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April 20, 2022

Email Compromise To Mass Phishing Campaign

Read Darktrace's in-depth analysis on the shift from business email compromise to mass phishing campaigns. Gain the knowledge to safeguard your business.
Written by
Shuh Chin Goh
Written by
Sam Lister
SOC Analyst
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
Shuh Chin Goh
Written by
Sam Lister
SOC Analyst
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20
Apr 2022

It is common for attackers to send large volumes of malicious emails from the email accounts which they compromise. Before carrying out this mass-mailing activity, there are predictable, preparatory steps which attackers take, such as registering mass-mailing applications and creating new inbox rules. In this blog, we will provide details of an attack observed in February 2022 in which a threat actor conducted a successful mass-mailing attack at a financial company based in Africa.

Attack summary

In February 2022, an attacker attempted to infiltrate the email environment of a financial services company based in Africa. At the beginning of February, the attacker likely gained a foothold in the company’s email environment by tricking an internal user into entering the credentials of their corporate email account into a phishing page. Over the following week, the attacker used the compromised account credentials to conduct a variety of activities, such as registering a mass-mailing application and creating a new inbox rule.

After taking these preparatory steps, the attacker went on to send out large volumes of phishing emails from the internal user’s email account. The attacker consequently obtained the credentials of several further internal corporate accounts. They used the credentials of one of these accounts to carry out similar preparatory steps (registering a mass-mailing application and creating a new inbox rule). After taking these steps, the attacker again sent large volumes of phishing emails from the account. At this point, the customer requested assistance from Darktrace’s SOC to aid investigation, and the intrusion was consequently contained by the company.

Since the attacker carried out their activities using a VPN and an Amazon cloud service, the endpoints from which the activities took place did not serve as particularly helpful indicators of an attack. However, prior to sending out phishing emails from internal users’ accounts, the attacker did carry out other predictable, preparatory activities. One of the main goals of this blog is to highlight that these behaviors serve as valuable signs of preparation for mass-mailing activity.

Attack timeline

Figure 1: Timeline of the intrusion

On February 3, the attacker sent a phishing email to the corporate account of an employee. The email was sent from the corporate account of an employee at a company with business ties to the victim enterprise. It is likely that the attacker had compromised this account prior to sending the phishing email from it. The phishing email in question claimed to be an overdue payment reminder. Within the email, there was a link hidden behind the display text “view invoice”. The hostname of the phishing link’s URL was a subdomain of questionpro[.]eu — an online survey platform. The page referred to by the URL was a fake Microsoft Outlook login page.

Figure 2: Destination of phishing link within the email sent by the attacker

Antigena Email, Darktrace’s email security solution, identified the highly unusual linguistic structure of the email, given its understanding of ‘normal’ for that sender. This was reflected in an inducement shift score of 100. However, in this case, the original URL of the phishing link was rewritten by Mimecast’s URL protection service in a way which made the full URL impossible to extract. Consequently, Antigena Email did not know what the original URL of the link was. Since the link was rewritten by Mimecast’s URL protection service, the email’s recipient will have received a warning notification in their browser upon clicking the link. It seems that the recipient ignored the warning, and consequently divulged their email account credentials to the attacker.

For Antigena Email to hold an email from a user’s mailbox, it must judge with high confidence that the email is malicious. In cases where the email contains no suspicious attachments or links, it is difficult for Antigena Email to obtain such high degrees of confidence, unless the email displays clear payload-independent malicious indicators, such as indicators of spoofing or indicators of extortion. In this case, the email, as seen by Antigena Email, didn’t contain any suspicious links or attachments (since Mimecast had rewritten the suspicious link) and the email didn’t contain any indicators of spoofing or extortion.

Figure 3: The email’s high inducement shift score highlights that the email’s linguistic content and structure were unusual for the email’s sender

Shortly after receiving the email, the internal user’s corporate device was observed making SSL connections to the questionpro[.]eu phishing endpoint. It is likely that the user divulged their email account credentials during these connections.

Figure 4: The above screenshot — obtained from Advanced Search — depicts the connections made by the account owner’s device on February 3

Between February 3 and February 7, the attacker logged into the user’s email account several times. Since these logins were carried out using a common VPN service, they were not identified as particularly unusual by Darktrace. However, during their login sessions, the attacker exhibited behavior which was highly unusual for the email account’s owner. The attacker was observed creating an inbox rule called “ _ ” on the user’s email account,[1] as well as registering and granting permissions to a mass-mailing application called Newsletter Software SuperMailer. These steps were taken by the attacker in preparation for their subsequent mass-mailing activity.

On February 7, the attacker sent out phishing emails from the user’s account. The emails were sent to hundreds of internal and external mailboxes. The email claimed to be an overdue payment reminder and it contained a questionpro[.]eu link hidden behind the display text “view invoice”. It is likely that the inbox rule created by the attacker caused all responses to this phishing email to be deleted. Attackers regularly create inbox rules on the email accounts which they compromise to ensure that responses to the malicious emails which they distribute are hidden from the accounts’ owners.[2]

Since Antigena Email does not have visibility of internal-to-internal emails, the phishing email was delivered fully weaponized to hundreds of internal mailboxes. On February 7, after the phishing email was sent from the compromised internal account, more than twenty internal devices were observed making SSL connections to the relevant questionpro[.]eu endpoint, indicating that many internal users had clicked the phishing link and possibly revealed their account credentials to the attacker.

Figure 5: The above screenshot — obtained from Advanced Search — depicts the large volume of connections made by internal devices to the phishing endpoint

Over the next five days, the attacker was observed logging into the corporate email accounts of at least six internal users. These logins were carried out from the same VPN endpoints as the attacker’s original logins. On February 11, the attacker was observed creating an inbox rule named “ , ” on one of these accounts. Shortly after, the attacker went on to register and grant permissions to the same mass-mailing application, Newsletter Software SuperMailer. As with the other account, these steps were taken by the attacker in preparation for subsequent mass-mailing activity.

Figure 6: The above screenshot — obtained from Advanced Search — outlines all of the actions involving the mass-mailing application that were taken by the attacker (accounts have been redacted)

On February 11, shortly after 08:30 (UTC), the attacker widely distributed a phishing email from this second user’s account. The phishing email was distributed to hundreds of internal and external mailboxes. Unlike the other phishing emails used by the attacker, this one claimed to be a purchase order notification, and it contained an HTML file named PurchaseOrder.html. Within this file, there was a link to a suspicious page on the public relations (PR) news site, everything-pr[.]com. After the phishing email was sent from the compromised internal account, more than twenty internal devices were observed making SSL connections to the relevant everything-pr[.]com endpoint, indicating that many internal users had opened the malicious attachment.

Figure 7: The above screenshot — obtained from Advanced Search — depicts the connections made by internal devices to the endpoint referenced in the malicious attachment

On February 11, the customer submitted an Ask the Expert (ATE) request to Darktrace’s SOC team. The guidance provided by the SOC helped the security team to contain the intrusion. The attacker managed to maintain a presence within the organization’s email environment for eight days. During these eight days, the attacker sent out large volumes of phishing emails from two corporate accounts. Before sending out these phishing emails, the attacker carried out predictable, preparatory actions. These actions included registering a mass-mailing application with Azure AD and creating an inbox rule.

Darktrace guidance

There are many learning points for this particular intrusion. First, it is important to be mindful of signs of preparation for malicious mass-mailing activity. After an attacker compromises an email account, there are several actions which they will likely perform before they send out large volumes of malicious emails. For example, they may create an inbox rule on the account, and they may register a mass-mailing application with Azure AD. The Darktrace models SaaS / Compliance / New Email Rule and SaaS / Admin / OAuth Permission Grant are designed to pick up on these behaviors.

Second, in cases where an attacker succeeds in sending out phishing emails from an internal, corporate account, it is advised that customers make use of Darktrace’s Advanced Search to identify users that may have divulged account credentials to the attacker. The phishing email sent from the compromised account will likely contain a suspicious link. Once the hostname of the link has been identified, it is possible to ask Advanced Search to display all HTTP or SSL connections to the host in question. If the hostname is www.example.com, you can get Advanced Search to display all SSL connections to the host by using the Advanced Search query, @fields.server_name:"www.example.com", and you can get Advanced Search to display all HTTP connections to the host by using the query, @fields.host:"www.example.com".

Third, it is advised that customers make use of Darktrace’s ‘watched domains’ feature[3] in cases where an attacker succeeds in sending out malicious emails from the accounts they compromise. If a hostname is added to the watched domains list, then a model named Compromise / Watched Domain will breach whenever an internal device is observed connecting to it. If Antigena Network is configured, then observed attempts to connect to the relevant host will be blocked if the hostname is added to the watched domains list with the ‘flag for Antigena’ toggle switched on. If an attacker succeeds in sending out a malicious email from an internal, corporate account, it is advised that customers add hostnames of phishing links within the email to the watched domains list and enable the Antigena flag. Doing so will cause Darktrace to identify and thwart any attempts to connect to the relevant phishing endpoints.

Figure 8: The above screenshot — obtained from the Model Editor — shows that Antigena Network prevented ten internal devices from connecting to phishing endpoints after the relevant phishing hostnames were added to the watched domains list on February 11

For Darktrace customers who want to find out more about phishing detection, refer here for an exclusive supplement to this blog.

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MITRE ATT&CK techniques observed

Thanks to Paul Jennings for his contributions.

Footnotes

1. https://docs.microsoft.com/en-us/powershell/module/exchange/new-inboxrule?view=exchange-ps

2. https://www.fireeye.com/current-threats/threat-intelligence-reports/rpt-fin4.html

3. https://customerportal.darktrace.com/product-guides/main/watched-domains

Written by
Shuh Chin Goh
Written by
Sam Lister
SOC Analyst
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
Shuh Chin Goh
Written by
Sam Lister
SOC Analyst

Anomaly-based threat hunting: Darktrace's approach in action

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May 8, 2025

Anomaly-based threat hunting: Darktrace's approach in action

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What is threat hunting?

Threat hunting in cybersecurity involves proactively and iteratively searching through networks and datasets to detect threats that evade existing automated security solutions. It is an important component of a strong cybersecurity posture.

There are several frameworks that Darktrace analysts use to guide how threat hunting is carried out, some of which are:

  • MITRE Attack
  • Tactics, Techniques, Procedures (TTPs)
  • Diamond Model for Intrusion Analysis
  • Adversary, Infrastructure, Victims, Capabilities
  • Threat Hunt Model – Six Steps
  • Purpose, Scope, Equip, Plan, Execute, Feedback
  • Pyramid of Pain

These frameworks are important in baselining how to run a threat hunt. There are also a combination of different methods that allow defenders diversity– regardless of whether it is a proactive or reactive threat hunt. Some of these are:

  • Hypothesis-based threat hunting
  • Analytics-driven threat hunting
  • Automated/machine learning hunting
  • Indicator of Compromise (IoC) hunting
  • Victim-based threat hunting

Threat hunting with Darktrace

At its core, Darktrace relies on anomaly-based detection methods. It combines various machine learning types that allows it to characterize what constitutes ‘normal’, based on the analysis of many different measures of a device or actor’s behavior. Those types of learning are then curated into what are called models.

Darktrace models leverage anomaly detection and integrate outputs from Darktrace Deep Packet Inspection, telemetry inputs, and additional modules, creating tailored activity detection.

This dynamic understanding allows Darktrace to identify, with a high degree of precision, events or behaviors that are both anomalous and unlikely to be benign.  On top of machine learning models for detection, there is also the ability to change and create models showcasing the tool’s diversity. The Model Editor allows security teams to specify values, priorities, thresholds, and actions they want to detect. That means a team can create custom detection models based on specific use cases or business requirements. Teams can also increase the priority of existing detections based on their own risk assessments to their environment.

This level of dexterity is particularly useful when conducting a threat hunt. As described above, and in previous ‘Inside the SOC’ blogs such a threat hunt can be on a specific threat actor, specific sector, or a  hypothesis-based threat hunt combined with ‘experimenting’ with some of Darktrace’s models.

Conducting a threat hunt in the energy sector with experimental models

In Darktrace’s recent Threat Research report “AI & Cybersecurity: The state of cyber in UK and US energy sectors” Darktrace’s Threat Research team crafted hypothesis-driven threat hunts, building experimental models and investigating existing models to test them and detect malicious activity across Darktrace customers in the energy sector.

For one of the hunts, which hypothesised utilization of PerfectData software and multi-factor authentication (MFA) bypass to compromise user accounts and destruct data, an experimental model was created to detect a Software-as-a-Service (SaaS) user performing activity relating to 'PerfectData Software’, known to allow a threat actor to exfiltrate whole mailboxes as a PST file. Experimental model alerts caused by this anomalous activity were analyzed, in conjunction with existing SaaS and email-related models that would indicate a multi-stage attack in line with the hypothesis.

Whilst hunting, Darktrace researchers found multiple model alerts for this experimental model associated with PerfectData software usage, within energy sector customers, including an oil and gas investment company, as well as other sectors. Upon further investigation, it was also found that in June 2024, a malicious actor had targeted a renewable energy infrastructure provider via a PerfectData Software attack and demonstrated intent to conduct an Operational Technology (OT) attack.

The actor logged into Azure AD from a rare US IP address. They then granted Consent to ‘eM Client’ from the same IP. Shortly after, the actor granted ‘AddServicePrincipal’ via Azure to PerfectData Software. Two days later, the actor created a  new email rule from a London IP to move emails to an RSS Feed Folder, stop processing rules, and mark emails as read. They then accessed mail items in the “\Sent” folder from a malicious IP belonging to anonymization network,  Private Internet Access Virtual Private Network (PIA VPN) [1]. The actor then conducted mass email deletions, deleting multiple instances of emails with subject “[Name] shared "[Company Name] Proposal" With You” from the  “\Sent folder”. The emails’ subject suggests the email likely contains a link to file storage for phishing purposes. The mass deletion likely represented an attempt to obfuscate a potential outbound phishing email campaign.

The Darktrace Model Alert that triggered for the mass deletes of the likely phishing email containing a file storage link.
Figure 1: The Darktrace Model Alert that triggered for the mass deletes of the likely phishing email containing a file storage link.

A month later, the same user was observed downloading mass mLog CSV files related to proprietary and Operational Technology information. In September, three months after the initial attack, another mass download of operational files occurred by this actor, pertaining to operating instructions and measurements, The observed patience and specific file downloads seemingly demonstrated an intent to conduct or research possible OT attack vectors. An attack on OT could have significant impacts including operational downtime, reputational damage, and harm to everyday operations. Darktrace alerted the impacted customer once findings were verified, and subsequent actions were taken by the internal security team to prevent further malicious activity.

Conclusion

Harnessing the power of different tools in a security stack is a key element to cyber defense. The above hypothesis-based threat hunt and custom demonstrated intent to conduct an experimental model creation demonstrates different threat hunting approaches, how Darktrace’s approach can be operationalized, and that proactive threat hunting can be a valuable complement to traditional security controls and is essential for organizations facing increasingly complex threat landscapes.

Credit to Nathaniel Jones (VP, Security & AI Strategy, Field CISO at Darktrace) and Zoe Tilsiter (EMEA Consultancy Lead)

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References

  1. https://spur.us/context/191.96.106.219

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About the author
Nathaniel Jones
VP, Security & AI Strategy, Field CISO

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May 6, 2025

Combatting the Top Three Sources of Risk in the Cloud

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With cloud computing, organizations are storing data like intellectual property, trade secrets, Personally Identifiable Information (PII), proprietary code and statistics, and other sensitive information in the cloud. If this data were to be accessed by malicious actors, it could incur financial loss, reputational damage, legal liabilities, and business disruption.

Last year data breaches in solely public cloud deployments were the most expensive type of data breach, with an average of $5.17 million USD, a 13.1% increase from the year before.

So, as cloud usage continues to grow, the teams in charge of protecting these deployments must understand the associated cybersecurity risks.

What are cloud risks?

Cloud threats come in many forms, with one of the key types consisting of cloud risks. These arise from challenges in implementing and maintaining cloud infrastructure, which can expose the organization to potential damage, loss, and attacks.

There are three major types of cloud risks:

1. Misconfigurations

As organizations struggle with complex cloud environments, misconfiguration is one of the leading causes of cloud security incidents. These risks occur when cloud settings leave gaps between cloud security solutions and expose data and services to unauthorized access. If discovered by a threat actor, a misconfiguration can be exploited to allow infiltration, lateral movement, escalation, and damage.

With the scale and dynamism of cloud infrastructure and the complexity of hybrid and multi-cloud deployments, security teams face a major challenge in exerting the required visibility and control to identify misconfigurations before they are exploited.

Common causes of misconfiguration come from skill shortages, outdated practices, and manual workflows. For example, potential misconfigurations can occur around firewall zones, isolated file systems, and mount systems, which all require specialized skill to set up and diligent monitoring to maintain

2. Identity and Access Management (IAM) failures

IAM has only increased in importance with the rise of cloud computing and remote working. It allows security teams to control which users can and cannot access sensitive data, applications, and other resources.

Cybersecurity professionals ranked IAM skills as the second most important security skill to have, just behind general cloud and application security.

There are four parts to IAM: authentication, authorization, administration, and auditing and reporting. Within these, there are a lot of subcomponents as well, including but not limited to Single Sign-On (SSO), Two-Factor Authentication (2FA), Multi-Factor Authentication (MFA), and Role-Based Access Control (RBAC).

Security teams are faced with the challenge of allowing enough access for employees, contractors, vendors, and partners to complete their jobs while restricting enough to maintain security. They may struggle to track what users are doing across the cloud, apps, and on-premises servers.

When IAM is misconfigured, it increases the attack surface and can leave accounts with access to resources they do not need to perform their intended roles. This type of risk creates the possibility for threat actors or compromised accounts to gain access to sensitive company data and escalate privileges in cloud environments. It can also allow malicious insiders and users who accidentally violate data protection regulations to cause greater damage.

3. Cross-domain threats

The complexity of hybrid and cloud environments can be exploited by attacks that cross multiple domains, such as traditional network environments, identity systems, SaaS platforms, and cloud environments. These attacks are difficult to detect and mitigate, especially when a security posture is siloed or fragmented.  

Some attack types inherently involve multiple domains, like lateral movement and supply chain attacks, which target both on-premises and cloud networks.  

Challenges in securing against cross-domain threats often come from a lack of unified visibility. If a security team does not have unified visibility across the organization’s domains, gaps between various infrastructures and the teams that manage them can leave organizations vulnerable.

Adopting AI cybersecurity tools to reduce cloud risk

For security teams to defend against misconfigurations, IAM failures, and insecure APIs, they require a combination of enhanced visibility into cloud assets and architectures, better automation, and more advanced analytics. These capabilities can be achieved with AI-powered cybersecurity tools.

Such tools use AI and automation to help teams maintain a clear view of all their assets and activities and consistently enforce security policies.

Darktrace / CLOUD is a Cloud Detection and Response (CDR) solution that makes cloud security accessible to all security teams and SOCs by using AI to identify and correct misconfigurations and other cloud risks in public, hybrid, and multi-cloud environments.

It provides real-time, dynamic architectural modeling, which gives SecOps and DevOps teams a unified view of cloud infrastructures to enhance collaboration and reveal possible misconfigurations and other cloud risks. It continuously evaluates architecture changes and monitors real-time activity, providing audit-ready traceability and proactive risk management.

Real-time visibility into cloud assets and architectures built from network, configuration, and identity and access roles. In this unified view, Darktrace / CLOUD reveals possible misconfigurations and risk paths.
Figure 1: Real-time visibility into cloud assets and architectures built from network, configuration, and identity and access roles. In this unified view, Darktrace / CLOUD reveals possible misconfigurations and risk paths.

Darktrace / CLOUD also offers attack path modeling for the cloud. It can identify exposed assets and highlight internal attack paths to get a dynamic view of the riskiest paths across cloud environments, network environments, and between – enabling security teams to prioritize based on unique business risk and address gaps to prevent future attacks.  

Darktrace’s Self-Learning AI ensures continuous cloud resilience, helping teams move from reactive to proactive defense.

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