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May 23, 2025

Defending the Frontlines: Proactive Cybersecurity in Local Government

To quickly identify and respond to threats before damage occurs, this local government relies on Darktrace to improve network visibility, stop insider threats, protect its email systems, and accelerate incident investigations.
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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.
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May 2025

Serving a population of over 165,000 citizens, this county government delivers essential services that enhance the quality of life for all of its residents in Florida, United States. From public safety and works to law enforcement, economic development, health, and community services, the county’s cybersecurity strategy plays a foundational role in protecting its citizens.

From flying blind to seeing the bigger picture

Safeguarding data from multiple systems, service providers, and citizens is a key aspect of the County’s Systems Management remit. Protecting sensitive information while enabling smooth engagement with multiple external partners poses a unique challenge; the types of data and potential threats are continuously evolving, but resources – both human and financial – remain consistently tight.

When the Chief Information Officer took on his role in 2024, building out a responsive defense-in-depth strategy was central to achieving these goals. However, with limited resources and complex needs, his small security team was struggling with high alert volumes, inefficient tools, and time-consuming investigations that frequently led nowhere.

Meanwhile, issues like insider threats, Denial of Service (DoS), and phishing attacks were growing; the inefficiencies were creating serious security vulnerabilities. As the CIO put it, he was flying blind. With so much data coming in, security analysts were in danger of missing the bigger picture.

“We would just see a single portion of data that could send us down a rabbit hole, thinking something’s going on – only to find out after spending days, weeks, or even months that it was nothing. If you’re only seeing one piece of the issue, it’s really difficult to identify whether something is a legitimate threat or a false positive.”

Local government’s unique cybersecurity challenges

According to the CIO, even with a bigger team, aligning and comparing all the data into a comprehensive, bigger picture would be a major challenge. “The thing about local government specifically is that it’s a complex security environment. We bring together a lot of different individuals and organizations, from construction workers to people who bring projects into our community to better the County. What we work with varies from day to day.”

The challenge wasn’t just about identifying threats, but also about doing so quickly enough to respond before damage was done. The CIO said this was particularly concerning when dealing with sophisticated threats: “We’re dealing with nation-state attackers nowadays, as opposed to ‘script kiddies.’ There’s no time to lose. We’ve got to have cybersecurity that can respond as quickly as they can attack.”

To achieve this, among the most critical challenges the CIO and his team needed to address were:

  • Contextual awareness and visibility across the network: The County team lacked the granular visibility needed to identify potentially harmful behaviors. The IT team needed a tool that uncovered hidden activities and provided actionable insights, with minimal manual intervention.
  • Augmenting human expertise and improving response times: Hiring additional analysts to monitor the environment is prohibitively expensive for many local governments. The IT team needed a cybersecurity solution that could augment existing skills while automating day-to-day tasks. More effective resource allocation would drive improved response times.
  • Preventing email-based threats: Phishing and malicious email links present a persistent threat. The County team needed a way to flag, identify, and hold suspicious messages automatically and efficiently. Given the team’s public service remit, contextual awareness is crucial to ensuring that no legitimate communications are accidentally blocked. Accuracy is extremely important.
  • Securing access and managing insider threats: Having already managed insider threats posed by former staff members, the IT team wanted to adopt a more proactive, deterrent-based approach towards employee IT resource use, preventing incidents before they could occur.

Proactive cybersecurity

Recognizing these challenges, the CIO and County sought AI-driven solutions capable of acting autonomously to support a lean IT team and give the big picture view needed, without getting lost in false positive alerts.

Ease of deployment was another key requirement: the CIO wanted to quickly establish a security baseline for County that would not require extensive pre-planning or disrupt existing systems. Having worked with Darktrace in previous roles, he knew the solution had the capacity to make the critical connections he was looking for, while delivering fast response times and reducing the burden on security teams.

When every second counts, we want to be as close to the same resources as our attackers are utilizing. We have got to have something that can respond as quickly as they can attack. For the County, that’s Darktrace.” – CIO, County Systems Management Department.

Closing network visibility gaps with Darktrace / NETWORK

The County chose Darktrace / NETWORK for unparalleled visibility into the County’s network. With the solution in place, the CIO and his team were able to identify and address previously hidden activities, uncovering insider threats in unexpected places. For example, one team member had installed an unauthorized anonymizer plug-in on their browser, posing a potentially serious security risk via traffic being sent out to the internet. “Darktrace immediately alerted on it,” said CIO. “We were able to deal with the threat proactively and quickly.”

Darktrace / NETWORK continuously monitored and updated its understanding of the County environment, intelligently establishing the different behaviors and network activity. The end result was a level of context awareness that enabled the team to focus on the alerts that mattered most, saving time and effort.

“Darktrace brings all the data we need together, into one picture. We’re able to see what’s going on at a glance, as opposed to spending time trying to identify real threats from false positives,” said the CIO. The ability to automate actions freed the team up to focus on more complex tasks, with 66% of network response actions being applied autonomously, taking the right action at the right time to stop the earliest signs of threatening activity. This reduced pressure on the County’s team members, while buying valuable containment time to perform deeper investigations.

The agentless deployment advantage

For the CIO, one of the major benefits of Darktrace / NETWORK is that it’s agentless. “Agents alert attackers to the presence of security in your environment, it helps them to understand that there’s something else they need to bring down your defenses,” he said. Using Darktrace to mirror network traffic, the County can maintain full visibility across all network entities without alerting attackers and respond to threatening activity at machine speed. “It allows me to sleep better at night, knowing that this tool can effectively unplug the network cable from that device and bring it offline,” said CIO.

Streamlining investigations with Darktrace Cyber AI Analyst

For lean security teams, contextual awareness is crucial in reducing the burden of alert fatigue. Using Cyber AI Analyst, the County team is able to take the pressure off, automatically investigating every relevant event, and reducing thousands of individual alerts to only a small number of incidents that require manual review.

For the County team, the benefits are clear: 520 investigation hours saved in one month, with an average of just 11 minutes investigation time per incident. For the CIO, Darktrace goes beyond reducing workloads, it actually drives security: “It identifies threats almost instantly, bringing together logs and behaviors into a single, clear view.”

The efficiency gain has been so significant that the CIO believes Darktrace augments capabilities beyond the size of a team of analysts. “You could have three analysts working around the clock, but it’s hard to bring all those logs and behaviors together in one place and communicate everything in a coordinated way. Nothing does that as quickly as Darktrace can.”

Catching the threats from within: Defense in depth with Darktrace / IDENTITY

One of the key benefits of Darktrace for the County was its breadth of capability and responsiveness. “We’re looking at everything from multi-factor authentication, insider threats, distributed denial of service attacks,” said the CIO. “I’ve worked with other products in the past, but I’ve never found a tool as good as Darktrace.”

Further insider threats uncovered by Darktrace / IDENTITY included insecure access practices. Some users had logins and passwords on shared network resources or in plain-text files. Darktrace alerted the security team and the threats were mitigated before serious damage was done.

Darktrace / IDENTITY gives organizations advanced visibility of application user behavior from unusual authentication, password sprays, account takeover, resource theft, and admin abuse. Security teams can take targeted actions including the forced log-off of a user or temporary disabling of an account to give the team time to verify legitimacy.

First line of defense against the number one attack vector: Enhancing email security with Darktrace / EMAIL

Email-based threats, such as phishing, are among the most common attack vectors in modern cybersecurity, and a key vector for ransomware attacks. Post implementation performance was so strong that the organization now plans to retire other tools, cutting costs without compromising on security.

Darktrace / EMAIL was one of the first tools that I implemented when I started here,” said CIO. “I really recognize the value of it in our environment.” In addition to detecting and flagging potentially malicious email, the CIO said an unexpected benefit has been the reinforcement of more security-aware behaviors among end users. “People are checking their junk folders now, alerting us and checking to see if something is legitimate or not.”

The CIO said that, unlike traditional email security tools that basically perform only one function, Darktrace has multiple additional capabilities that deliver extra layers of protection compared to one-dimensional alternatives. For example, AI-employee feedback loops leverage insights gained from individual users to not only improve detection rates, but also provide end users with contextual security awareness training, to enhance greater understanding of the risks.

Straightforward integration, ease of use

The County wanted a powerful, responsive solution – without demanding pre-installation or integration needs, and with maximum ease of use. “The integration is relatively painless,” said the CIO. “That’s another real benefit, you can bring Darktrace into your environment and have it up and running faster than you could ever hire additional analysts to look at the same data.”

The team found that, compared to competing products, where there was extensive setup, overhead, and resources, “Darktrace is almost plug-and-play.” According to the CIO, the solution started ingesting information and providing notifications immediately: “You can turn on defense or response mechanisms at a granular level, for email or network – or both at the same time.”

The County sees Darktrace as an integral part of its cybersecurity strategy into the future. “Having worked with Darktrace in the past, it was an easy decision for me to agree to a multi-year partnership,” said the CIO “As we continue to build out our defense-in-depth strategy, the ability to use Darktrace to manage other data sources and identify new, additional behavior will be crucial to our proactive, risk-based approach.”

Darktrace has the capacity to meet the organization’s need for exceptional responsiveness, without burning out teams. “If you’re not overburdening the teams that you do have with significant workloads, they have a lot more agility to deal with things on the fly,” said the CIO.

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
The Darktrace Community

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May 26, 2026

Journey of a Threat: How Multi-Layered AI Works in Darktrace / EMAIL

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Darktrace / EMAIL is an implementation of the Darktrace methodology – a multi-layered AI system built into a single product. As with other Darktrace products, Darktrace / EMAIL learns the expected behaviours of an organization and its employees to identify novel threats and anomalous activity.

The diagram below represents the architecture of Darktrace / EMAIL’s multi-layered AI: a structured visualization of how intelligence is built, step by step, from raw data to actionable insight. Each layer plays a distinct role, feeding into the next: collecting data, understanding behaviour, analysing intent, making decisions, and presenting clear outcomes.

It all starts with an email

In this blog, we’ll follow a malicious email as it passes through the Darktrace / EMAIL system, showing exactly what happens as it travels through each layer of the pyramid, from basic data extraction to AI-powered metric creation, and finally deciding on any autonomous actions.

Let’s take this example email. As an end-user, you can see that this is an obvious extortion attempt where an adversary is threatening legal action if money isn’t paid within 24 hours, but how does Darktrace figure that out?

Part 1: Data Gathering

Processing of an email begins on point-of-transit for all inbound, outbound, or lateral emails. The first step is to extract information directly. This includes taking information from the headers (such as sending and receiving addresses, sender IP address, routing, and authentication protocols), as well as extraction of raw HTML and CSS data from the email itself.

This directly extracted information only allows for immediate surface level analysis, such as identifying signature-based attacks (known malicious addresses / domains), but is insufficient for identifying novel threats, complex attacks, or potential email or vendor compromise. This is where Darktrace’s AI analysis shines.

In this example, the SPF, DKIM, and DMARC authentication all passed successfully, showing that even malicious emails can still bypass these signature-based checks. Even with this success, Darktrace will continue to analyse the email.

Diving deeper into the technical information, we can see further information extracted from the headers, including aggregations from the header information, historical calculations such as the frequency and volume of emails to and from a particular domain, and much more.

Part 2: Social Graphing

Social Graphing involves the analysis of sending and receiving behaviours of different mailboxes to create peer-groups. Mailboxes who often send and receive to and from the same mailboxes, or exhibit other correlated behaviours, will be clustered together using a collection of unsupervised AI clustering systems. These groups may represent uses in the same teams who perform similar activity, groups of external facing mailboxes which often receive unsolicited emails, or groups of VIP users (such as C-suite or executives).

Social graphing is an essential component of Darktrace’s pattern of life analysis. This clustering allows Darktrace to understand the responsibilities of individuals – for example, behaviours which are anomalous for one group of users may be completely expected of another group.

In our example, the email was sent to 3 different users within the organization. As part of the social graphing, an “Association Anomaly” is calculated which indicates the likelihood that these users would receive emails from this user or domain, based on historical patterns.

Part 3: Metric Calculation

Metrics are calculated for every email, representing more complex characteristics of an email which can’t be directly extracted. Darktrace / EMAIL features over 1000 unique metrics, calculated both algorithmically and using an ensemble of AI systems.

Algorithmically calculated (non-AI) metrics include further historical calculations, and counts of features such as code blocks, and hidden text, to name a few.

AI-driven metrics include Inducement Classification which uses Natural Language Processing to identify potential phishing, solicitation, or extortion attempts; Named Entity Recognition to identify PII and other sensitive data within an email to support Data Loss Prevention; and many more.

We can follow our example email through this process and view the outcome of these metric calculations. Looking at the language metrics for this email, we can see that our email has reported a high extortion inducement, along with identification of banking information and language indicating urgency.

Part 4: Evaluation and Combination Engine (models)

Once all metrics have been calculated for an email, it gets sent to an evaluation and combination engine where the metrics are compared against blocks of logic to determine if an email contains a threat. One key model which alerted for this example message was a model to tag and block extortion attempts.

Since our example email has a high inducement score for extortion, along the presence of a bitcoin wallet address in the message, this model alerts. When a model in the engine is activated, actions are taken – in this case adding a tag to the email to flag it as extortion in the console and hold the email to prevent it from reaching the end-user mailbox.

Part 5: Meta-Modelling and Actions

Once the models have been run, the actions are taken against the email. If the email hasn’t been blocked or held, this is the point where it will reach the end-user's mailbox.

In the Darktrace / EMAIL UI, all actions models which alerted for an email and actions taken as a result can be seen. At the top of this page, you can see the alert indicating an extortion attempt along with the action to hold the message.

Alongside this, a meta-classifier is used to calculate an overall anomaly score for each email, based on how much the email differs from the pattern of life for the user. The score of the email is boosted by any actions that have taken place.

Part 6: Campaign Clustering

All emails are passed through the Darktrace / EMAIL campaign clustering system. This system creates clusters based on related features within the emails to identify groups of emails with the same sender or intent.

In our case, the email was identified as part of a campaign, alongside other emails which were also identified as extortion attempts against a small group of recipients.

Email campaigns may have additional actions applied to them if the campaign is deemed malicious, and in this case, you can see that the autonomous response was to hold all emails in the campaign. This means that if an email manages to avoid being blocked in the evaluation and combination engine but gets identified as part of the campaign, the hold action will be applied to it retroactively.

Part 7: Cyber AI Analyst

Darktrace’s Cyber AI Analyst presents key information and anomaly indicators for each email, such as further information about authentication, specific metrics, or other identified anomalies and mismatches.

Cyber AI Analyst can also utilize data from Darktrace / EMAIL to enhance its investigation of incidents from other Darktrace products, correlating relevant information to build a fuller picture. More information about the Cyber AI Analyst is available in the Darktrace AI Arsenal.

Part 8: Data Presentation (UI)

Once all processing has taken place against the email, it is presented in the Darktrace / EMAIL UI. Here, members of the SOC team can investigate incidents and anomalies, interact with malicious emails to see why they were blocked, and much more.

Our email stands out here with its 100 anomaly score. Every email which passes through a Darktrace / EMAIL will undergo the same thorough and rigorous analysis to identify potential risks, apply autonomous actions where required, and will ultimately be assigned a score to be displayed here. By providing a single overall score in the UI, rather than presenting emails in full, Darktrace / EMAIL allows SOC teams to more easily identify which emails are most important to investigate, increasing efficiency and reducing alert fatigue.

Take the next step

Many email security tools on the market that claim to be AI-driven are in fact bolting AI onto attack-centric approaches, which rely on automating the identification of known threats. These approaches struggle, and will continue to struggle, with adapting to novel, AI-generated threats.

By analyzing every email within its deeply integrated, multi-layered AI system, Darktrace / EMAIL is able to identify the subtle threats that others miss. This depth not only improves detection accuracy, but enables confident, autonomous action, giving security teams clearer insight into AI outcomes and greater control while supporting users.

For a full deep dive into each stage of the AI system, check out the white paper: A Guide to the Multi-Layered AI in Darktrace / EMAIL

Learn more about securing AI in your enterprise.

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Jamie Bali
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May 26, 2026

Darktrace named a Leader in the 2026 Gartner® Magic Quadrant™ for Network Detection and Response (NDR) For the Second Consecutive Year

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Continued recognition in NDR  

Darktrace has been recognized as a Leader in the 2026 Gartner® Magic Quadrant™ for Network Detection and Response (NDR), marking the second consecutive year in the Leaders quadrant.

We believe this consistency reflects sustained ability to execute, adapt, and deliver outcomes as the market evolves.

While we are immensely proud to be recognized by industry analysts as a Leader in NDR, that's just part of the story. Darktrace was also Named the Only 2025 Gartner® Peer Insights™ Customers’ Choice for Network Detection and Response based on direct customer feedback and real-world experience.

We believe the combination of these two signals is important. One reflects how the market is evaluated. The other reflects how technology performs in practice.

Why Darktrace continues to be recognized as a leader

We believe our position as a Leader for the second consecutive year reflects a combination of our sustained ability to execute in NDR, continued AI innovation, and proven delivery of security outcomes for customers and partners worldwide.

We also feel that our leadership in the NDR market is a testament to our unique and multi-layered AI approach, for which we were recognized as No.7 on Fast Company’s Most Innovative AI Companies of 2026 list, plus one of the hottest AI cybersecurity companies in CRN's AI 100.

Adapting to complex, real-world environments

Organizations are no longer protecting a single network perimeter. They are securing a mix of users, devices, applications, and data that move across hybrid environments.

Darktrace has focused on maintaining visibility and detection across these conditions, allowing security teams to understand activity as it scales.

Supporting organizations globally, not just technically

Security outcomes are shaped as much by deployment and support as they are by detection capability.

Darktrace continues to invest in regional presence across 29 countries around the world, helping organizations operationalize NDR in ways that align with local requirements, internal processes, and team structures.

Continuing to push AI beyond detection

AI in cybersecurity is often positioned as a way to improve detection accuracy. But the more important shift is how AI can influence decision-making and response.

Darktrace continues to develop models that learn from both live environments and historical incident data, combining real-time behavioral analysis with insights derived from prior attack patterns.

Using technologies such as the Incident Graph and DIGEST (Darktrace Incident Graph Evaluation for Security Threats), activity is not analyzed in isolation. Instead, relationships between users, devices, connections, and events are mapped over time, allowing the system to reconstruct how an incident is unfolding and how similar incidents have progressed in the past.

By evaluating these patterns, Darktrace can assess the likelihood that an incident will escalate, prioritizing the activity that poses the greatest risk and surfacing the most relevant context for investigation.

This shifts security operations from simply identifying anomalies to understanding their trajectory, helping teams anticipate potential impact and respond earlier with greater precision.

Why NDR is shifting from reactive detection to proactive, AI-driven security

Traditional approaches to NDR have been built around reactively identifying threats once they become clearly visible. That model is increasingly difficult to rely on.

Attackers are no longer operating in ways that stand out. They use valid credentials, trusted tools, and low-and-slow techniques that blend into everyday activity. By the time something looks obviously malicious, the impact is often already underway.

This is the core limitation of reactive detection. It depends on recognizing something that already looks like a threat.

As a result, many of the most consequential incidents today fall into a gap.

Insider activity, compromised credentials, and novel attacks rarely trigger traditional alerts because they do not follow known patterns. On the surface, they often appear legitimate, making them difficult to distinguish from normal behavior without deeper context.

This is why we believe this Gartner recognition reflects a broader shift in NDR toward autonomous, proactive and pre‑emptive security operations.

By understanding normal behavior within an environment, it is possible to identify subtle deviations rather than waiting for confirmation of threats as they are taking place.

Darktrace’s Self-Learning AI is designed for behavioral understanding. By continuously learning each organization’s normal patterns, it can detect deviations in real time, enabling a proactive and pre-emptive model of NDR where security teams can respond to early signs of risk as they emerge, reducing the window in which attacks can develop.

In multiple cases, this behavioral approach has led to early threat detection where Darktrace identified completely unknown threats, including pre-CVE zero-day activity. By detecting subtle behavioral changes before vulnerabilities were publicly disclosed or widely understood, organizations can mitigate threats before they do damage.

This shift is subtle but important. Modern NDR solutions must shift from a system that explains what happened to one that helps prevent threats from developing in the first place, and Darktrace is proud to be at the forefront of this shift - helping organizations build and maintain a state of proactive network resilience.

Continuing to innovate at the forefront of NDR

In our view, recognition as a Leader reflects where the market is today. Continuing to innovate defines what comes next.

As businesses evolve, new technologies like AI tools and agents introduce new security risks and challenges; security teams need more than simple detection. They need a complete understanding of risk as it develops, the ability to investigate it in context, and to contain threats at machine speed.  

Darktrace / NETWORK is built to deliver across that full spectrum. Its Self-Learning AI continuously adapts to each organization’s environment, identifying subtle behavioral changes that signal emerging threats. Integrated investigation and autonomous response reduce the time between detection and action, allowing teams to move with greater speed and confidence.

This combination enables organizations to detect and contain known, unknown, and insider threats as they develop, while also strengthening resilience over time.

As a two-time Leader in the Gartner® Magic Quadrant™ for NDR and the only 2025 Gartner® Peer Insights™ Customers’ Choice, we feel Darktrace continues to evolve its platform to meet the demands of modern environments, delivering a more complete and adaptive approach to network security.

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Disclaimer: The 2026 Gartner® Magic Quadrant™ for Network Detection and Response (NDR) ,The 2026 Gartner® Magic Quadrant™ for Network Detection and Response (NDR), Thomas Lintemuth, Charanpal Bhogal, Nahim Fazal, 18 May 2026.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. Magic Quadrant is a registered trademark of Gartner, Inc. and/or its affiliates and is used herein with permission. All rights reserved.

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Mikey Anderson
Product Marketing Manager, Network Detection & Response
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