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June 9, 2021

Enhancing Cybersecurity: Attack Surface Management

Explore effective strategies and learn how organizations can enhance Attack Surface Management using artificial intelligence (AI) automation. Read more.
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
Vincent Thiele
Deputy CISO
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09
Jun 2021

Effective attack surface management breaks down into four key parts:

  • Discovery
  • Assessment and prioritisation
  • Risk prevention
  • Integration

Discovery

The most important part of any attack surface management process is the discovery phase. As we’ve mentioned previously, most organizations miss as much as 30 to 50 percent of their true attack surface. This creates huge blind spots when it comes to understanding the real risks your organization is facing. In fact, we believe that something like 80% of all organizations’ cybersecurity problems exist due to blind spots in their attack surface. Eliminating those blind spots should be your core goal when setting out to discover your attack surface.

One of the biggest contributing factors to these blind spots is scoping. Organizations tend to work within a predefined scope when it comes to discovery – whether that’s within a defined IT infrastructure or a set of IP addresses that the organization uses and wants to protect.

However, the reality is that any would-be attackers out there do not care about your scope. Whether you have a vulnerability in-house, via an external supplier, or in a cloud environment; an attacker will find it and try to misuse it.

On top of this, with modern organizations having so many external dependencies, regulatory bodies are starting to insist that financial services companies look beyond the boundaries of their own networks when analysing risk.

For example, the Digital Operational Resilience of the financial sector (DORA), extends the focus of risk management to cover all external assets of the parties they have relationships with (such as fourth and fifth parties, or parties that you even don't know you have a relationship with), as well as any services and infrastructure that can impact on the organization’s day-to-day resilience.

Taking a zero-scope approach to your attack surface is therefore essential. This means that tracking down the full extent of your attack surface is not something that can be left to human endeavour. Relying on people to trace and discover your connections would be hugely expensive, time consuming, and error prone. So, a prerequisite of effective discovery is automation. AI and algorithmic-based discovery is the only way to uncover the bulk of your attack surface.

Assessment and Prioritization

Monitoring your attack surface is not a one-time, set-and-forget process because your attack surface is not static; it’s constantly evolving and changing. This means you need to be continuously monitoring it for changes, and you need to be alerted when those changes occur, so that you can decide whether or not something needs your attention. This data needs to be dynamic and as close to real-time as you can get.Only once you know what your full attack surface looks like can you really start to analyse the risk types presented to the business. These risks can be extensive and need prioritisation according to the threat presented to the brand. As the discovery process continues, you need an automated risk assessment tool to save time and effort. It will tell you what the most pressing risks are, so you can focus on the mitigating process. Then, even when the discovery process is ongoing, new risks are automatically reported on, and added to right lists. This ensures you stay up-to-date on the actual risks to the organization – removing a lot of the stress from the process for CISOs.

Risk Prevention

There is a flipside to seeing your whole attack surface. Having a comprehensive overview of every risk your organization faces can be terrifying – you are going to uncover a multitude of things you’d never considered. This can leave you facing one big question: “Do I really want to know all of this?” Most CISOs and cybersecurity professionals are already busy with all the things they do know about, so you need to have a way of striping out and solving some of the possibly lower priority but easier to solve risks in your report. This is again where automation can come into play. Automatically categorizing similar risk types throughout your attack surface will save time and effort when reducing risks.

Integration

Finally, it doesn’t matter how much data you have on something; if it’s not actionable it’s ultimately not going to be practical to use. So you need to be able to connect all that data coming from your attack surface monitoring into your existing internal processes and systems (your PSA, ITSM, or ESM tools etc). That way you can build it into your existing cybersecurity structure and minimise extra work.

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
Vincent Thiele
Deputy CISO

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November 12, 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

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About the author
Christina Kreza
Cyber Analyst

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November 6, 2025

Darktrace Named the Only 2025 Gartner® Peer Insights™ Customers’ Choice for Network Detection and Response

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Darktrace: The only Customers’ Choice for NDR in 2025

In a year defined by rapid change across the threat landscape, recognition from those who use and rely on security technology every day means the most.

That’s why we’re proud to share that Darktrace has been named the only Customers’ Choice in the 2025 Gartner® Peer Insights™ Voice of the Customer for Network Detection and Response (NDR).

Out of 11 leading NDR vendors evaluated, Darktrace stood alone as the sole Customers’ Choice, a recognition that we feel reflects not just our innovation, but the trust and satisfaction of the customers who secure their networks with Darktrace every day.

What the Gartner® Peer Insights™ Voice of the Customer means

“Voice of the Customer” is a document that synthesizes Gartner Peer Insights reviews into insights for buyers of technology and services. This aggregated peer perspective, along with the individual detailed reviews, is complementary to Gartner expert research and can play a key role in your buying process. Peers are verified reviewers of a technology product or service, who not only rate the offering, but also provide valuable feedback to consider before making a purchase decision. Vendors placed in the upper-right “Customers’ Choice” quadrant of the “Voice of the Customer” have scores that meet or exceed the market average for both axes (User Interest and Adoption, and Overall Experience).It’s not just a rating. We feel it’s a reflection of genuine customer sentiment and success in the field.

In our view, Customers consistently highlight Darktrace’s ability to:

  • Detect and respond to unknown threats in real time
  • Deliver unmatched visibility across IT, OT, and cloud environments
  • Automate investigations and responses through AI-driven insights

We believe this recognition reinforces what our customers already know: that Darktrace helps them see, understand, and stop attacks others miss.

A rare double: recognized by customers and analysts alike

This distinction follows another major recogniton. Darktrace’s placement as a Leader in the Gartner® Magic Quadrant™ for Network Detection and Response earlier this year.

That makes Darktrace the only vendor to achieve both:

  • A Leader status in the Gartner Magic Quadrant for NDR, and
  • A Customers’ Choice in Gartner Peer Insights 2025

It’s a rare double that we feel reflects both industry leadership and customer trust, two perspectives that, together, define what great cybersecurity looks like.

A Customers’ Choice across the network and the inbox

To us, this recognition also builds on Darktrace’s momentum across multiple domains. Earlier this year, Darktrace was also named a Customers’ Choice for Email Security Platforms in the Gartner® Peer Insights™ report.

With more than 1,000 verified reviews across Network Detection and Response, Email Security Platforms, and Cyber Physical Systems (CPS), we at Darktrace are proud to be trusted across the full attack surface, from the inbox to the industrial network.

Thank you to our customers

We’re deeply grateful to every customer who shared their experience with Darktrace on Gartner Peer Insights. Your insights drive our innovation and continue to shape how we protect complex, dynamic environments across the world.

Discover why customers choose Darktrace for network and email security.

Gartner® Peer Insights™ content consists of the opinions of individual end users based on their own experiences, and should not be construed as statements of fact, nor do they represent the views of Gartner or its affiliates. Gartner does not endorse any vendor, product or service depicted in this content nor makes any warranties, expressed or implied, with respect to this content, about its accuracy or completeness, including any warranties of merchantability or fitness for a particular purpose.

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

Magic Quadrant and Peer Insights are registered trademarks of Gartner, Inc. and/or its affiliates and is used herein with permission. All rights reserved.

Gartner, Voice of the Customer for Network Detection and Response, By Peer Community Contributor, 30 October 2025

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About the author
Mikey Anderson
Product Marketing Manager, Network Detection & Response
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