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May 19, 2023

Darktrace Stops Large-Scale Account Hijack

Learn how Darktrace detected and stopped a large-scale account hijack that led to a phishing attack. Protect your business with these insights.
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
Zoe Tilsiter
Cyber Analyst
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19
May 2023

Introduction 

As malicious actors across the threat landscape continue to take advantage of the widespread adoption of Software-as-a-Service (SaaS) platforms and multi-factor authentication (MFA) services to gain unauthorized access to organizations’ networks, it is crucial to have appropriate security tools in place to defend against account compromise at the earliest stage.

One method frequently employed by attackers is account takeover. Account takeovers occur when a threat actor exploits credentials to login to a SaaS account, often from an unusual location where the genuine actor does not usually login from. 

Access to these accounts can be caused by harvesting credentials through phishing emails and password spray attacks, or by exploiting insecure cloud safety practices such as not having MFA enabled on user accounts, requiring only user credentials for authentication. Once the integrity of the account is compromised, the threat actor can conduct further activity, such as delivering malware, reading and exfiltrating sensitive data, and sending out phishing emails to harvest further internal and external user credentials, repeating the attack cycle [1,2]. 

In early 2023, Darktrace detected a large-scale account takeover and phishing attack on the network of a customer in the education sector that affected hundreds of accounts and resulted in thousands of emails being forwarded outside of the network. The exceptional degree of visibility provided by Darktrace DETECT™ allowed for the detection of adversarial activity at every stage of the kill chain, and direct support from the Darktrace Analyst team via the Ask the Expert (ATE) service ensured the customer was fully informed and equipped to implement remedial action. 

Details of Attack Chain

Darktrace observed the same pattern of activity on all hijacked accounts on the customer’s network; login from unfamiliar locations, enablement of a mail forwarding rule that forwards all incoming emails to malicious email addresses, and the sending of phishing emails followed by their deletion. 

Figure 1: Timeline of attack on hijacked SaaS accounts.

Initial Access

Darktrace DETECT first detected anomalous SaaS activity on the customer environment on January 14, 2023, and then again on February 3, when multiple SaaS accounts were observed logging in from atypical locations with rare IP addresses and geographically impossible travel timings, or logging in whilst the account owner was active elsewhere. Subsequent investigation using open-source intelligence (OSINT) sources revealed one of the IP addressed had recently been associated with brute-force or password spray attempt.

This pattern of unusual login behavior persisted throughout the timeframe of the attack, with more unique accounts generating model breaches each day for similarly anomalous logins. As MFA authentication was not enforced for these user logins, the initial intrusion process was enabled by requiring only credentials for authentication.

Sending Emails 

The compromised accounts were also seen sending out emails with the subject ‘Email HELP DESK’ to external and internal recipients. This was likely represented a threat actor employing social engineering tactics to gain the trust of the recipient by posing as an internal help desk.

Mail Forwarding

Following the successful logins, compromised accounts began creating email rules to forward mail to external email addresses, some of which were associated with domains that had hits for malicious activity according to OSINT sources [3].

  • chotunai[.]com
  • bymercy[.]com
  • breazeim[.]com
  • brandoza[.]com

Forwarding mail is a commonly observed tactic during SaaS compromises to control lines of communication. Malicious actors often attempt to insert themselves into ongoing correspondence for illicit purposes, such as exfiltrating sensitive information, gaining persistent access to the compromised email or redirecting invoice payments. 

Email Deletions

Shortly after the mail forwarding activity, compromised accounts were detected performing anomalous email deletions en masse. Further investigation revealed that these accounts had previously sent a large volume of phishing emails and this mass deletion likely represented an attempt to conceal these activities by deleting them from their outboxes.

On February 10, the customer applied a mass password reset on all accounts that Darktrace had identified as compromised and provisioned, privileged accounts with MFA. They have indicated that those measures successfully halted the compromise, addressing the initial point of entry.  

Darktrace Coverage

Using its Self-Learning AI, Darktrace effectively demonstrated its ability to detect unusual SaaS activity that could indicate that an account has been hijacked by malicious actors. Rather than relying on a traditional rules and signature-based approach, Darktrace models develop an understanding of the network itself and can instantly recognize when a compromised deviates from its expected pattern of life.

Figure 2: Detection of unusual SaaS activity on hijacked SaaS account.

Initial Access

Initial access was detected by the following models:

  • Security Integration / High Severity Integration Detection  
  • SaaS / Unusual Activity / Activity from Multiple Unusual IPs 
  • SaaS / Access / Unusual External Source for SaaS Credential Use 
  • SaaS / Compromise / Login From Rare Endpoint While User Is Active 

Initial access was also detected by the following Cyber AI Analyst Incidents:

  • Possible Hijack of Office365 Account 

The model breaches and AI Analyst incidents detected logins from 100% rare external IP addresses in conjunction with a lack of MFA usage, as depicted in Figure 3.

Figure 3: Breach log showing initial detection of a SaaS login from a 100% rare IP where MFA was not used.
Figure 4: Initial detection of unusual SaaS activity visualized in Darktrace's SaaS console.

Mail Forwarding

Mail forwarding was detected by the following models:

  • SaaS / Admin / Mail Forwarding Enabled 

Compromised accounts were largely detected configuring mail forwarding rules to external email addresses, ostensibly to establish persistence on the network and exfiltrate sensitive correspondence.

Figure 5: The enablement of mail forwarding was detected as 100% new or uncommon for the account in question.

Mass Email Deletion

Mass email deletion was detected by the following models:

  • SaaS / Compromise / Suspicious Login and Mass Email Deletes 
  • SaaS / Resource / Mass Email Deletes from Rare Location 
Figure 6: Compromised account deleting phishing emails it had previously sent from the outbox.

Darktrace detected accounts performing highly anomalous mass email deletions from rare locations. The actors deleted the email “Email HELP DESK” which was later confirmed as being the primary phishing email used in the attack. Deletions were observed on compromised accounts’ outboxes, presumably to conceal the malicious activity.

Darktrace also detected this linked pattern of activity in sequential models such as: 

  • SaaS / Compromise / Unusual Login, Sent Mail, Deleted Sent
  • SaaS / Compromise / Suspicious Login and Mass Email Deletes 

Ask the Expert

The customer used the ATE service to request more technical information and support concerning the attack. Darktrace’s 24/7 team of analysts were able to offer expert assistance and further details to assist in the subsequent investigations and remediation steps. 

Further Detection and Response  

Unfortunately, the customer did not have Darktrace/Email™ enabled at the time of the attack. Darktrace/Email has visibility over inbound and outbound mail-flow which provides an oversight on potential data loss incidents. In this case, Darktrace DETECT/Email would have been able to provide full visibility over the phishing emails sent by the compromised accounts, as well as the attackers attempts to spoof an internal helpdesk. Further to this, the new Analysis Outlook integration helps employees understand why an email is suspicious and enables them report emails directly to the security team, which helps to continuously build user awareness of phishing attacks. 

Darktrace/Email also enhances Darktrace/Network™ detections by triggering ‘Email Nexus’ models within Darktrace/Network, where malicious activity is detected across the digital estate, correlating moving from SaaS compromised logins to mass email spam being sent out by compromised users

Figure 7: Email Nexus models within the Darktrace/Network enhanced by Darktrace/Email

Darktrace RESPOND™ was not enabled on the customer environment at the time of the attack; if it were, Darktrace would have been able to autonomously take action against the SaaS model breaches detecting across multiple of the kill chain. RESPOND would have disabled the hijacked accounts or force them to log out for a period of time, whilst also disabling the inbox rules that had been established by malicious actors. This would have given the customer’s security team valuable time to analyze the incident and mitigate the situation, preventing the attack from escalating any further. 

Conclusion

Ultimately, Darktrace demonstrated its unparalleled visibility over customer networks which allowed for the detection of this large-scale targeted SaaS account takeover, and the subsequent phishing attack. It underscores the importance of defense in depth; critically, MFA was not enforced for this environment which likely made the targeted organization far more susceptible to compromise via credential theft. The phishing activity detected by Darktrace following this account compromise also highlights the need for email protection in any security stack. 

Darktrace’s visibility meant allowed it to detect the attack at a high degree of granularity, including the account logins, email forwarding rule creations, outbound mail, and the mass deletions of phishing emails. Darktrace’s anomaly-based detection means it does not have to rely on signatures, rules or known indicators of compromise (IoCs) when identifying an emerging threat, instead placing the emphasis on recognizing a user’s deviation from its normal behavior.

However, without the presence of an autonomous response technology able to instantly intervene and stop ongoing attacks, organizations will always be reacting to attacks once the damage is done. Darktrace RESPOND is uniquely placed to take action against suspicious activity as soon as it is detected, preventing attacks from escalating and saving customers from significant disruption to their business.

Credit to: Zoe Tilsiter, Cyber Analyst, Gernice Lee, Cyber Analyst.

Appendices

Models Breached

SaaS / Access / Unusual External Source for SaaS Credential Use

SaaS / Admin / Mail Forwarding Enabled

SaaS / Compliance / Microsoft Cloud App Security Alert Detected

SaaS / Compromise / SaaS Anomaly Following Anomalous Login 

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 / Unusual Activity / Multiple Unusual External Sources For SaaS Credential

SaaS / Unusual Activity / Activity from Multiple Unusual IPs

SaaS / Unusual Activity / Multiple Unusual SaaS Activities 

Security Integration / Low Severity Integration Detection

Security Integration / High Severity Integration Detection

List of IoCs

brandoza[.]com - domain - probable domain of forwarded email address

breazeim[.]com - domain - probable domain of forwarded email address

bymercy[.]com - domain - probable domain of forwarded email address

chotunai[.]com - domain - probable domain of forwarded email address

MITRE ATT&CK Mapping

Tactic: INITIAL ACCESS, PERSISTENCE, PRIVILEGE ESCILATION, DEFENSE EVASION

Technique: T1078.004 – Cloud Accounts

Tactic: COLLECTION

Technique: T1114- Email Collection

Tactic:COLLECTION

Technique: T1114.003- Email Forwarding Rule

Tactic: IMPACT

Technique: T1485- Data Destruction

Tactic: DEFENSE EVASION

Technique: T1578.003 – Delete Cloud Instance

References

[1] Darktrace, 2022, Cloud Application Security_ Protect your SaaS with Self-Learning AI.pdf

[2] https://www.cloudflare.com/en-gb/learning/access-management/account-takeover/ 

[3] https://www.virustotal.com/gui/domain/chotunai.com 

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
Zoe Tilsiter
Cyber Analyst

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November 19, 2025

Securing Generative AI: Managing Risk in Amazon Bedrock with Darktrace / CLOUD

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Security risks and challenges of generative AI in the enterprise

Generative AI and managed foundation model platforms like Amazon Bedrock are transforming how organizations build and deploy intelligent applications. From chatbots to summarization tools, Bedrock enables rapid agent development by connecting foundation models to enterprise data and services. But with this flexibility comes a new set of security challenges, especially around visibility, access control, and unintended data exposure.

As organizations move quickly to operationalize generative AI, traditional security controls are struggling to keep up. Bedrock’s multi-layered architecture, spanning agents, models, guardrails, and underlying AWS services, creates new blind spots that standard posture management tools weren’t designed to handle. Visibility gaps make it difficult to know which datasets agents can access, or how model outputs might expose sensitive information. Meanwhile, developers often move faster than security teams can review IAM permissions or validate guardrails, leading to misconfigurations that expand risk. In shared-responsibility environments like AWS, this complexity can blur the lines of ownership, making it critical for security teams to have continuous, automated insight into how AI systems interact with enterprise data.

Darktrace / CLOUD provides comprehensive visibility and posture management for Bedrock environments, automatically detecting and proactively scanning agents and knowledge bases, helping teams secure their AI infrastructure without slowing down expansion and innovation.

A real-world scenario: When access goes too far

Consider a scenario where an organization deploys a Bedrock agent to help internal staff quickly answer business questions using company knowledge. The agent was connected to a knowledge base pointing at documents stored in Amazon S3 and given access to internal services via APIs.

To get the system running quickly, developers assigned the agent a broad execution role. This role granted access to multiple S3 buckets, including one containing sensitive customer records. The over-permissioning wasn’t malicious; it stemmed from the complexity of IAM policy creation and the difficulty of identifying which buckets held sensitive data.

The team assumed the agent would only use the intended documents. However, they did not fully consider how employees might interact with the agent or how it might act on the data it processed.  

When an employee asked a routine question about quarterly customer activity, the agent surfaced insights that included regulated data, revealing it to someone without the appropriate access.

This wasn’t a case of prompt injection or model manipulation. The agent simply followed instructions and used the resources it was allowed to access. The exposure was valid under IAM policy, but entirely unintended.

How Darktrace / CLOUD prevents these risks

Darktrace / CLOUD helps organizations avoid scenarios like unintended data exposure by providing layered visibility and intelligent analysis across Bedrock and SageMaker environments. Here’s how each capability works in practice:

Configuration-level visibility

Bedrock deployments often involve multiple components: agents, guardrails, and foundation models, each with its own configuration. Darktrace / CLOUD indexes these configurations so teams can:

  1. Inspect deployed agents and confirm they are connected only to approved data sources.
  2. Track evaluation job setups and their links to Amazon S3 datasets, uncovering hidden data flows that could expose sensitive information.
  3. Maintain full awareness of all AI components, reducing the chance of overlooked assets introducing risk.

By unifying configuration data across Bedrock, SageMaker, and other AWS services, Darktrace / CLOUD provides a single source of truth for AI asset visibility. Teams can instantly see how each component is configured and whether it aligns with corporate security policies. This eliminates guesswork, accelerates audits, and helps prevent misaligned settings from creating data exposure risks.

 Agents for bedrock relationship views.
Figure 1: Agents for bedrock relationship views

Architectural awareness

Complex AI environments can make it difficult to understand how components interact. Darktrace / CLOUD generates real-time architectural diagrams that:

  1. Visualize relationships between agents, models, and datasets.
  1. Highlight unintended data access paths or risk propagation across interconnected services.

This clarity helps security teams spot vulnerabilities before they lead to exposure. By surfacing these relationships dynamically, Darktrace / CLOUD enables proactive risk management, helping teams identify architectural drift, redundant data connections, or unmonitored agents before attackers or accidental misuse can exploit them. This reduces investigation time and strengthens compliance confidence across AI workloads.

Figure 2: Full Bedrock agent architecture including lambda and IAM permission mapping
Figure 2: Full Bedrock agent architecture including lambda and IAM permission mapping

Access & privilege analysis

IAM permissions apply to every AWS service, including Bedrock. When Bedrock agents assume IAM roles that were broadly defined for other workloads, they often inherit excessive privileges. Without strict least-privilege controls, the agent may have access to far more data and services than required, creating avoidable security exposure. Darktrace / CLOUD:

  1. Reviews execution roles and user permissions to identify excessive privileges.
  2. Flags anomalies that could enable privilege escalation or unauthorized API actions.

This ensures agents operate within the principle of least privilege, reducing attack surface. Beyond flagging risky roles, Darktrace / CLOUD continuously learns normal patterns of access to identify when permissions are abused or expanded in real time. Security teams gain context into why an action is anomalous and how it could affect connected assets, allowing them to take targeted remediation steps that preserve productivity while minimizing exposure.

Misconfiguration detection

Misconfigurations are a leading cause of cloud security incidents. Darktrace / CLOUD automatically detects:

  1. Publicly accessible S3 buckets that may contain sensitive training data.
  2. Missing guardrails in Bedrock deployments, which can allow inappropriate or sensitive outputs.
  3. Other issues such as lack of encryption, direct internet access, and root access to models.  

By surfacing these risks early, teams can remediate before they become exploitable. Darktrace / CLOUD turns what would otherwise be manual reviews into automated, continuous checks, reducing time to discovery and preventing small oversights from escalating into full-scale incidents. This automated assurance allows organizations to innovate confidently while keeping their AI systems compliant and secure by design.

Configuration data for Anthropic foundation model
Figure 3: Configuration data for Anthropic foundation model

Behavioral anomaly detection

Even with correct configurations, behavior can signal emerging threats. Using AWS CloudTrail, Darktrace / CLOUD:

  1. Monitors for unusual data access patterns, such as agents querying unexpected datasets.
  2. Detects anomalous training job invocations that could indicate attempts to pollute models.

This real-time behavioral insight helps organizations respond quickly to suspicious activity. Because it learns the “normal” behavior of each Bedrock component over time, Darktrace / CLOUD can detect subtle shifts that indicate emerging risks, before formal indicators of compromise appear. The result is faster detection, reduced investigation effort, and continuous assurance that AI-driven workloads behave as intended.

Conclusion

Generative AI introduces transformative capabilities but also complex risks that evolve alongside innovation. The flexibility of services like Amazon Bedrock enables new efficiencies and insights, yet even legitimate use can inadvertently expose sensitive data or bypass security controls. As organizations embrace AI at scale, the ability to monitor and secure these environments holistically, without slowing development, is becoming essential.

By combining deep configuration visibility, architectural insight, privilege and behavior analysis, and real-time threat detection, Darktrace gives security teams continuous assurance across AI tools like Bedrock and SageMaker. Organizations can innovate with confidence, knowing their AI systems are governed by adaptive, intelligent protection.

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Adam Stevens
Senior Director of Product, Cloud | Darktrace

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November 19, 2025

Unmasking Vo1d: Inside Darktrace’s Botnet Detection

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What is Vo1d APK malware?

Vo1d malware first appeared in the wild in September 2024 and has since evolved into one of the most widespread Android botnets ever observed. This large-scale Android malware primarily targets smart TVs and low-cost Android TV boxes. Initially, Vo1d was identified as a malicious backdoor capable of installing additional third-party software [1]. Its functionality soon expanded beyond the initial infection to include deploying further malicious payloads, running proxy services, and conducting ad fraud operations. By early 2025, it was estimated that Vo1d had infected 1.3 to 1.6 million devices worldwide [2].

From a technical perspective, Vo1d embeds components into system storage to enable itself to download and execute new modules at any time. External researchers further discovered that Vo1d uses Domain Generation Algorithms (DGAs) to create new command-and-control (C2) domains, ensuring that regardless of existing servers being taken down, the malware can quickly reconnect to new ones. Previous published analysis identified dozens of C2 domains and hundreds of DGA seeds, along with new downloader families. Over time, Vo1d has grown increasingly sophisticated with clear signs of stronger obfuscation and encryption methods designed to evade detection [2].

Darktrace’s coverage

Earlier this year, Darktrace observed a surge in Vo1d-related activity across customer environments, with the majority of affected customers based in South Africa. Devices that had been quietly operating as expected began exhibiting unusual network behavior, including excessive DNS lookups. Open-source intelligence (OSINT) has long highlighted South Africa as one of the countries most impacted by Vo1d infections [2].

What makes the recent activity particularly interesting is that the surge observed by Darktrace appears to be concentrated specifically in South African environments. This localized spike suggests that a significant number of devices may have been compromised, potentially due to vulnerable software, outdated firmware, or even preloaded malware. Regions with high prevalence of low-cost, often unpatched devices are especially susceptible, as these everyday consumer electronics can be quietly recruited into the botnet’s network. This specifically appears to be the case with South Africa, where public reporting has documented widespread use of low-cost boxes, such as non-Google-certified Android TV sticks, that frequently ship with outdated firmware [3].

The initial triage highlighted the core mechanism Vo1d uses to remain resilient: its use of DGA. A DGA deterministically creates a large list of pseudo-random domain names on a predictable schedule. This enables the malware to compute hundreds of candidate domains using the same algorithm, instead of using a hard-coded single C2 hostname that defenders could easily block or take down. To ensure reproducible from the infected device’s perspective, Vo1d utilizes DGA seeds. These seeds might be a static string, a numeric value, or a combination of underlying techniques that enable infected devices to generate the same list of candidate domains for a time window, provided the same DGA code, seed, and date are used.

Interestingly, Vo1d’s DGA seeds do not appear to be entirely unpredictable, and the generated domains lack fully random-looking endings. As observed in Figure 1, there is a clear pattern in the names generated. In this case, researchers identified that while the first five characters would change to create the desired list of domain names, the trailing portion remained consistent as part of the seed: 60b33d7929a, which OSINT sources have linked to the Vo1d botnet. [2]. Darktrace’s Threat Research team also identified a potential second DGA seed, with devices in some cases also engaging in activity involving hostnames matching the regular expression /[a-z]{5}fc975904fc9\.(com|top|net). This second seed has not been reported by any OSINT vendors at the time of writing.

Another recurring characteristic observed across multiple cases was the choice of top-level domains (TLDs), which included .com, .net, and .top.

Figure 1: Advanced Search results showing DNS lookups, providing a glimpse on the DGA seed utilized.

The activity was detected by multiple models in Darktrace / NETWORK™, which triggered on devices making an unusually large volume of DNS requests for domains uncommon across the network.

During the network investigation, Darktrace analysts traced Vo1d’s infrastructure and uncovered an interesting pattern related to responder ASNs. A significant number of connections pointed to AS16509 (AMAZON-02). By hosting redirectors or C2 nodes inside major cloud environments, Vo1d is able to gain access to highly available and geographically diverse infrastructure. When one node is taken down or reported, operators can quickly enable a new node under a different IP within the same ASN. Another feature of cloud infrastructure that hardens Vo1d’s resilience is the fact that many organizations allow outbound connections to cloud IP ranges by default, assuming they are legitimate. Despite this, Darktrace was able to identify the rarity of these endpoints, identifying the unusualness of the activity.

Analysts further observed that once a generated domain successfully resolved, infected devices consistently began establishing outbound connections to ephemeral port ranges like TCP ports 55520 and 55521. These destination ports are atypical for standard web or DNS traffic. Even though the choice of high-numbered ports appears random, it is likely far from not accidental. Commonly used ports such as port 80 (HTTP) or 443 (HTTPS) are often subject to more scrutiny and deeper inspection or content filtering, making them riskier for attackers. On the other hand, unregistered ports like 55520 and 55521 are less likely to be blocked, providing a more covert channel that blends with outbound TCP traffic. This tactic helps evade firewall rules that focus on common service ports. Regardless, Darktrace was able to identify external connections on uncommon ports to locations that the network does not normally visit.

The continuation of the described activity was identified by Darktrace’s Cyber AI Analyst, which correlated individual events into a broader interconnected incident. It began with the multiple DNS requests for the algorithmically generated domains, followed by repeated connections to rare endpoints later confirmed as attacker-controlled infrastructure. Cyber AI Analyst’s investigation further enabled it to categorize the events as part of the “established foothold” phase of the attack.

Figure 2: Cyber AI Analyst incident illustrating the transition from DNS requests for DGA domains to connections with resolved attacker-controlled infrastructure.

Conclusion

The observations highlighted in this blog highlight the precision and scale of Vo1d’s operations, ranging from its DGA-generated domains to its covert use of high-numbered ports. The surge in affected South African environments illustrate how regions with many low-cost, often unpatched devices can become major hubs for botnet activity. This serves as a reminder that even everyday consumer electronics can play a role in cybercrime, emphasizing the need for vigilance and proactive security measures.

Credit to Christina Kreza (Cyber Analyst & Team Lead) and Eugene Chua (Principal Cyber Analyst & Team Lead)

Edited by Ryan Traill (Analyst Content Lead)

Appendices

Darktrace Model Detections

  • Anomalous Connection / Devices Beaconing to New Rare IP
  • Anomalous Connection / Multiple Connections to New External TCP Port
  • Anomalous Connection / Multiple Failed Connections to Rare Endpoint
  • Compromise / DGA Beacon
  • Compromise / Domain Fluxing
  • Compromise / Fast Beaconing to DGA
  • Unusual Activity / Unusual External Activity

List of Indicators of Compromise (IoCs)

  • 3.132.75[.]97 – IP address – Likely Vo1d C2 infrastructure
  • g[.]sxim[.]me – Hostname – Likely Vo1d C2 infrastructure
  • snakeers[.]com – Hostname – Likely Vo1d C2 infrastructure

Selected DGA IoCs

  • semhz60b33d7929a[.]com – Hostname – Possible Vo1d C2 DGA endpoint
  • ggqrb60b33d7929a[.]com – Hostname – Possible Vo1d C2 DGA endpoint
  • eusji60b33d7929a[.]com – Hostname – Possible Vo1d C2 DGA endpoint
  • uacfc60b33d7929a[.]com – Hostname – Possible Vo1d C2 DGA endpoint
  • qilqxfc975904fc9[.]top – Hostname – Possible Vo1d C2 DGA endpoint

MITRE ATT&CK Mapping

  • T1071.004 – Command and Control – DNS
  • T1568.002 – Command and Control – Domain Generation Algorithms
  • T1568.001 – Command and Control – Fast Flux DNS
  • T1571 – Command and Control – Non-Standard Port

[1] https://news.drweb.com/show/?lng=en&i=14900

[2] https://blog.xlab.qianxin.com/long-live-the-vo1d_botnet/

[3] https://mybroadband.co.za/news/broadcasting/596007-warning-for-south-africans-using-specific-types-of-tv-sticks.html

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.

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About the author
Christina Kreza
Cyber Analyst
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