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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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July 6, 2026

NIST Just Proved It: AI Security Can’t Be Solved With Rules

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Static AI guardrails are inherently limited

As organizations adopt generative AI, many still assume that the right set of guardrails will be enough. The problem is you can’t anticipate every way these systems might be misused, abused or attacked. What NIST has done is put a mathematical foundation under that intuition.

In recent research building on Gödel’s incompleteness theorems, which showed that any system built on a fixed set of rules will always have gaps, NIST demonstrates that there is no finite set of guardrails that can be universally robust against adversarial prompts. In plain terms, if your defense is based on a fixed set of rules, there will always be inputs that bypass them. Not because the rules are badly written, but because the problem space is bigger than static rules can ever cover.

This is not new in cybersecurity - detection rules have always had to live with this trade-off. What is different with GenAI is the scale and shape of that problem. These systems are built on human language, and human language is not bounded. It is fluid, contextual and deliberately ambiguous. The number of ways intent can be hidden is effectively limitless. You are not defending against a defined protocol or a fixed exploit chain. You are defending against the entire expressive capacity of people.

So attempting to create a complete set of rules is the wrong starting point. It assumes the problem can be deterministically described. NIST’s work shows that it cannot. Organizations still need a way to manage AI risk, but the traditional approach of defining allowed and disallowed patterns is always going to lag behind what is actually happening. The same input can be benign in one context and risky in another, and static rules struggle to capture that distinction.

The question then is what fills that gap?

AI security must shift from rules to behavior

What's required is a shift in what you are trying to understand. Rules try to describe what should and shouldn't happen. Behavior shows you what is happening. Or to put it another way, if inputs are unbounded and adversaries adapt, the only stable signal is behavior.

In a GenAI context, that means analyzing how an AI model is being used, how prompts evolve over time, how outputs are shaped, and where AI agent interactions start to drift from what is expected. It means moving from static definitions of bad to a more dynamic understanding of intent.

Instead of trying to predict every bad prompt, you focus on identifying when behavior starts to move outside expected norms. Instead of asking whether a single input matches a rule, you ask whether the overall pattern of activity makes sense for the system and how it’s being used.

Guardrails remain important but they are only one layer

This does not eliminate the need for guardrails. They still play a role. But they will never address the entire problem space and are simply one part of your defense in depth approach.

NIST’s proof is useful because it makes this explicit. It removes the assumption that with enough effort, a complete rule set is achievable. It isn’t.

Once you accept that, the shift becomes unavoidable. This is no longer a problem of writing better rules, but of understanding behavior in a space where the possible inputs are effectively unbounded.

For security leaders, that changes the nature of the problem. It is less about defining what should be allowed, and more about recognizing when something is no longer consistent with expected behavior.

That does not remove the need for guardrails, but it does change their role. They set boundaries, but they do not define understanding. The gap between the two is where risk now sits.

In the end, this is what “can’t be solved with rules” really means. Rules will always leave gaps, and those gaps are not theoretical. They show up in how systems actually behave Not what we expect them to do, or what we intended them to do, but what they are doing in practice. That is where the signal is, and increasingly, that is where the security problem sits.

References:

https://www.nist.gov/news-events/news/2026/06/nist-mathematical-proof-supports-transition-continuous-monitor-and-update

https://ieeexplore.ieee.org/document/11475847

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About the author
Andrew Hollister
Principal Solutions Engineer, Cyber Technician

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July 1, 2026

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

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The Reality of Securing AI in Motion

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

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

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

1. AI agents with human access but no human judgment

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

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

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

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

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

2. Increased digital complexity and expanded attack surface

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

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

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

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

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

3. Shadow AI is already everywhere

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

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

The result is a lack of visibility into:

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

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

4. Built-in guardrails are not enough

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

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

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

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

The next phase of cybersecurity: securing AI

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

• Understanding AI behavior

• Identifying risk in real time

• Maintaining governance without slowing innovation

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

Embrace AI with confidence with Darktrace / SECURE AI

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

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

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

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

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

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

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