Mimecast Link Rewriting: A False Sense of Security Exposed
Gain insight into modern email security methods to ensure you avoid pitfalls of traditional email gateways. Learn why rewriting links isn't the best approach.
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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04
Nov 2020
Many organizations feel secure in the knowledge that their email gateway is rewriting all of the harmful links targeting their employees. Link rewriting is a common technique that involves encoding URLs sent via email into a link that redirects the user to the gateway’s own servers. These servers contain some unique codes that then track the user and perform later checks to determine whether the link is malicious.
This blog reveals why the sense of protection this gives is a fallacy, and how rewriting links does not equate to protecting the end user from actual harm. In fact, gateways’ reliance on this technique is actually an indicator of one of their fundamental flaws: their reliance on rules and signatures of previously recognized threats, and their consequent inability to stop threats on the first encounter. The reason these tools pre-emptively rewrite links is so they can make a determination later on: with the link now pointing to their own servers, they can leverage their updated assessment of that link and block a malicious site, once more information has become available (often once ‘patient zero’ has become infected; and the damage is already done).
Email security that recognizes and blocks threats on the first encounter has no need to rewrite every link.
How to measure success
If the sheer number of links rewritten is to be our measure of success, then traditional gateways win every time. For instance, Mimecast will usually rewrite 100% of the harmful links that Antigena Email locks. In fact, it rewrites nearly 100% of all links. That even includes links pointing to trusted websites like LinkedIn and Twitter, and even emails containing links to the recipient’s own website. So when tim.cook[at]apple.com receives a link to apple.com, for example, ‘mimecast.com’ will still dominate the URL.
Some organizations suffering from low first-encounter catch rates with their gateways have responded by increasing employee education: training the human to spot the giveaways of a phishing email. With email attacks getting more targeted and sophisticated, humans should never be considered the last line of defense, and rewriting links makes the situation even worse. If you’re training your users to watch which links they’re clicking, and every one of those links reads ‘mimecast.com’, how are your users supposed to learn what’s good, bad, or sketchy when every URL looks the same?
Moreover, when Mimecast’s URL gateway is down, these rewritten links don’t work (and the same applies to protected attachments). This results in business downtime which is intolerable for businesses in these critical and challenging times.
We can see the effect of blanket rewriting through Darktrace’s user interface, which shows us the frequency of rewritten links over time. Looking back over three days, this particular customer – who was trialing Antigena Email alongside Mimecast, received 155,008 emails containing rewritten links. Of those, 1,478 were anomalous, and Darktrace’s AI acted to immediately lock those links, protecting even the first recipient from harm. The remaining 153,530 links were all unnecessarily rewritten.
Figure 1: Over 155,000 inbound emails contained rewritten Mimecast links
If it comes to actually stopping the threat when a user goes to click that rewritten link, gateway tools fail. Their reliance on legacy checks like reputation, deny-lists, and rules and signatures mean that malicious content will sometimes sit for days or weeks without any meaningful action, as the technology requires at least one – and usually many – ‘patient zeros’ before determining a URL or an attachment as malicious, and updating their deny-lists.
Let’s look at the case of an attack launched from entirely new infrastructure: from a freshly purchased domain, and containing a newly created malicious payload. None of the typical metrics legacy tools search for appear as malicious, and so of course, the threat gets through, and ‘patient zero’ is infected.
Figure 2: ‘Patient Zero’ denotes the first victim of an email attack.
It inevitably takes time for the malicious link to be recognized as malicious, and for that to be reported. By this point, large swathes of the workforce have also become infected. We can call this the ‘time to detection’.
Figure 3: The time to detection
As legacy tools then update their lists in recognition of the attack, the malware continues to infect the organization, with more users engaging in the contents of the email.
Figure 4: The legacy tool reacts
Finally, the legacy tool reacts, updating its deny-list and providing substantive action to protect the end user from harm. By this point, hundreds of users across multiple organizations may have interacted with the links in some way.
Figure 5: Many ‘patient zeros’ are required before the threat is deny-listed
Email gateways’ reliance on rewriting links is directly related to their legacy approach to detection. They do it so that later down the line, when they have updated information about a potential attack, they can take action. Until then, it’s just a rewritten link, and if clicked on, it will bring the user to whatever website was hiding underneath it.
These links are also rewritten in an attempt to grasp an understanding of what user network behavior looks like. But far from giving an accurate or in-depth picture of network activity, this method barely scratches the surface of the wider behaviors of users across the organization.
Alongside Darktrace’s Enterprise Immune System, Antigena Email can pull these insights directly from a unified, central AI engine that has complete and direct visibility over an organization’s entire digital estate – not just links accessed from emails, but network activity as a whole – and not a makeshift version where it is assumed people only visit links through emails. It also pulls insights from user behavior in the cloud and across SaaS applications – from Salesforce to Microsoft Teams.
Taking real action in real time
While gateways rewrite everything in order to leave the door open to make assessments later on, Darktrace is able to take action when it needs to – before the email poses a threat in the inbox. The technology is uniquely able to do this due to its high success rates for malicious emails seen on first encounter. And it’s able to achieve such high success rates because it takes a much more sophisticated approach to detection that uses AI to catch a threat – regardless of whether or not that threat has been seen before.
Darktrace’s understanding of ‘normal’ for the human behind email communications allows it to not only detect subtle deviations that are indicative of a cyber-threat, but respond to that threat at the point of delivery. This response is targeted, proportionate and non-disruptive, and varies according to the nature of the attack. While Darktrace’s unsupervised machine learning can accurately identify deviations from ‘normal’, its supervised machine learning models are able to classify the intention behind the email; what the attacker is trying to do (extort information, solicit a payment, harvest credentials, or convince the user to download a malicious attachment).
Crucially, organizations trialing both approaches to security find that Antigena Email consistently identifies threats that Mimecast and other tools miss. With the scale and sophistication of email attacks growing, the need for a proactive and modern approach to email security is paramount. Organizations need to ensure they are measuring their sense of protection with the right yardstick, and adopt a technology that can take meaningful action before damage is done.
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.
Inside Akira’s SonicWall Campaign: Darktrace’s Detection and Response
Introduction: Background on Akira SonicWall campaign
Between July and August 2025, security teams worldwide observed a surge in Akira ransomware incidents involving SonicWall SSL VPN devices [1]. Initially believed to be the result of an unknown zero-day vulnerability, SonicWall later released an advisory announcing that the activity was strongly linked to a previously disclosed vulnerability, CVE-2024-40766, first identified over a year earlier [2].
On August 20, 2025, Darktrace observed unusual activity on the network of a customer in the US. Darktrace detected a range of suspicious activity, including network scanning and reconnaissance, lateral movement, privilege escalation, and data exfiltration. One of the compromised devices was later identified as a SonicWall virtual private network (VPN) server, suggesting that the incident was part of the broader Akira ransomware campaign targeting SonicWall technology.
As the customer was subscribed to the Managed Detection and Response (MDR) service, Darktrace’s Security Operations Centre (SOC) team was able to rapidly triage critical alerts, restrict the activity of affected devices, and notify the customer of the threat. As a result, the impact of the attack was limited - approximately 2 GiB of data had been observed leaving the network, but any further escalation of malicious activity was stopped.
Threat Overview
CVE-2024-40766 and other misconfigurations
CVE-2024-40766 is an improper access control vulnerability in SonicWall’s SonicOS, affecting Gen 5, Gen 6, and Gen 7 devices running SonicOS version 7.0.1 5035 and earlier [3]. The vulnerability was disclosed on August 23, 2024, with a patch released the same day. Shortly after, it was reported to be exploited in the wild by Akira ransomware affiliates and others [4].
Almost a year later, the same vulnerability is being actively targeted again by the Akira ransomware group. In addition to exploiting unpatched devices affected by CVE-2024-40766, security researchers have identified three other risks potentially being leveraged by the group [5]:
*The Virtual Office Portal can be used to initially set up MFA/TOTP configurations for SSLVPN users.
Thus, even if SonicWall devices were patched, threat actors could still target them for initial access by reusing previously stolen credentials and exploiting other misconfigurations.
Akira Ransomware
Akira ransomware was first observed in the wild in March 2023 and has since become one of the most prolific ransomware strains across the threat landscape [6]. The group operates under a Ransomware-as-a-Service (RaaS) model and frequently uses double extortion tactics, pressuring victims to pay not only to decrypt files but also to prevent the public release of sensitive exfiltrated data.
The ransomware initially targeted Windows systems, but a Linux variant was later observed targeting VMware ESXi virtual machines [7]. In 2024, it was assessed that Akira would continue to target ESXi hypervisors, making attacks highly disruptive due to the central role of virtualisation in large-scale cloud deployments. Encrypting the ESXi file system enables rapid and widespread encryption with minimal lateral movement or credential theft. The lack of comprehensive security protections on many ESXi hypervisors also makes them an attractive target for ransomware operators [8].
Victimology
Akira is known to target organizations across multiple sectors, most notably those in manufacturing, education, and healthcare. These targets span multiple geographic regions, including North America, Latin America, Europe and Asia-Pacific [9].
Figure 1: Geographical distribution of organization’s affected by Akira ransomware in 2025 [9].
Common Tactics, Techniques and Procedures (TTPs) [7][10]
Initial Access Targets remote access services such as RDP and VPN through vulnerability exploitation or stolen credentials.
Reconnaissance Uses network scanning tools like SoftPerfect and Advanced IP Scanner to map the environment and identify targets.
Lateral Movement Moves laterally using legitimate administrative tools, typically via RDP.
Persistence Employs techniques such as Kerberoasting and pass-the-hash, and tools like Mimikatz to extract credentials. Known to create new domain accounts to maintain access.
Command and Control Utilizes remote access tools including AnyDesk, RustDesk, Ngrok, and Cloudflare Tunnel.
Exfiltration Uses tools such as FileZilla, WinRAR, WinSCP, and Rclone. Data is exfiltrated via protocols like FTP and SFTP, or through cloud storage services such as Mega.
Darktrace’s Coverage of Akira ransomware
Reconnaissance
Darktrace first detected of unusual network activity around 05:10 UTC, when a desktop device was observed performing a network scan and making an unusual number of DCE-RPC requests to the endpoint mapper (epmapper) service. Network scans are typically used to identify open ports, while querying the epmapper service can reveal exposed RPC services on the network.
Multiple other devices were also later seen with similar reconnaissance activity, and use of the Advanced IP Scanner tool, indicated by connections to the domain advanced-ip-scanner[.]com.
Lateral movement
Shortly after the initial reconnaissance, the same desktop device exhibited unusual use of administrative tools. Darktrace observed the user agent “Ruby WinRM Client” and the URI “/wsman” as the device initiated a rare outbound Windows Remote Management (WinRM) connection to two domain controllers (REDACTED-dc1 and REDACTED-dc2). WinRM is a Microsoft service that uses the WS-Management (WSMan) protocol to enable remote management and control of network devices.
Darktrace also observed the desktop device connecting to an ESXi device (REDACTED-esxi1) via RDP using an LDAP service credential, likely with administrative privileges.
Credential access
At around 06:26 UTC, the desktop device was seen fetching an Active Directory certificate from the domain controller (REDACTED-dc1) by making a DCE-RPC request to the ICertPassage service. Shortly after, the device made a Kerberos login using the administrative credential.
Figure 3: Darktrace’s detection of the of anomalous certificate download and subsequent Kerberos login.
Further investigation into the device’s event logs revealed a chain of connections that Darktrace’s researchers believe demonstrates a credential access technique known as “UnPAC the hash.”
This method begins with pre-authentication using Kerberos’ Public Key Cryptography for Initial Authentication (PKINIT), allowing the client to use an X.509 certificate to obtain a Ticket Granting Ticket (TGT) from the Key Distribution Center (KDC) instead of a password.
The next stage involves User-to-User (U2U) authentication when requesting a Service Ticket (ST) from the KDC. Within Darktrace's visibility of this traffic, U2U was indicated by the client and service principal names within the ST request being identical. Because PKINIT was used earlier, the returned ST contains the NTLM hash of the credential, which can then be extracted and abused for lateral movement or privilege escalation [11].
Figure 4: Flowchart of Kerberos PKINIT pre-authentication and U2U authentication [12].
Figure 5: Device event log showing the Kerberos Login and Kerberos Ticket events.
Analysis of the desktop device’s event logs revealed a repeated sequence of suspicious activity across multiple credentials. Each sequence included a DCE-RPC ICertPassage request to download a certificate, followed by a Kerberos login event indicating PKINIT pre-authentication, and then a Kerberos ticket event consistent with User-to-User (U2U) authentication.
Darktrace identified this pattern as highly unusual. Cyber AI Analyst determined that the device used at least 15 different credentials for Kerberos logins over the course of the attack.
By compromising multiple credentials, the threat actor likely aimed to escalate privileges and facilitate further malicious activity, including lateral movement. One of the credentials obtained via the “UnPAC the hash” technique was later observed being used in an RDP session to the domain controller (REDACTED-dc2).
C2 / Additional tooling
At 06:44 UTC, the domain controller (REDACTED-dc2) was observed initiating a connection to temp[.]sh, a temporary cloud hosting service. Open-source intelligence (OSINT) reporting indicates that this service is commonly used by threat actors to host and distribute malicious payloads, including ransomware [13].
Shortly afterward, the ESXi device was observed downloading an executable named “vmwaretools” from the rare external endpoint 137.184.243[.]69, using the user agent “Wget.” The repeated outbound connections to this IP suggest potential command-and-control (C2) activity.
Figure 6: Cyber AI Analyst investigation into the suspicious file download and suspected C2 activity between the ESXI device and the external endpoint 137.184.243[.]69.
Figure 7: Packet capture (PCAP) of connections between the ESXi device and 137.184.243[.]69.
Data exfiltration
The first signs of data exfiltration were observed at around 7:00 UTC. Both the domain controller (REDACTED-dc2) and a likely SonicWall VPN device were seen uploading approximately 2 GB of data via SSH to the rare external endpoint 66.165.243[.]39 (AS29802 HVC-AS). OSINT sources have since identified this IP as an indicator of compromise (IoC) associated with the Akira ransomware group, known to use it for data exfiltration [14].
Figure 8: Cyber AI Analyst incident view highlighting multiple unusual events across several devices on August 20. Notably, it includes the “Unusual External Data Transfer” event, which corresponds to the anomalous 2 GB data upload to the known Akira-associated endpoint 66.165.243[.]39.
Cyber AI Analyst
Throughout the course of the attack, Darktrace’s Cyber AI Analyst autonomously investigated the anomalous activity as it unfolded and correlated related events into a single, cohesive incident. Rather than treating each alert as isolated, Cyber AI Analyst linked them together to reveal the broader narrative of compromise. This holistic view enabled the customer to understand the full scope of the attack, including all associated activities and affected assets that might otherwise have been dismissed as unrelated.
Figure 9: Overview of Cyber AI Analyst’s investigation, correlating all related internal and external security events across affected devices into a single pane of glass.
Containing the attack
In response to the multiple anomalous activities observed across the network, Darktrace's Autonomous Response initiated targeted mitigation actions to contain the attack. These included:
Blocking connections to known malicious or rare external endpoints, such as 137.184.243[.]69, 66.165.243[.]39, and advanced-ip-scanner[.]com.
Blocking internal traffic to sensitive ports, including 88 (Kerberos), 3389 (RDP), and 49339 (DCE-RPC), to disrupt lateral movement and credential abuse.
Enforcing a block on all outgoing connections from affected devices to contain potential data exfiltration and C2 activity.
Figure 10: Autonomous Response actions taken by Darktrace on an affected device, including the blocking of malicious external endpoints and internal service ports.
Managed Detection and Response
As this customer was an MDR subscriber, multiple Enhanced Monitoring alerts—high-fidelity models designed to detect activity indicative of compromise—were triggered across the network. These alerts prompted immediate investigation by Darktrace’s SOC team.
Upon determining that the activity was likely linked to an Akira ransomware attack, Darktrace analysts swiftly acted to contain the threat. At around 08:05 UTC, devices suspected of being compromised were quarantined, and the customer was promptly notified, enabling them to begin their own remediation procedures without delay.
A wider campaign?
Darktrace’s SOC and Threat Research teams identified at least three additional incidents likely linked to the same campaign. All targeted organizations were based in the US, spanning various industries, and each have indications of using SonicWall VPN, indicating it had likely been targeted for initial access.
Across these incidents, similar patterns emerged. In each case, a suspicious executable named “vmwaretools” was downloaded from the endpoint 85.239.52[.]96 using the user agent “Wget”, bearing some resemblance to the file downloads seen in the incident described here. Data exfiltration was also observed via SSH to the endpoints 107.155.69[.]42 and 107.155.93[.]154, both of which belong to the same ASN also seen in the incident described in this blog: S29802 HVC-AS. Notably, 107.155.93[.]154 has been reported in OSINT as an indicator associated with Akira ransomware activity [15]. Further recent Akira ransomware cases have been observed involving SonicWall VPN, where no similar executable file downloads were observed, but SSH exfiltration to the same ASN was. These overlapping and non-overlapping TTPs may reflect the blurring lines between different affiliates operating under the same RaaS.
Lessons from the campaign
This campaign by Akira ransomware actors underscores the critical importance of maintaining up-to-date patching practices. Threat actors continue to exploit previously disclosed vulnerabilities, not just zero-days, highlighting the need for ongoing vigilance even after patches are released. It also demonstrates how misconfigurations and overlooked weaknesses can be leveraged for initial access or privilege escalation, even in otherwise well-maintained environments.
Darktrace’s observations further reveal that ransomware actors are increasingly relying on legitimate administrative tools, such as WinRM, to blend in with normal network activity and evade detection. In addition to previously documented Kerberos-based credential access techniques like Kerberoasting and pass-the-hash, this campaign featured the use of UnPAC the hash to extract NTLM hashes via PKINIT and U2U authentication for lateral movement or privilege escalation.
Credit to Emily Megan Lim (Senior Cyber Analyst), Vivek Rajan (Senior Cyber Analyst), Ryan Traill (Analyst Content Lead), and Sam Lister (Specialist Security Researcher)
Appendices
Darktrace Model Detections
Anomalous Connection / Active Remote Desktop Tunnel
Anomalous Connection / Data Sent to Rare Domain
Anomalous Connection / New User Agent to IP Without Hostname
Anomalous Connection / Possible Data Staging and External Upload
Anomalous Connection / Rare WinRM Incoming
Anomalous Connection / Rare WinRM Outgoing
Anomalous Connection / Uncommon 1 GiB Outbound
Anomalous Connection / Unusual Admin RDP Session
Anomalous Connection / Unusual Incoming Long Remote Desktop Session
Anomalous Connection / Unusual Incoming Long SSH Session
Anomalous Connection / Unusual Long SSH Session
Anomalous File / EXE from Rare External Location
Anomalous Server Activity / Anomalous External Activity from Critical Network Device
Anomalous Server Activity / Outgoing from Server
Anomalous Server Activity / Rare External from Server
Compliance / Default Credential Usage
Compliance / High Priority Compliance Model Alert
Compliance / Outgoing NTLM Request from DC
Compliance / SSH to Rare External Destination
Compromise / Large Number of Suspicious Successful Connections
Compromise / Sustained TCP Beaconing Activity To Rare Endpoint
Device / Anomalous Certificate Download Activity
Device / Anomalous SSH Followed By Multiple Model Alerts
Device / Anonymous NTLM Logins
Device / Attack and Recon Tools
Device / ICMP Address Scan
Device / Large Number of Model Alerts
Device / Network Range Scan
Device / Network Scan
Device / New User Agent To Internal Server
Device / Possible SMB/NTLM Brute Force
Device / Possible SMB/NTLM Reconnaissance
Device / RDP Scan
Device / Reverse DNS Sweep
Device / Suspicious SMB Scanning Activity
Device / UDP Enumeration
Unusual Activity / Unusual External Data to New Endpoint
Unusual Activity / Unusual External Data Transfer
User / Multiple Uncommon New Credentials on Device
User / New Admin Credentials on Client
User / New Admin Credentials on Server
Enhanced Monitoring Models
Compromise / Anomalous Certificate Download and Kerberos Login
Device / Initial Attack Chain Activity
Device / Large Number of Model Alerts from Critical Network Device
Device / Multiple Lateral Movement Model Alerts
Device / Suspicious Network Scan Activity
Unusual Activity / Enhanced Unusual External Data Transfer
Antigena/Autonomous Response Models
Antigena / Network / External Threat / Antigena File then New Outbound Block
Out of Character: Detecting Vendor Compromise and Trusted Relationship Abuse with Darktrace
What is Vendor Email Compromise?
Vendor Email Compromise (VEC) refers to an attack where actors breach a third-party provider to exploit their access, relationships, or systems for malicious purposes. The initially compromised entities are often the target’s existing partners, though this can extend to any organization or individual the target is likely to trust.
Itsits at the intersection of supply chain attacks and business email compromise (BEC), blending technical exploitation with trust-based deception. Attackers often infiltrate existing conversations, leveraging AI to mimic tone and avoid common spelling and grammar pitfalls. Malicious content is typically hosted on otherwise reputable file sharing platforms, meaning any shared links initially seem harmless.
While techniques to achieve initial access may have evolved, the goals remain familiar. Threat actors harvest credentials, launch subsequent phishing campaigns, attempt to redirect invoice payments for financial gain, and exfiltrate sensitive corporate data.
Why traditional defenses fall short
These subtle and sophisticated email attacks pose unique challenges for defenders. Few busy people would treat an ongoing conversation with a trusted contact with the same level of suspicion as an email from the CEO requesting ‘URGENT ASSISTANCE!’ Unfortunately, many traditional secure email gateways (SEGs) struggle with this too. Detecting an out-of-character email, when it does not obviously appear out of character, is a complex challenge. It’s hardly surprising, then, that 83% of organizations have experienced a security incident involving third-party vendors [1].
This article explores how Darktrace detected four different vendor compromise campaigns for a single customer, within a two-week period in 2025. Darktrace / EMAIL successfully identified the subtle indicators that these seemingly benign emails from trusted senders were, in fact, malicious. Due to the configuration of Darktrace / EMAIL in this customer’s environment, it was unable to take action against the malicious emails. However, if fully enabled to take Autonomous Response, it would have held all offending emails identified.
How does Darktrace detect vendor compromise?
The answer lies at the core of how Darktrace operates: anomaly detection. Rather than relying on known malicious rules or signatures, Darktrace learns what ‘normal’ looks like for an environment, then looks for anomalies across a wide range of metrics. Despite the resourcefulness of the threat actors involved in this case, Darktrace identified many anomalies across these campaigns.
Different campaigns, common traits
A wide variety of approaches was observed. Individuals, shared mailboxes and external contractors were all targeted. Two emails originated from compromised current vendors, while two came from unknown compromised organizations - one in an associated industry. The sender organizations were either familiar or, at the very least, professional in appearance, with no unusual alphanumeric strings or suspicious top-level domains (TLDs). Subject line, such as “New Approved Statement From [REDACTED]” and “[REDACTED] - Proposal Document” appeared unremarkable and were not designed to provoke heightened emotions like typical social engineering or BEC attempts.
All emails had been given a Microsoft Spam Confidence Level of 1, indicating Microsoft did not consider them to be spam or malicious [2]. They also passed authentication checks (including SPF, and in some cases DKIM and DMARC), meaning they appeared to originate from an authentic source for the sender domain and had not been tampered with in transit.
All observed phishing emails contained a link hosted on a legitimate and commonly used file-sharing site. These sites were often convincingly themed, frequently featuring the name of a trusted vendor either on the page or within the URL, to appear authentic and avoid raising suspicion. However, these links served only as the initial step in a more complex, multi-stage phishing process.
Figure 1: A legitimate file sharing site used in phishing emails to host a secondary malicious link.
Figure 2: Another example of a legitimate file sharing endpoint sent in a phishing email and used to host a malicious link.
If followed, the recipient would be redirected, sometimes via CAPTCHA, to fake Microsoft login pages designed to capturing credentials, namely http://pub-ac94c05b39aa4f75ad1df88d384932b8.r2[.]dev/offline[.]html and https://s3.us-east-1.amazonaws[.]com/s3cure0line-0365cql0.19db86c3-b2b9-44cc-b339-36da233a3be2ml0qin/s3cccql0.19db86c3-b2b9-44cc-b339-36da233a3be2%26l0qn[.]html#.
The latter made use of homoglyphs to deceive the user, with a link referencing ‘s3cure0line’, rather than ‘secureonline’. Post-incident investigation using open-source intelligence (OSINT) confirmed that the domains were linked to malicious phishing endpoints [3] [4].
Figure 3: Fake Microsoft login page designed to harvest credentials.
Figure 4: Phishing kit with likely AI-generated image, designed to harvest user credentials. The URL uses ‘s3cure0line’ instead of ‘secureonline’, a subtle misspelling intended to deceive users.
Darktrace Anomaly Detection
Some senders were unknown to the network, with no previous outbound or inbound emails. Some had sent the email to multiple undisclosed recipients using BCC, an unusual behavior for a new sender.
Where the sender organization was an existing vendor, Darktrace recognized out-of-character behavior, in this case it was the first time a link to a particular file-sharing site had been shared. Often the links themselves exhibited anomalies, either being unusually prominent or hidden altogether - masked by text or a clickable image.
Crucially, Darktrace / EMAIL is able to identify malicious links at the time of processing the emails, without needing to visit the URLs or analyze the destination endpoints, meaning even the most convincing phishing pages cannot evade detection – meaning even the most convincing phishing emails cannot evade detection. This sets it apart from many competitors who rely on crawling the endpoints present in emails. This, among other things, risks disruption to user experience, such as unsubscribing them from emails, for instance.
Darktrace was also able to determine that the malicious emails originated from a compromised mailbox, using a series of behavioral and contextual metrics to make the identification. Upon analysis of the emails, Darktrace autonomously assigned several contextual tags to highlight their concerning elements, indicating that the messages contained phishing links, were likely sent from a compromised account, and originated from a known correspondent exhibiting out-of-character behavior.
Figure 5: Tags assigned to offending emails by Darktrace / EMAIL.
Figure 6: A summary of the anomalous email, confirming that it contained a highly suspicious link.
Out-of-character behavior caught in real-time
In another customer environment around the same time Darktrace / EMAIL detected multiple emails with carefully crafted, contextually appropriate subject lines sent from an established correspondent being sent to 30 different recipients. In many cases, the attacker hijacked existing threads and inserted their malicious emails into an ongoing conversation in an effort to blend in and avoid detection. As in the previous, the attacker leveraged a well-known service, this time ClickFunnels, to host a document containing another malicious link. Once again, they were assigned a Microsoft Spam Confidence Level of 1, indicating that they were not considered malicious.
Figure 7: The legitimate ClickFunnels page used to host a malicious phishing link.
This time, however, the customer had Darktrace / EMAIL fully enabled to take Autonomous Response against suspicious emails. As a result, when Darktrace detected the out-of-character behavior, specifically, the sharing of a link to a previously unused file-sharing domain, and identified the likely malicious intent of the message, it held the email, preventing it from reaching recipients’ inboxes and effectively shutting down the attack.
Figure 8: Darktrace / EMAIL’s detection of malicious emails inserted into an existing thread.*
*To preserve anonymity, all real customer names, email addresses, and other identifying details have been redacted and replaced with fictitious placeholders.
Legitimate messages in the conversation were assigned an Anomaly Score of 0, while the newly inserted malicious emails identified and were flagged with the maximum score of 100.
Key takeaways for defenders
Phishing remains big business, and as the landscape evolves, today’s campaigns often look very different from earlier versions. As with network-based attacks, threat actors are increasingly leveraging legitimate tools and exploiting trusted relationships to carry out their malicious goals, often staying under the radar of security teams and traditional email defenses.
As attackers continue to exploit trusted relationships between organizations and their third-party associates, security teams must remain vigilant to unexpected or suspicious email activity. Protecting the digital estate requires an email solution capable of identifying malicious characteristics, even when they originate from otherwise trusted senders.
Credit to Jennifer Beckett (Cyber Analyst), Patrick Anjos (Senior Cyber Analyst), Ryan Traill (Analyst Content Lead), Kiri Addison (Director of Product)
Appendices
IoC - Type - Description + Confidence
- http://pub-ac94c05b39aa4f75ad1df88d384932b8.r2[.]dev/offline[.]html#p – fake Microsoft login page
- https://s3.us-east-1.amazonaws[.]com/s3cure0line-0365cql0.19db86c3-b2b9-44cc-b339-36da233a3be2ml0qin/s3cccql0.19db86c3-b2b9-44cc-b339-36da233a3be2%26l0qn[.]html# - link to domain used in homoglyph attack
The content provided in this blog is published by Darktrace for general informational purposes only and reflects our understanding of cybersecurity topics, trends, incidents, and developments at the time of publication. While we strive to ensure accuracy and relevance, the information is provided “as is” without any representations or warranties, express or implied. Darktrace makes no guarantees regarding the completeness, accuracy, reliability, or timeliness of any information presented and expressly disclaims all warranties.
Nothing in this blog constitutes legal, technical, or professional advice, and readers should consult qualified professionals before acting on any information contained herein. Any references to third-party organizations, technologies, threat actors, or incidents are for informational purposes only and do not imply affiliation, endorsement, or recommendation.
Darktrace, its affiliates, employees, or agents shall not be held liable for any loss, damage, or harm arising from the use of or reliance on the information in this blog.
The cybersecurity landscape evolves rapidly, and blog content may become outdated or superseded. We reserve the right to update, modify, or remove any content
![Geographical distribution of organization’s affected by Akira ransomware in 2025 [9].](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/68e684a90c107be86fa5c2e0_Screenshot%202025-10-08%20at%207.53.20%E2%80%AFAM.png)
![Flowchart of Kerberos PKINIT pre-authentication and U2U authentication [12].](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/68e53a2b5e9394d5a5cbebb7_Screenshot%202025-10-07%20at%209.04.43%E2%80%AFAM.png)
![Cyber AI Analyst investigation into the suspicious file download and suspected C2 activity between the ESXI device and the external endpoint 137.184.243[.]69.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/68e53a8ea01e348d5a62a6c3_Screenshot%202025-10-07%20at%209.06.31%E2%80%AFAM.png)
![Packet capture (PCAP) of connections between the ESXi device and 137.184.243[.]69.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/68e53ae5304f84a4192967db_Screenshot%202025-10-07%20at%209.07.53%E2%80%AFAM.png)
![Cyber AI Analyst incident view highlighting multiple unusual events across several devices on August 20. Notably, it includes the “Unusual External Data Transfer” event, which corresponds to the anomalous 2 GB data upload to the known Akira-associated endpoint 66.165.243[.]39.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/68e53b26d90343a0a6ab3bb2_Screenshot%202025-10-07%20at%209.09.02%E2%80%AFAM.png)
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