue.

The result is familiar: alert fatigue, “too many highs,” and remediation that trails behind the threat landscape. Darktrace / Proactive Exposure Management addresses this by pairing precise, endpoint‑level context with clear, financial insight so teams can prioritize confidently and mobilize faster.

A powerful combination: No-Telemetry Endpoint Agent + Cost-Benefit Analysis

Darktrace / Proactive Exposure Management now uniquely combines technical precision with business clarity in a single workflow.  With this release, Darktrace / Proactive Exposure Management delivers a more holistic approach, uniting technical context and financial insight to drive proactive risk reduction. The result is a single solution that helps security teams stay ahead of threats while reducing noise, delays, and complexity.

  • No-Telemetry Endpoint: Collects installed software data and maps it to known CVEs—without network traffic—providing device-level vulnerability context and operational relevance.
  • Cost-Benefit Analysis for Patching: Calculates ROI by comparing patching effort with potential exploit impact, factoring in headcount time, device count, patch difficulty, and automation availability.

Introducing the No-Telemetry Endpoint Agent

Darktrace’s new endpoint agent inventories installed software on devices and maps it to known CVEs without collecting network data so you can prioritize using real device context and available security controls.

By grounding vulnerability findings in the reality of each endpoint, including its software footprint and existing controls, teams can cut through generic severity scores and focus on what matters most. The agent is ideal for remote devices, BYOD-adjacent fleets, or environments standardizing on Darktrace, and is available without additional licensing cost.

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

Built-In Cost-Benefit Analysis for Patching

Security teams often know what needs fixing but stakeholders need to understand why now. Darktrace’s new cost-benefit calculator compares the total cost to patch against the potential cost of exploit, producing an ROI for the patch action that expresses security action in clear financial terms.

Inputs like engineer time, number of affected devices, patch difficulty, and automation availability are factored in automatically. The result is a business-aligned justification for every patching decision—helping teams secure buy-in, accelerate approvals, and move work forward with one-click ticketing, CSV export, or risk acceptance.

Darktrace / Proactive Exposure Management Cost Benefit Analysis
Figure 2: Darktrace / Proactive Exposure Management Cost Benefit Analysis

A Smarter, Faster Approach to Exposure Management

Together, the no-telemetry endpoint and Cost–Benefit Analysis advance the CTEM motion from theory to practice. You gain higher‑fidelity discovery and validation signals at the device level, paired with business‑ready justification that accelerates mobilization. The result is fewer distractions, clearer priorities, and faster measurable risk reduction. This is not from chasing every alert, but by focusing on what moves the needle now.

  • Smarter Prioritization: Device‑level context trims noise and spotlights the exposures that matter for your business.
  • Faster Decisions: Built‑in ROI turns technical urgency into executive clarity—speeding approvals and action.
  • Practical Execution: Privacy‑conscious endpoint collection and ticketing/export options fit neatly into existing workflows.
  • Better Outcomes: Close the loop faster—discover, prioritize, validate, and mobilize—on the same operating surface.

Committed to innovation

These updates are part of the broader Darktrace release, which also included:

1. Major innovations in cloud security with the launch of the industry’s first fully automated cloud forensics solution, reinforcing Darktrace’s leadership in AI-native security.

2. Darktrace Network Endpoint eXtended Telemetry (NEXT) is revolutionizing NDR with the industry’s first mixed-telemetry agent using Self-Learning AI.

3. Improvements to our OT product, purpose built for industrial infrastructure, Darktrace / OT now brings dedicated OT dashboard, segmentation-aware risk modeling, and expanded visibility into edge assets and automation protocols.

Join our Live Launch Event

When? 

December 9, 2025

What will be covered?

Join our live broadcast to experience how Darktrace is eliminating blind spots for detection and response across your complete enterprise with new innovations in Agentic AI across our ActiveAI Security platform. Industry leaders from IDC will join Darktrace customers to discuss challenges in cross-domain security, with a live walkthrough reshaping the future of Network Detection & Response, Endpoint Detection & Response, Email Security, and SecOps in novel threat detection and autonomous investigations.

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Kelland Goodin
Product Marketing Specialist
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