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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
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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 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)

[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

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June 12, 2025

Breaking Silos: Why Unified Security is Critical in Hybrid World

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Hybrid environments demand end-to-end visibility to stop modern attacks

Hybrid environments are a dominant trend in enterprise technology, but they continue to present unique issues to the defenders tasked with securing them. By 2026, Gartner predicts that 75% of organizations will adopt hybrid cloud strategies [1]. At the same time, only 23% of organizations report full visibility across cloud environments [2].

That means a strong majority of organizations do not have comprehensive visibility across both their on-premises and cloud networks. As a result, organizations are facing major challenges in achieving visibility and security in hybrid environments. These silos and fragmented security postures become a major problem when considering how attacks can move between different domains, exploiting the gaps.

For example, an attack may start with a phishing email, leading to the compromise of a cloud-based application identity and then moving between the cloud and network to exfiltrate data. Some attack types inherently involve multiple domains, like lateral movement and supply chain attacks, which target both on-premises and cloud networks.

Given this, unified visibility is essential for security teams to reduce blind spots and detect threats across the entire attack surface.

Risks of fragmented visibility

Silos arise due to separate teams and tools managing on-premises and cloud environments. Many teams have a hand in cloud security, with some common ones including security, infrastructure, DevOps, compliance, and end users, and these teams can all use different tools. This fragmentation increases the likelihood of inconsistent policies, duplicate alerts, and missed threats. And that’s just within the cloud, not even considering the additional defenses involved with network security.

Without a unified security strategy, gaps between these infrastructures and the teams which manage them can leave organizations vulnerable to cyber-attacks. The lack of visibility between on-premises and cloud environments contributes to missed threats and delayed incident response. In fact, breaches involving stolen or compromised credentials take an average of 292 to identify and contain [3]. That’s almost ten months.

The risk of fragmented visibility runs especially high as companies undergo cloud migrations. As organizations transition to cloud environments, they still have much of their data in on-premises networks, meaning that maintaining visibility across both on-premises and cloud environments is essential for securing critical assets and ensuring seamless operations.

Unified visibility is the solution

Unified visibility is achieved by having a single-pane-of-glass view to monitor both on-premises and cloud environments. This type of view brings many benefits, including streamlined detection, faster response times, and reduced complexity.

This can only be accomplished through integrations or interactions between the teams and tools involved with both on-premises security and cloud security.

AI-driven platforms, like Darktrace, are especially well equipped to enable the real-time monitoring and insights needed to sustain unified visibility. This is because they can handle the large amounts of data and data types.

Darktrace accomplishes this by plugging into an organization’s infrastructure so the AI can ingest and analyze data and its interactions within the environment to form an understanding of the organization’s normal behavior, right down to the granular details of specific users and devices. The system continually revises its understanding about what is normal based on evolving evidence.

This dynamic understanding of normal means that the AI engine can identify, with a high degree of precision, events or behaviors that are both anomalous and unlikely to be benign. This helps reduce noise while surfacing real threats, across cloud and on-prem environments without manual tuning.

In this way, given its versatile AI-based, platform approach, Darktrace empowers security teams with real-time monitoring and insights across both the network and cloud.

Unified visibility in the modern threat landscape

As part of the Darktrace ActiveAI Security Platform™, Darktrace / CLOUD works continuously across public, private, hybrid, and multi-cloud deployments. With real-time Cloud Asset Enumeration and Dynamic Architecture Modeling, Darktrace / CLOUD generates up-to-date architecture diagrams, giving SecOps and DevOps teams a unified view of cloud infrastructures.

It is always on the lookout for changes, driven by user and service activity. For example, unusual user activity can significantly raise the asset’s score, prompting Darktrace’s AI to update its architectural view and keep a living record of the cloud’s ever-changing landscape, providing near real-time insights into what’s happening.

This continuous architectural awareness ensures that security teams have a real-time understanding of cloud behavior and not just a static snapshot.

Darktrace / CLOUD’s unified view of AWS and Azure cloud posture and compliance over time.
Figure 1. Darktrace / CLOUD’s unified view of AWS and Azure cloud posture and compliance over time.

With this dynamic cloud visibility and monitoring, Darktrace / CLOUD can help unify and secure environments.

Real world example: Remote access supply chain attacks

Sectop Remote Access Trojan (RAT) malware, also known as ‘ArchClient2,’ is a .NET RAT that contains information stealing capabilities and allows threat actors to monitor and control targeted computers. It is commonly distributed through drive-by downloads of illegitimate software via malvertizing.

Darktrace has been able to detect and respond to Sectop RAT attacks using unified visibility and platform-wide coverage. In one such example, Darktrace observed one device making various suspicious connections to unusual endpoints, likely in an attempt to receive C2 information, perform beaconing activity, and exfiltrate data to the cloud.

This type of supply chain attack can jump from the network to the cloud, so a unified view of both environments helps shorten detection and response times, therefore mitigating potential impact. Darktrace’s ability to detect these cross-domain behaviors stems from its AI-driven, platform-native visibility.

Conclusion

Organizations need unified visibility to secure complex, hybrid environments effectively against threats and attacks. To achieve this type of comprehensive visibility, the gaps between legacy security tools across on-premises and cloud networks can be bridged with platform tools that use AI to boost data analysis for highly accurate behavioral prediction and anomaly detection.

Read more about the latest trends in cloud security in the blog “Protecting Your Hybrid Cloud: The Future of Cloud Security in 2025 and Beyond.”

References:

1. Gartner, May 22, 2023, “10 Strategic Data and Analytics Predictions Through 2028

2. Cloud Security Alliance, February 14, 2024, “Cloud Security Alliance Survey Finds 77% of Respondents Feel Unprepared to Deal with Security Threats

3. IBM, “Cost of a Data Breach Report 2024

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About the author
Pallavi Singh
Product Marketing Manager, OT Security & Compliance

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OT

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June 11, 2025

Proactive OT security: Lessons on supply chain risk management from a rogue Raspberry Pi

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Understanding supply chain risk in manufacturing

For industries running Industrial Control Systems (ICS) such as manufacturing and fast-moving consumer goods (FMCG), complex supply chains mean that disruption to one weak node can have serious impacts to the entire ecosystem. However, supply chain risk does not always originate from outside an organization’s ICS network.  

The implicit trust placed on software or shared services for maintenance within an ICS can be considered a type of insider threat [1], where defenders also need to look ‘from within’ to protect against supply chain risk. Attackers have frequently mobilised this form of insider threat:

  • Many ICS and SCADA systems were compromised during the 2014 Havex Watering Hole attack, where via operators’ implicit trust in the trojanized versions of legitimate applications, on legitimate but compromised websites [2].
  • In 2018, the world’s largest manufacturer of semiconductors and processers shut down production for three days after a supplier installed tainted software that spread to over 10,000 machines in the manufacturer’s network [3].
  • During the 2020 SolarWinds supply chain attack, attackers compromised a version of Orion software that was deployed from SolarWinds’ own servers during a software update to thousands of customers, including tech manufacturing companies such as Intel and Nvidia [4].

Traditional approaches to ICS security have focused on defending against everything from outside the castle walls, or outside of the ICS network. As ICS attacks become more sophisticated, defenders must not solely rely on static perimeter defenses and prevention. 

A critical part of active defense is understanding the ICS environment and how it operates, including all possible attack paths to the ICS including network connections, remote access points, the movement of data across zones and conduits and access from mobile devices. For instance, original equipment manufacturers (OEMs) and vendors often install remote access software or third-party equipment in ICS networks to facilitate legitimate maintenance and support activities, which can unintentionally expand the ICS’ attack surface.  

This blog describes an example of the convergence between supply chain risk and insider risk, when a vendor left a Raspberry Pi device in a manufacturing customer’s ICS network without the customer’s knowledge.

Case study: Using unsupervised machine learning to detect pre-existing security issues

Raspberry Pi devices are commonly used in SCADA environments as low-cost, remotely accessible data collectors [5][6][7]. They are often paired with Industrial Internet of Things (IIoT) for monitoring and tracking [8]. However, these devices also represent a security risk because their small physical size and time-consuming nature of physical inspection makes them easy to overlook. This poses a security risk, as these devices have previously been used to carry out USB-based attacks or to emulate Ethernet-over-USB connections to exfiltrate sensitive data [8][9].

In this incident, a Darktrace customer was unaware that their supplier had installed a Raspberry Pi device on their ICS network. Crucially, the installation occurred prior to Darktrace’s deployment on the customer’s network. 

For other anomaly detection tools, this order of events meant that this third-party device would likely have been treated as part of the customer’s existing infrastructure. However, after Darktrace was deployed, it analyzed the metadata from the encrypted HTTPS and DNS connections that the Raspberry Pi made to ‘call home’ to the supplier and determined that these connections were  unusual compared to the rest of the devices in the network, even in the absence of any malicious indicators of compromise (IoCs).  

Darktrace triggered the following alerts for this unusual activity that consequently notified the customer to the pre-existing threat of an unmanaged device already present in their network:

  • Compromise / Sustained SSL or HTTP Increase
  • Compromise / Agent Beacon (Short Period)
  • Compromise / Agent Beacon (Medium Period)
  • Compromise / Agent Beacon (Long Period)
  • Tags / New Raspberry Pi Device
  • Device / DNS Requests to Unusual Server
  • Device / Anomaly Indicators / Spike in Connections to Rare Endpoint Indicator
Darktrace’s External Sites Summary showing the rarity of the external endpoint that the Raspberry Pi device ‘called home’ to and the model alerts triggered.  
Figure 1: Darktrace’s External Sites Summary showing the rarity of the external endpoint that the Raspberry Pi device ‘called home’ to and the model alerts triggered.  

Darktrace’s Cyber AI Analyst launched an autonomous investigation into the activity, correlating related events into a broader incident and generating a report outlining the potential threat along with supporting technical details.

Darktrace’s anomaly-based detection meant that the Raspberry Pi device did not need to be observed performing clearly malicious behavior to alert the customer to the security risk, and neither can defenders afford to wait for such escalation.

Why is this significant?

In 2021 a similar attack took place. Aiming to poison a Florida water treatment facility, attackers leveraged a TeamViewer instance that had been dormant on the system for six months, effectively allowing the attacker to ‘live off the land’ [10].  

The Raspberry Pi device in this incident also remained outside the purview of the customer’s security team at first. It could have been leveraged by a persistent attacker to pivot within the internal network and communicate externally.

A proactive approach to active defense that seeks to minimize and continuously monitor the attack surface and network is crucial.  

The growing interest in manufacturing from attackers and policymakers

Significant motivations for targeting the manufacturing sector and increasing regulatory demands make the convergence of supply chain risk, insider risk, and the prevalence of stealthy living-off-the-land techniques particularly relevant to this sector.

Manufacturing is consistently targeted by cybercriminals [11], and the sector’s ‘just-in-time’ model grants attackers the opportunity for high levels of disruption. Furthermore, under NIS 2, manufacturing and some food and beverage processing entities are now designated as ‘important’ entities. This means stricter incident reporting requirements within 24 hours of detection, and enhanced security requirements such as the implementation of zero trust and network segmentation policies, as well as measures to improve supply chain resilience [12][13][14].

How can Darktrace help?

Ultimately, Darktrace successfully assisted a manufacturing organization in detecting a potentially disruptive 'near-miss' within their OT environment, even in the absence of traditional IoCs.  Through passive asset identification techniques and continuous network monitoring, the customer improved their understanding of their network and supply chain risk.  

While the swift detection of the rogue device allowed the threat to be identified before it could escalate, the customer could have reduced their time to respond by using Darktrace’s built-in response capabilities, had Darktrace’s Autonomous Response capability been enabled.  Darktrace’s Autonomous Response can be configured to target specific connections on a rogue device either automatically upon detection or following manual approval from the security team, to stop it communicating with other devices in the network while allowing other approved devices to continue operating. Furthermore, the exportable report generated by Cyber AI Analyst helps security teams to meet NIS 2’s enhanced reporting requirements.  

Sophisticated ICS attacks often leverage insider access to perform in-depth reconnaissance for the development of tailored malware capabilities.  This case study and high-profile ICS attacks highlight the importance of mitigating supply chain risk in a similar way to insider risk.  As ICS networks adapt to the introduction of IIoT, remote working and the increased convergence between IT and OT, it is important to ensure the approach to secure against these threats is compatible with the dynamic nature of the network.  

Credit to Nicole Wong (Principal Cyber Analyst), Matthew Redrup (Senior Analyst and ANZ Team Lead)

[related-resource]

Appendices

MITRE ATT&CK Mapping

  • Infrastructure / New Raspberry Pi Device - INITIAL ACCESS - T1200 Hardware Additions
  • Device / DNS Requests to Unusual Server - CREDENTIAL ACCESS, COLLECTION - T1557 Man-in-the-Middle
  • Compromise / Agent Beacon - COMMAND AND CONTROL - T1071.001 Web Protocols

References

[1] https://www.cisa.gov/topics/physical-security/insider-threat-mitigation/defining-insider-threats

[2] https://www.trendmicro.com/vinfo/gb/threat-encyclopedia/web-attack/139/havex-targets-industrial-control-systems

[3]https://thehackernews.com/2018/08/tsmc-wannacry-ransomware-attack.html

[4] https://www.theverge.com/2020/12/21/22194183/intel-nvidia-cisco-government-infected-solarwinds-hack

[5] https://www.centreon.com/monitoring-ot-with-raspberry-pi-and-centreon/

[6] https://ieeexplore.ieee.org/document/9107689

[7] https://www.linkedin.com/pulse/webicc-scada-integration-industrial-raspberry-pi-devices-mryff

[8] https://www.rowse.co.uk/blog/post/how-is-the-raspberry-pi-used-in-the-iiot

[9] https://sepiocyber.com/resources/whitepapers/raspberry-pi-a-friend-or-foe/#:~:text=Initially%20designed%20for%20ethical%20purposes,as%20cyberattacks%20and%20unauthorized%20access

[10] https://edition.cnn.com/2021/02/10/us/florida-water-poison-cyber/index.html

[11] https://www.mxdusa.org/2025/02/13/top-cyber-threats-in-manufacturing/

[12] https://www.shoosmiths.com/insights/articles/nis2-what-manufacturers-and-distributors-need-to-know-about-europes-new-cybersecurity-regime

[13] https://www.goodaccess.com/blog/nis2-require-zero-trust-essential-security-measure#zero-trust-nis2-compliance

[14] https://logisticsviewpoints.com/2024/11/06/the-impact-of-nis-2-regulations-on-manufacturing-supply-chains/

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About the author
Nicole Wong
Cyber Security Analyst
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