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December 13, 2023

Defending Against Personalized Cyber Attacks

Stay informed about the latest trends in cyber threats with Darktrace experts, including how attacks are evolving and becoming more personalized.
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.
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The Darktrace Community
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13
Dec 2023

Cyber-attacks are getting personal. The usual opportunistic “spray and pray” attacks that reach many would-be targets at once are still present, but as cyber defence has advanced, today’s more sophisticated campaigns take precise aim at a particular company.

Threat actors willingly put in extra time and effort to realize a bigger payday at the end of it, but developments in the tools they have at their disposal are also making targeted, personal attacks easier.

CAPTCHA-breaking AI techniques like computer vision and convolutional neural networks can be used to gather information on an organization’s attack surface, and Generative AI is able to perform OSINT collection on a specific target, or targets, within an organization. Once inside, attackers can further leverage AI to automatically tweak attacks and create novel, highly targeted threats that elude defenses.

A new white paper, The CISO’s Guide to Cyber AI, explains how CISOs and their teams can make smarter use of defensive AI and machine learning (ML) to protect today’s digital environments from these and more advanced novel threats.

Today’s threats don’t necessarily resemble past attacks  

Darktrace analytics pointed to a sharp rise in novel cyber-attacks earlier this year. Generative AI and large language model (LLM) tools continue to lower the barrier to entry for threat actors, making it easier than ever to build smarter, faster, more targeted attacks.

But while attacks are getting personal, security tools that apply AI in the wrong way won’t see these attacks coming.

Here’s why: most cyber security tools and platforms rely on a combination of supervised machine learning, deep learning, and transformers to train and inform their systems. This entails shipping your company’s data out to a large data lake housed somewhere in the cloud where it gets blended with attack data from thousands of other organizations. The resulting homogenized data set gets used to train AI systems — yours and everyone else’s — to recognize patterns of attack based on previously encountered threats.

At its conception, this was a reasonably smart way of approaching cyber security. For a long time, the assumption that today’s threats will resemble yesterday’s attacks was a valid one. But in an age where the commoditization of cyber-crime has lowered the bar-to-entry for attackers, and where Generative AI and other open-source tools are enabling personalized attacks at scale, this is no longer the case.

Darktrace has seen evidence this year of a marked rise in more sophisticated attack techniques. Between May and July this year, our Cyber AI Research Centre observed that multistage payload attacks, in which a malicious email encourages the recipient to follow a series of steps before delivering a payload or attempting to harvest sensitive information, have increased by an average of 59% across Darktrace customers. Some of this will be QR code phishing, the latest trend in attack tactics, others will include automation. The speed of these types of attacks will likely rise as greater automation and AI are adopted and applied by attackers.

This ‘historical’ approach is not able to identify threats that haven’t been seen before: attacks that use new malware, novel social engineering, and those that are targeted to your organization. There are no indicators of compromise (IoCs) to teach your system to recognize these kinds of attacks.

IoC-based defenses won’t necessarily spot strange and unusual activity by an authorized user, device, or known IP address until threat actors tip their hand — and by then it’s too late. Looking for repeat patterns works well for detecting threats that resemble past attacks, but this increasingly won’t be the case. The only way to spot unique and novel threats is to build cyber security that’s tailored to you, and that requires a whole new approach.

Smarter use of AI levels the playing field

Security teams and adversaries continue to innovate to gain the upper-hand, and the advantage of time.

Since AI equips even novice cyber criminals to mount sophisticated attacks, AI must evolve to do three things:

  • Understand and continue to learn what “normal” looks like for your unique digital environment
  • Detect and alert on any anomalous behavior the instant it occurs
  • Initiate a targeted response to contain threats and give your analysts more time, without disrupting the flow of business

Darktrace uses Self-Learning AI to understand what constitutes ‘normal’ for everyone and everything in your business, including cloud resources, identities, email accounts, endpoint devices, and even OT controllers. As the name suggests, Self-Learning AI trains itself, developing and maintaining deep understanding of ‘patterns of life’ for your business environment. Used in combination with other AI methods such as LLMs, generative AI, and supervised ML, Self-Learning AI identifies novel cyber-threats most static (backward-looking) tools miss.

The technology learns ‘on the job’ and from scratch, without relying on historical data or a massive upfront effort by your team to train the system. Probabilistic mathematics revise assumptions about behavior on a constant basis so the system keeps itself up-to-date without repeat efforts by your team.

The result is that areas of risk, as well as real-time emerging attacks, are brought to the surface – regardless of whether those attacks have been seen before in the wild.

Surgical attacks warrant surgical response

Supervised ML continues to serve a purpose, but the dawning age of novel and AI-led attacks favors a more proactive approach to securing the cloud. Tools must take greater responsibility for their own education and greater initiative via autonomous response.

What some solutions call response ultimately amounts to sending alerts and opening tickets that create more needless work for analysts. Other tools claim to automate response, but either take very limited actions like automating the process of ticket creation, or overly ambitious steps like quarantining entire systems.

Darktrace’s dynamic understanding of your environment enables a truly autonomous and precise cloud-native response. Its understanding of ‘normal’ for every user and device allows it to enforce ‘normal’ – cutting out only the malicious activity, while allowing normal business to continue functioning.

How this response will take place will depend on where Darktrace is deployed in your environment. In the network, it might mean blocking specific, anomalous connections over a certain port. In the cloud, it could mean detaching EC2 instances and applying security groups to contain only assets at risk. In email, this could be locking links or flattening attachments.

Get personal with ‘One on One’ Security

The widespread accessibility of generative AI has altered the threat landscape permanently, allowing cyber-criminals to deploy unique and personalized attacks at scale and at machine speed. In the near future, we can expect to see more novel and sophisticated phishing attacks, new automated creation of malicious code, sustained attack campaigns targeting an individual or company, and even deep fakes designed to elicit human trust.

To meet the needs of today and tomorrow, cyber security needs to leverage AI deeply and intelligently – not just using it to automate outdated historical approaches, or bolting generative AI onto existing products to keep up with the latest trend. Since 2013 Darktrace has been using AI in a fundamentally unique way: a system that learns your unique organization and understands what’s normal at a granular level. Only with this personalized understanding can you be confident in your ability as an organization to identify and shut down novel threats on the first encounter.

This form of personalized, ‘One on One’ security is a no longer a ‘nice to have’ for defenders. ‘Spray and pray’ tactics will continue to exist, but the attacks most likely to slip through the net and cause you damage are the sophisticated, the personal, and the never-before-seen. That’s what Self-Learning AI was built for – learning your business to deliver personalized cyber security, meeting every attack one-on-one.

The CISO’s Guide to Cyber AI overviews the differences between common AI approaches in cyber security and offers a high-level checklist for choosing the ideal solution for stopping attacks — including new novel threats.  To learn more about making the smartest use of AI to stop novel and targeted cloud attacks, download the guide today.

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
The Darktrace Community

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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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