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April 29, 2020

How Email Attackers Are Buying Domain Names to Get Inboxes

Explore how mass domain purchasing allows cyber-criminals to stay ahead of legacy email tools — and how cyber AI stops the threats that slip through.
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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29
Apr 2020

It is by now common knowledge that the vast majority of cyber-threats start with an email. In the current working conditions, this is more true than ever – with a recent study reporting a 30,000% increase in phishing, websites, and malware targeting remote users.

Many email security tools struggle to detect threats they encounter for the first time. Attackers know this and are leveraging many techniques to take advantage of this fundamental flaw. This includes automation to mutate common threat variants, resulting in a massive increase in unknown threats. Another technique, which will be the focus of this blog post, is the rapid and widespread creation of new domains in order to evade reputation checks and signature-based detection.

The recent surge in domain creation

While traditional tools have to rely on identifying campaigns and patterns across multiple emails to establish whether or not an email is malicious, Cyber AI technology doesn’t require classifying emails into buckets in order to know they don’t belong. There is no need, therefore, to actively track campaigns. But as security researchers, it’s hard to miss some trends.

Since the coronavirus outbreak, we have seen the number of domains registered related to COVID-19 increase by 130,000. In this time, 60% of all spear phishing threats neutralized by Antigena Email were related to COVID-19 or remote work. Another recent study determined that 10,000 coronavirus-related domains are created every day, with roughly nine out of ten of these either malicious or attempting to generate sales of fake products.

With attackers also taking advantage of changing online behaviors arising from the pandemic, another trend we’ve seen is the proliferation of the keyword ‘Zoom’ in some of the unpopular domains that bypassed traditional tools, as attackers leverage the video conferencing platform’s recent rise in usage.

“I believe that hackers identified coronavirus as something users are desperate to find information on. Panic leads to irrational thinking and people forget the basics of cyber security.”

— COO, Atlas VPN

I recently wrote a blog post on the idea of ‘fearware’ and why it’s so successful. Right now, people are desperate for information, and attackers know this. Cyber-criminals play into fear, uncertainty, and doubt (FUD) through a number of mechanisms, and we have since seen a variety of imaginative attempts to engage recipients. These emails range from fake ‘virus trackers’, to sending emails purporting to be from Amazon, claiming an unmanageable rise in newly registered accounts, and demanding “re-registration” of the recipient’s credit card details should they wish to keep their account.

Domain name purchasing: A vicious cycle

Purchasing thousands of new domains and sending malicious emails en masse is a tried and tested technique that cyber-criminals have been leveraging for decades. Now with automation, they’re doing it faster than ever before.

Here’s why it works.

Traditional security tools work by analyzing emails in isolation, measuring them against static blacklists of ‘known bads’. By way of analogy, the gateway tool here is acting like a security guard standing at the perimeter of an organization’s physical premises, asking every individual who enters: “are you malicious?”

The binary answer to this sole question is extracted by looking at some metadata around the email, including the sender’s IP, their email address domain, and any embedded links or attachments. They analyze this data in a vacuum, and at face value, with no consideration towards the relationship between that data, the recipient, and the rest of the business. They run reputation checks, asking “have I seen this IP or domain before?” Crucially, if the answer is no, they let them straight through.

To spell that out, if the domain is brand new, it won’t have a reputation, and as these traditional tools have a limited ability to identify potential harmful elements via any other means, they have no choice but to let them in by default.

These methods barely scratch the surface of a much wider range of characteristics that a malicious email might contain. And as email threats get ever more sophisticated, the ‘innocent until proven guilty approach’ is not enough. For a comprehensive check, we would want to ask: does the domain have any previous relationship with the recipient? The organization as a whole? Does it look suspiciously visually similar to other domains? Is this the first time we’ve seen an inbound email from this user? Has anybody in the organization ever shared a link with this domain? Has any user ever visited this link?

Legacy tools are blatantly asking the wrong questions, to which attackers know the answers. And usually, they can skirt by these inattentive security guards by paying just a few pennies for new domains.

How to buy your way in

Let’s look at the situation from an attacker’s perspective. They just need one email to land and it could be keys to the kingdom, so an upfront purchase of a few thousand new domains will almost inevitably pay off. And they’d pay the price as long as it’s working and they’re profiting.

This is exactly what attackers are doing. Newly-registered domains consistently get through gateways until these traditional tools are armed with enough information to determine that the domains are bad, by which point thousands or even millions of emails could have been successfully delivered. As soon as the attack infrastructure is worn out, the attackers will abandon it, and very easily just purchase and deploy a new set of domains.

And so, the vicious cycle continues. Like a game of ‘whack-a-mole’, these legacy ‘solutions’ will continue to hammer down on recognized ‘bad’ emails – all the while more malicious domains are being created in the thousands in preparation for the next campaign. This is the ‘Domain Game’, and it’s a hard game for defenders to win.

Asking the right questions

Thankfully, the solution to this problem is as simple as the problem itself. It requires a movement away from the legacy approach and towards deploying technology that is up to par with the speed and scale of today’s attackers.

In the last two years, new technologies have emerged that leverage AI, seeking to understand the human behind the email address. Rather than inspecting incoming traffic at the surface-level and asking binary questions, this paradigm shift away from this insufficient legacy approach asks the right questions: not simply “are you malicious?”, but crucially: “do you belong?”

Informed by a nuanced understanding of the recipient, their peers, and the organization at large, every inbound, outbound, and internal email is analyzed in context, and is then re-analyzed over and over again in light of evolving evidence. Asking the right questions and understanding the human invariably sets a far higher standard for acceptable catch rates with unknown threats on first encounter. This approach far outpaces traditional email defenses which have proven to fail and leave companies and their employees vulnerable to malicious emails sitting in their inboxes.

Rather than desperately bashing away at blacklisted domains and IP addresses in an ill-fated attempt to beat the attackers, we can change the game altogether, tilting the scales in favor of the defenders – securing our inboxes and our organizations at large.

Learn more about Antigena Email.

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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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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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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