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September 30, 2020

Exploring AI Email Security & Human Behavior

Read how Darktrace AI is revolutionizing email security. Understand the human behavior of email attacks and how to mitigate your team's malware risks.
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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30
Sep 2020

At the heart of any email attack is the goal of moving the recipient to engage: whether that’s clicking a link, filling in a form, or opening an attachment. And with over nine in ten cyber-attacks starting with an email, this attack vector continues to prove successful, despite organizations’ best efforts to safeguard their workforce by deploying email gateways and training employees to spot phishing attempts.

Email attackers have seen such success because they understand their victims. They know that, ultimately, human beings are creatures of habit, prone to error, and susceptible to their emotions. Years of experience has allowed attackers to fine tune their emails making them more plausible and more provocative. Automated tools are now increasing the speed and scale at which criminals can buy new domains and send emails en masse. This makes it even easier to ‘A/B test’ attack methods: abandoning those that don’t see high success rates and capitalizing on those that do.

We can classify phishing attempts into five broad categories, each aiming to trigger a different emotional reaction and elicit a response.

  • Fear: “We have detected a virus on your device, log in to your McAfee account.”
  • Curiosity: “You have 3 new voicemails, click here.”
  • Generosity: “COVID-19 has greatly impacted homelessness in your area. Donate now.”
  • Greed: “Only 23 iPhones left to give away, act now!”
  • Concern: “Coronavirus outbreak in your area: Find out more.”

It’s worth noting that today’s increasingly dynamic workforces are more susceptible to these techniques, isolated in their homes and hungry for new information.

Turning to tech

As email attacks continue to trick employees and find success, many organizations have realized that the built-in security tools that come with their email provider aren’t enough to defend against today’s attacks. Additional email gateways are successful in catching spam and other low-hanging fruit, but fail to stop advanced attacks – particularly those leveraging novel malware, new domains, or advanced techniques. These advanced attacks are also the most damaging to businesses.

This failure is due to an inherent weakness in the legacy approach of traditional security tools. They compare inbound mail against lists of ‘known bad’ IPs, domains, and file hashes. Senders and recipients are treated simply as data points – ignoring the nuances of the human beings behind the keyboards.

Looking at these metrics in isolation fails to take into account the full context that can only be gained by understanding the people behind email interactions: where they usually log in from, who they communicate with, how they write, and what types of attachments they send and receive. It is this rich, personal context that reveals seemingly benign emails to be unmistakably malicious, especially when other data fails to reveal the danger.

Misunderstanding the human

Frustrated with the ineffectiveness of traditional tools, many organizations think that the solution is to minimize the chances that employees engage with malicious emails through comprehensive employee training. Indeed, companies often attempt to train their employees to spot malicious emails to compensate for their technology’s lack of detection.

Considering humans to be the last line of defense is dangerous, and this approach overlooks the fact that today’s sophisticated fakes can appear indistinguishable to legitimate mails. It's only when you really break an email down beyond the text, beyond the personal name, beyond the domain and email address (in the case of compromised trusted senders), that you can decipher between real and fake.

Large data breaches of recent years have given attackers greater access than ever to corporate emails and stolen passwords, and so supply chain attacks are becoming increasingly common. When attackers take over a trusted account or an existing email thread, how can an employee be expected to notice a subtle change in wording or the different type of attached document? However rigorous the internal training program and regardless of how vigilant employees are, we are now at the point where humans cannot spot these very subtle indicators. And one click is all it takes.

Understanding the human

Email security, for a long time, remains an unsolved piece of the complex cyber security puzzle. The failure of both traditional tools and employee training has prompted organizations to take a radically different approach. Thousands of businesses across the world, in both the public and private sector, use artificial intelligence that understands the human behind the keyboard and forms a nuanced and continually evolving understanding of email interactions across the business.

By learning what a human does, who they interact with, how they write, and the substance of a typical conversation between any two or more people, AI begins to understand the habits of employees, and over time it builds a comprehensive picture of their normal patterns of behavior. Most importantly, AI is self-learning, continuously revising its understanding of ‘normal’ so that when employees’ habits change, so does the AI’s understanding.

This enables the technology to detect behavioral anomalies that fall outside of an employee’s ‘pattern of life’, or the pattern of life for the organization as a whole.

This fundamentally new approach to email security enables the system to recognize the subtle indicators of a threat and make accurate decisions to stop or allow emails to pass through, even if a threat has never been seen before.

Sitting behind email gateways, this self-learning technology has extremely high catch rates. It has caught countless malicious emails that other tools missed, from impersonations of senior financial personnel to ‘fearware’ that played on the workforce’s uncertainties at a time of pandemic.

Attackers are continuing to innovate, and automation has led to a new wave of email threats. 88% of security leaders now believe that cyber-attacks powered by offensive AI are inevitable. The email threat landscape is rapidly changing, and we can expect to receive more hoax emails that are more convincing. Now is a crucial moment for organizations to prepare for this eventuality by adopting AI in their email defenses.

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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December 4, 2025

How Darktrace is ending email security silos with new capabilities in cross-domain detection, DLP, and native Microsoft integrations

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A new era of reputation-aware, unified email security

Darktrace / EMAIL is redefining email defense with new innovations that close email security silos and empower SOC teams to stop multi-stage attacks – without disrupting business operations.  

By extending visibility across interconnected domains, Darktrace catches the 17% of threats that leading SEGs miss, including multi-stage attacks like email bombing and cloud platform abuse. Its label-free behavioral DLP protects sensitive data without reliance on manual rules or classification, while DMARC strengthens brand trust and authenticity. With native integrations for Microsoft Defender and Security Copilot, SOC teams can now investigate and respond faster, reducing risk and maintaining operational continuity across the enterprise.

Summary of what’s new:

  • Cross-domain AI-native detection unifying email, identity, and SaaS
  • Label-free behavioral DLP for effortless data protection
  • Microsoft Defender and Security Copilot integrations for streamlined investigation and response

Why email security must evolve

Today’s attacks don’t stop at the inbox. They move across domains – email to identity, SaaS, and network – exploiting the blind spots between disconnected tools. Yet most email security solutions still operate in isolation, unable to see or respond beyond the message itself.

In 2024, Darktrace detected over 30 million phishing attempts: 38% targeting high-value individuals and almost a third using novel social engineering, including AI-generated text. Generative AI is amplifying the realism and scale of social engineering, while customers face a wave of new techniques like email bombing, where attackers flood inboxes to distract or manipulate users, and polymorphic malware, which continuously evolves to evade static defenses.

Meanwhile, defenders are exposed to traditional DLP tools that create operational drag with high false positives and rigid policies. Accidental insider breachers remain a major risk to organizations: 6% of all data breaches are caused by misdelivery, and 95% of those incidents involve personal data.

Tool sprawl compounds the issue. The average enterprise manages around 75 security products, and 69% report operational strain as a result. This complexity is counterproductive – and with legacy SEGs failing to adapt to detect threats that exploit human behavior, analysts are left juggling an unwieldy patchwork of fragmented defenses.

The bottom line? Siloed email defenses can’t keep pace with today’s AI-driven, cross domain attacks.

Beyond detection: AI built for modern threats

Darktrace / EMAIL is uniquely designed to catch the threats SEGs miss, powered by Self-Learning AI. It learns the communication patterns of every user – correlating behavioral signals from email, identity, and SaaS – to identify the subtle, context-driven deviations that define advanced social engineering and supply chain attacks.

Unlike tools that rely on static rules or historical attack data, Darktrace’s AI assumes a zero trust posture, treating every interaction as a potential risk. It detects novel threats in real time, including those that exploit trusted relationships or mimic legitimate business processes. And because Darktrace’s technology is natively unified, it delivers precise, coordinated responses that neutralize threats in real time.

Powerful innovations to Darktrace / EMAIL

Improved, multi-domain threat detection and response

With this update, Darktrace reveals multi-domain detection linking behavioral signals across email, identity, and SaaS to uncover advanced attacks. Darktrace leverages its existing agentic platform to understand behavioral deviations in any communication channel and take precise actions regardless of the domain.  

This innovation enables customers to:

  • Correlate behavioral signals across domains to expose cross-channel threats and enable coordinated response
  • Link email and identity intelligence to neutralize multi-stage attacks, including advanced email bombing campaigns

Detection accuracy is further strengthened through layering with traditional threat intelligence:

  • Integrated antivirus verdicts improve detection efficacy by adding traditional file scanning
  • Structured threat intelligence (STIX/TAXII) enriches alerts with global context for faster triage and prioritization

Expanded ecosystem visibility also includes:

  • Salesforce integration, enabling automatic action on potentially malicious tickets auto-created from emails – accelerating threat response and reducing manual burden

Advancements in label-free DLP

Darktrace is delivering the industry’s first label-free data loss prevention (DLP) solution powered by a proprietary domain specific language model (DSLM).  

This update expands DLP to protect against both secrets and personally identifiable information (PII), safeguarding sensitive data without relying on status rules or manual classification. The DSLM is tuned for email/DLP semantics so it understands entities, PII patterns, and message context quickly enough to enforce at send time.

Key enhancements include:

  • Behaviorally enhanced PII detection that automatically defines over 35+ new categories, including personal, financial, and health data  
  • Added detail to DLP alerts in the UI, showing exactly how and when DLP policies were applied
  • Enhanced Cyber AI Analyst narratives to explain detection logic, making it easier to investigate and escalate incidents

And for further confidence in outbound mail, discover new updates to DMARC, with support for BIMI logo verification, automatic detection of both MTA-STS and TLS records, and data exports for deeper analysis and reporting. Accessible for all organizations, available now on the Azure marketplace.

Streamlined SOC workflows, with Microsoft-native integrations

This update introduces new integrations that simplify SOC operations, unify visibility, and accelerate response. By embedding directly into the Microsoft ecosystem – with Defender and Security Copilot – analysts gain instant access to correlated insights without switching consoles.

New innovations include:

  • Unified quarantine management with Microsoft Defender, centralizing containment within the native Microsoft interface and eliminating console hopping
  • Ability to surface threat insights directly in Copilot via the Darktrace Email Analysis Agent, eliminating data hunting and simplifying investigations
  • Automatic ticket creation in JIRA when users report suspicious messages
  • Sandbox analysis integration, enabling payload inspection in isolated environments directly from the Darktrace UI

Committed to innovation

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

  1. Major innovations in cloud security with the launch of the industry’s first fully automated cloud forensics solution, reinforcing Darktrace’s leadership in AI-native security.
  2. Redefining NDR with industry-first autonomous threat investigation from network to endpoint  
  3. Innovations to our suite of Exposure Management & Attack Surface Management tools

As attackers exploit gaps between tools, the Darktrace ActiveAI Security Platform delivers unified detection, automated investigation, and autonomous response across cloud, endpoint, email, network, and OT. With full-stack visibility and AI-native workflows, Darktrace empowers security teams to detect, understand, and stop novel threats before they escalate.

Join our Live Launch Event

When? December 9, 2025

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

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About the author
Carlos Gray
Senior Product Marketing Manager, Email

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December 4, 2025

The 17% of email threats SEGs miss – and how Darktrace catches them

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17%: The figure that changes your risk math

Most organizations deploy a Secure Email Gateway (SEG) assuming it will catch whatever their native email security provider would not be able to. But the data tells a different story. Nearly one in six of the riskiest inbound emails still evade the native + SEG layers on the first pass – 17% is the average SEG miss rate after Microsoft filtering.  

How did we calculate the miss rate? The figure comes from a volume-weighted analysis of real-world enterprise deployments where Darktrace operated alongside a SEG, compared to deployments without a SEG. It’s based on how each security layer treated malicious emails on the first instance – if the SEG missed the email at the initial filtering but caught it minutes or hours later we considered it a miss, because the threat had already been exposed to the user. We computed the mean per category miss count across the top three widely deployed SEGs and divided that by the total number of threats that had already bypassed native filters. The resulting rate is 17.8%, conservatively communicated as “about 17%.”

This result is a powerful directional signal – not a guarantee for every environment – but significant enough to merit a closer look.

What SEGs miss most (and why it matters)

Our analysis shows that SEGs most frequently miss context-driven, low-signal attacks.

Darktrace catches more threats than SEGs across a range of attack vectors

These are the kinds of emails that look convincing to recipients and rely on business context, without overtly malicious indicators, including:

Solicitation and fraudulent requests (~21% miss rate)

Deceptive invoices, vendor “updates,” payment term changes, or urgent favors. These messages often lack obvious payloads and exploit business process mimicry, making them nearly indistinguishable from genuine correspondence in the eyes of static, rule-based filters dependent on payload analysis. 22% of breaches stemming from external actors were a result of social engineering in 2025 (Verizon 2025 Data Breach Investigations Report).

Phishing links (~20% miss rate)

Links to credential harvesters or later-weaponized sites using new or compromised domains, redirects, or shorteners. URL rotation and staging evade list-based controls; the linguistic and workflow context looks routine. This also includes threats that leverage legitimate cloud platforms to disguise their intent and avoid reputation analysis.  Phishing remains one of the most expensive cause of breaches, an average cost of $4.8 million (IBM Cost of a Data Breach Report 2025).

User impersonation (~19% miss rate)

Convincing messages that mimic executives, colleagues, or partners, often with subtle display-name or address manipulation. These attacks rely on social engineering and context, bypassing static detection and reputation checks.

Other notable misses: Credential harvesting lures and forged/abused sender addresses, both typically light on static indicators but heavy on contextual clues. 

Why SEGs miss these emails

Let’s look at some of the reasons SEGs fail to catch more advanced, context-driven attacks.

  1. Attack-centric bias. SEGs excel at recognizing known-bad indicators (spam, commodity malware). But today’s high-impact threats are supercharged by AI and can be hyper-customized with polymorphic malware or personalized social engineering. They mirror normal business communications and weaponize trust, not binary patterns.  
  2. Limited behavioral understanding. Without modeling each user’s “normal” pattern of life, subtle anomalies (timing, tone, counterpart, transaction patterns) can look benign, even if they should be flagged. Some modern solutions have begun to incorporate behavioral analysis into their products, but these are still supplements for additional information rather than integrated into the core threat detection engine.
  3. Assumed trust. Account compromise and attacks that abuse legitimate services exploit trust. SEGs weren’t designed to handle these kinds of threats, in fact, they assume trust in order to minimize false positives, leaving them wide open to attackers.  
  4. Siloed detection. Email rarely tells the whole story. Attacks pivot across email, identity, and SaaS; single-channel tools can’t connect those dots in real time. This issue is exacerbated when email security vendors are only focused on email activity, ignoring activity beyond the inbox like network or cloud account activity.
  5. Adaptive evasion. Fast domain churn, benign-looking links, and clean hosting on trusted platforms routinely outpace static rules and blocklists. No matter how great your threat intelligence or threat research teams may be, there is a reliance on a first victim – which leads to defenders remaining one step behind attackers. 

How Darktrace / EMAIL catches the threats SEGs miss

Everywhere a SEG falters, Darktrace excels. Let’s take a look why.

  • Self-Learning AI: Darktrace learns the unique communication patterns of every user, department, and supplier, flagging the subtle deviations that typify social engineering and impersonation. 
  • A zero trust approach: According to Gartner, many organizations fail to extend their zero-trust strategy to email, leaving a critical gap. Darktrace assumes no trust, applying the zero trust principle across all aspects of email communication.
  • Cross-domain context: Correlates behavior across email, identity, and SaaS, exposing multi-stage campaigns that a siloed SEG can’t piece together. 
  • Better together with native providers: Operates alongside your native email security – not against it – so protection is additive. Darktrace ingests native signals and orchestrate unified quarantine without duplicating policy stacks or forcing you to disable built-in protections. 

For example: one of our customers, a global enterprise saw a surge of “document-share” notifications from a trusted collaboration platform. The domain and authentication looked fine; their SEG allowed it. Darktrace / EMAIL flagged it because the supplier’s sharing behavior and permission scope deviated from normal (volume, recipients, and access level). Follow-up confirmed the supplier account was compromised. Behavioral context – not rules or signatures – made the difference. 

Three steps to building a modern email security stack

Let’s end with three strategic takeaways for ensuring your email security is fit-for-purpose.

  1. Defense-in-depth = diversity, not duplication

Why it matters: Two security layers with the same detection philosophy (e.g. SEG + native email security) create overlapping blind spots. Both native email security providers and SEGs are attack-centric solutions that rely on past threats and threat intelligence. True defense-in-depth ensures you are asking different questions of every email that comes through.

How to apply: Pair your native email security with behavioral AI that learns how your business communicates. Eliminate redundant layers that only add cost and latency. 

  1. Coordinate the layers you keep

Why it matters:  Layers that don’t talk create delays and hand-offs; SEGs often become sole decision-makers by forcing native protections off. 

How to apply:  Favor an ICES approach that ingests native signals and can orchestrate unified quarantine, so detections become actions in one motion. 

  1. Quantify your security gap with a POV

Why it matters:  Every environment is different. You need evidence before making changes to your stack.

How to apply:  Run Darktrace / EMAIL in observe mode next to your current stack to surface exactly what’s still getting through. Use those results to plan your transition and measure improvement. 

Ready to claim 17% more protection? Request a demo with Darktrace / EMAIL to quantify what your SEG is missing, then decide how much of that residual risk you’re willing to accept. We’ll help you plan a clean, staged transition that preserves native protections and streamlines operations.  In the meantime, calculate your potential ROI using Darktrace / EMAIL with our handy calculator.

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About the author
Carlos Gray
Senior Product Marketing Manager, Email
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