Blog
/
/
September 13, 2022

Compliance Threat: RedLine Information Stealer

Darktrace reveals the compliance risks posed by the RedLine information stealer. Read about their analysis and how to defend against this cyber 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
Steven Sosa
Analyst Team Lead
Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
13
Sep 2022

With the continued rise of malware as a service (MaaS), it is now easier than ever to find and deploy information stealers [1]. Given this, it is crucial that companies begin to prioritize good cyber hygiene, and address compliance issues within their environments. Thanks to MaaS, attackers with little to no experience can amplify what might seem like a low-risk attack, into a significant compromise. This blog will investigate a compromise that could have been mitigated with better cyber hygiene and enhanced awareness around compliance issues.

Figure 1: Timeline of the attack

In May 2022 Darktrace DETECT/Network identified a device linked with multiple compliance alerts for ‘torrent’ activity within a Latin American telecommunications company. This culminated in the device downloading a suspicious executable file from an archived webpage. At first, analysis of the downloaded file indicated that it could be a legitimate, albeit outdated software relevant to the client’s industry vertical (SNMPc management tool for GeoDesy GD-300). However, as this was the first event before further suspicious activities, it was also possible that the software downloaded was packaged with malware and marked an initial compromise. Since early April, the device had regularly breached compliance alerts for both BitTorrent and uTorrent (a BitTorrent client). These connections occurred over a common torrenting port, 6881, and may have represented the infection vector.  

Figure 2: View of archived webpage which the suspicious executable was downloaded from

Shortly after the executable was downloaded, Darktrace DETECT alerted a new outbound SSH connection with the following notice in Advanced Search: ‘SSH::Heuristic_Login_Success’. This was highlighted because the breach device did not commonly make connections over this protocol and the destination was a never-before-seen Bulgarian IP address (79.142.70[.]239). The connection lasted 4 minutes, and the device downloaded 31.36 MB of data. 

Following this, the breach device was seen making unusual HTTP connections to rare Russian and Danish endpoints using suspicious user agents. The Russian endpoint was noted for hosting a text file (‘incricinfo[.]com') that listed a single domain which was recently registered. The connections to the Danish endpoint were made to an IP with a URI that OSINT connected to the use of the BeamWinHTTP loader [2]. This loader can be used to download and execute other malware strains, in particular information stealers [3]. 

Figure 3: Screenshot of Russian endpoint with link to incricinfo[.]com 
Figure 4: Cyber AI Analyst highlighting the unusual HTTP connectivity that occurred prior to the multiple suspicious file downloads

At the same time as the connections with the unusual user agents, the device was also seen downloading an executable file from the endpoint, ‘Yuuichirou-hanma[.]s3[.]pl-waw[.]scw[.]cloud’. Analysis of the file indicated that it may be used to deploy further malware and potentially unwanted programs (PUPs). BeamWinHTTP also causes installation of these PUPs which helps to load more nefarious programs and spread compromise. 

This behavior was then seen as the device downloaded 5 different executable files from the endpoint, ‘hakhaulogistics[.]com’. This domain is linked to a Vietnamese logistics company that Darktrace had marked as new within the environment; it is possible that this domain was compromised and being used to host malicious infrastructure. At the point of compromise, several of the downloads were labeled as malicious by popular OSINT [4]. Additionally, at least one of the files was explicitly linked to the RedLine Information Stealer.  

Shortly after, the device made connections to a known Tor relay node. Tor is commonly used as an avenue for C2 communication as it offers a way for attackers to anonymize and obfuscate their activity. It was at this point that the first Proactive Threat Notification (PTN) for this activity occurred. This ensured immediate follow-up investigation from Darktrace SOC and a timeline of events and impacted devices were issued to the customer’s security team directly. 

Figure 5: Cyber AI Analyst highlighting the unusual executable downloads as well as the subsequent Tor connections. The file poweroff[.]exe has been highlighted by several OSINT sources as being potentially malicious

By this point, Darktrace had identified a large volume of unusual outbound HTTP POSTs to a variety of endpoints that seemed to have no obvious function or service. Following these POST requests, the compromised device was seen initiating a long SSL connection to the domain, ‘www[.]qfhwji6fnpiad3gs[.]com’, which is likely to have be generated by an algorithm (DGA). Lastly, a little while after the SSL connections, the device was seen downloading another executable file from the Russian domain ‘test-hf[.]su’. Research on the file again suggested that it was associated with RedLine Stealer [5].  

Figure 6: AIA highlighting additional unusual HTTP connections that were linked with the numeric exe download

Dangers of Non-Compliance 

Whilst the RedLine compromise was a matter of customer concern, the gap in their security was not visibility but rather best practice. It is important to note that prior to these events, the device was commonly seen sending and receiving connections associated with torrenting. In the past it has been observed that RedLine Stealer masquerades as ‘cracked’ software (software that has had its copy protection removed) [6]. In this instance, the initial download of the false ‘SNMPc’ executable may have been proof of this behavior. 

This is a reminder that torrenting is also extremely popular as a peer-to-peer vector for transferring malicious files. Combined with the possibility of network throttling or unapproved VPN use, torrents are usually considered non-compliant within corporate settings. Whether the events here were kickstarted due to a user unwittingly downloading malicious software, or exposure to a malicious actor via BitTorrent use, both cases represent a user circumventing existing compliance controls or a lack of compliance control in general. It is important for organizations to make sure that their users are acting in ways that limit the company’s exposure to nefarious actors. Companies should routinely encourage proper cyber hygiene and implement access controls that block certain activities such as torrenting if threats like these are to be stopped in the future.  

Regardless of what users are doing, Darktrace is positioned to detect and take action on compliance breaches and activity resulting from lack of compliance. The variety of C2 domains used in this blog incident were too quick for most security tools to alert on or for human teams to triage. However, this was no problem for Cyber AI analyst, which was able to draw together aspects of the attack across the kill chain and save a significant amount of time for both the customer security team and Darktrace SOC analysts. If active, Darktrace RESPOND could have blocked activities like the initial BitTorrent connections and incoming download, but with the right preventative measures, it wouldn’t have to. Darktrace PREVENT works continuously to harden defenses and preempt attackers, closing any vulnerabilities before they can be exploited. This includes performing attack surface management, attack path modelling, and security awareness training. In this case, Darktrace PREVENT could have highlighted torrenting activity as part of a potentially harmful attack path and recommended the best actions to mitigate it.

‘No Prior Experience required’ 

In the past, only highly skilled attackers could create and use the tools needed to attack organizations. With Ransomware-as-a-Service (RaaS) proving highly profitable, however, it is no surprise that malware is also becoming a lucrative business. As SaaS can help legitimate companies with no development experience to use and maintain apps, MaaS can help attackers with little to no hacking experience compromise organizations and achieve their goals. RedLine Stealer is readily available, and not prohibitively expensive, meaning attacks can be carried out more frequently, and on a wider range of victims. The incident explored in this blog is proof of this, and a strong indication that security comes not only from strong visibility but also compliance and best practice too. With a powerful defensive tool like PREVENT, security teams can save time while feeling confident that they are keeping ahead of these aspects of security.

Thanks to Adam Stevens for his contributions to this blog.

Appendices

Darktrace Model Breaches

·      Anomalous Connection / Multiple HTTP POSTs to Rare Hostname 

·      Anomalous Connection / New User Agent to IP Without Hostname

·      Anomalous File / EXE from Rare External Location

·      Anomalous File / Multiple EXE from Rare External 

·      Anomalous File / Numeric Exe Download

·      Anomalous Server Activity / New User Agent from Internet Facing System

·      Compliance / SSH to Rare External Destination

·      Compromise / Anomalous File then Tor 

·      Compromise / Possible Tor Usage 

·      Device / Initial Breach Chain Compromise

·      Device / Long Agent Connection to New Endpoint

References

[1] https://blog.sonicwall.com/en-us/2021/12/the-rise-and-growth-of-malware-as-a-service/

[2] https://asec.ahnlab.com/en/33679/  

[3] https://asec.ahnlab.com/en/20930/

[4] https://www.virustotal.com/gui/file/acfc06b4bcda03ecf4f9dc9b27c510b58ae3a6a9baf1ee821fc624467944467b & https://www.virustotal.com/gui/file/dad6311f96df65f40d9599c84907bae98306f902b1489b03768294b7678a5e79 

[5] https://www.virustotal.com/gui/file/ff7574f9f1d15594e409bee206f5db6c76db7c90dda2ae4f241b77cd0c7b6bf6

[6] https://asec.ahnlab.com/en/30445/

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
Steven Sosa
Analyst Team Lead

More in this series

No items found.

Blog

/

OT

/

September 4, 2025

Rethinking Signature-Based Detection for Power Utility Cybersecurity

Default blog imageDefault blog image

Lessons learned from OT cyber attacks

Over the past decade, some of the most disruptive attacks on power utilities have shown the limits of signature-based detection and reshaped how defenders think about OT security. Each incident reinforced that signatures are too narrow and reactive to serve as the foundation of defense.

2015: BlackEnergy 3 in Ukraine

According to CISA, on December 23, 2015, Ukrainian power companies experienced unscheduled power outages affecting a large number of customers — public reports indicate that the BlackEnergy malware was discovered on the companies’ computer networks.

2016: Industroyer/CrashOverride

CISA describes CrashOverride malwareas an “extensible platform” reported to have been used against critical infrastructure in Ukraine in 2016. It was capable of targeting industrial control systems using protocols such as IEC‑101, IEC‑104, and IEC‑61850, and fundamentally abused legitimate control system functionality to deliver destructive effects. CISA emphasizes that “traditional methods of detection may not be sufficient to detect infections prior to the malware execution” and recommends behavioral analysis techniques to identify precursor activity to CrashOverride.

2017: TRITON Malware

The U.S. Department of the Treasury reports that the Triton malware, also known as TRISIS or HatMan, was “designed specifically to target and manipulate industrial safety systems” in a petrochemical facility in the Middle East. The malware was engineered to control Safety Instrumented System (SIS) controllers responsible for emergency shutdown procedures. During the attack, several SIS controllers entered a failed‑safe state, which prevented the malware from fully executing.

The broader lessons

These events revealed three enduring truths:

  • Signatures have diminishing returns: BlackEnergy showed that while signatures can eventually identify adapted IT malware, they arrive too late to prevent OT disruption.
  • Behavioral monitoring is essential: CrashOverride demonstrated that adversaries abuse legitimate industrial protocols, making behavioral and anomaly detection more effective than traditional signature methods.
  • Critical safety systems are now targets: TRITON revealed that attackers are willing to compromise safety instrumented systems, elevating risks from operational disruption to potential physical harm.

The natural progression for utilities is clear. Static, file-based defenses are too fragile for the realities of OT.  

These incidents showed that behavioral analytics and anomaly detection are far more effective at identifying suspicious activity across industrial systems, regardless of whether the malicious code has ever been seen before.

Strategic risks of overreliance on signatures

  • False sense of security: Believing signatures will block advanced threats can delay investment in more effective detection methods.
  • Resource drain: Constantly updating, tuning, and maintaining signature libraries consumes valuable staff resources without proportional benefit.
  • Adversary advantage: Nation-state and advanced actors understand the reactive nature of signature defenses and design attacks to circumvent them from the start.

Recommended Alternatives (with real-world OT examples)

 Alternative strategies for detecting cyber attacks in OT
Figure 1: Alternative strategies for detecting cyber attacks in OT

Behavioral and anomaly detection

Rather than relying on signatures, focusing on behavior enables detection of threats that have never been seen before—even trusted-looking devices.

Real-world insight:

In one OT setting, a vendor inadvertently left a Raspberry Pi on a customer’s ICS network. After deployment, Darktrace’s system flagged elastic anomalies in its HTTPS and DNS communication despite the absence of any known indicators of compromise. The alerting included sustained SSL increases, agent‑beacon activity, and DNS connections to unusual endpoints, revealing a possible supply‑chain or insider risk invisible to static tools.  

Darktrace’s AI-driven threat detection aligns with the zero-trust principle of assuming the risk of a breach. By leveraging AI that learns an organization’s specific patterns of life, Darktrace provides a tailored security approach ideal for organizations with complex supply chains.

Threat intelligence sharing & building toward zero-trust philosophy

Frameworks such as MITRE ATT&CK for ICS provide a common language to map activity against known adversary tactics, helping teams prioritize detections and response strategies. Similarly, information-sharing communities like E-ISAC and regional ISACs give utilities visibility into the latest tactics, techniques, and procedures (TTPs) observed across the sector. This level of intel can help shift the focus away from chasing individual signatures and toward building resilience against how adversaries actually operate.

Real-world insight:

Darktrace’s AI embodies zero‑trust by assuming breach potential and continually evaluating all device behavior, even those deemed trusted. This approach allowed the detection of an anomalous SharePoint phishing attempt coming from a trusted supplier, intercepted by spotting subtle patterns rather than predefined rules. If a cloud account is compromised, unauthorized access to sensitive information could lead to extortion and lateral movement into mission-critical systems for more damaging attacks on critical-national infrastructure.

This reinforces the need to monitor behavioral deviations across the supply chain, not just known bad artifacts.

Defense-in-Depth with OT context & unified visibility

OT environments demand visibility that spans IT, OT, and IoT layers, supported by risk-based prioritization.

Real-world insight:

Darktrace / OT offers unified AI‑led investigations that break down silos between IT and OT. Smaller teams can see unusual outbound traffic or beaconing from unknown OT devices, swiftly investigate across domains, and get clear visibility into device behavior, even when they lack specialized OT security expertise.  

Moreover, by integrating contextual risk scoring, considering real-world exploitability, device criticality, firewall misconfiguration, and legacy hardware exposure, utilities can focus on the vulnerabilities that genuinely threaten uptime and safety, rather than being overwhelmed by CVE noise.  

Regulatory alignment and positive direction

Industry regulations are beginning to reflect this evolution in strategy. NERC CIP-015 requires internal network monitoring that detects anomalies, and the standard references anomalies 15 times. In contrast, signature-based detection is not mentioned once.

This regulatory direction shows that compliance bodies understand the limitations of static defenses and are encouraging utilities to invest in anomaly-based monitoring and analytics. Utilities that adopt these approaches will not only be strengthening their resilience but also positioning themselves for regulatory compliance and operational success.

Conclusion

Signature-based detection retains utility for common IT malware, but it cannot serve as the backbone of security for power utilities. History has shown that major OT attacks are rarely stopped by signatures, since each campaign targets specific systems with customized tools. The most dangerous adversaries, from insiders to nation-states, actively design their operations to avoid detection by signature-based tools.

A more effective strategy prioritizes behavioral analytics, anomaly detection, and community-driven intelligence sharing. These approaches not only catch known threats, but also uncover the subtle anomalies and novel attack techniques that characterize tomorrow’s incidents.

Continue reading
About the author
Daniel Simonds
Director of Operational Technology

Blog

/

Identity

/

August 21, 2025

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

Default 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.

Continue reading
About the author
Rajendra Rushanth
Cyber Analyst
Your data. Our AI.
Elevate your network security with Darktrace AI