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March 8, 2024

Malicious Use of Dropbox in Phishing Attacks

Understand the tactics of phishing attacks that exploit Dropbox and learn how to recognize and mitigate these emerging cybersecurity threats.
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
Ryan Traill
Content Manager - Digital Customer Success
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08
Mar 2024

Evolving Phishing Attacks

While email has long been the vector of choice for carrying out phishing attacks, threat actors, and their tactics, techniques, and procedures (TTPs), are continually adapting and evolving to keep pace with the emergence of new technologies that represent new avenues to exploit. As previously discussed by the Darktrace analyst team, several novel threats relating to the abuse of commonly used services and platforms were observed throughout 2023, including the rise of QR Code Phishing and the use of Microsoft SharePoint and Teams in phishing campaigns.

Dropbox Phishing Attacks

It should, therefore, come as no surprise that the malicious use of other popular services has gained traction in recent years, including the cloud storage platform Dropbox.

With over 700 million registered users [1], Dropbox has established itself as a leading cloud storage service celebrated for its simplicity in file storage and sharing, but in doing so it has also inadvertently opened a new avenue for threat actors to exploit. By leveraging the legitimate infrastructure of Dropbox, threat actors are able to carry out a range of malicious activities, from convincing their targets to unknowingly download malware to revealing sensitive information like login credentials.

Darktrace Detection of Dropbox Phishing Attack

Darktrace detected a malicious attempt to use Dropbox in a phishing attack in January 2024, when employees of a Darktrace customer received a seemingly innocuous email from a legitimate Dropbox address. Unbeknownst to the employees, however, a malicious link had been embedded in the contents of the email that could have led to a widespread compromise of the customer’s Software-as-a-Service (SaaS) environment. Fortunately for this customer, Darktrace / EMAIL quickly identified the suspicious emails and took immediate actions to stop them from being opened. If an email was accessed by an employee, Darktrace / IDENTITY was able to recognize any suspicious activity on the customer’s SaaS platform and bring it to the immediate detection of their security team.

Attack overview

Initial infection  

On January 25, 2024, Darktrace / EMAIL observed an internal user on a customer’s SaaS environment receiving an inbound email from ‘no-reply@dropbox[.]com’, a legitimate email address used by the Dropbox file storage service.  Around the same time 15 other employees also received the same email.

The email itself contained a link that would lead a user to a PDF file hosted on Dropbox, that was seemingly named after a partner of the organization. Although the email and the Dropbox endpoint were both legitimate, Darktrace identified that the PDF file contained a suspicious link to a domain that had never previously been seen on the customer’s environment, ‘mmv-security[.]top’.  

Darktrace understood that despite being sent from a legitimate service, the email’s initiator had never previously corresponded with anyone at the organization and therefore treated it with suspicion. This tactic, whereby a legitimate service sends an automated email using a fixed address, such as ‘no-reply@dropbox[.]com’, is often employed by threat actors attempting to convince SaaS users to follow a malicious link.

As there is very little to distinguish between malicious or benign emails from these types of services, they can often evade the detection of traditional email security tools and lead to disruptive account takeovers.

As a result of this detection, Darktrace / EMAIL immediately held the email, stopping it from landing in the employee’s inbox and ensuring the suspicious domain could not be visited. Open-source intelligence (OSINT) sources revealed that this suspicious domain was, in fact, a newly created endpoint that had been reported for links to phishing by multiple security vendors [2].

A few days later on January 29, the user received another legitimate email from ‘no-reply@dropbox[.]com’ that served as a reminder to open the previously shared PDF file. This time, however, Darktrace / EMAIL moved the email to the user’s junk file and applied a lock link action to prevent the user from directly following a potentially malicious link.

Figure 1: Anomaly indicators associated with the suspicious emails sent by ’no.reply@dropbox[.]com’, and the corresponding actions performed by Darktrace / EMAIL

Unfortunately for the customer in this case, their employee went on to open the suspicious email and follow the link to the PDF file, despite Darktrace having previously locked it.

Figure 2: Confirmation that the SaaS user read the suspicious email and followed the link to the PDF file hosted on Dropbox, despite it being junked and link locked.

Darktrace / NETWORK subsequently identified that the internal device associated with this user connected to the malicious endpoint, ‘mmv-security[.]top’, a couple of days later.

Further investigation into this suspicious domain revealed that it led to a fake Microsoft 365 login page, designed to harvest the credentials of legitimate SaaS account holders. By masquerading as a trusted organization, like Microsoft, these credential harvesters are more likely to appear trustworthy to their targets, and therefore increase the likelihood of stealing privileged SaaS account credentials.  

Figure 3: The fake Microsoft login page that the user was directed to after clicking the link in the PDF file.

Suspicious SaaS activity

In the days following the initial infection, Darktrace / IDENTITY began to observe a string of suspicious SaaS activity being performed by the now compromised Microsoft 365 account.

Beginning on January 31, Darktrace observed a number of suspicious SaaS logins from multiple unusual locations that had never previously accessed the account, including 73.95.165[.]113. Then on February 1, Darktrace detected unusual logins from the endpoints 194.32.120[.]40 and 185.192.70[.]239, both of which were associated with ExpressVPN indicating that threat actors may have been using a virtual private network (VPN) to mask their true location.

FIgure 4: Graph Showing several unusual logins from different locations observed by Darktrace/Apps on the affected SaaS account.

Interestingly, the threat actors observed during these logins appeared to use a valid multi-factor authentication (MFA) token, indicating that they had successfully bypassed the customer’s MFA policy. In this case, it appears likely that the employee had unknowingly provided the attackers with an MFA token or unintentionally approved a login verification request. By using valid tokens and meeting the necessary MFA requirements, threat actors are often able to remain undetected by traditional security tools that view MFA as the silver bullet. However, Darktrace’s anomaly-based approach to threat detection allows it to quickly identify unexpected activity on a device or SaaS account, even if it occurs with legitimate credentials and successfully passed authentication requirements, and bring it to the attention of the customer’s security team.

Shortly after, Darktrace observed an additional login to the SaaS account from another unusual location, 87.117.225[.]155, this time seemingly using the HideMyAss (HMA) VPN service. Following this unusual login, the actor was seen creating a new email rule on the compromised Outlook account. The new rule, named ‘….’, was intended to immediately move any emails from the organization’s accounts team directly to the ‘Conversation History’ mailbox folder. This is a tactic often employed by threat actors during phishing campaigns to ensure that their malicious emails (and potential responses to them) are automatically moved to less commonly visited mailbox folders in order to remain undetected on target networks. Furthermore, by giving this new email rule a generic name, like ‘….’ it is less likely to draw the attention of the legitimate account holder or the organizations security team.

Following this, Darktrace / EMAIL observed the actor sending updated versions of emails that had previously been sent by the legitimate account holder, with subject lines containing language like “Incorrect contract” and “Requires Urgent Review”, likely in an attempt to illicit some kind of follow-up action from the intended recipient.  This likely represented threat actors using the compromised account to send further malicious emails to the organization’s accounts team in order to infect additional accounts across the customer’s SaaS environment.

Unfortunately, Darktrace's Autonomous Response was not deployed in the customer’s SaaS environment in this instance, meaning that the aforementioned malicious activity did not lead to any mitigative actions to contain the compromise. Had RESPOND been enabled in autonomous response mode at the time of the attack, it would have quickly moved to log out and disable the suspicious actor as soon as they had logged into the SaaS environment from an unusual location, effectively shutting down this account takeover attempt at the earliest opportunity.

Nevertheless, Darktrace / EMAIL's swift identification and response to the suspicious phishing emails, coupled with Darktrace / IDENTITY's detection of the unusual SaaS activity, allowed the customer’s security team to quickly identify the offending SaaS actor and take the account offline before the attack could escalate further

Conclusion

As organizations across the world continue to adopt third-party solutions like Dropbox into their day-to-day business operations, threat actors will, in turn, continue to seek ways to exploit these and add them to their arsenal. As illustrated in this example, it is relatively simple for attackers to abuse these legitimate services for malicious purposes, all while evading detection by endpoint users and security teams alike.

By leveraging these commonly used platforms, malicious actors are able to carry out disruptive cyber-attacks, like phishing campaigns, by taking advantage of legitimate, and seemingly trustworthy, infrastructure to host malicious files or links, rather than relying on their own infrastructure. While this tactic may bypass traditional security measures, Darktrace’s Self-Learning AI enables it to recognize unusual senders within an organization’s email environment, even if the email itself seems to have come from a legitimate source, and prevent them from landing in the target inbox. In the event that a SaaS account does become compromised, Darktrace is able to identify unusual login locations and suspicious SaaS activities and bring them to the attention of the customer for remediation.

In addition to the prompt identification of emerging threats, Darktrace's Autonomous Response is uniquely placed to take swift autonomous action against any suspicious activity detected within a customer’s SaaS environment, effectively containing any account takeover attempts in the first instance.

Credit to Ryan Traill, Threat Content Lead, Emily Megan Lim, Cyber Security Analyst

Appendices

Darktrace Model Detections  

- Model Breach: SaaS / Access::Unusual External Source for SaaS Credential Use

- Model Breach: SaaS / Unusual Activity::Multiple Unusual External Sources For SaaS Credential

- Model Breach: SaaS / Access::Unusual External Source for SaaS Credential Use

- Model Breach: SaaS / Access::Unusual External Source for SaaS Credential Use

- Model Breach: SaaS / Unusual Activity::Multiple Unusual SaaS Activities

- Model Breach: SaaS / Unusual Activity::Unusual MFA Auth and SaaS Activity

- Model Breach: SaaS / Compromise::Unusual Login and New Email Rule

- Model Breach: SaaS / Compliance::Anomalous New Email Rule

- Model Breach: SaaS / Compliance::New Email Rule

- Model Breach: SaaS / Compromise::SaaS Anomaly Following Anomalous Login

- Model Breach: Device / Suspicious Domain

List of Indicators of Compromise (IoCs)

Domain IoC

mmv-security[.]top’ - Credential Harvesting Endpoint

IP Address

73.95.165[.]113 - Unusual Login Endpoint

194.32.120[.]40 - Unusual Login Endpoint

87.117.225[.]155 - Unusual Login Endpoint

MITRE ATT&CK Mapping

DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS

T1078.004 - Cloud Accounts

DISCOVERY

T1538 - Cloud Service Dashboard

RESOURCE DEVELOPMENT

T1586 - Compromise Accounts

CREDENTIAL ACCESS

T1539 - Steal Web Session Cookie

PERSISTENCE

T1137 - Outlook Rules

INITIAL ACCESS

T156.002 Spearphishing Link

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
Ryan Traill
Content Manager - Digital Customer Success

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July 27, 2026

Hiding in Plain Sight: Uncovering a Multi-Stage Ransomware Attack Through Behavioral Detection

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Why ransomware has changed

Ransomware attacks have continued to increase globally, with 698 incidents reported in May 2026, representing a 48% rise compared to 472 incidents in May 2025 [1]. At the same time, the ransomware landscape is evolving. Several major ransomware groups, including LockBit [2], have been disrupted by successful joint law enforcement operations, resulting in a shift away from a small number of dominant actors towards a more fragmented and distributed ecosystem. This is increasingly composed of smaller groups who play a specialized role in the attack, such as initial access brokers, affiliates or developers.

As a result, ransomware tactics, techniques, and procedures (TTPs) are becoming more diverse and less predictable. On top of this, adversaries are leveraging native tools and legitimate penetration testing frameworks to evade detection. Anomaly-based detection is therefore critical to identify pre-ransomware activity, rather than relying on signatures associated with a handful of well-known ransomware groups.

As these attacks often unfold over several days, there is a critical window for defenders to act. In this context, behavioral-based detection plays a vital role in identifying suspicious pre-ransomware activity, and enabling early intervention before encryption or exfiltration occurs.

Inside a modern ransomware intrusion

In early 2026, Darktrace detected activity within a customer’s environment related to a multi-stage ransomware intrusion from the initial compromise. This activity does not appear to be attributable to a specific ransomware group, and no known ransomware payload was observed until the final stage.

The attack aligns with a broader industry trend in which compromised virtual private network (VPN) credentials are used as an entry point, followed by rapid internal reconnaissance and lateral movement using legitimate administrative tools. This growing preference for native tools and legitimate frameworks in cyber-attacks illustrates that it is increasingly unreliable to depend solely on traditional indicators of compromise such as known malware signatures or exploit detection.

The intrusion also involved the use of Sliver, an open-source adversary emulation framework, which is increasingly observed in real-world attacks. Originally designed for penetration testing and red teaming, Sliver has gained traction among threat actors as a stealthier alternative to more heavily signatured frameworks such as Cobalt Strike. As a legitimate framework, its use further complicates detection for security tools that rely on known malicious signatures.

Darktrace’s detection of a ransomware event in a customer’s environment

The initial compromise appears to have occurred via compromised credentials used over the VPN shortly before, or at the onset of the first indicators of suspicious activity. While it remains unclear as to how or when the threat actors gained access to these credentials, the use of initial access brokers (IABs) is a common feature of modern ransomware operations. This suggests that access to the environment may have been established several days or weeks beforehand.

The intrusion unfolded over three days, presenting multiple opportunities for early detection and intervention before ransomware deployment. The attack progressed through a compressed but structured sequence: initial access and reconnaissance were completed within hours, followed by privilege escalation and lateral movement the next day, and culminating in data exfiltration and encryption shortly thereafter. Throughout each stage, distinct behavioral anomalies emerged across the network providing clear indicators of malicious activity well before the ransomware was deployed.

While Darktrace’s Autonomous Response capability was enabled within the customer’s environment, it was not fully configured across the impacted devices, allowing the attack to progress to ransomware deployment. Had Autonomous Response been fully deployed across the affected systems, it could have taken targeted action against the earliest stages of malicious activity, potentially disrupting the intrusion before it escalated.

Figure 1: Timeline of the attack progression.

Day 1: Reconnaissance and privilege escalation

The threat actor gained access via compromised VPN credentials and initiated internal reconnaissance. Darktrace detected anomalous scanning behavior, including unusual port scanning activity and widespread network enumeration.

Specifically, Darktrace detected a high volume of east-west scanning activity across a broad range of ports, with TCP connections targeting ports 21, 80, 445, 4899 and 8080. Associated URIs suggested the use of Nmap, a widely used penetration testing tool. This highlights how attackers often leverage legitimate penetration testing tools for malicious reconnaissance, enabling them to blend into normal network activity and evade traditional signature-based detection methods.

Figure 2: Darktrace's detection of a sharp increase in anomalous internal connections, triggering multiple high-severity model alerts associated with reconnaissance activity.

Several devices were observed using administrative credentials to carry out privileged actions in a manner that was highly anomalous for the environment. This activity was accompanied by behavior consistent with SMB authentication scanning, suggesting efforts to identify and access additional systems. As the activity intensified, an increasing number of devices became involved, signalling lateral movement and further spread across the network.

Darktrace also identified privilege escalation through active directory (AD) replication abuse, specifically via the drsuapi::DRSGetNCChanges function. This technique allows an attacker with sufficient privileges to request directory replication data from a domain controller (DC), enabling them to extract credentials, including password hashes, without directly interacting with user accounts. Commonly associated with ‘DCSync’ attacks, this technique is frequently used to obtain highly privileged credentials and enable further escalation within an environment.

Figure 3: Darktrace’s detection of anomalous AD replication activity indicative of privilege escalation.

This activity was seen alongside the use of the now obsolete SMBv1, repeated NTLM authentication attempts using multiple variations of ‘Administrator’ credentials, reverse DNS scanning, and large-scale network scanning. Darktrace observed widespread use of SMBv1 across the customer’s environment, exposing a significant security weakness. As a legacy protocol with well-documented weaknesses, SMBv1 can be exploited to facilitate lateral movement, allowing the attackers to expand their access following initial compromise.

Day 3: Lateral Movement, Command & Control, and Exfiltration

Two days later, the attacker escalated privileges and expanded their foothold using living-off-the-land (LOTL) techniques such as PSExec, WMI, and RDP. Concurrently, Darktrace identified command-and-control (C2)-style communications consistent with the Sliver framework, alongside rare outbound connections to cloud infrastructure indicating potential data exfiltration. The volume and severity of observed activity increased as attack behavior intensified.

The device was observed conducting extensive lateral movement, leveraging LOTL techniques to evade detection. Activity included WMI execution (e.g. ExecQuery), DCE-RPC activity, SMB sessions and file writes, most of which were successful, as well as the deployment of PSEXESVC.exe via ADMIN$ shares and prolonged RDP sessions. Darktrace identified this behavior as highly anomalous for the environment. Such activity is commonly associated with the transfer of attacker tooling, remote command execution, and the establishment of persistent access across compromised systems.  

Figure 4: Darktrace’s detection of a spike in RPC binding events indicative of potential lateral movement.

On the same day, Darktrace detected C2-style SSL communications originating from multiple internal devices to rare external endpoints. These connections exhibited anomalous characteristics, including invalid SSL certificates and repeated connection patterns resembling beaconing. Analysis of the observed JA3 fingerprint further linked the activity to Sliver, the adversary simulation framework referenced earlier, as the hash has previously been associated with Sliver-related infrastructure [3]. The use of this framework reflects a broader trend of attackers repurposing legitimate offensive security tools for stealthy C2 communications. Connections to 137[.]220[.]59[.]55 (ASN AS20473 AS-VULTR) indicated that the communications were likely routed via a virtual private server (VPS) hosted by Vultr. Attackers often utilize VPS infrastructure from legitimate cloud providers like Vultr to obscure their true origin, blend into benign traffic, and evade IP-based detection mechanisms [4].

Figure 5: Darktrace’s Cyber AI Analyst detection of two linked unusual connections to Vultr infrastructure.

Darktrace also observed a device initiating SSL connections to safedata.s3[.]wasabisys[.]com, an endpoint associated with Wasabi cloud storage. Darktrace recognized that neither the destination nor the associated IP address had previously been observed within the environment.  More than 200 MB of data was subsequently uploaded externally to endpoints sharing the same JA3 client hash, indicating a sustained transfer session and potential data exfiltration to third-party storage. The apparent exfiltration prior to encryption is consistent with a double-extortion ransomware strategy.

Figure 6: Darktrace’s Cyber AI Analyst detection of more than 30 rare outbound connections to a Wasabi cloud storage endpoint, indicative of potential data exfiltration

Day 4: Encryption

The attack culminated in ransomware deployment, marking the transition from suspicious network activity to a business-impacting incident. Using SMB-based propagation, the threat actor encrypted thousands of files across the network, affecting multiple systems and disrupting normal operations. Throughout the encryption event, the legacy SMBv1 protocol was used extensively across multiple internal systems, resulting in a significant increase in newly encrypted files.

Figure 7: Darktrace’s detection of abnormal spikes in SMB activity and associated model alerts, indicative of ransomware encryption and propagation.

Darktrace’s Cyber AI Analyst automatically investigated and correlated the encryption activity and related events into a single incident narrative, providing the customer with real-time visibility into the attack while significantly reducing investigation time.

Figure 8: Darktrace’s Cyber AI Analyst’s investigation into the encryption activity. AI Analyst incident detailing example encryption activity in real time. Related events are automatically correlated and summarized into a clear narrative, reducing investigation time.

Defender action recommendations

What Could Have Stopped the Attack Earlier?

Although the attack ultimately resulted in ransomware deployment, there were multiple opportunities to detect, contain, and disrupt the intrusion before encryption occurred. The following actions could have significantly reduced the overall impact:

Detect and investigate indicators of reconnaissance and lateral movement

  • Unusual scanning
  • Active Directory replication anomalies consistent with DCSync activity
  • Anomalous use of native tools and processes indicative of LOTL attacks
  • Unusual use of common reconnaissance tools such as Nmap and NetScan

Contain compromised credentials and affected devices

  • Disable and reset compromised VPN credentials
  • Isolate devices performing anomalous scanning and lateral movement activity

Block suspicious external communications and data exfiltration

  • Use anomaly-based detection to detect and block repeated outbound connections to rare external infrastructure
  • Prevent data exfiltration to unauthorized cloud storage services such as Wasabi

Conclusion

The incident highlights the importance of anomaly-based detection, particularly against attacks that primarily use native or legitimate tools to evade traditional security measures. Darktrace identified suspicious activity from the first day of the compromise, providing multiple opportunities to disrupt the intrusion before it progressed to lateral movement and data exfiltration.

In this instance, detection was not the limiting factor; response time was. Prompt investigation and containment of devices exhibiting anomalous behavior could have prevented lateral movement, data exfiltration, and ultimately ransomware deployment.

As adversaries increasingly prioritize stealth over custom malware, relying instead on legitimate tools, valid credentials, and trusted infrastructure, traditional signature-based detection becomes less effective. Identifying subtle behavioral deviations early remains critical to disrupting attacks before they escalate into full-scale ransomware incidents.

Credit to Alexandra Evzona (Cyber Analyst), Priya Thapa (Senior Cyber Analyst)
Edited by Ryan Traill (Content Manager)

Appendices

References

[1] https://industrialcyber.co/ransomware/check-point-reports-ransomware-attacks-jump-48-year-over-year-despite-decline-in-overall-cyberattack-activity/

[2] https://www.europol.europa.eu/media-press/newsroom/news/law-enforcement-disrupt-worlds-biggest-ransomware-operation

[3] https://fieldeffect.com/blog/field-effect-mitigates-not-so-simplehelp-exploits-enabling-deployment-of-backdoors

[4] https://www.darktrace.com/blog/from-vps-to-phishing-how-darktrace-uncovered-saas-hijacks-through-virtual-infrastructure-abuse

Indicators of Compromise (IoCs)

IP Addresses

  • 137[.]220[.]59[.]55 – Potential C2 infrastructure (Vultr AS20473)
  • 38[.]27[.]106[.]123 – Wasabi cloud storage endpoint associated with potential data exfiltration
  • 38[.]27[.]106[.]128 – Wasabi cloud storage endpoint associated with potential data exfiltration
  • 38[.]27[.]106[.]117 – Wasabi cloud storage endpoint associated with potential data exfiltration

Domains

  • safedata[.]s3[.]wasabisys[.]com – Potential data exfiltration endpoint
  • *.wasabisys[.]com – Associated Wasabi cloud storage infrastructure

JA3 Fingerprint

  • d6828e30ab66774a91a96ae93be4ae4c – Associated with the Sliver adversary emulation framework

Files

  • Delete[.]me – File observed during reconnaissance activity, commonly associated with NetScan

Darktrace Model Coverage

·       Anomalous Connection / Active Remote Desktop Tunnel

·       Anomalous Connection / Anomalous Remote Registry Service Control

·       Anomalous Connection / Multiple Failed Windows UDP

·       Anomalous Connection / New or Uncommon Service Control

·       Anomalous Connection / New or Uncommon Service Enumeration

·       Anomalous Connection / New User Agent to IP Without Hostname

·       Anomalous Connection / SMB Enumeration

·       Anomalous Connection / Suspicious Activity On High Risk Device

·       Anomalous Connection / Suspicious Read Write Ratio

·       Anomalous Connection / Sustained MIME Type Conversion

·       Anomalous Connection / Uncommon 1 GiB Outbound

·       Anomalous Connection / Unusual Admin RDP Session

·       Anomalous Connection / Unusual Admin SMB Session

·       Anomalous Connection / Unusual SMB Version 1 Connectivity

·       Anomalous File / EXE from Rare External Location

·       Anomalous File / Internal / Additional Extension Appended to SMB File

·       Anomalous Server Activity / Outgoing from Server

·       Compromise / Beaconing Activity To External Rare

·       Compromise / Ransomware / Possible Ransom Note Read

·       Compromise / Ransomware / Ransom or Offensive Words Written to SMB

·       Compromise / Ransomware / Suspicious SMB Activity

·       Device / Anonymous NTLM Logins

·       Device / Attack and Recon Tools

·       Device / Initial Attack Chain Activity

·       Device / Large Number of Model Alerts

·       Device / Long Agent Connection to New Endpoint

·       Device / Multiple Lateral Movement Model Alerts

·       Device / Network Scan

·       Device / New or Uncommon SMB Named Pipe

·       Device / New or Unusual Remote Command Execution

·       Device / New User Agent

·       Device / Possible RPC Lateral Movement

·       Device / Possible SMB/NTLM Brute Force

·       Device / RDP Scan

·       Device / SMB Lateral Movement

·       Device / SMB Session Brute Force (Non-Admin)

·       Device / SMB Version 1 Access Failures

·       Device / Suspicious File Delete Activity

·       Device / Suspicious Network Scan Activity

·       Device / Unusual SMB Error Detected

·       Device / Unusual SMB To Critical Resource

·       Device / Unusual Winreg Operation

·       Unusual Activity / Multiple Failed Internal Connections

·       Unusual Activity / Possible RPC Recon Activity

·       Unusual Activity / Sustained Anomalous SMB Activity

·       Unusual Activity / Unusual External Data to New Endpoint

·       Unusual Activity / Unusual External Data Transfer

·       Unusual Activity / Unusual File Storage Data Transfer

·       Unusual Activity / Unusual Large Internal Transfer

·       User / New Admin Credentials on Client

·       User / NTLM Login from Unauthenticated Device

Autonomous Response Model Alerts

·       Antigena / Network / External Threat / Antigena Ransomware Block

·       Antigena / Network / External Threat / Antigena Suspicious File Block

·       Antigena / Network / Insider Threat / Antigena Active Threat SMB Write Block

·       Antigena / Network / Insider Threat / Antigena Internal Anomalous File Activity

·       Antigena / Network / Insider Threat / Antigena Large Data Volume Outbound Block

·       Antigena / Network / Insider Threat / Antigena Network Scan Block

·       Antigena / Network / Insider Threat / Antigena Unusual Privileged User Activities Block

·       Antigena / Network / Manual / Quarantine Device

·       Antigena / Network / Significant Anomaly / Antigena Alerts Over Time Block

·       Antigena / Network / Significant Anomaly / Antigena Controlled and Model Alert

·       Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Client Block

·       Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Server Block 100

·       Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block

MITRE ATT&CK MAPPING

Command and control - Protocol Tunneling - T1572

Command and control – Web Protocols – T1071.001

Credential Access- Exploitation for Credential Access- T1212

Credential Access- Password Guessing- T1110

Discovery- File and Directory Discovery- T1083

Discovery- Network Service Discovery- T1046

Discovery- Network Share Discovery- T1135

Discovery- Remote System Discovery- T1018

Exfiltration- Exfiltration Over C2 Channel- T1041

Exfiltration- Exfiltration to Cloud Storage- T1567

Impact- Data Encrypted for Impact- T1486

Impact- Data Encrypted for Impact- T1486

Impact- Service Stop - T1489

Initial Access- Public-Facing Application- T1190

Lateral Movement- Exploitation of Remote Services- T1210

Lateral Movement- Remote Desktop Protocol- T1021

Lateral Movement- SMB/Windows Admin Shares- T1021

Lateral Movement- Taint Shared Content- T1080

Persistence- Modify Registry- T1112

Privilege Escalation- Exploitation for Privilege Escalation- T0890

Privilege Escalation- Valid Accounts- T1078

Reconnaissance- Scanning IP Blocks- T1595

Reconnaissance- Vulnerability Scanning- T1595

Resource Development- Malware- T1588

Stealth- File Deletion- T1070

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About the author
Alexandra Evzona
Cyber Analyst

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July 24, 2026

Darktrace / EMAIL Expands Behavioral Defense Across Email and Collaboration Workflows

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Email and collaboration tools do more than carry messages. They are where organizations approve payments, share sensitive data, reset credentials, and make thousands of everyday decisions. Increasingly, they are interfaces through which humans direct AI agents in their daily activity. Email, Slack and Teams are high volume, rich with sensitive data, and an easy place to hide malicious activity.

The opportunity isn’t lost on bad actors. Darktrace / EMAIL detected more than 32 million high-confidence phishing emails globally in 2025, and 70% of those messages passed DMARC authentication.  Phishing is increasingly difficult to detect and familiar trust signals alone are not enough. People and security teams need to understand how a message fits the normal behavior of the sender, recipient, and organization. They also need to correlate activity across platforms to spot threats that span multiple channels.

To effectively secure against today’s evolved threats, security teams need to act at two levels: they need to help each employee make a safer decision ‘in the moment’, and they need to understand the wider patterns that may expose the business to risk.

Darktrace is introducing four new capabilities in Darktrace / EMAIL to address both challenges. The new features explain suspicious content more clearly to end users, strengthen the capabilities of Darktrace / Adaptive Human Defense with richer guidance, let organizations define their own patterns for detecting sensitive data in messages, and give security teams a process-level view of risk across email and collaboration workflows.

Darktrace / EMAIL Inbox Analysis highlights risky content within your emails

A warning is more useful when it explains what the user should look at. To help do that, we’ve expanded Darktrace / EMAIL’s Inbox Analysis Add-In to highlight potentially dangerous content within the body of emails that Darktrace / EMAIL flags as potentially suspicious or high risk.  

The add-in can highlight language designed to create urgency, financial references, requests for payment, suspicious links, and content that is unusual for the sender. Each highlighted element includes a pop up that explains why it may be suspicious. Instead of asking an employee to accept a verdict without context, the analysis helps them examine the message and make a more informed decision.

Enhanced Just-In-Time Training Banners in Darktrace / Adaptive Human Defense

Enhanced Just-In-Time Training Banners build on the same principle. The banners now include a contextual header, actionable advice, and specific detection context. This gives employees more useful guidance at the point of risk without adding unnecessary information or cognitive load.

Together, the capabilities help turn a warning into a short learning moment. Employees can see what looks unusual, understand what action to take, and build their judgment.

Custom Sensitive Data Detection in Darktrace / EMAIL - Data Loss Prevention

Sensitive data is different for every business. Standard categories such as payment card details or government identifiers matter, but organizations also have their own customer codes, project names, research formats, account structures, and internal identifiers.

Custom Sensitive Data Detection in Darktrace / EMAIL - Data Loss Prevention allows administrators to write custom expressions for the data their organization needs to protect. Matched content can trigger existing model actions and data loss prevention (DLP) workflows, extending Darktrace's DLP capabilities.

This extends data loss detection beyond a fixed library of common data types. Security teams can apply controls to information that is sensitive in the context of their own organization and adapt those controls as the business changes.

Introducing Email and Collaboration Workflow Risk Posture Dashboards

Some of the most important risks are not isolated events. They are repeated ways of working that create an opening for error, misuse, or attack. For example, a payment request may be one suspicious message, but a recurring approval workflow that relies on weak verification is a business process risk.

The new Email and Collaboration Workflow Risk Posture Dashboard analyzes email and collaboration data across Email, Microsoft Teams, Slack and Zoom to provide a process-level view of risk in the organization. These may include financial authorization workflows, sensitive data sharing patterns, and activity that could expose credentials.

The dashboard brings these patterns into a view and provides actionable recommendations. This helps security teams determine where to investigate or strengthen controls, where ownership needs to be clarified, and where the business may need to change a risky process. It gives CISOs a clearer view of how human and communication risk is embedded in everyday operations, not only where individual alerts occur.

Behavior connects the individual decision to the wider risk

These capabilities build on Darktrace’s unique behavioral approach to security. We use Adaptive AI to learn how people and AI normally behave within an organization, creating the context needed to recognize when activity changes.

Within the Darktrace Behavioral Defense Platform, Darktrace / EMAIL helps protect people against phishing, account takeover, data exfiltration, and human risk across email and collaboration tools. The new capabilities extend that protection in both directions. They give employees clearer context for the decision in front of them, while giving security leaders a broader view of the workflows and behavior that create risk across the organization.

The result is not simply more alerts. It is a better understanding of why something is risky, what action to take, and where the organization can reduce risk before a familiar process becomes an easy route for an attacker.

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About the author
Carlos Gray
Senior Product Marketing Manager, Email
Your data. Our AI.
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