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
The Darktrace Threat Research Team
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Aug 2024
Introduction: Darktrace's Threat Research
Defenders must understand the threat landscape in order to protect against it. We can do that with threat intelligence.
At Darktrace, we approach threat intelligence with a unique perspective. Unlike traditional security vendors that rely on established patterns from past incidents, our strategy is rooted in the belief that identifying behavioral anomalies is crucial for identifying both known and novel threats.
For our analysts and researchers, the incidents detected by our AI mark the beginning of a deeper investigation, aiming to connect mitigated threats to wider trends from across the threat landscape. Through hindsight analysis, we have highlighted numerous threats, including zero day, N day, and other novel attacks, showcasing their evolving nature and Darktrace’s ability to identify them.
For the first half of 2024, we’ve observed major trends around subscription-based attack models, advanced TTPs, and sophisticated email attacks. Read on to discover some of our key insights into the current cybersecurity threat landscape.
Malware-as-a-Service continues to pose significant risk for organizations
Many of the prevalent threats observed by Darktrace heavily utilized Malware-as-a-Service (MaaS) tools. This is likely because of the lucrative subscription-based income of MaaS ecosystems as well as the low barrier to entry and high demand. By offering pre-packed, plug-and-play malware, the MaaS market has enabled even inexperienced attackers to carry out potentially disruptive attacks, regardless of their level of skill or technical ability.
When comparing the latest observed threats with the previous half year’s data, there are several returning threats, notably Mirai, AsyncRAT, Emotet, and NjRAT.
This highlights that while MaaS strains often adapt their TTPs from one campaign to the next, many strains remain unchanged yet continue to achieve success. This suggests that some security teams and organizations are still falling short in defending their environments.
Figure 1: The diagram above represents Darktrace detections containing IoCs associated with particular threats. The size of the bubble displayed relates to the frequency of detections observed across the Darktrace fleet.
The persistence of known malware strains and information stealers particularly affects smaller organizations that are likely under-resourced and outsource portions of their security responsibilities. Additionally, larger organizations with poor cyber hygiene or extensive guest subnets may also be at risk.
The Darktrace experts anticipate that MaaS will remain a prevalent part of the threat landscape for the foreseeable future.
Double extortion methods are now prevalent amongst ransomware strains
As ransomware continues to be a top security concern for organizations, Darktrace’s Threat Research team has identified three predominant ransomware strains impacting customers: Akira, Lockbit, and Black Basta.
While these ransomware families are not new, they have remained vigilant threats in recent years, indicating that these variants are continuing to evolve and adopt new, sophisticated tactics to circumvent security measures. As organizations harden their digital defenses by understanding and pre-empting the TTPs of known ransomware strains, threat actors often incorporate new strategies making them more sophisticated, faster, and harder to defend against.
One such strategy noted by Darktrace is the adoption of double extortion methods. Malicious actors will not only encrypt their target’s data, but also exfiltrate sensitive files with threat of publication if the ransom is not paid.
In the case of Akira in particular, Darktrace observed attackers attempting to exfiltrate data within 12 hours of the initial file encryption, all but confirming that double extortion is a standard part of their playbook.
Email phishing shows no signs of slowing down
With a majority of attacks originating from email, it is crucial that organizations secure the inbox and beyond.
Between December 21, 2023, and July 5, 2024, Darktrace / EMAIL detected 17.8 million phishing emails across the fleet, with 62% of these phishing emails successfully bypassing Domain-based Message Authentication, Reporting, and Conformance (DMARC) verification checks.
These are not the only types of email attacks we observed. Darktrace detected 550,000 malicious QR codes that, when scanned, would direct recipients to a malicious endpoint where attackers can infect a device with malware or steal a user’s login credentials.
While most traditional email security measures are not able to scan for QR codes, Darktrace / EMAIL is not only able to detect them but also identify their destination, blocking any emails found to lead to suspicious endpoints.
Conclusion
The threat landscape continues to evolve, but new threats often build upon old foundations rather than replacing them. While we have observed the emergence of new malware families, many attacks are carried out by the usual suspects that we have seen over the last few years, still utilizing familiar techniques and malware variants. This indicates that cyber threats persist due to the abundance of exploitable vulnerabilities.
In the realm of email security, familiar attacks are also changing, with more impersonations of trusted companies and multistage payload attacks. These email campaigns target select organizations, or even individuals, more efficiently than traditional mass phishing attacks.
As attacks appear with greater frequency and sophistication, defenders must have timely detection and containment capabilities to handle all emerging threats. Read the complete 2024 Half-Year Threat Report to discover all the latest threat landscape trends and the Darktrace Threat Research team’s recommendations.
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.
Darktrace's Cyber AI Analyst in Action: 4 Real-World Investigations into Advanced Threat Actors
As AI reshapes the cybersecurity landscape, Darktrace’s Cyber AI Analyst automates early-stage investigations, mimicking human reasoning to detect and respond to threats at machine speed. This blog explores four real-world cases where it identified sophisticated threat actors, including nation-state adversaries.
Introducing the AI Maturity Model for Cybersecurity
The AI Maturity Model for Cybersecurity is the most detailed guide of its kind, grounded in real use cases and expert insight. It empowers CISOs to make strategic decisions, not just about what AI to adopt, but how to do it in a way that strengthens their organization over time and achieves successful outcomes.
Introducing Version 2 of Darktrace’s Embedding Model for Investigation of Security Threats (DEMIST-2)
Learn how Darktrace’s DEMIST-2 embedding model delivers high-accuracy threat classification and detection across any environment, outperforming larger models with efficiency and precision.
From PowerShell to Payload: Darktrace’s Detection of a Novel Cryptomining Malware
What is Cryptojacking?
Cryptojacking remains one of the most persistent cyber threats in the digital age, showing no signs of slowing down. It involves the unauthorized use of a computer or device’s processing power to mine cryptocurrencies, often without the owner’s consent or knowledge, using cryptojacking scripts or cryptocurrency mining (cryptomining) malware [1].
Unlike other widespread attacks such as ransomware, which disrupt operations and block access to data, cryptomining malware steals and drains computing and energy resources for mining to reduce attacker’s personal costs and increase “profits” earned from mining [1]. The impact on targeted organizations can be significant, ranging from data privacy concerns and reduced productivity to higher energy bills.
As cryptocurrency continues to grow in popularity, as seen with the ongoing high valuation of the global cryptocurrency market capitalization (almost USD 4 trillion at time of writing), threat actors will continue to view cryptomining as a profitable venture [2]. As a result, illicit cryptominers are being used to steal processing power via supply chain attacks or browser injections, as seen in a recent cryptojacking campaign using JavaScript [3][4].
Therefore, security teams should maintain awareness of this ongoing threat, as what is often dismissed as a "compliance issue" can escalate into more severe compromises and lead to prolonged exposure of critical resources.
This blog will discuss Darktrace’s successful detection of the malicious activity, the role of Autonomous Response in halting the cryptojacking attack, include novel insights from Darktrace’s threat researchers on the cryptominer payload, showing how the attack chain was initiated through the execution of a PowerShell-based payload.
Darktrace’s Coverage of Cryptojacking via PowerShell
In July 2025, Darktrace detected and contained an attempted cryptojacking incident on the network of a customer in the retail and e-commerce industry.
The threat was detected when a threat actor attempted to use a PowerShell script to download and run NBMiner directly in memory.
The initial compromise was detected on July 22, when Darktrace / NETWORK observed the use of a new PowerShell user agent during a connection to an external endpoint, indicating an attempt at remote code execution.
Specifically, the targeted desktop device established a connection to the rare endpoint, 45.141.87[.]195, over destination port 8000 using HTTP as the application-layer protocol. Within this connection, Darktrace observed the presence of a PowerShell script in the URI, specifically ‘/infect.ps1’.
Darktrace’s analysis of this endpoint (45.141.87[.]195[:]8000/infect.ps1) and the payload it downloaded indicated it was a dropper used to deliver an obfuscated AutoIt loader. This attribution was further supported by open-source intelligence (OSINT) reporting [5]. The loader likely then injected NBMiner into a legitimate process on the customer’s environment – the first documented case of NBMiner being dropped in this way.
Figure 1: Darktrace’s detection of a device making an HTTP connection with new PowerShell user agent, indicating PowerShell abuse for command-and-control (C2) communications.
Script files are often used by malicious actors for malware distribution. In cryptojacking attacks specifically, scripts are used to download and install cryptomining software, which then attempts to connect to cryptomining pools to begin mining operations [6].
Inside the payload: Technical analysis of the malicious script and cryptomining loader
To confidently establish that the malicious script file dropped an AutoIt loader used to deliver the NBMiner cryptominer, Darktrace’s threat researchers reverse engineered the payload. Analysis of the file ‘infect.ps1’ revealed further insights, ultimately linking it to the execution of a cryptominer loader.
Figure 2: Screenshot of the ‘infect.ps1’ PowerShell script observed in the attack.
The ‘infect.ps1’ script is a heavily obfuscated PowerShell script that contains multiple variables of Base64 and XOR encoded data. The first data blob is XOR’d with a value of 97, after decoding, the data is a binary and stored in APPDATA/local/knzbsrgw.exe. The binary is AutoIT.exe, the legitimate executable of the AutoIt programming language. The script also performs a check for the existence of the registry key HKCU:\\Software\LordNet.
The second data blob ($cylcejlrqbgejqryxpck) is written to APPDATA\rauuq, where it will later be read and XOR decoded. The third data blob ($tlswqbblxmmr)decodes to an obfuscated AutoIt script, which is written to %LOCALAPPDATA%\qmsxehehhnnwioojlyegmdssiswak. To ensure persistence, a shortcut file named xxyntxsmitwgruxuwqzypomkhxhml.lnk is created to run at startup.
Figure 3: Screenshot of second stage AutoIt script.
The observed AutoIt script is a process injection loader. It reads an encrypted binary from /rauuq in APPDATA, then XOR-decodes every byte with the key 47 to reconstruct the payload in memory. Next, it silently launches the legitimate Windows app ‘charmap.exe’ (Character Map) and obtains a handle with full access. It allocates executable and writable memory inside that process, writes the decrypted payload into the allocated region, and starts a new thread at that address. Finally, it closes the thread and process handles.
The binary that is injected into charmap.exe is 64-bit Windows binary. On launch, it takes a snapshot of running processes and specifically checks whether Task Manager is open. If Task Manager is detected, the binary kills sigverif.exe; otherwise, it proceeds. Once the condition is met, NBMiner is retrieved from a Chimera URL (https://api[.]chimera-hosting[.]zip/frfnhis/zdpaGgLMav/nbminer[.]exe) and establishes persistence, ensuring that the process automatically restarts if terminated. When mining begins, it spawns a process with the arguments ‘-a kawpow -o asia.ravenminer.com:3838 -u R9KVhfjiqSuSVcpYw5G8VDayPkjSipbiMb.worker -i 60’ and hides the process window to evade detection.
Figure 4: Observed NBMiner arguments.
The program includes several evasion measures. It performs anti-sandboxing by sleeping to delay analysis and terminates sigverif.exe (File Signature Verification). It checks for installed antivirus products and continues only when Windows Defender is the sole protection. It also verifies whether the current user has administrative rights. If not, it attempts a User Account Control (UAC) bypass via Fodhelper to silently elevate and execute its payload without prompting the user. The binary creates a folder under %APPDATA%, drops rtworkq.dll extracted from its own embedded data, and copies ‘mfpmp.exe’ from System32 into that directory to side-load ‘rtworkq.dll’. It also looks for the registry key HKCU\Software\kap, creating it if it does not exist, and reads or sets a registry value it expects there.
Zooming Out: Darktrace Coverage of NBMiner
Darktrace’s analysis of the malicious PowerShell script provides clear evidence that the payload downloaded and executed the NBMiner cryptominer. Once executed, the infected device is expected to attempt connections to cryptomining endpoints (mining pools). Darktrace initially observed this on the targeted device once it started making DNS requests for a cryptominer endpoint, “gulf[.]moneroocean[.]stream” [7], one minute after the connection involving the malicious script.
Figure 5: Darktrace Advanced Search logs showcasing the affected device making a DNS request for a Monero mining endpoint.
Though DNS requests do not necessarily mean the device connected to a cryptominer-associated endpoint, Darktrace detected connections to the endpoint specified in the DNS Answer field: monerooceans[.]stream, 152.53.121[.]6. The attempted connections to this endpoint over port 10001 triggered several high-fidelity model alerts in Darktrace related to possible cryptomining mining activity. The IP address and destination port combination (152.53.121[.]6:10001) has also been linked to cryptomining activity by several OSINT security vendors [8][9].
Figure 6: Darktrace’s detection of a device establishing connections with the Monero Mining-associated endpoint, monerooceans[.]stream over port 10001.
Darktrace / NETWORK grouped together the observed indicators of compromise (IoCs) on the targeted device and triggered an additional Enhanced Monitoring model designed to identify activity indicative of the early stages of an attack. These high-fidelity models are continuously monitored and triaged by Darktrace’s SOC team as part of the Managed Threat Detection service, ensuring that subscribed customers are promptly notified of malicious activity as soon as it emerges.
Figure 7: Darktrace’s correlation of the initial PowerShell-related activity with the cryptomining endpoint, showcasing a pattern indicative of an initial attack chain.
Darktrace’s Cyber AI Analyst launched an autonomous investigation into the ongoing activity and was able to link the individual events of the attack, encompassing the initial connections involving the PowerShell script to the ultimate connections to the cryptomining endpoint, likely representing cryptomining activity. Rather than viewing these seemingly separate events in isolation, Cyber AI Analyst was able to see the bigger picture, providing comprehensive visibility over the attack.
Figure 8: Darktrace’s Cyber AI Analyst view illustrating the extent of the cryptojacking attack mapped against the Cyber Kill Chain.
Darktrace’s Autonomous Response
Fortunately, as this customer had Darktrace configured in Autonomous Response mode, Darktrace was able to take immediate action by preventing the device from making outbound connections and blocking specific connections to suspicious endpoints, thereby containing the attack.
Figure 9: Darktrace’s Autonomous Response actions automatically triggered based on the anomalous connections observed to suspicious endpoints.
Specifically, these Autonomous Response actions prevented the outgoing communication within seconds of the device attempting to connect to the rare endpoints.
Figure 10: Darktrace’s Autonomous Response blocked connections to the mining-related endpoint within a second of the initial connection.
Additionally, the Darktrace SOC team was able to validate the effectiveness of the Autonomous Response actions by analyzing connections to 152.53.121[.]6 using the Advanced Search feature. Across more than 130 connection attempts, Darktrace’s SOC confirmed that all were aborted, meaning no connections were successfully established.
Figure 11: Advanced Search logs showing all attempted connections that were successfully prevented by Darktrace’s Autonomous Response capability.
Conclusion
Cryptojacking attacks will remain prevalent, as threat actors can scale their attacks to infect multiple devices and networks. What’s more, cryptomining incidents can often be difficult to detect and are even overlooked as low-severity compliance events, potentially leading to data privacy issues and significant energy bills caused by misused processing power.
Darktrace’s anomaly-based approach to threat detection identifies early indicators of targeted attacks without relying on prior knowledge or IoCs. By continuously learning each device’s unique pattern of life, Darktrace can detect subtle deviations that may signal a compromise.
In this case, the cryptojacking attack was quickly identified and mitigated during the early stages of malware and cryptomining activity. Darktrace's Autonomous Response was able to swiftly contain the threat before it could advance further along the attack lifecycle, minimizing disruption and preventing the attack from potentially escalating into a more severe compromise.
Credit to Keanna Grelicha (Cyber Analyst) and Tara Gould (Threat Research Lead)
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.
From VPS to Phishing: How Darktrace Uncovered SaaS Hijacks through Virtual Infrastructure Abuse
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
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.
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
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)
• 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.
![Darktrace’s detection of a device establishing connections with the Monero Mining-associated endpoint, monerooceans[.]stream over port 10001.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/68ae120122e002f39b1d5b67_Screenshot%202025-08-26%20at%2012.58.52%E2%80%AFPM.png)
