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April 10, 2025

Email bombing exposed: Darktrace’s email defense in action

Darktrace detected an email bomb attack flooding inboxes with high volumes of messages, uncovering unusual email patterns and subsequent network anomalies.
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
Maria Geronikolou
Cyber Analyst
Written by
Ryan Traill
Content Manager - Digital Customer Success
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10
Apr 2025

What is email bombing?

An email bomb attack, also known as a "spam bomb," is a cyberattack where a large volume of emails—ranging from as few as 100 to as many as several thousand—are sent to victims within a short period.

How does email bombing work?

Email bombing is a tactic that typically aims to disrupt operations and conceal malicious emails, potentially setting the stage for further social engineering attacks. Parallels can be drawn to the use of Domain Generation Algorithm (DGA) endpoints in Command-and-Control (C2) communications, where an attacker generates new and seemingly random domains in order to mask their malicious connections and evade detection.

In an email bomb attack, threat actors typically sign up their targeted recipients to a large number of email subscription services, flooding their inboxes with indirectly subscribed content [1].

Multiple threat actors have been observed utilizing this tactic, including the Ransomware-as-a-Service (RaaS) group Black Basta, also known as Storm-1811 [1] [2].

Darktrace detection of email bombing attack

In early 2025, Darktrace detected an email bomb attack where malicious actors flooded a customer's inbox while also employing social engineering techniques, specifically voice phishing (vishing). The end goal appeared to be infiltrating the customer's network by exploiting legitimate administrative tools for malicious purposes.

The emails in these attacks often bypass traditional email security tools because they are not technically classified as spam, due to the assumption that the recipient has subscribed to the service. Darktrace / EMAIL's behavioral analysis identified the mass of unusual, albeit not inherently malicious, emails that were sent to this user as part of this email bombing attack.

Email bombing attack overview

In February 2025, Darktrace observed an email bombing attack where a user received over 150 emails from 107 unique domains in under five minutes. Each of these emails bypassed a widely used and reputable Security Email Gateway (SEG) but were detected by Darktrace / EMAIL.

Graph showing the unusual spike in unusual emails observed by Darktrace / EMAIL.
Figure 1: Graph showing the unusual spike in unusual emails observed by Darktrace / EMAIL.

The emails varied in senders, topics, and even languages, with several identified as being in German and Spanish. The most common theme in the subject line of these emails was account registration, indicating that the attacker used the victim’s address to sign up to various newsletters and subscriptions, prompting confirmation emails. Such confirmation emails are generally considered both important and low risk by email filters, meaning most traditional security tools would allow them without hesitation.

Additionally, many of the emails were sent using reputable marketing tools, such as Mailchimp’s Mandrill platform, which was used to send almost half of the observed emails, further adding to their legitimacy.

 Darktrace / EMAIL’s detection of an email being sent using the Mandrill platform.
Figure 2: Darktrace / EMAIL’s detection of an email being sent using the Mandrill platform.
Darktrace / EMAIL’s detection of a large number of unusual emails sent during a short period of time.
Figure 3: Darktrace / EMAIL’s detection of a large number of unusual emails sent during a short period of time.

While the individual emails detected were typically benign, such as the newsletter from a legitimate UK airport shown in Figure 3, the harmful aspect was the swarm effect caused by receiving many emails within a short period of time.

Traditional security tools, which analyze emails individually, often struggle to identify email bombing incidents. However, Darktrace / EMAIL recognized the unusual volume of new domain communication as suspicious. Had Darktrace / EMAIL been enabled in Autonomous Response mode, it would have automatically held any suspicious emails, preventing them from landing in the recipient’s inbox.

Example of Darktrace / EMAIL’s response to an email bombing attack taken from another customer environment.
Figure 4: Example of Darktrace / EMAIL’s response to an email bombing attack taken from another customer environment.

Following the initial email bombing, the malicious actor made multiple attempts to engage the recipient in a call using Microsoft Teams, while spoofing the organizations IT department in order to establish a sense of trust and urgency – following the spike in unusual emails the user accepted the Teams call. It was later confirmed by the customer that the attacker had also targeted over 10 additional internal users with email bombing attacks and fake IT calls.

The customer also confirmed that malicious actor successfully convinced the user to divulge their credentials with them using the Microsoft Quick Assist remote management tool. While such remote management tools are typically used for legitimate administrative purposes, malicious actors can exploit them to move laterally between systems or maintain access on target networks. When these tools have been previously observed in the network, attackers may use them to pursue their goals while evading detection, commonly known as Living-off-the-Land (LOTL).

Subsequent investigation by Darktrace’s Security Operations Centre (SOC) revealed that the recipient's device began scanning and performing reconnaissance activities shortly following the Teams call, suggesting that the user inadvertently exposed their credentials, leading to the device's compromise.

Darktrace’s Cyber AI Analyst was able to identify these activities and group them together into one incident, while also highlighting the most important stages of the attack.

Figure 5: Cyber AI Analyst investigation showing the initiation of the reconnaissance/scanning activities.

The first network-level activity observed on this device was unusual LDAP reconnaissance of the wider network environment, seemingly attempting to bind to the local directory services. Following successful authentication, the device began querying the LDAP directory for information about user and root entries. Darktrace then observed the attacker performing network reconnaissance, initiating a scan of the customer’s environment and attempting to connect to other internal devices. Finally, the malicious actor proceeded to make several SMB sessions and NTLM authentication attempts to internal devices, all of which failed.

Device event log in Darktrace / NETWORK, showing the large volume of connections attempts over port 445.
Figure 6: Device event log in Darktrace / NETWORK, showing the large volume of connections attempts over port 445.
Darktrace / NETWORK’s detection of the number of the login attempts via SMB/NTLM.
Figure 7: Darktrace / NETWORK’s detection of the number of the login attempts via SMB/NTLM.

While Darktrace’s Autonomous Response capability suggested actions to shut down this suspicious internal connectivity, the deployment was configured in Human Confirmation Mode. This meant any actions required human approval, allowing the activities to continue until the customer’s security team intervened. If Darktrace had been set to respond autonomously, it would have blocked connections to port 445 and enforced a “pattern of life” to prevent the device from deviating from expected activities, thus shutting down the suspicious scanning.

Conclusion

Email bombing attacks can pose a serious threat to individuals and organizations by overwhelming inboxes with emails in an attempt to obfuscate potentially malicious activities, like account takeovers or credential theft. While many traditional gateways struggle to keep pace with the volume of these attacks—analyzing individual emails rather than connecting them and often failing to distinguish between legitimate and malicious activity—Darktrace is capable of identifying and disrupting these sophisticated attacks.

Thanks to its Self-Learning AI and Autonomous Response capabilities, Darktrace ensures that even seemingly benign email activity is not lost in the noise.

Credit to Maria Geronikolou (Cyber Analyst and SOC Shift Supervisor) and Cameron Boyd (Cyber Security Analyst), Steven Haworth (Senior Director of Threat Modeling), Ryan Traill (Content Manager)

[related-resource]

Appendices

[1] https://www.microsoft.com/en-us/security/blog/2024/05/15/threat-actors-misusing-quick-assist-in-social-engineering-attacks-leading-to-ransomware/

[2] https://thehackernews.com/2024/12/black-basta-ransomware-evolves-with.html

Darktrace Models Alerts

Internal Reconnaissance

·      Device / Suspicious SMB Scanning Activity

·      Device / Anonymous NTLM Logins

·      Device / Network Scan

·      Device / Network Range Scan

·      Device / Suspicious Network Scan Activity

·      Device / ICMP Address Scan

·      Anomalous Connection / Large Volume of LDAP Download

·      Device / Suspicious LDAP Search Operation

·      Device / Large Number of Model Alerts

Get the latest insights on emerging cyber threats

This report explores the latest trends shaping the cybersecurity landscape and what defenders need to know in 2025

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
Maria Geronikolou
Cyber Analyst
Written by
Ryan Traill
Content Manager - Digital Customer Success

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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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June 29, 2026

How Darktrace Transformed Cybersecurity at Our Health Center: A CIO’s Perspective

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How Darktrace Transformed Cybersecurity at Our Health Center: A CIO’s Perspective

In my role as CIO, I bring years of experience leading IT for healthcare organizations. I’ve seen firsthand the unique cybersecurity challenges that nonprofit health centers face: limited budgets, small IT teams, and the constant pressure to prioritize patient care over technology investments. Yet, the threat landscape for health is relentless, and the stakes for protecting patient data and ensuring operational continuity have never been higher. It’s a balancing act.

The search for a better solution

Like many nonprofits, organizations I work at start with Microsoft’s security stack. The discounted pricing for nonprofits makes it an obvious choice, and Microsoft Defender provided a solid foundation for endpoint and email security. However, I quickly realized that relying on a single vendor, even one as robust as Microsoft, left gaps in our defenses. Cybersecurity is never one-size-fits-all, which is why my preference was to layer an additional solution on top of our native security to improve our security posture.

Teams needed a solution that could layer seamlessly on top of Microsoft, without adding complexity or draining limited resources. That’s when I found Darktrace. I had heard of their reputation after seeing how other organizations used Darktrace to secure their infrastructure and was impressed by their AI-native, agentless approach and agreed to a proof of value (POV).

Our goal was to elavate Microsoft with an additional layer of intelligence- one that could seamlessly integrate, operate autonomously, and support a small team without increasing overhead. We turned to Darktrace because its AI-native, agentless approach offered a fundamentally different way to detect and respond to threats, learning our environment in real time and filling gaps that traditional tools can miss. With a quick POV, we were able to validate how effectively Darktrace works alongside Microsoft to deliver a more complete and resilient security architecture.

Why Darktrace stood out

From the start, Darktrace differentiated itself in several critical ways:

  • Deep visibility: Unlike other solutions that rely simply on host-based monitoring with endpoint agents, Darktrace operates passively at the network layer and integrates via APIs for email and identity security. This gave full visibility into network traffic that we previously didn’t have, going beyond our existing endpoint-based tools without adding additional maintenance overhead for our small IT team.
  • AI-native from the ground up: Darktrace wasn’t just layering AI on top of an existing product; it was built with AI at its core. Their autonomous detection and response to threats immediately reduced the need for constant human supervision. In a world where cyber-attacks are increasingly sophisticated and subtle, having an AI that learns our environment and adapts in real time is invaluable.
  • Comprehensive coverage: We started with a POV focused on email security, but quickly expanded to full deployment across our entire infrastructure. Darktrace’s products now protect our email, network, and identity layers, providing visibility and defense against lateral movement and abnormal behavior that traditional tools often miss.

Integration and workflow: Smooth and simple

One of the most impressive aspects of Darktrace is how easy it was to integrate into an existing environment. For network security, it was as simple as plugging an appliance into our top-of-rack switch – no downtime, no complex configuration. For email and identity, API integrations meant we could be up and running in hours, not weeks.

This simplicity extended to day-to-day operations. Our IT team received regular security reports, and any time we had questions or needed to adjust policies, Darktrace’s support team was there with white-glove service. Their responsiveness- even in the middle of the night- gave us confidence that we had true partners, not just a vendor.

Real-world impact: Threats stopped, time saved

The results spoke for themselves. During the time with Darktrace, I did not experience any security incidents. The team slept better at night knowing that Darktrace was monitoring for anomalies and proactively blocking suspicious activity, alerting us even before we noticed anything was wrong.

A memorable example was during an Electronic Health Record (EHR) upgrade, when my team forgot to adjust the policy in advance. Darktrace’s autonomous response was so effective that it blocked our upgrade activities- proof that nothing, not even internal changes, could slip by unnoticed. This level of vigilance meant that ransomware, data exfiltration attempts, or insider threats would be detected and contained before causing harm.

While I can’t share specific ROI numbers, the value was clear: we’ve avoided costly breaches, reduced the time spent investigating alerts, and eliminated the performance drag of agent-based tools. With Darktrace layered on top of Microsoft, I’ve hit the right balance of maximum protection with minimal spending. The cost of Darktrace / EMAIL was competitive, especially when factoring in the included Managed Detection and Response (MDR) service, which provides expert human oversight on top of the AI.

Key differentiators over the competition

  • Extending visibility beyond the endpoint: Traditional host-based monitoring solutions, such as EDR, play a critical role in securing individual devices. By adding a network detection and response (NDR) layer, we gained visibility into activity across our wider digital environment, surfacing threats that move laterally, operate between devices, or bypass endpoint controls. Darktrace also stood out for its ability to learn our normal patterns of behavior and identify subtle deviations in real time, not just known indicators of compromise. Because this is delivered through passive, non-disruptive monitoring, we were able to strengthen our defenses without adding complexity or impacting performance.
  • Layered security without complexity: Darktrace elevated our Microsoft foundation without creating conflicts or requiring us to disable existing protections. This layered approach maximized our security posture without adding operational burden.
  • Expert partnership: Beyond technology, Darktrace’s team acted as true partners, guiding us through deployment, providing ongoing support, and helping us interpret findings. This partnership was as valuable as the technology itself.

Advice for other nonprofits

If you’re an IT leader in a nonprofit, my advice is simple: look for solutions that are easy to deploy, intelligent in their response, and cost-effective. Don’t settle for more endpoint based tools that overlap with what you already have. Seek out a layered approach that covers your blind spots – especially at the network and email layers- at a price point that suits your organization.

Most importantly, don’t be afraid to evaluate new solutions. Even if you’re inundated with vendor pitches, you owe it to your organization to explore options that could save you time, money, and sleepless nights.

For organizations I work at, combining Microsoft’s security stack with Darktrace’s AI-native, platform struck the right balance between protection and practicality. We gained enterprise-grade security without sacrificing performance or stretching our budget. In the end, that meant more resources for what matters most: delivering care to our patients. If you’re facing similar challenges, I encourage you to consider how Darktrace could transform your security posture, and give your team the peace of mind they deserve.

For the organization I work in, combining Microsoft with Darktrace delivered a clear step-change in our security posture. Microsoft provided the foundation, while Darktrace’s behavioral intelligence added visibility into the unknown, surfacing emerging threats based on deviations in real-time activity, not just known indicators.

The result was enterprise-grade protection without added overhead, allowing us to stay focused on patient outcomes, not security operations. For organizations facing similar pressures, this layered approach offers a smarter, more efficient path to securing modern environments.

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About the author
Mice Chen
Chief Information Security Officer
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