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October 14, 2024

How Triada Affects Banking and Communication Apps

Explore the intricacies of the Triada Trojan and its targeting of communication and banking apps. Learn how to safeguard against this threat.
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
Justin Torres
Cyber Analyst
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14
Oct 2024

The rise of android malware

Recently, there has been a significant increase in malware strains targeting mobile devices, with a growing number of Android-based malware families, such as banking trojans, which aim to steal sensitive banking information from organizations and individuals worldwide.

These malware families attempt to access users’ accounts to steal online banking credentials and cookies, bypass multi-factor authentication (MFA), and conduct automatic transactions to steal funds [1]. They often masquerade as legitimate software or communications from social media platforms to compromise devices. Once installed, they use tactics such as keylogging, dumping cached credentials, and searching the file system for stored passwords to steal credentials, take over accounts, and potentially perform identity theft [1].

One recent example is the Antidot Trojan, which infects devices by disguising itself as an update page for Google Play. It establishes a command-and-control (C2) channel with a server, allowing malicious actors to execute commands and collect sensitive data [2].

Despite these malware’s ability to evade detection by standard security software, for example, by changing their code [3], Darktrace recently detected another Android malware family, Triada, communicating with a C2 server and exfiltrating data.

Triada: Background and tactics

First surfacing in 2016, Triada is a modular mobile trojan known to target banking and financial applications, as well as popular communication applications like WhatsApp, Facebook, and Google Mail [4]. It has been deployed as a backdoor on devices such as CTV boxes, smartphones, and tablets during the supply chain process [5]. Triada can also be delivered via drive-by downloads, phishing campaigns, smaller trojans like Leech, Ztorg, and Gopro, or more recently, as a malicious module in applications such as unofficial versions of WhatsApp, YoWhatsApp, and FM WhatsApp [6] [7].

How does Triada work?

Once downloaded onto a user’s device, Triada collects information about the system, such as the device’s model, OS version, SD card space, and list of installed applications, and sends this information to a C2 server. The server then responds with a configuration file containing the device’s personal identification number and settings, including the list of modules to be installed.

After a device has been successfully infected by Triada, malicious actors can monitor and intercept incoming and outgoing texts (including two-factor authentication messages), steal login credentials and credit card information from financial applications, divert in-application purchases to themselves, create fake messaging and email accounts, install additional malicious applications, infect devices with ransomware, and take control of the camera and microphone [4] [7].

For devices infected by unofficial versions of WhatsApp, which are downloaded from third-party app stores [9] and from mobile applications such as Snaptube and Vidmate , Triada collects unique device identifiers, information, and keys required for legitimate WhatsApp to work and sends them to a remote server to register the device [7] [12]. The server then responds by sending a link to the Triada payload, which is downloaded and launched. This payload will also download additional malicious modules, sign into WhatsApp accounts on the target’s phone, and request the same permissions as the legitimate WhatsApp application, such as access to SMS messages. If granted, a malicious actor can sign the user up for paid subscriptions without their knowledge. Triada then collects information about the user’s device and mobile operator and sends it to the C2 server [9] [12].

How does Triada avoid detection?

Triada evades detection by modifying the Zygote process, which serves as a template for every application in the Android OS. This enables the malware to become part of every application launched on a device [3]. It also substitutes system functions and conceals modules from the list of running processes and installed apps, ensuring that the system does not raise the alarm [3]. Additionally, as Triada connects to a C2 server on the first boot, infected devices remain compromised even after a factory reset [4].

Triada attack overview

Across multiple customer deployments, devices were observed making a large number of connections to a range of hostnames, primarily over encrypted SSL and HTTPS protocols. These hostnames had never previously been observed on the customers’ networks and appear to be algorithmically generated. Examples include “68u91.66foh90o[.]com”, “92n7au[.]uhabq9[.]com”, “9yrh7.mea5ms[.]com”, and “is5jg.3zweuj[.]com”.

External Sites Summary Graph showing the rarity of the hostname “92n7au[.]uhabq9[.]com” on a customer network.
Figure 1: External Sites Summary Graph showing the rarity of the hostname “92n7au[.]uhabq9[.]com” on a customer network.

Most of the IP addresses associated with these hostnames belong to an ASN associated with the cloud provider Alibaba (i.e., AS45102 Alibaba US Technology Co., Ltd). These connections were made over a range of high number ports over 1000, most commonly over 30000 such as 32091, which Darktrace recognized as extremely unusual for the SSL and HTTPS protocols.

Screenshot of a Model Alert Event log showing a device connecting to the endpoint “is5jg[.]3zweuj[.]com” over port 32091.
Figure 2: Screenshot of a Model Alert Event log showing a device connecting to the endpoint “is5jg[.]3zweuj[.]com” over port 32091.

On several customer deployments, devices were seen exfiltrating data to hostnames which also appeared to be algorithmically generated. This occurred via HTTP POST requests containing unusual URI strings that were made without a prior GET request, indicating that the infected device was using a hardcoded list of C2 servers.

Screenshot of a Model Alert Event Log showing the device posting the string “i8xps1” to the hostname “72zf6.rxqfd[.]com.
Figure 3: Screenshot of a Model Alert Event Log showing the device posting the string “i8xps1” to the hostname “72zf6.rxqfd[.]com.
 Screenshot of a Model Alert Event Log showing the device posting the string “sqyjyadwwq” to the hostname “9yrh7.mea5ms[.]com”.
Figure 4: Screenshot of a Model Alert Event Log showing the device posting the string “sqyjyadwwq” to the hostname “9yrh7.mea5ms[.]com”.

These connections correspond with reports that devices affected by Triada communicate with the C2 server to transmit their information and receive instructions for installing the payload.

A number of these endpoints have communicating files associated with the unofficial WhatsApp versions YoWhatsApp and FM WhatsApp [11] [12] [13] . This could indicate that the devices connecting to these endpoints were infected via malicious modules in the unofficial versions of WhatsApp, as reported by open-source intelligence (OSINT) [10] [12]. It could also mean that the infected devices are using these connections to download additional files from the C2 server, which could infect systems with additional malicious modules related to Triada.

Moreover, on certain customer deployments, shortly before or after connecting to algorithmically generated hostnames with communicating files linked to YoWhatsApp and FM WhatsApp, devices were also seen connecting to multiple endpoints associated with WhatsApp and Facebook.

Figure 5: Screenshot from a device’s event log showing connections to endpoints associated with WhatsApp shortly after it connected to “9yrh7.mea5ms[.]com”.

These surrounding connections indicate that Triada is attempting to sign in to the users’ WhatsApp accounts on their mobile devices to request permissions such as access to text messages. Additionally, Triada sends information about users’ devices and mobile operators to the C2 server.

The connections made to the algorithmically generated hostnames over SSL and HTTPS protocols, along with the HTTP POST requests, triggered multiple Darktrace models to alert. These models include those that detect connections to potentially algorithmically generated hostnames, connections over ports that are highly unusual for the protocol used, unusual connectivity over the SSL protocol, and HTTP POSTs to endpoints that Darktrace has determined to be rare for the network.

Conclusion

Recently, the use of Android-based malware families, aimed at stealing banking and login credentials, has become a popular trend among threat actors. They use this information to perform identity theft and steal funds from victims worldwide.

Across affected customers, multiple devices were observed connecting to a range of likely algorithmically generated hostnames over SSL and HTTPS protocols. These devices were also seen sending data out of the network to various hostnames via HTTP POST requests without first making a GET request. The URIs in these requests appeared to be algorithmically generated, suggesting the exfiltration of sensitive network data to multiple Triada C2 servers.

This activity highlights the sophisticated methods used by malware like Triada to evade detection and exfiltrate data. It underscores the importance of advanced security measures and anomaly-based detection systems to identify and mitigate such mobile threats, protecting sensitive information and maintaining network integrity.

Credit to: Justin Torres (Senior Cyber Security Analyst) and Anna Gilbertson (Cyber Security Analyst).

Appendices

Darktrace Model Detections

Model Alert Coverage

Anomalous Connection / Application Protocol on Uncommon Port

Anomalous Connection / Multiple Connections to New External TCP Port

Anomalous Connection / Multiple HTTP POSTS to Rare Hostname

Anomalous Connections / Multiple Failed Connections to Rare Endpoint

Anomalous Connection / Suspicious Expired SSL

Compromise / DGA Beacon

Compromise / Domain Fluxing

Compromise / Fast Beaconing to DGA

Compromise / Sustained SSL or HTTP Increase

Compromise / Unusual Connections to Rare Lets Encrypt

Unusual Activity / Unusual External Activity

AI Analyst Incident Coverage

Unusual Repeated Connections to Multiple Endpoints

Possible SSL Command and Control

Unusual Repeated Connections

List of Indicators of Compromise (IoCs)

Ioc – Type - Description

  • is5jg[.]3zweuj[.]com - Hostname - Triada C2 Endpoint
  • 68u91[.]66foh90o[.]com - Hostname - Triada C2 Endpoint
  • 9yrh7[.]mea5ms[.]com - Hostname - Triada C2 Endpoint
  • 92n7au[.]uhabq9[.]com - Hostname - Triada C2 Endpoint
  • 4a5x2[.]fs4ah[.]com - Hostname - Triada C2 Endpoint
  • jmll4[.]66foh90o[.]com - Hostname - Triada C2 Endpoint
  • mrswd[.]wo87sf[.]com - Hostname - Triada C2 Endpoint
  • lptkw[.]s4xx6[.]com - Hostname - Triada C2 Endpoint
  • ya27fw[.]k6zix6[.]com - Hostname - Triada C2 Endpoint
  • w0g25[.]66foh90o[.]com - Hostname - Triada C2 Endpoint
  • kivr8[.]wd6vy[.]com - Hostname - Triada C2 Endpoint
  • iuwe64[.]ct8pc6[.]com - Hostname - Triada C2 Endpoint
  • qefgn[.]8z0le[.]com - Hostname - Triada C2 Endpoint
  • a6y0x[.]xu0h7[.]com - Hostname - Triada C2 Endpoint
  • wewjyw[.]qb6ges[.]com - Hostname - Triada C2 Endpoint
  • vx9dle[.]n0qq3z[.]com - Hostname - Triada C2 Endpoint
  • 72zf6[.]rxqfd[.]com - Hostname - Triada C2 Endpoint
  • dwq[.]fsdw4f[.]com - Hostname - Triada C2 Endpoint
  • tqq6g[.]66foh90o[.]com - Hostname - Triada C2 Endpoint
  • 1rma1[.]4f8uq[.]com - Hostname - Triada C2 Endpoint
  • 0fdwa[.]7j3gj[.]com - Hostname - Triada C2 Endpoint
  • 5a7en[.]1e42t[.]com - Hostname - Triada C2 Endpoint
  • gmcp4[.]1e42t[.]com - Hostname - Triada C2 Endpoint
  • g7190[.]rt14v[.]com - Hostname - Triada C2 Endpoint
  • goyvi[.]2l2wa[.]com - Hostname - Triada C2 Endpoint
  • zq6kk[.]ca0qf[.]com - Hostname - Triada C2 Endpoint
  • sv83k[.]bn3avv[.]com - Hostname - Triada C2 Endpoint
  • 9sae7h[.]ct8pc6[.]com - Hostname - Triada C2 Endpoint
  • jpygmk[.]qt7tqr[.]com - Hostname - Triada C2 Endpoint
  • av2wg[.]rt14v[.]com - Hostname - Triada C2 Endpoint
  • ugbrg[.]osz1p[.]com - Hostname - Triada C2 Endpoint
  • hw2dm[.]wtws9k[.]com - Hostname - Triada C2 Endpoint
  • kj9atb[.]hai8j1[.]com - Hostname - Triada C2 Endpoint
  • pls9b[.]b0vb3[.]com - Hostname - Triada C2 Endpoint
  • 8rweau[.]j7e7r[.]com - Hostname - Triada C2 Endpoint
  • wkc5kn[.]j7e7r[.]com - Hostname - Triada C2 Endpoint
  • v58pq[.]mpvflv[.]com - Hostname - Triada C2 Endpoint
  • zmai4k[.]huqp3e[.]com - Hostname - Triada C2 Endpoint
  • eajgum[.]huqp3e[.]com - Hostname - Triada C2 Endpoint
  • mxl9zg[.]kv0pzv[.]com - Hostname - Triada C2 Endpoint
  • ad1x7[.]mea5ms[.]com - Hostname - Triada C2 Endpoint
  • ixhtb[.]s9gxw8[.]com - Hostname - Triada C2 Endpoint
  • vg1ne[.]uhabq9[.]com - Hostname - Triada C2 Endpoint
  • q5gd0[.]birxpk[.]com - Hostname - Triada C2 Endpoint
  • dycsw[.]h99n6[.]com - Hostname - Triada C2 Endpoint
  • a3miu[.]h99n6[.]com - Hostname - Triada C2 Endpoint
  • qru62[.]5qwu8b5[.]com - Hostname - Triada C2 Endpoint
  • 3eox8[.]abxkoop[.]com - Hostname - Triada C2 Endpoint
  • 0kttj[.]bddld[.]com - Hostname - Triada C2 Endpoint
  • gjhdr[.]xikuj[.]com - Hostname - Triada C2 Endpoint
  • zq6kk[.]wm0hd[.]com - Hostname - Triada C2 Endpoint
  • 8.222.219[.]234 - IP Address - Triada C2 Endpoint
  • 8.222.244[.]205 - IP Address - Triada C2 Endpoint
  • 8.222.243[.]182 - IP Address - Triada C2 Endpoint
  • 8.222.240[.]127 - IP Address - Triada C2 Endpoint
  • 8.219.123[.]139 - IP Address - Triada C2 Endpoint
  • 8.219.196[.]124 - IP Address - Triada C2 Endpoint
  • 8.222.217[.]73 - IP Address - Triada C2 Endpoint
  • 8.222.251[.]253 - IP Address - Triada C2 Endpoint
  • 8.222.194[.]254 - IP Address - Triada C2 Endpoint
  • 8.222.251[.]34 - IP Address - Triada C2 Endpoint
  • 8.222.216[.]105 - IP Address - Triada C2 Endpoint
  • 47.245.83[.]167 - IP Address - Triada C2 Endpoint
  • 198.200.54[.]56 - IP Address - Triada C2 Endpoint
  • 47.236.113[.]126 - IP Address - Triada C2 Endpoint
  • 47.241.47[.]128 - IP Address - Triada C2 Endpoint
  • /iyuljwdhxk - URI - Triada C2 URI
  • /gvuhlbzknh - URI - Triada C2 URI
  • /sqyjyadwwq - URI - Triada C2 URI
  • /cncyz3 - URI - Triada C2 URI
  • /42k0zk - URI - Triada C2 URI
  • /75kdl5 - URI - Triada C2 URI
  • /i8xps1 - URI - Triada C2 URI
  • /84gcjmo - URI - Triada C2 URI
  • /fkhiwf - URI - Triada C2 URI

MITRE ATT&CK Mapping

Technique Name - Tactic - ID - Sub-Technique of

Data Obfuscation - COMMAND AND CONTROL - T1001

Non-Standard Port - COMMAND AND CONTROL - T1571

Standard Application Layer Protocol - COMMAND AND CONTROL ICS - T0869

Non-Application Layer Protocol - COMMAND AND CONTROL - T1095

Masquerading - EVASION ICS - T0849

Man in the Browser - COLLECTION - T1185

Web Protocols - COMMAND AND CONTROL - T1071.001 -T1071

External Proxy - COMMAND AND CONTROL - T1090.002 - T1090

Domain Generation Algorithms - COMMAND AND CONTROL - T1568.002 - T1568

Web Services - RESOURCE DEVELOPMENT - T1583.006 - T1583

DNS - COMMAND AND CONTROL - T1071.004 - T1071

Fast Flux DNS - COMMAND AND CONTROL - T1568.001 - T1568

One-Way Communication - COMMAND AND CONTROL - T1102.003 - T1102

Digital Certificates - RESOURCE DEVELOPMENT - T1587.003 - T1587

References

[1] https://www.checkpoint.com/cyber-hub/cyber-security/what-is-trojan/what-is-a-banking-trojan/

[2] https://cyberfraudcentre.com/the-rise-of-the-antidot-android-banking-trojan-a-comprehensive-guide

[3] https://www.zimperium.com/glossary/banking-trojans/

[4] https://www.geeksforgeeks.org/what-is-triada-malware/

[5] https://www.infosecurity-magazine.com/news/malware-infected-devices-retailers/

[6] https://www.pcrisk.com/removal-guides/24926-triada-trojan-android

[7] https://securelist.com/malicious-whatsapp-mod-distributed-through-legitimate-apps/107690/

[8] https://securityboulevard.com/2024/02/impact-of-badbox-and-peachpit-malware-on-android-devices/

[9] https://threatpost.com/custom-whatsapp-build-malware/168892/

[10] https://securelist.com/triada-trojan-in-whatsapp-mod/103679/

[11] https://www.virustotal.com/gui/domain/is5jg.3zweuj.com/relations

[12] https://www.virustotal.com/gui/domain/92n7au.uhabq9.com/relations

[13] https://www.virustotal.com/gui/domain/68u91.66foh90o.com/relations

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
Justin Torres
Cyber Analyst

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August 21, 2025

From VPS to Phishing: How Darktrace Uncovered SaaS Hijacks through Virtual Infrastructure Abuse

VPS phishingDefault blog imageDefault blog image

What is a VPS and how are they abused?

A Virtual Private Server (VPS) is a virtualized server that provides dedicated resources and control to users on a shared physical device.  VPS providers, long used by developers and businesses, are increasingly misused by threat actors to launch stealthy, scalable attacks. While not a novel tactic, VPS abuse is has seen an increase in Software-as-a-Service (SaaS)-targeted campaigns as it enables attackers to bypass geolocation-based defenses by mimicking local traffic, evade IP reputation checks with clean, newly provisioned infrastructure, and blend into legitimate behavior [3].

VPS providers like Hyonix and Host Universal offer rapid setup and minimal open-source intelligence (OSINT) footprint, making detection difficult [1][2]. These services are not only fast to deploy but also affordable, making them attractive to attackers seeking anonymous, low-cost infrastructure for scalable campaigns. Such attacks tend to be targeted and persistent, often timed to coincide with legitimate user activity, a tactic that renders traditional security tools largely ineffective.

Darktrace’s investigation into Hyonix VPS abuse

In May 2025, Darktrace’s Threat Research team investigated a series of incidents across its customer base involving VPS-associated infrastructure. The investigation began with a fleet-wide review of alerts linked to Hyonix (ASN AS931), revealing a noticeable spike in anomalous behavior from this ASN in March 2025. The alerts included brute-force attempts, anomalous logins, and phishing campaign-related inbox rule creation.

Darktrace identified suspicious activity across multiple customer environments around this time, but two networks stood out. In one instance, two internal devices exhibited mirrored patterns of compromise, including logins from rare endpoints, manipulation of inbox rules, and the deletion of emails likely used in phishing attacks. Darktrace traced the activity back to IP addresses associated with Hyonix, suggesting a deliberate use of VPS infrastructure to facilitate the attack.

On the second customer network, the attack was marked by coordinated logins from rare IPs linked to multiple VPS providers, including Hyonix. This was followed by the creation of inbox rules with obfuscated names and attempts to modify account recovery settings, indicating a broader campaign that leveraged shared infrastructure and techniques.

Darktrace’s Autonomous Response capability was not enabled in either customer environment during these attacks. As a result, no automated containment actions were triggered, allowing the attack to escalate without interruption. Had Autonomous Response been active, Darktrace would have automatically blocked connections from the unusual VPS endpoints upon detection, effectively halting the compromise in its early stages.

Case 1

Timeline of activity for Case 1 - Unusual VPS logins and deletion of phishing emails.
Figure 1: Timeline of activity for Case 1 - Unusual VPS logins and deletion of phishing emails.

Initial Intrusion

On May 19, 2025, Darktrace observed two internal devices on one customer environment initiating logins from rare external IPs associated with VPS providers, namely Hyonix and Host Universal (via Proton VPN). Darktrace recognized that these logins had occurred within minutes of legitimate user activity from distant geolocations, indicating improbable travel and reinforcing the likelihood of session hijacking. This triggered Darktrace / IDENTITY model “Login From Rare Endpoint While User Is Active”, which highlights potential credential misuse when simultaneous logins occur from both familiar and rare sources.  

Shortly after these logins, Darktrace observed the threat actor deleting emails referring to invoice documents from the user’s “Sent Items” folder, suggesting an attempt to hide phishing emails that had been sent from the now-compromised account. Though not directly observed, initial access in this case was likely achieved through a similar phishing or account hijacking method.

 Darktrace / IDENTITY model "Login From Rare Endpoint While User Is Active", which detects simultaneous logins from both a common and a rare source to highlight potential credential misuse.
Figure 2: Darktrace / IDENTITY model "Login From Rare Endpoint While User Is Active", which detects simultaneous logins from both a common and a rare source to highlight potential credential misuse.

Case 2

Timeline of activity for Case 2 – Coordinated inbox rule creation and outbound phishing campaign.
Figure 3: Timeline of activity for Case 2 – Coordinated inbox rule creation and outbound phishing campaign.

In the second customer environment, Darktrace observed similar login activity originating from Hyonix, as well as other VPS providers like Mevspace and Hivelocity. Multiple users logged in from rare endpoints, with Multi-Factor Authentication (MFA) satisfied via token claims, further indicating session hijacking.

Establishing control and maintaining persistence

Following the initial access, Darktrace observed a series of suspicious SaaS activities, including the creation of new email rules. These rules were given minimal or obfuscated names, a tactic often used by attackers to avoid drawing attention during casual mailbox reviews by the SaaS account owner or automated audits. By keeping rule names vague or generic, attackers reduce the likelihood of detection while quietly redirecting or deleting incoming emails to maintain access and conceal their activity.

One of the newly created inbox rules targeted emails with subject lines referencing a document shared by a VIP at the customer’s organization. These emails would be automatically deleted, suggesting an attempt to conceal malicious mailbox activity from legitimate users.

Mirrored activity across environments

While no direct lateral movement was observed, mirrored activity across multiple user devices suggested a coordinated campaign. Notably, three users had near identical similar inbox rules created, while another user had a different rule related to fake invoices, reinforcing the likelihood of a shared infrastructure and technique set.

Privilege escalation and broader impact

On one account, Darktrace observed “User registered security info” activity was shortly after anomalous logins, indicating attempts to modify account recovery settings. On another, the user reset passwords or updated security information from rare external IPs. In both cases, the attacker’s actions—including creating inbox rules, deleting emails, and maintaining login persistence—suggested an intent to remain undetected while potentially setting the stage for data exfiltration or spam distribution.

On a separate account, outbound spam was observed, featuring generic finance-related subject lines such as 'INV#. EMITTANCE-1'. At the network level, Darktrace / NETWORK detected DNS requests from a device to a suspicious domain, which began prior the observed email compromise. The domain showed signs of domain fluxing, a tactic involving frequent changes in IP resolution, commonly used by threat actors to maintain resilient infrastructure and evade static blocklists. Around the same time, Darktrace detected another device writing a file named 'SplashtopStreamer.exe', associated with the remote access tool Splashtop, to a domain controller. While typically used in IT support scenarios, its presence here may suggest that the attacker leveraged it to establish persistent remote access or facilitate lateral movement within the customer’s network.

Conclusion

This investigation highlights the growing abuse of VPS infrastructure in SaaS compromise campaigns. Threat actors are increasingly leveraging these affordable and anonymous hosting services to hijack accounts, launch phishing attacks, and manipulate mailbox configurations, often bypassing traditional security controls.

Despite the stealthy nature of this campaign, Darktrace detected the malicious activity early in the kill chain through its Self-Learning AI. By continuously learning what is normal for each user and device, Darktrace surfaced subtle anomalies, such as rare login sources, inbox rule manipulation, and concurrent session activity, that likely evade traditional static, rule-based systems.

As attackers continue to exploit trusted infrastructure and mimic legitimate user behavior, organizations should adopt behavioral-based detection and response strategies. Proactively monitoring for indicators such as improbable travel, unusual login sources, and mailbox rule changes, and responding swiftly with autonomous actions, is critical to staying ahead of evolving threats.

Credit to Rajendra Rushanth (Cyber Analyst), Jen Beckett (Cyber Analyst) and Ryan Traill (Analyst Content Lead)

References

·      1: https://cybersecuritynews.com/threat-actors-leveraging-vps-hosting-providers/

·      2: https://threatfox.abuse.ch/asn/931/

·      3: https://www.cyfirma.com/research/vps-exploitation-by-threat-actors/

Appendices

Darktrace Model Detections

•   SaaS / Compromise / Unusual Login, Sent Mail, Deleted Sent

•   SaaS / Compromise / Suspicious Login and Mass Email Deletes

•   SaaS / Resource / Mass Email Deletes from Rare Location

•   SaaS / Compromise / Unusual Login and New Email Rule

•   SaaS / Compliance / Anomalous New Email Rule

•   SaaS / Resource / Possible Email Spam Activity

•   SaaS / Unusual Activity / Multiple Unusual SaaS Activities

•   SaaS / Unusual Activity / Multiple Unusual External Sources For SaaS Credential

•   SaaS / Access / Unusual External Source for SaaS Credential Use

•   SaaS / Compromise / High Priority Login From Rare Endpoint

•   SaaS / Compromise / Login From Rare Endpoint While User Is Active

List of Indicators of Compromise (IoCs)

Format: IoC – Type – Description

•   38.240.42[.]160 – IP – Associated with Hyonix ASN (AS931)

•   103.75.11[.]134 – IP – Associated with Host Universal / Proton VPN

•   162.241.121[.]156 – IP – Rare IP associated with phishing

•   194.49.68[.]244 – IP – Associated with Hyonix ASN

•   193.32.248[.]242 – IP – Used in suspicious login activity / Mullvad VPN

•   50.229.155[.]2 – IP – Rare login IP / AS 7922 ( COMCAST-7922 )

•   104.168.194[.]248 – IP – Rare login IP / AS 54290 ( HOSTWINDS )

•   38.255.57[.]212 – IP – Hyonix IP used during MFA activity

•   103.131.131[.]44 – IP – Hyonix IP used in login and MFA activity

•   178.173.244[.]27 – IP – Hyonix IP

•   91.223.3[.]147 – IP – Mevspace Poland, used in multiple logins

•   2a02:748:4000:18:0:1:170b[:]2524 – IPv6 – Hivelocity VPS, used in multiple logins and MFA activity

•   51.36.233[.]224 – IP – Saudi ASN, used in suspicious login

•   103.211.53[.]84 – IP – Excitel Broadband India, used in security info update

MITRE ATT&CK Mapping

Tactic – Technique – Sub-Technique

•   Initial Access – T1566 – Phishing

                       T1566.001 – Spearphishing Attachment

•   Execution – T1078 – Valid Accounts

•   Persistence – T1098 – Account Manipulation

                       T1098.002 – Exchange Email Rules

•   Command and Control – T1071 – Application Layer Protocol

                       T1071.001 – Web Protocols

•   Defense Evasion – T1036 – Masquerading

•   Defense Evasion – T1562 – Impair Defenses

                       T1562.001 – Disable or Modify Tools

•   Credential Access – T1556 – Modify Authentication Process

                       T1556.004 – MFA Bypass

•   Discovery – T1087 – Account Discovery

•      Impact – T1531 – Account Access Removal

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 without notice.

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Rajendra Rushanth
Cyber Analyst

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August 15, 2025

From Exploit to Escalation: Tracking and Containing a Real-World Fortinet SSL-VPN Attack

Fortinet SSL-VPN AttackDefault blog imageDefault blog image

Threat actors exploiting Fortinet CVEs

Over the years, Fortinet has issued multiple alerts about a wave of sophisticated attacks targeting vulnerabilities in its SSL-VPN infrastructure. Despite the release of patches to address these vulnerabilities, threat actors have continued to exploit a trio of Common Vulnerabilities and Exposures (CVEs) disclosed between 2022 and 2024 to gain unauthorized access to FortiGate devices.

Which vulnerabilities are exploited?

The vulnerabilities—CVE-2022-42475, CVE-2023-27997, and CVE-2024-21762—affect Fortinet’s SSL-VPN services and have been actively exploited by threat actors to establish initial access into target networks.

The vulnerabilities affect core components of FortiOS, allowing attackers to execute remote code on affected systems.

CVE-2022-42475

Type: Heap-Based Buffer Overflow in FortiOS SSL-VPN

Impact: Remote Code Execution (Actively Exploited)

This earlier vulnerability also targets the SSL-VPN interface and has been actively exploited in the wild. It allows attackers to execute arbitrary code remotely by overflowing a buffer in memory, often used to deploy malware or establish persistent backdoors [6].

CVE-2023-27997

Type: Heap-Based Buffer Overflow in FortiOS and FortiProxy

Impact: Remote Code Execution

This flaw exists in the SSL-VPN component of both FortiOS and FortiProxy. By exploiting a buffer overflow in the heap memory, attackers can execute malicious code remotely. This vulnerability is particularly dangerous because it can be triggered without authentication, making it ideal for an initial compromise [5].

CVE-2024-21762

Type: Out-of-Bounds Write in sslvpnd

Impact: Remote Code Execution

This vulnerability affects the SSL-VPN daemon (sslvpnd) in FortiOS. It allows unauthenticated remote attackers to send specially crafted HTTP requests that write data outside of allocated memory bounds. This can lead to arbitrary code execution, giving attackers full control over a device [4].

In short, these flaws enable remote attackers to execute arbitrary code without authentication by exploiting memory corruption issues such as buffer overflows and out-of-bounds writes. Once inside, threat actors use symbolic link (symlink) in order to maintain persistence on target devices across patches and firmware updates. This persistence then enables them to bypass security controls and manipulate firewall configurations, effectively turning patched systems into long-term footholds for deeper network compromise [1][2][3].

Darktrace’s Coverage

Darktrace detected a series of suspicious activities originating from a compromised Fortinet VPN device, including anomalous HTTP traffic, internal network scanning, and SMB reconnaissance, all indicative of post-exploitation behavior. Following initial detection by Darktrace’s real-time models, its Autonomous Response capability swiftly acted on the malicious activity, blocking suspicious connections and containing the threat before further compromise could occur.

Further investigation by Darktrace’s Threat Research team uncovered a stealthy and persistent attack that leveraged known Fortinet SSL-VPN vulnerabilities to facilitate lateral movement and privilege escalation within the network.

Phase 1: Initial Compromise – Fortinet VPN Exploitation

The attack on a Darktrace customer likely began on April 11 with the exploitation of a Fortinet VPN device running an outdated version of FortiOS. Darktrace observed a high volume of HTTP traffic originating from this device, specifically targeting internal systems. Notably, many of these requests were directed at the /cgi-bin/ directory,  a common target for attackers attempting to exploit web interfaces to run unauthorized scripts or commands. This pattern strongly indicated remote code execution attempts via the SSL-VPN interface [7].

Once access was gained, the threat actor likely modified existing firewall rules, a tactic often used to disable security controls or create hidden backdoors for future access. While Darktrace does not have direct visibility into firewall configuration changes, the surrounding activity and post-exploitation behavior indicated that such modifications were made to support long-term persistence within the network.

HTTP activity from the compromised Fortinet device, including repeated requests to /cgi-bin/ over port 8080.
Figure 1: HTTP activity from the compromised Fortinet device, including repeated requests to /cgi-bin/ over port 8080

Phase 2: Establishing Persistence & Lateral Movement

Shortly after the initial compromise of the Fortinet VPN device, the threat actor began to expand their foothold within the internal network. Darktrace detected initial signs of network scanning from this device, including the use of Nmap to probe the internal environment, likely in an attempt to identify accessible services and vulnerable systems.

Darktrace’s detection of unusual network scanning activities on the affected device.
Figure 2: Darktrace’s detection of unusual network scanning activities on the affected device.

Around the same time, Darktrace began detecting anomalous activity on a second device, specifically an internal firewall interface device. This suggested that the attacker had established a secondary foothold and was leveraging it to conduct deeper reconnaissance and move laterally through the network.

In an effort to maintain persistence within the network, the attackers likely deployed symbolic links in the SSL-VPN language file directory on the Fortinet device. While Darktrace did not directly observe symbolic link abuse, Fortinet has identified this as a known persistence technique in similar attacks [2][3]. Based on the observed post-exploitation behavior and likely firewall modifications, it is plausible that such methods were used here.

Phase 3: Internal Reconnaissance & Credential Abuse

With lateral movement initiated from the internal firewall interface device, the threat actor proceeded to escalate their efforts to map the internal network and identify opportunities for privilege escalation.

Darktrace observed a successful NTLM authentication from the internal firewall interface to the domain controller over the outdated protocol SMBv1, using the account ‘anonymous’. This was immediately followed by a failed NTLM session connection using the hostname ‘nmap’, further indicating the use of Nmap for enumeration and brute-force attempts. Additional credential probes were also identified around the same time, including attempts using the credential ‘guest’.

Darktrace detection of a series of login attempts using various credentials, with a mix of successful and unsuccessful attempts.
Figure 3: Darktrace detection of a series of login attempts using various credentials, with a mix of successful and unsuccessful attempts.

The attacker then initiated DCE_RPC service enumeration, with over 300 requests to the Endpoint Mapper endpoint on the domain controller. This technique is commonly used to discover available services and their bindings, often as a precursor to privilege escalation or remote service manipulation.

Over the next few minutes, Darktrace detected more than 1,700 outbound connections from the internal firewall interface device to one of the customer’s subnets. These targeted common services such as FTP (port 21), SSH (22), Telnet (23), HTTP (80), and HTTPS (443). The threat actor also probed administrative and directory services, including ports 135, 137, 389, and 445, as well as remote access via RDP on port 3389.

Further signs of privilege escalation attempts were observed with the detection of over 300 Netlogon requests to the domain controller. Just over half of these connections were successful, indicating possible brute-force authentication attempts, credential testing, or the use of default or harvested credentials.

Netlogon and DCE-RPC activity from the affected device, showing repeated service bindings to epmapper and Netlogon, followed by successful and failed NetrServerAuthenticate3 attempts.
Figure 4: Netlogon and DCE-RPC activity from the affected device, showing repeated service bindings to epmapper and Netlogon, followed by successful and failed NetrServerAuthenticate3 attempts.

Phase 4: Privilege Escalation & Remote Access

A few minutes later, the attacker initiated an RDP session from the internal firewall interface device to an internal server. The session lasted over three hours, during which more than 1.5MB of data was uploaded and over 5MB was downloaded.

Notably, no RDP cookie was observed during this session, suggesting manual access, tool-less exploitation, or a deliberate attempt to evade detection. While RDP cookie entries were present on other occasions, none were linked to this specific session—reinforcing the likelihood of stealthy remote access.

Additionally, multiple entries during and after this session show SSL certificate validation failures on port 3389, indicating that the RDP connection may have been established using self-signed or invalid certificates, a common tactic in unauthorized or suspicious remote access scenarios.

Darktrace’s detection of an RDP session from the firewall interface device to the server, lasting over 3 hours.
Figure 5: Darktrace’s detection of an RDP session from the firewall interface device to the server, lasting over 3 hours.

Darktrace Autonomous Response

Throughout the course of this attack, Darktrace’s Autonomous Response capability was active on the customer’s network. This enabled Darktrace to autonomously intervene by blocking specific connections and ports associated with the suspicious activity, while also enforcing a pre-established “pattern of life” on affected devices to ensure they were able to continue their expected business activities while preventing any deviations from it. These actions were crucial in containing the threat and prevent further lateral movement from the compromised device.

Darktrace’s Autonomous Response targeted specific connections and restricted affected devices to their expected patterns of life.
Figure 6: Darktrace’s Autonomous Response targeted specific connections and restricted affected devices to their expected patterns of life.

Conclusion

This incident highlights the importance of important staying on top of patching and closely monitoring VPN infrastructure, especially for internet-facing systems like Fortinet devices. Despite available patches, attackers were still able to exploit known vulnerabilities to gain access, move laterally and maintain persistence within the customer’s network.

Attackers here demonstrated a high level of stealth and persistence. Not only did they gain access to the network and carry out network scans and lateral movement, but they also used techniques such as symbolic link abuse, credential probing, and RDP sessions without cookies to avoid detection.  Darktrace’s detection of the post-exploitation activity, combined with the swift action of its Autonomous Response technology, successfully blocked malicious connections and contained the attack before it could escalate

Credit to Priya Thapa (Cyber Analyst), Vivek Rajan (Cyber Analyst), and Ryan Traill (Analyst Content Lead)

Appendices

Real-time Detection Model Alerts

·      Device / Suspicious SMB Scanning Activity

·      Device / Anomalous Nmap Activity

·      Device / Network Scan

·      Device / RDP Scan

·      Device / ICMP Address Scan

Autonomous Response Model Alerts:  

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

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

MITRE ATT&CK Mapping

Initial Access – External Remote Services – T1133

Initial Access – Valid Accounts – T1078

Execution – Exploitation for Client Execution – T1203

Persistence – Account Manipulation – T1098

Persistence – Application Layer Protocol – T1071.001

Privilege Escalation – Exploitation for Privilege Escalation – T1068

Privilege Escalation – Valid Accounts – T1078

Defense Evasion – Masquerading – T1036

Credential Access – Brute Force – T1110

Discovery – Network Service Scanning – T1046

Discovery – Remote System Discovery – T1018

Lateral Movement – Remote Services – T1021

Lateral Movement – Software Deployment Tools – T1072

Collection – Data from Local System – T1005

Collection – Data Staging – T1074

Exfiltration – Exfiltration Over Alternative Protocol – T1048

References

[1]  https://www.tenable.com/blog/cve-2024-21762-critical-fortinet-fortios-out-of-bound-write-ssl-vpn-vulnerability

[2] https://thehackernews.com/2025/04/fortinet-warns-attackers-retain.html

[3] https://www.cisa.gov/news-events/alerts/2025/04/11/fortinet-releases-advisory-new-post-exploitation-technique-known-vulnerabilities

[4] https://www.fortiguard.com/psirt/FG-IR-24-015

[5] https://www.tenable.com/blog/cve-2023-27997-heap-based-buffer-overflow-in-fortinet-fortios-and-fortiproxy-ssl-vpn-xortigate

[6]  https://www.tenable.com/blog/cve-2022-42475-fortinet-patches-zero-day-in-fortios-ssl-vpns

[7] https://www.fortiguard.com/encyclopedia/ips/12475

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About the author
Priya Thapa
Cyber Analyst
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