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April 2, 2023

Enhancing Security Teams with AI-Powered Email Solutions

Discover email-based attack challenges & how AI security solutions can tackle these attacks with autonomous action, optimized workflows, and user visibility.
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
Dan Fein
VP, Product
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02
Apr 2023

The modern security team faces challenges on all fronts – it is too often overstretched dealing with an increased attack surface, enabling workforces for secure remote work, and managing multiple security tools to protect that workforce. Added to that, the surge in more sophisticated phishing campaigns – now supported by AI tools – means that it’s harder than ever to pre-empt attacks. 

The needs of the security team should be a key consideration when deploying an email security solution, as it’s them who will be accountable for the success and maintenance of the product. Minimizing time spent inside the user interface – through trusted detection and response technology combined with intuitive reporting and optimized workflows – should be front of mind for vendors in order to assure teams of their value.

Taking security teams off the frontline 

No team should be spending all of their time maintaining email security policies, releasing emails that shouldn’t have been held, or holding back emails that should have been – all the things that traditional email security solutions have almost forced them to become accustomed to. A day in the life of an admin shouldn’t include tens – and certainly not hundreds – of minutes spent in their email security dashboard. 

At the moment, teams are logging in far too often, and when they do, they’re forced to make individual decisions about safe listing and blocking domains, or releasing emails. These can lead to the creation of blanket rules that open up future windows for attackers – unintended consequences that ultimately create more work in the future. This type of hand-to-hand combat puts security teams on the frontline, when their time could be much better spent doing the high-level strategic work humans are best at.  

Understanding You: A Different Approach to Email Security

In today’s discussions about email security, there is a consensus that relying on a gateway is no longer feasible. The new era is one of ICES (Integrated cloud email security) solutions and other tools leveraging artificial intelligence and APIs. But there's no point adopting new technology with an old philosophy – and most of these solutions use AI to automate the same old approach: looking at past attacks to try and stop the next. 

This is where Darktrace/Email takes a fundamentally different and unique approach. It’s not just about using AI; it’s about using it in the right capacity. Our AI understands you – learning where users log in from, who they email, their behavior throughout the day – to tailor the detection and response process according to their individual profile. There’s no point withholding an email if only a tiny element of it poses a risk – Darktrace/Email takes the least aggressive action required to neutralize a threat. Instead of a blanket allow-deny criteria, it can rewrite links or withhold attachments based on its knowledge of the user’s normal inbox activity. Stopping malicious emails while allowing legitimate emails through – with risky elements neutralized – lifts security teams out of the fire-fighting activities described earlier and frees up their time for more strategic and valuable decision-making.

This is going to get me to reduce my current email security stack… this is going to take it to that level that I need it to”

- Early Look Customer, Darktrace/Email 

Account Takeover 

Embedded account takeover protection is an essential component of modern email security. Security teams need visibility not just over email breaches but of what happens once an attacker has control of an inbox, particularly in the most damaging use cases like Business Email Compromise (BEC) and ransomware. This entails understanding a user’s behavior in their inbox, outbound emails and beyond into their wider account activity. Darktrace captures a user’s activity across email and their Microsoft or Google account in a single pane of glass – detecting and countering all of the markers that could signify a compromised account.  

Insights from other cloud applications and network devices gleaned from Darktrace's wider visibility of the business can bring a 360° understanding of the user, further enhancing detection of account takeover and other harmful activity.

Figure 1: A 360° understanding of a user reveals their digital touchpoints beyond Microsoft

What ‘user-friendly’ actually looks like 

The best user interface is one that you never have to log into. In an ideal world, teams are able to visit their tools less frequently because intelligent AI is automating work previously done by humans. This is made possible by Darktrace’s precision detection and response technology, which takes appropriate action on emails and accounts to neutralize threats without disrupting day-to-day business operations. 

The second-best user interface is one where you can quickly log in and get key insights fast, whether that’s regarding an action taken or the current activity of a user – and then get out. Darktrace/Email enables teams to get key information quickly, at both a high and granular level.  The dashboard offers immediate insights into users and emails, with a real-time snapshot of active user identities, targeted user and actioned emails, segmented by type of attack. 

At every touchpoint, Darktrace reduces friction with optimized workflows. From being able to quickly identify VIPs to safely previewing links and attachments, security teams can get the information they need without needing to switch between windows or navigate inaccessible interfaces. Explainable AI gives users natural-language summaries of individual emails or the overall health of an email environment, and simplified action flows allow security teams to personalize security for different employees – for example, sending VIPs a unique notification, or taking extra precautions around employees who work in accounting. Taken together, this meaning that admins can spend even less time managing policies. 

Figure 2: Darktrace/Email dashboard displaying key information about the email environment in a single pane of glass

The ideal interface is also the one that’s the most accessible to you. The mobile app guarantees convenience for security teams, making available all the main functions of the interface for on-the-go analysis at any time or place. Teams can travel or leave the office while retaining the peace of mind that if a critical incident was to occur, they would be able to get instant visibility on the data and take action without needing to get back to their desks.  

Figure 3: Security admins are able to preview, analyze, and act on emails directly from the Darktrace Mobile App

With every passing day, the security team can rest easier. Every activity is taken into account to help the AI tune and adapt over time to become even better at detecting and responding to threats.   

Having email on the app is going to be game changing” 

- Early Look Customer, Darktrace/Email 

Getting the full picture

Most often, email is the entry point from which a threat actor moves stealthily throughout an organization collecting information and assets. Most solutions look at email in isolation, without prioritizing or connecting disparate events into a wider pattern. 

In contrast, Darktrace/Email integrates seamlessly with Darktrace's Cyber AI Analyst, a technology that conducts autonomous enterprise-wide investigations around every alert produced by the wider Darktrace platform. Through this integration, malicious email activity is analyzed and displayed in the context of the full security incident to which it belongs. As a result, security teams can see why and how a wider problem might have originated in email and spread to other apps, endpoints, or the wider corporate network.

Empowering employees to take an active role in security

The role of the security team can be made more difficult if employees take a lax or disengaged approach to security – or if a user is given too much control, and has the ability to make potentially dangerous decisions. Training employees on security procedures is another to-do which can easily fall to the bottom of the agenda during busy periods, especially as point-in-time phishing simulations have proven to be not particularly effective. 

To this end, Darktrace/Email uses Explainable AI to say in natural language what it thought about an email, and delivers its findings not just to the security team, but optionally to the wider workforce as well. Delivered in the form of contextual banners in emails, periodic digests, or directly in Outlook, these insights transform security education from a quarterly or yearly exercise into real-time security awareness. Our next blog will dive deeper into how employee engagement can support the security team’s efforts and harden defenses throughout the organization. 

Because Darktrace is built on a fundamentally different approach, it not only stops novel and targeted sophisticated attacks but allows legitimate emails to flow through. This is what makes it a truly set-and-forget technology, with the AI taking on much of the heavy lifting previously undertaken by security teams. 

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
Dan Fein
VP, Product

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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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