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February 2, 2022

Why AAA Washington Chose Autonomous Response

Learn how AAA Washington improved cybersecurity with an autonomous response. Explore the reasons and benefits behind this strategic decision.
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
Ron Nichols
Senior Information Security Analyst at AAA Washington (Guest Contributor)
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02
Feb 2022

AAA Washington is best known for its emergency road service, but operates in a broader range of areas including insurance and travel. Our priorities from a security side are two-fold: making sure we are adequately prepared to defend against advanced and pertinent threats like ransomware, and protecting the sensitive data of our employees and our members.

About two years ago, we hit a fork in the road. Our information security team was conscious that we had a gap in real-time monitoring, and in particular, 24/7 response. It wasn’t that we didn’t already have tools in place, or that we weren’t shipping logs, we just didn’t have a 24/7 protocol. So if an attack were to come in at 3am, for example, we weren’t confident enough in our ability to take immediate action to contain the threat.

So we looked at two options. It was our Matrix ‘red pill or blue pill’ moment: a choice between the willingness to learn a life-changing truth by taking the red pill, or taking the blue pill and opting for the more traditional path.

For us, that blue pill – and what many recommended at the time – was the option of consulting an external 24/7 Security Operations Center. We knew this would solve our problem, but it also had a lot of drawbacks, mainly around time consumption: you have to get a service-level agreement (SLA) in place, set up SNMP traps, ship logs over to the SOC, who are then tasked with untangling those logs. You know that the SOC is then looking at AAA Washington’s environment along with hundreds of others. You’ve got to develop a relationship with the SOC technician who doesn’t know the nuances of your environment or your business logic…

So understandably there was a level of reluctance there.

And then we had the red pill, which for us, was Darktrace, offering AI technology that could learn our environment all by itself, and respond autonomously to emerging attacks. No steep learning curve, no ongoing maintenance.

We had to try it. Cloud deployments are available but even for our on-prem arrangement, the trial process was a no-brainer: we got the box, plugged it in, and we were off and going. If we didn’t like it, all we had to do was unplug it and ship it back.

The visibility Darktrace gave us was immediately apparent, and in that first week it alerted us to the fact that every other night, 1GB of outbound traffic was going to an East Coast data center from our back-up appliance. We thought we knew what was going on in our digital enterprise, but we had no idea – Darktrace providing that knowledge and filling those gaps showed us that this was heading exactly in the direction we wanted.

Autonomous Response

So full marks for visibility and anomaly detection, but what about that response capability that led us to consider Darktrace in the first place? We were keen to see what actions Antigena would recommend and assess their accuracy and severity.

Being naturally risk-averse at AAA Washington, we initially set Antigena up in human confirmation mode, meaning an operator had to give the green light before it took action. It took about two weeks for it to learn the nuances of our digital environment, and it wasn’t long before we found its actions were extremely accurate, and minimally disruptive.

It never took drastic action like quarantining a device, it simply stopped what we needed it to. It played a significant role in protecting us in the wake of some high-profile attacks, including the SUNBURST attacks and the more recent Log4shell vulnerability.

Adapting to a hybrid cloud strategy

In the two years since deploying Darktrace, we have made significant changes to our digital infrastructure – including, like so many others, migrating to the cloud. I wondered whether we would lose the visibility and protection we got from Darktrace when this happened.

But with its dedicated SaaS Modules for Microsoft 365 and others, Darktrace had this covered. It’s been able to shed a light on malicious activity occurring across our full Microsoft 365 product suite.

We can see things like unusual email forwarding rules that indicate an account takeover. With other tools, it takes six to eight clicks to find that information. The information is available, but accessing that data is a complex and convoluted process. Darktrace delivers that holy grail of having a single pane of glass view in a security tool. Having that detailed one stop view means reducing mean time to understanding, and mean time to response.

Self-Learning AI on the endpoint

And when large-scale remote working came about, Darktrace again brought visibility and Autonomous Response to cover our endpoint devices, protecting them from threats like ransomware that would go undetected from network coverage alone. The ability to stop these threats at the first hurdle, before they spread and infected other devices, was crucial for us.

It was another case of Darktrace adapting, and another reason I’m confident about working with Darktrace as a long-term partner: every time I think Darktrace is going to not be as relevant, these new developments bring us up to speed.

Keeping the show on the road

Darktrace has done exactly what we wanted to do by filling that gap we had in 24/7 response. But it has gone further by proving that time and time again, it can adapt as our digital infrastructure changes and grows, and can cover our employees wherever they work.

The technology presents us with all the information we need in a single pane of glass with the Threat Visualizer. With the Mobile App, I can get notifications of high-priority alerts and Darktrace’s autonomous actions, wherever I am. And when there’s a serious incident, there is always someone available to offer support and get me what I need to know, fast.

Taking that red pill all those months ago was one of the best decisions I’ve made as an IT security professional. Whatever challenges are down the road, I’m confident Darktrace will be there to meet them.

Hear from more Darktrace customers

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
Ron Nichols
Senior Information Security Analyst at AAA Washington (Guest Contributor)

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April 16, 2025

Why Data Classification Isn’t Enough to Prevent Data Loss

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Why today’s data is fundamentally difficult to protect

Data isn’t what it used to be. It’s no longer confined to neat rows in a database, or tucked away in a secure on-prem server. Today, sensitive information moves freely between cloud platforms, SaaS applications, endpoints, and a globally distributed workforce – often in real time. The sheer volume and diversity of modern data make it inherently harder to monitor, classify, and secure. And the numbers reflect this challenge – 63% of breaches stem from malicious insiders or human error.

This complexity is compounded by an outdated reliance on manual data management. While data classification remains critical – particularly to ensure compliance with regulations like GDPR or HIPAA – the burden of managing this data often falls on overstretched security teams. Security teams are expected to identify, label, and track data across sprawling ecosystems, which can be time-consuming and error-prone. Even with automation, rigid policies that depend on pre-defined data classification miss the mark.

From a data protection perspective, if manual or basic automated classification is the sole methodology for preventing data loss, critical data will likely slip through the cracks. Security teams are left scrambling to fill the gaps, facing compliance risks and increasing operational overhead. Over time, the hidden costs of these inefficiencies pile up, draining resources and reducing the effectiveness of your entire security posture.

What traditional data classification can’t cover

Data classification plays an important role in data loss prevention, but it's only half the puzzle. It’s designed to spot known patterns and apply labels, yet the most common causes of data breaches don’t follow rules. They stem from something far harder to define: human behavior.

When Darktrace began developing its data loss detection capabilities, the question wasn’t what data to protect — it was how to understand the people using it. The numbers pointed clearly to where AI could make the biggest difference: 22% of email data breaches stem directly from user error, while malicious insider threats remain the most expensive, costing organizations an average of $4.99 million per incident.

Data classification is blind to nuance – it can’t grasp intent, context, or the subtle red flags that often precede a breach. And no amount of labeling, policy, or training can fully account for the reality that humans make mistakes. These problems require a system that sees beyond the data itself — one that understands how it’s being used, by whom, and in what context. That’s why Darktrace leans into its core strength: detecting the subtle symptoms of data loss by interpreting human behavior, not just file labels.

Achieving autonomous data protection with behavioral AI

Rather than relying on manual processes to understand what’s important, Darktrace uses its industry-leading AI to learn how your organization uses data — and spot when something looks wrong.

Its understanding of business operations allows it to detect subtle anomalies around data movement for your use cases, whether that’s a misdirected email, an insecure cloud storage link, or suspicious activity from an insider. Crucially, this detection is entirely autonomous, with no need for predefined rules or static labels.

Darktrace uses its contextual understanding of each user to stop all types of sensitive or misdirected data from leaving the organization
Fig 1: Darktrace uses its contextual understanding of each user to stop all types of sensitive or misdirected data from leaving the organization

Darktrace / EMAIL’s DLP add-on continuously learns in real time, enabling:

  • Automatic detection: Identifies risky data behavior to catch threats that traditional approaches miss – from human error to sophisticated insider threats.
  • A dynamic range of actions: Darktrace always aims to avoid business disruption in its blocking actions, but this can be adjusted according to the unique risk appetite of each customer – taking the most appropriate response for that business from a whole scale of possibilities.
  • Enhanced context: While Darktrace doesn’t require sensitivity data labeling, it integrates with Microsoft Purview to ingest sensitivity labels and enrich its understanding of the data – for even more accurate decision-making.

Beyond preventing data loss, Darktrace uses DLP activity to enhance its contextual understanding of the user itself. In other words, outbound activity can be a useful symptom in identifying a potential account compromise, or can be used to give context to that user’s inbound activity. Because Darktrace sees the whole picture of a user across their inbound, outbound, and lateral mail, as well as messaging (and into collaboration tools with Darktrace / IDENTITY), every interaction informs its continuous learning of normal.

With Darktrace, you can achieve dynamic data loss prevention for the most challenging human-related use cases – from accidental misdirected recipients to malicious insiders – that evade detection from manual classification. So don’t stand still on data protection – make the switch to autonomous, adaptive DLP that understands your business, data, and people.

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About the author
Carlos Gray
Senior Product Marketing Manager, Email

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April 14, 2025

Email bombing exposed: Darktrace’s email defense in action

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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 able to identify and stop these sophisticated attacks without latency.

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 (Analyst Content Lead)

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

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About the author
Maria Geronikolou
Cyber Analyst
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