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October 2, 2024

How Darktrace won an email security trial by learning the business, not the breach

Discover how Darktrace identified a sophisticated business email compromise (BEC) attack to successfully acquire a prospective customer in a trial alongside two other email security vendors. This case demonstrates the clear differentiator of true unsupervised machine learning applied to the right use cases, compared to miscellaneous vendor hype around AI.
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
Carlos Gray
Senior Product Marketing Manager, Email
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02
Oct 2024

Recently, Darktrace ran a customer trial of our email security product for a leading European infrastructure operator looking to upgrade its email protection.

During this prospective customer trial, Darktrace encountered several security incidents that penetrated existing security layers. Two of these incidents were Business Email Compromise (BEC) attacks, which we’re going to take a closer look at here.  

Darktrace was deployed for a trial at the same time as two other email security vendors, who were also being evaluated by the prospective customer. Darktrace’s superior detection of threats in this trial laid the groundwork for the respective company to choose our product.

Let’s dig into some of the elements of this Darktrace tech win and how they came to light during this trial.

Why truly intelligent AI starts learning from scratch

Darktrace’s detection capabilities are powered by true unsupervised machine learning, which detects anomalous activity from its ever-evolving understanding of normal for every unique environment. Consequently, it learns every business from the beginning, training on an organization’s data to understand normal for its users, devices, assets and the millions of connections between them.  

This learning period takes around a week, during which the AI hones its understanding of the business to a precise degree. At this stage, the system may produce some noise or lack precision, but this is a testament to our unsupervised machine learning. Unlike solutions that promise faster results by relying on preset assumptions, our AI takes the necessary time to learn from scratch, ensuring a deeper understanding and increasingly accurate detection over time.

Real threats detected by Darktrace

Attack 1: Supply chain attack

BEC and supply chain attacks are notoriously difficult to detect, as they take advantage of established, trusted senders.  

This attack came from a legitimate server via a known supplier with which the prospective customer had active and ongoing communication. Using the compromised account, the attacker didn’t just send out randomized spam, they crafted four sophisticated social engineering emails with the aim of soliciting users to click on a link – directly tapping into existing conversations. Darktrace / EMAIL was configured in passive mode during this trial; it would otherwise have held the emails before they arrived in the inbox. Luckily in this instance, one user reported the email to the CISO before any other users clicked the link. Upon investigation, the link contained timed ransomware detonation.  

Darktrace was the only vendor that caught any of these four emails. Our unique behavioral AI approach enables Darktrace / EMAIL to protect customers from even the most sophisticated attacks that abuse prior trust and relationships.

How did Darktrace catch this attack that other vendors missed?

With traditional email security, security teams have been obliged to allow entire organizations to eliminate false positives – on the premise that it’s easier to make a broad decision based on an entire known domain and assume that potential risk of a supply chain attack.

By contrast, Darktrace adopts a zero trust mentality, analyzing every email to understand whether communication that has previously been safe remains safe. That’s why Darktrace is uniquely positioned to detect BEC, based on its deep learning of internal and external users. Because it creates individual profiles for every account, group and business composed of multiple signals, it can detect deviations in their communication patterns based on the context and content of each message. We think of this as the ‘self-learning’ vs ‘learning the breach’ differentiator.

Fig 1: Darktrace analysis of one of four malicious emails sent by the trusted supplier. It gives it an anomaly score of 100, despite it being from a known correspondent with a known domain relationship and moderate mailing history.

If set in autonomous mode where it can apply actions, Darktrace / EMAIL would have quarantined all four emails. Using machine learning indicators such as ‘Inducement Shift’ and ‘General Behavioral Anomaly’, it deemed the four emails ‘Out of Character’. It also identified the link as highly likely to be phishing, based purely on its context. These indicators are critical because the link itself belonged to a widely used legitimate domain, leveraging their established internet reputation to appear safe.  

Around an hour later the supplier regained control of the account and sent a legitimate email alerting a wide distribution list to the phishing emails sent. Darktrace was able to discern the previously sent malicious emails from the current legitimate emails and allowed these emails through. Compared to other vendors that have a static understanding of malicious which needs to be updated (in cases like this, once a supplier is de-compromised), Darktrace’s deep understanding of external entities enables further nuance and precision in determining good from bad.

Fig 2: Darktrace let through four emails (subject line: Virus E-Mail) from the supplier once they had regained control of the compromised account, with a limited anomaly score despite having held the previous malicious emails. If any actions had been taken a red icon would show on the right-hand side – in this instance Darktrace did not take action and let the emails through.

Attack 2: Microsoft 365 account takeover

As part of building behavioral profiles of every email user, Darktrace analyzes their wider account activity. Account activity, such as unusual login patterns and administrative activity, is a key variable to detect account compromise before malicious activity occurs, but it also feeds into Darktrace’s understanding of which emails should belong in every user’s inbox.  

When the customer experienced an account compromise on day two of the trial, Darktrace began an investigation and was able to provide the full breakdown and scope of the incident.

The account was compromised via an email, which Darktrace would have blocked if it had been deployed autonomously at the time. Once the account had been compromised, detection details included:

  • Unusual Login and Account Update
  • Multiple Unusual External Sources for SaaS Credential
  • Unusual Activity Block
  • Login From Rare Endpoint While User is Active
Fig 3: Darktrace flagged the following indicators of compromise that deviated from normal behavior for the user in question, signaling an account takeover

With Darktrace / EMAIL, every user is analyzed for behavioral signals including authentication and configuration activity. Here the unusual login, credential input and rare endpoint were all clear signals a compromised account, contextualized against what is normal for that employee. Because Darktrace isn’t looking at email security merely from the perspective of the inbox. It constantly reevaluates the identity of each individual, group and organization (as defined by their behavioral signals), to determine precisely what belongs in the inbox and what doesn’t.  

In this instance, Darktrace / EMAIL would have blocked the incident were it not deployed in passive mode. In the initial intrusion it would have blocked the compromising email. And once the account was compromised, it would have taken direct blocking actions on the account based on the anomalous activity it detected, providing an extra layer of defense beyond the inbox.  

Account takeover protection is always part of Darktrace / EMAIL, which can be extended to fully cover Microsoft 365 SaaS with Darktrace / IDENTITY. By bringing SaaS activity into scope, security teams also benefit from an extended set of use cases including compliance and resource management.

Why this customer committed to Darktrace / EMAIL

“Darktrace was the only AI vendor that showed learning,” – CISO, Trial Customer

Throughout this trial, Darktrace evolved its understanding of the trial customer’s business and its email users. It identified attacks that other vendors did not, while allowing safe emails through. Furthermore, the CISO explicitly cited Darktrace as the only technology that demonstrated autonomous learning. As well as catching threats that other vendors did not, the CISO saw maturity areas such as how Darktrace dealt with non-productive mail and business-as-usual emails, without any user input.  Because of the nature of unsupervised ML, Darktrace’s learning of right and wrong will never be static or complete – it will continue to revise its understanding and adapt to the changing business and communications landscape.

This case study highlights a key tenet of Darktrace’s philosophy – that a rules and tuning-based approach will always be one step behind. Delivering benign emails while holding back malicious emails from the same domain demonstrates that safety is not defined in a straight line, or by historical precedent. Only by analyzing every email in-depth for its content and context can you guarantee that it belongs.  

While other solutions are making efforts to improve a static approach with AI, Darktrace’s AI remains truly unsupervised so it is dynamic enough to catch the most agile and evolving threats. This is what allows us to protect our customers by plugging a vital gap in their security stack that ensures they can meet the challenges of tomorrow's email attacks.

Interested in learning more about Darktrace / EMAIL? Check out our product hub.

Download: Darktrace / EMAIL Solution Brief

Discover the most advanced cloud-native AI email security solution to protect your domain and brand while preventing phishing, novel social engineering, business email compromise, account takeover, and data loss.

  • Gain up to 13 days of earlier threat detection and maximize ROI on your current email security
  • Experience 20-25% more threat blocking power with Darktrace / EMAIL
  • Stop the 58% of threats bypassing traditional email security

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
Carlos Gray
Senior Product Marketing Manager, Email

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May 12, 2026

Resilience at the Speed of AI: Defending the Modern Campus with Darktrace

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Why higher education is a different cybersecurity battlefield

After four decades in IT, now serving as both CIO and CISO, I’ve learned one simple truth: cybersecurity is never “done.” It’s a constant game of cat and mouse. Criminals evolve. Technologies advance. Regulations expand. But in higher education, the challenge is uniquely complex.

Unlike a bank or a military installation, we can’t lock down networks to a narrow set of approved applications. Higher education environments are open by design. Students collaborate globally, faculty conduct cutting-edge research, and administrators manage critical operations, all of which require seamless access to the internet, global networks, cloud platforms, and connected systems.

Combine that openness with expanding regulatory mandates and tight budgets, and the balancing act becomes clear.

Threat actors don’t operate under the same constraints. Often well-funded and sponsored by nation-states with significant resources, they’re increasingly organized, strategic, and innovative.

That sophistication shows up in the tactics we face every day, from social engineering and ransomware to AI-driven impersonation attacks. We’re dealing with massive volumes of data, countless signals, and a very small window between detection and damage.

No human team, no matter how talented or how numerous, can manually sift through that noise at the speed required.

Discovering a force multiplier

Nothing in cybersecurity is 100% foolproof. I never “set it and forget it.” But for institutions balancing rising threats and finite resources, the Darktrace ActiveAI Security Platform™ offers something incredibly valuable: peace of mind through speed and scale.

It closes the gap between detection and response in a way humans can’t possibly match. At the speed of light, it can quarantine, investigate, and contain anomalous activity.

I’ve purchased and deployed Darktrace three separate times at three different institutions because I’ve seen firsthand what it can do and what it enables teams like mine to achieve.

I first encountered Darktrace while serving as CIO for a large multi-campus college system. What caught my attention was Darktrace's Self-Learning AI, and its ability to learn what "normal" looked like across our network. Instead of relying solely on static signatures or rigid rules, Darktrace built a behavioral baseline unique to our environment and alerted us in real time when something simply didn’t look right.

In higher education, where strict lockdowns aren’t realistic, that behavioral model made all the difference. We deployed it across five campuses, and the impact was immediate. Operating 24/7, Darktrace surfaced threats in ways our team couldn’t replicate manually.

Over time, the Darktrace platform evolved alongside the changing threat landscape, expanding into intrusion prevention, cloud visibility, and email security. At subsequent institutions, including Washington College, Darktrace was one of my first strategic investments.

Revealing the hidden threat other tools missed

One of the most surprising investigations of my career involved a data leak. Leadership suspected sensitive information from high-level meetings was being exposed, but our traditional tools couldn’t provide any answers.

Using Darktrace’s deep network visibility, down to packet-level data, we traced unusual connections to our CCTV camera system, which had been configured with a manufacturer’s default password. A small group of employees had hacked into the CCTV cameras, accessed audio-enabled recordings from boardroom meetings, and stored copies locally.

No other tool in our environment could have surfaced those connections the way Darktrace did. It was a clear example of why using AI to deeply understand how your organization, systems, and tools normally behave, matters: threats and risks don’t always look the way we expect.

Elevating a D-rating into a A-level security program

When I arrived at my last CISO role, the institution had recently experienced a significant ransomware attack. Attackers located  data  which informed their setting  ransom demands to an amount they knew would likely result in payment. It was a sobering example of how calculated and strategic modern cybercriminals have become.

Third-party cyber ratings reflected that reality, with a  D rating.

To raise the bar, we implemented a comprehensive security program and integrated layered defenses; -deploying state of the art tools and methods-  across the environment, with Darktrace at its core.

After a 90-day learning period to establish our behavioral baseline, we transitioned the platform into fully autonomous mode. In a single 30-day span, Darktrace conducted more than 2,500 investigations and autonomously resolved 92% of all false positives.

For a small team, that’s transformative. Instead of drowning in alerts, my staff focused on less than  200 meaningful cases that warranted human review.

Today, we maintain a perfect A rating from third-party assessors and have remained cybersafe.

Peace of mind isn’t about complacency

The effect of Darktrace as a force multiplier has a real human impact.

With the time reclaimed through automation, we expanded community education programs and implemented simulated phishing exercises. Through sustained training and awareness efforts, we reduced social engineering susceptibility from nearly 45% to under 5%.

On a personal level, Darktrace allows me to sleep better at night and take time off knowing we have intelligent systems monitoring and responding around the clock. For any CIO or CISO carrying institutional risk on their shoulders, that matters.

The next era: AI vs. AI

A new chapter in cybersecurity is unfolding as adversaries leverage AI to enhance scale, speed, and believability. Phishing campaigns are more personalized, impersonation attempts are more precise, and deepfake video technology, including live video, is disturbingly authentic. At the same time, organizations are rapidly adopting AI across their own environments —from GenAI assistants to embedded tools to autonomous agents. These systems don’t operate within fixed rules. They act across email, cloud, SaaS, and identity systems, often with broad permissions, and their behavior can evolve over time in ways that are difficult to predict or control.

That creates a new kind of security challenge. It’s not just about defending against AI-powered threats but understanding and governing how AI behaves within your environment, including what it can access, how it acts, and where risk begins to emerge.

From my perspective, this is a natural next step for Darktrace.

Darktrace brings a level of maturity and behavioral understanding uniquely suited to the complexity of AI environments. Self-Learning AI learns the normal patterns of each business to interpret context, uncover subtle intent, and detect meaningful deviations without relying on predefined rules or signatures. Extending into securing AI by bringing real-time visibility and control to GenAI assistants, AI agents, development environments and Shadow AI, feels like the logical evolution of what Darktrace already does so well.

Just as importantly, Darktrace is already built for dynamic, cross-domain environments where risk doesn’t sit in a single tool or control plane. In higher education, activity already spans multiple systems and, with AI, that interconnection only accelerates.

Having deployed Darktrace multiple times, I have confidence it’s uniquely positioned to lead in this space and help organizations adopt AI with greater visibility and control.

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Since authoring this blog, Irving Bruckstein has transitioned to the role of Chief Executive Officer of the Cyberaigroup.

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About the author
Irving Bruckstein
CEO CyberAIgroup

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May 11, 2026

The Next Step After Mythos: Defending in a World Where Compromise is Expected

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Is Anthropic’s Mythos a turning point for cybersecurity?

Anthropic’s recent announcements around their Mythos model, alongside the launch of Project Glasswing, have generated significant interest across the cybersecurity industry.

The closed-source nature of the Mythos model has understandably attracted a degree of skepticism around some of the claims being made. Additionally, Project Glasswing was initially positioned as a way for software vendors to accelerate the proactive discovery of vulnerabilities in their own code; however, much of the attention has focused on the potential for AI to identify exploitable vulnerabilities for those with malicious intent.

Putting questions around the veracity of those claims to one side – which, for what it’s worth, do appear to be at least partially endorsed by independent bodies such as the UK’s AI Security Institute – this should not be viewed as a critical turning point for the industry. Rather, it reflects the natural direction of travel.

How Mythos affects cybersecurity teams  

At Darktrace, extolling the virtues of AI within cybersecurity is understandably close to our hearts. However, taking a step back from the hype, we’d like to consider what developments like this mean for security teams.

Whether it’s Mythos or another model yet to be released, it’s worth remembering that there is no fundamental difference between an AI discovered vulnerability and one discovered by a human. The change is in the pace of discovery and, some may argue, the lower the barrier to entry.

In the hands of a software developer, this is unquestionably positive. Faster discovery enables earlier remediation and more proactive security. But in the hands of an attacker, the same capability will likely lead to a greater number of exploitable vulnerabilities being used in the wild and, critically, vulnerabilities that are not yet known to either the vendor or the end user.

That said, attackers have always been able to find exploitable vulnerabilities and use them undetected for extended periods of time. The use of AI does not fundamentally change this reality, but it does make the process faster and, unfortunately, more likely to occur at scale.

While tools such as Darktrace / Attack Surface Management and / Proactive Exposure Management  can help security teams prioritize where to patch, the emergence of AI-driven vulnerability discovery reinforces an important point: patching alone is not a sufficient control against modern cyber-attacks.

Rethinking defense for a world where compromise is expected

Rather than assuming vulnerabilities can simply be patched away, defenders are better served by working from the assumption that their software is already vulnerable - and always will be -and build their security strategy accordingly.

Under that assumption, defenders should expect initial access, particularly across internet exposed assets, to become easier for attackers. What matters then is how quickly that foothold is detected, contained, and prevented from expanding.

For defenders, this places renewed emphasis on a few core capabilities:

  • Secure-by-design architectures and blast radius reduction, particularly around identity, MFA, segmentation, and Zero Trust principles
  • Early, scalable detection and containment, favoring behavioral and context-driven signals over signatures alone
  • Operational resilience, with the expectation of more frequent early-stage incidents that must be managed without burning out teams

How Darktrace helps organizations proactively defend against cyber threats

At Darktrace, we support security teams across all three of these critical capabilities through a multi-layered AI approach. Our Self-Learning AI learns what’s normal for your organization, enabling real-time threat detection, behavioral prediction, incident investigation and autonomous response. - all while empowering your security team with visibility and control.

To learn more about Darktrace’s application of AI to cybersecurity download our White Paper here.  

Reducing blast radius through visibility and control

Secure-by-design principles depend on understanding how users, devices, and systems behave. By learning the normal patterns of identity and network activity, Darktrace helps teams identify when access is being misused or when activity begins to move beyond expected boundaries. This makes it possible to detect and contain lateral movement early, limiting how far an attacker can progress even after initial access.

Detecting and containing threats at the earliest stage  

As AI accelerates vulnerability discovery, defenders need to identify exploitation before it is formally recognized. Darktrace’s behavioral understanding approach enables detection of subtle deviations from normal activity, including those linked to previously unknown vulnerabilities.

A key example of this is our research on identifying cyber threats before public CVE disclosures, demonstrating that assessing activity against what is normal for a specific environment, rather than relying on predefined indicators of compromise, enables detection of intrusions exploiting previously unknown vulnerabilities days or even weeks before details become publicly available.

Additionally, our Autonomous Response capability provides fast, targeted containment focused on the most concerning events, while allowing normal business operations to continue. This has consistently shown that even when attackers use techniques never seen before, Darktrace’s Autonomous Response can contain threats before they have a chance to escalate.

Scaling response without increasing operational burden

As early-stage incidents become more frequent, the ability to investigate and respond efficiently becomes critical. Darktrace’s Cyber AI Analyst’s AI-driven investigation capabilities automatically correlate activity across the environment, prioritizing the most significant threats and reducing the need for manual triage. This allows security teams to respond faster and more consistently, without increasing workload or burnout.

What effective defense looks like in an AI-accelerated landscape

Developments like Mythos highlight a reality that has been building for some time: the window between exposure and exploitation is shrinking, and in many cases, it may disappear entirely. In that environment, relying on patching alone becomes increasingly reactive, leaving little room to respond once access has been established.

The more durable approach is to assume that compromise will occur and focus on controlling what happens next. That means identifying early signs of misuse, containing threats before they spread, and maintaining visibility across the environment so that isolated signals can be understood in context.

AI plays a role on both sides of this equation. While it enables attackers to move faster, it also gives defenders the ability to detect subtle changes in behavior, prioritize what matters, and respond in real time. The advantage will not come from adopting AI in isolation, but from applying it in a way that reduces the gap between detection and action.

AI may be accelerating parts of the attack lifecycle, but the fundamentals of defense, detection, and containment still apply. If anything, they matter more than ever – and AI is just as powerful a tool for defenders as it is for attackers.

To learn more about Darktrace and Mythos read more on our blog: Mythos vs Ethos: Defending in an Era of AI‑Accelerated Vulnerability Discovery

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About the author
Toby Lewis
Head of Threat Analysis
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