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July 26, 2022

Identifying PrivateLoader Network Threats

Learn how Darktrace identifies network-based indicators of compromise for the PrivateLoader malware. Gain insights into advanced threat detection.
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
Sam Lister
Specialist Security Researcher
Written by
Shuh Chin Goh
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26
Jul 2022

Instead of delivering their malicious payloads themselves, threat actors can pay certain cybercriminals (known as pay-per-install (PPI) providers) to deliver their payloads for them. Since January 2022, Darktrace’s SOC has observed several cases of PPI providers delivering their clients’ payloads using a modular malware downloader known as ‘PrivateLoader’.

This blog will explore how these PPI providers installed PrivateLoader onto systems and outline the steps which the infected PrivateLoader bots took to install further malicious payloads. The details provided here are intended to provide insight into the operations of PrivateLoader and to assist security teams in identifying PrivateLoader bots within their own networks.  

Threat Summary 

Between January and June 2022, Darktrace identified the following sequence of network behaviours within the environments of several Darktrace clients. Patterns of activity involving these steps are paradigmatic examples of PrivateLoader activity:

1. A victim’s device is redirected to a page which instructs them to download a password-protected archive file from a file storage service — typically Discord Content Delivery Network (CDN)

2. The device contacts a file storage service (typically Discord CDN) via SSL connections

3. The device either contacts Pastebin via SSL connections, makes an HTTP GET request with the URI string ‘/server.txt’ or ‘server_p.txt’ to 45.144.225[.]57, or makes an HTTP GET request with the URI string ‘/proxies.txt’ to 212.193.30[.]45

4. The device makes an HTTP GET request with the URI string ‘/base/api/statistics.php’ to either 212.193.30[.]21, 85.202.169[.]116, 2.56.56[.]126 or 2.56.59[.]42

5. The device contacts a file storage service (typically Discord CDN) via SSL connections

6. The device makes a HTTP POST request with the URI string ‘/base/api/getData.php’ to either 212.193.30[.]21, 85.202.169[.]116, 2.56.56[.]126 or 2.56.59[.]42

7. The device finally downloads malicious payloads from a variety of endpoints

The PPI Business 

Before exploring PrivateLoader in more detail, the pay-per-install (PPI) business should be contextualized. This consists of two parties:  

1. PPI clients - actors who want their malicious payloads to be installed onto a large number of target systems. PPI clients are typically entry-level threat actors who seek to widely distribute commodity malware [1]

2. PPI providers - actors who PPI clients can pay to install their malicious payloads 

As the smugglers of the cybercriminal world, PPI providers typically advertise their malware delivery services on underground web forums. In some cases, PPI services can even be accessed via Clearnet websites such as InstallBest and InstallShop [2] (Figure 1).  

Figure 1: A snapshot of the InstallBest PPI login page [2]


To utilize a PPI provider’s service, a PPI client must typically specify: 

(A)  the URLs of the payloads which they want to be installed

(B)  the number of systems onto which they want their payloads to be installed

(C)  their geographical targeting preferences. 

Payment of course, is also required. To fulfil their clients’ requests, PPI providers typically make use of downloaders - malware which instructs the devices on which it is running to download and execute further payloads. PPI providers seek to install their downloaders onto as many systems as possible. Follow-on payloads are usually determined by system information garnered and relayed back to the PPI providers’ command and control (C2) infrastructure. PPI providers may disseminate their downloaders themselves, or they may outsource the dissemination to third parties called ‘affiliates’ [3].  

Back in May 2021, Intel 471 researchers became aware of PPI providers using a novel downloader (dubbed ‘PrivateLoader’) to conduct their operations. Since Intel 471’s public disclosure of the downloader back in Feb 2022 [4], several other threat research teams, such as the Walmart Cyber Intel Team [5], Zscaler ThreatLabz [6], and Trend Micro Research [7] have all provided valuable insights into the downloader’s behaviour. 

Anatomy of a PrivateLoader Infection

The PrivateLoader downloader, which is written in C++, was originally monolithic (i.e, consisted of only one module). At some point, however, the downloader became modular (i.e, consisting of multiple modules). The modules communicate via HTTP and employ various anti-analysis methods. PrivateLoader currently consists of the following three modules [8]: 

  • The loader module: Instructs the system on which it is running to retrieve the IP address of the main C2 server and to download and execute the PrivateLoader core module
  • The core module: Instructs the system on which it is running to send system information to the main C2 server, to download and execute further malicious payloads, and to relay information regarding installed payloads back to the main C2 server
  • The service module: Instructs the system on which it is running to keep the PrivateLoader modules running

Kill Chain Deep-Dive 

The chain of activity starts with the user’s browser being redirected to a webpage which instructs them to download a password-protected archive file from a file storage service such as Discord CDN. Discord is a popular VoIP and instant messaging service, and Discord CDN is the service’s CDN infrastructure. In several cases, the webpages to which users’ browsers were redirected were hosted on ‘hero-files[.]com’ (Figure 2), ‘qd-files[.]com’, and ‘pu-file[.]com’ (Figure 3). 

Figure 2: An image of a page hosted on hero-files[.]com - an endpoint which Darktrace observed systems contacting before downloading PrivateLoader from Discord CDN
Figure 3: An image of a page hosted on pu-file[.]com- an endpoint which Darktrace observed systems contacting before downloading PrivateLoader from Discord CDN


On attempting to download cracked/pirated software, users’ browsers were typically redirected to download instruction pages. In one case however, a user’s device showed signs of being infected with the malicious Chrome extension, ChromeBack [9], immediately before it contacted a webpage providing download instructions (Figure 4). This may suggest that cracked software downloads are not the only cause of users’ browsers being redirected to these download instruction pages (Figure 5). 

Figure 4: The event log for this device (taken from the Darktrace Threat Visualiser interface) shows that the device contacted endpoints associated with ChromeBack ('freychang[.]fun') prior to visiting a page ('qd-file[.]com') which instructed the device’s user to download an archive file from Discord CDN
 Figure 5: An image of the website 'crackright[.]com'- a provider of cracked software. Systems which attempted to download software from this website were subsequently led to pages providing instructions to download a password-protected archive from Discord CDN


After users’ devices were redirected to pages instructing them to download a password-protected archive, they subsequently contacted cdn.discordapp[.]com over SSL. The archive files which users downloaded over these SSL connections likely contained the PrivateLoader loader module. Immediately after contacting the file storage endpoint, users’ devices were observed either contacting Pastebin over SSL, making an HTTP GET request with the URI string ‘/server.txt’ or ‘server_p.txt’ to 45.144.225[.]57, or making an HTTP GET request with the URI string ‘/proxies.txt’ to 212.193.30[.]45 (Figure 6).

Distinctive user-agent strings such as those containing question marks (e.g. ‘????ll’) and strings referencing outdated Chrome browser versions were consistently seen in these HTTP requests. The following chrome agent was repeatedly observed: ‘Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36’.

In some cases, devices also displayed signs of infection with other strains of malware such as the RedLine infostealer and the BeamWinHTTP malware downloader. This may suggest that the password-protected archives embedded several payloads.

Figure 6: This figure, obtained from Darktrace's Advanced Search interface, represents the post-infection behaviour displayed by a PrivateLoader bot. After visiting hero-files[.]com and downloading the PrivateLoader loader module from Discord CDN, the device can be seen making HTTP GET requests for ‘/proxies.txt’ and ‘/server.txt’ and contacting pastebin[.]com

It seems that PrivateLoader bots contact Pastebin, 45.144.225[.]57, and 212.193.30[.]45 in order to retrieve the IP address of PrivateLoader’s main C2 server - the server which provides PrivateLoader bots with payload URLs. This technique used by the operators of PrivateLoader closely mirrors the well-known espionage tactic known as ‘dead drop’.

The dead drop is a method of espionage tradecraft in which an individual leaves a physical object such as papers, cash, or weapons in an agreed hiding spot so that the intended recipient can retrieve the object later on without having to come in to contact with the source. When threat actors host information about core C2 infrastructure on intermediary endpoints, the hosted information is analogously called a ‘Dead Drop Resolver’ or ‘DDR’. Example URLs of DDRs used by PrivateLoader:

  • https://pastebin[.]com/...
  • http://212.193.30[.]45/proxies.txt
  • http://45.144.225[.]57/server.txt
  • http://45.144.255[.]57/server_p.txt

The ‘proxies.txt’ DDR hosted on 212.193.40[.]45 contains a list of 132 IP address / port pairs. The 119th line of this list includes a scrambled version of the IP address of PrivateLoader’s main C2 server (Figures 7 & 8). Prior to June, it seems that the main C2 IP address was ‘212.193.30[.]21’, however, the IP address appears to have recently changed to ‘85.202.169[.]116’. In a limited set of cases, Darktrace also observed PrivateLoader bots retrieving payload URLs from 2.56.56[.]126 and 2.56.59[.]42 (rather than from 212.193.30[.]21 or 85.202.169[.]116). These IP addresses may be hardcoded secondary C2 address which PrivateLoader bots use in cases where they are unable to retrieve the primary C2 address from Pastebin, 212.193.30[.]45 or 45.144.255[.]57 [10]. 

Figure 7: Before June, the 119th entry of the ‘proxies.txt’ file lists '30.212.21.193' -  a scrambling of the ‘212.193.30[.]21’ main C2 IP address
Figure 8: Since June, the 119th entry of the ‘proxies.txt’ file lists '169.85.116.202' - a scrambling of the '85.202.169[.]116' main C2 IP address

Once PrivateLoader bots had retrieved C2 information from either Pastebin, 45.144.225[.]57, or 212.193.30[.]45, they went on to make HTTP GET requests for ‘/base/api/statistics.php’ to either 212.193.30[.]21, 85.202.169[.]116, 2.56.56[.]126, or 2.56.59[.]42 (Figure 9). The server responded to these requests with an XOR encrypted string. The strings were encrypted using a 1-byte key [11], such as 0001101 (Figure 10). Decrypting the string revealed a URL for a BMP file hosted on Discord CDN, such as ‘hxxps://cdn.discordapp[.]com/attachments/978284851323088960/986671030670078012/PL_Client.bmp’. These encrypted URLs appear to be file download paths for the PrivateLoader core module. 

Figure 9: HTTP response from server to an HTTP GET request for '/base/api/statistics.php'
Figure 10: XOR decrypting the string with the one-byte key, 00011101, outputs a URL in CyberChef

After PrivateLoader bots retrieved the 'cdn.discordapp[.]com’ URL from 212.193.30[.]21, 85.202.169[.]116, 2.56.56[.]126, or 2.56.59[.]42, they immediately contacted Discord CDN via SSL connections in order to obtain the PrivateLoader core module. Execution of this module resulted in the bots making HTTP POST requests (with the URI string ‘/base/api/getData.php’) to the main C2 address (Figures 11 & 12). Both the data which the PrivateLoader bots sent over these HTTP POST requests and the data returned via the C2 server’s HTTP responses were heavily encrypted using a combination of password-based key derivation, base64 encoding, AES encryption, and HMAC validation [12]. 

Figure 11: The above image, taken from Darktrace's Advanced Search interface, shows a PrivateLoader bot carrying out the following steps: contact ‘hero-files[.]com’ --> contact ‘cdn.discordapp[.]com’ --> retrieve ‘/proxies.txt’ from 212.193.30[.]45 --> retrieve ‘/base/api/statistics.php’ from 212.193.30[.]21 --> contact ‘cdn.discordapp[.]com --> make HTTP POST request with the URI ‘base/api/getData.php’ to 212.193.30[.]21
Figure 12: A PCAP of the data sent via the HTTP POST (in red), and the data returned by the C2 endpoint (in blue)

These ‘/base/api/getData.php’ POST requests contain a command, a campaign name and a JSON object. The response may either contain a simple status message (such as “success”) or a JSON object containing URLs of payloads. After making these HTTP connections, PrivateLoader bots were observed downloading and executing large volumes of payloads (Figure 13), ranging from crypto-miners to infostealers (such as Mars stealer), and even to other malware downloaders (such as SmokeLoader). In some cases, bots were also seen downloading files with ‘.bmp’ extensions, such as ‘Service.bmp’, ‘Cube_WW14.bmp’, and ‘NiceProcessX64.bmp’, from 45.144.225[.]57 - the same DDR endpoint from which PrivateLoader bots retrieved main C2 information. These ‘.bmp’ payloads are likely related to the PrivateLoader service module [13]. Certain bots made follow-up HTTP POST requests (with the URI string ‘/service/communication.php’) to either 212.193.30[.]21 or 85.202.169[.]116, indicating the presence of the PrivateLoader service module, which has the purpose of establishing persistence on the device (Figure 14). 

Figure 13: The above image, taken from Darktrace's Advanced Search interface, outlines the plethora of malware payloads downloaded by a PrivateLoader bot after it made an HTTP POST request to the ‘/base/api/getData.php’ endpoint. The PrivateLoader service module is highlighted in red
Figure 14: The event log for a PrivateLoader bot, obtained from the Threat Visualiser interface, shows a device making HTTP POST requests to ‘/service/communication.php’ and connecting to the NanoPool mining pool, indicating successful execution of downloaded payloads

In several observed cases, PrivateLoader bots downloaded another malware downloader called ‘SmokeLoader’ (payloads named ‘toolspab2.exe’ and ‘toolspab3.exe’) from “Privacy Tools” endpoints [14], such as ‘privacy-tools-for-you-802[.]com’ and ‘privacy-tools-for-you-783[.]com’. These “Privacy Tools” domains are likely impersonation attempts of the legitimate ‘privacytools[.]io’ website - a website run by volunteers who advocate for data privacy [15]. 

After downloading and executing malicious payloads, PrivateLoader bots were typically seen contacting crypto-mining pools, such as NanoPool, and making HTTP POST requests to external hosts associated with SmokeLoader, such as hosts named ‘host-data-coin-11[.]com’ and ‘file-coin-host-12[.]com’ [16]. In one case, a PrivateLoader bot went on to exfiltrate data over HTTP to an external host named ‘cheapf[.]link’, which was registered on the 14th March 2022 [17]. The name of the file which the PrivateLoader bot used to exfiltrate data was ‘NOP8QIMGV3W47Y.zip’, indicating information stealing activities by Mars Stealer (Figure 15) [18]. By saving the HTTP stream as raw data and utilizing a hex editor to remove the HTTP header portions, the hex data of the ZIP file was obtained. Saving the hex data using a ‘.zip’ extension and extracting the contents, a file directory consisting of system information and Chrome and Edge browsers’ Autofill data in cleartext .txt file format could be seen (Figure 16).

Figure 15: A PCAP of a PrivateLoader bot’s HTTP POST request to cheapf[.]link, with data sent by the bot appearing to include Chrome and Edge autofill data, as well as system information
Figure 16: File directory structure and files of the ZIP archive 

When left unattended, PrivateLoader bots continued to contact C2 infrastructure in order to relay details of executed payloads and to retrieve URLs of further payloads. 

Figure 17: Timeline of the attack

Darktrace Coverage 

Most of the incidents surveyed for this article belonged to prospective customers who were trialling Darktrace with RESPOND in passive mode, and thus without the ability for autonomous intervention. However in all observed cases, Darktrace DETECT was able to provide visibility into the actions taken by PrivateLoader bots. In one case, despite the infected bot being disconnected from the client’s network, Darktrace was still able to provide visibility into the device’s network behaviour due to the client’s usage of Darktrace/Endpoint. 

If a system within an organization’s network becomes infected with PrivateLoader, it will display a range of anomalous network behaviours before it downloads and executes malicious payloads. For example, it will contact Pastebin or make HTTP requests with new and unusual user-agent strings to rare external endpoints. These network behaviours will generate some of the following alerts on the Darktrace UI:

  • Compliance / Pastebin 
  • Device / New User Agent and New IP
  • Device / New User Agent
  • Device / Three or More New User Agents
  • Anomalous Connection / New User Agent to IP Without Hostname
  • Anomalous Connection / POST to PHP on New External Host
  • Anomalous Connection / Posting HTTP to IP Without Hostname

Once the infected host obtains URLs for malware payloads from a C2 endpoint, it will likely start to download and execute large volumes of malicious files. These file downloads will usually cause Darktrace to generate some of the following alerts:

  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Numeric Exe Download
  • Anomalous File / Masqueraded File Transfer
  • Anomalous File / Multiple EXE from Rare External Locations
  • Device / Initial Breach Chain Compromise

If RESPOND is deployed in active mode, Darktrace will be able to autonomously block the download of additional malware payloads onto the target machine and the subsequent beaconing or crypto-mining activities through network inhibitors such as ‘Block matching connections’, ‘Enforce pattern of life’ and ‘Block all outgoing traffic’. The ‘Enforce pattern of life’ action results in a device only being able to make connections and data transfers which Darktrace considers normal for that device. The ‘Block all outgoing traffic’ action will cause all traffic originating from the device to be blocked. If the customer has Darktrace’s Proactive Threat Notification (PTN) service, then a breach of an Enhanced Monitoring model such as ‘Device / Initial Breach Chain Compromise’ will result in a Darktrace SOC analyst proactively notifying the customer of the suspicious activity. Below is a list of Darktrace RESPOND (Antigena) models which would be expected to breach due to PrivateLoader activity. Such models can seriously hamper attempts made by PrivateLoader bots to download malicious payloads. 

  • Antigena / Network / External Threat / Antigena Suspicious File Block
  • Antigena / Network / Significant Anomaly / Antigena Controlled and Model Breach
  • Antigena / Network / External Threat / Antigena File then New Outbound Block
  • Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block 
  • Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block

In one observed case, the infected bot began to download malicious payloads within one minute of becoming infected with PrivateLoader. Since RESPOND was correctly configured, it was able to immediately intervene by autonomously enforcing the device’s pattern of life for 2 hours and blocking all of the device’s outgoing traffic for 10 minutes (Figure 17). When malware moves at such a fast pace, the availability of autonomous response technology, which can respond immediately to detected threats, is key for the prevention of further damage.  

Figure 18: The event log for a Darktrace RESPOND (Antigena) model breach shows Darktrace RESPOND performing inhibitive actions once the PrivateLoader bot begins to download payloads

Conclusion

By investigating PrivateLoader infections over the past couple of months, Darktrace has observed PrivateLoader operators making changes to the downloader’s main C2 IP address and to the user-agent strings which the downloader uses in its C2 communications. It is relatively easy for the operators of PrivateLoader to change these superficial network-based features of the malware in order to evade detection [19]. However, once a system becomes infected with PrivateLoader, it will inevitably start to display anomalous patterns of network behaviour characteristic of the Tactics, Techniques and Procedures (TTPs) discussed in this blog.

Throughout 2022, Darktrace observed overlapping patterns of network activity within the environments of several customers, which reveal the archetypal steps of a PrivateLoader infection. Despite the changes made to PrivateLoader’s network-based features, Darktrace’s Self-Learning AI was able to continually identify infected bots, detecting every stage of an infection without relying on known indicators of compromise. When configured, RESPOND was able to immediately respond to such infections, preventing further advancement in the cyber kill chain and ultimately preventing the delivery of floods of payloads onto infected devices.

IoCs

MITRE ATT&CK Techniques Observed

References

[1], [8],[13] https://www.youtube.com/watch?v=Ldp7eESQotM  

[2] https://news.sophos.com/en-us/2021/09/01/fake-pirated-software-sites-serve-up-malware-droppers-as-a-service/

[3] https://www.researchgate.net/publication/228873118_Measuring_Pay-per Install_The_Commoditization_of_Malware_Distribution 

[4], [15] https://intel471.com/blog/privateloader-malware

[5] https://medium.com/walmartglobaltech/privateloader-to-anubis-loader-55d066a2653e 

[6], [10],[11], [12] https://www.zscaler.com/blogs/security-research/peeking-privateloader 

[7] https://www.trendmicro.com/en_us/research/22/e/netdooka-framework-distributed-via-privateloader-ppi.html

[9] https://www.gosecure.net/blog/2022/02/10/malicious-chrome-browser-extension-exposed-chromeback-leverages-silent-extension-loading/

[14] https://www.proofpoint.com/us/blog/threat-insight/malware-masquerades-privacy-tool 

[16] https://asec.ahnlab.com/en/30513/ 

[17]https://twitter.com/0xrb/status/1515956690642161669

[18] https://isc.sans.edu/forums/diary/Arkei+Variants+From+Vidar+to+Mars+Stealer/28468

[19] http://detect-respond.blogspot.com/2013/03/the-pyramid-of-pain.html

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
Sam Lister
Specialist Security Researcher
Written by
Shuh Chin Goh

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December 3, 2025

Darktrace Named as a Leader in 2025 Gartner® Magic Quadrant™ for Email Security Platforms

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Darktrace is proud to be named as a Leader in the Gartner® Magic Quadrant™ for Email Security Platforms (ESP). We believe this recognition reflects what our customers already know: our product is exceptional – and so is the way we deliver it.

In July 2025, Darktrace was named a Customers’ Choice in the Gartner® Peer Insights™ Voice of the Customer for Email Security, a distinction given to vendors who have scores that meet or exceed the market average for both axes (User Interest and Adoption, and Overall Experience). To us, both achievements are testament to the customer-first approach that has fueled our rapid growth. We feel this new distinction from Gartner validates the innovation, efficacy, and customer-centric delivery that set Darktrace apart.

A Gartner Magic Quadrant is a culmination of research in a specific market, giving you a wide-angle view of the relative positions of the market’s competitors. CIOs and CISOs can use this research to make informed decisions about which email security platform can best accomplish their goals. We encourage our customers to read the full report to get the complete picture.

This acknowledgement follows the recent recognition of Darktrace / NETWORK, also designated a Leader in the Gartner Magic Quadrant for Network Detection & Response and named the only Customers’ Choice in its category.

Why do we believe Darktrace is leading in the email security market?

Our relentless innovation which drives proven results  

At Darktrace we continue to push the frontier of email security, with industry-first AI-native detection and response capabilities that go beyond traditional SEG approaches. How do we do it?

  • With a proven approach that gets results. Darktrace’s unique business-centric anomaly detection catches advanced phishing, supply chain compromises, and BEC attacks – detecting them on average 13 days earlier than attack-centric solutions. That’s why 75% of our customers have removed their SEG and now rely on their native email security provider combined with Darktrace.
  • By offering comprehensive protection beyond the inbox. Darktrace / EMAIL goes further than traditional inbound filtering, delivering account and messaging protection, DLP, and DMARC capabilities, ensuring best-in-class security across inbound, outbound, and domain protection scenarios.  
  • Continuous innovation. We are ranked second highest in the Gartner Critical Capabilities research for core email security function, likely thanks to our product strategy and rapid pace of innovation. We’ve release major capabilities twice a year for nearly five years, including advanced AI models and expanded coverage for collaboration platforms.

We deliver exceptional customer experiences worldwide

Darktrace’s leadership isn’t just about excelling in technology, it’s about delivering an outstanding experience that customers value. Let’s dig into what makes our customers tick.

  • Proven loyalty from our base. Recognition from Gartner Peer Insights as a Customers’ Choice, combined with a 4.8-star rating (based on 340 reviews as of November 2025), demonstrates for us the trust of thousands of organizations worldwide, not just the analysts.  
  • Customer-first support. Darktrace goes beyond ticket-only models with dedicated account teams and award-winning service, backed by significant headcount growth in technical support and analytics roles over the past year.
  • Local expertise. With offices spanning continents, Darktrace is able to provide regional language support and tailored engagement from teams on the ground, ensuring personalized service and a human-first experience.

Darktrace enhances security stacks with a partner-first architecture

There are plenty of tools out there than encourage a siloed approach. Darktrace / EMAIL plays well with others, enhancing your native security provider and allowing you to slim down your stack. It’s designed to set you up for future growth, with:

  • A best-in-breed platform approach. Natively built on Self-Learning AI, Darktrace / EMAIL delivers deep integration with our / NETWORK, / IDENTITY, and / CLOUD products as part of a unified platforms – that enables and enhances comprehensive enterprise-wise security.
  • Optimized workflows. Darktrace integrates tightly with an extended ecosystem of security tools – including a strategic partnership with Microsoft enabling unified threat response and quarantine capabilities – bringing constant innovation to all of your SOC workflows.  
  • A channel-first strategy. Darktrace is making significant investments in partner-driven architectures, enabling integrated ecosystems that deliver maximum value and future-ready security for our customers.

Analyst recognized. Customer approved.  

Darktrace / EMAIL is not just another inbound email security tool; it’s an advanced email security platform trusted by thousands of users to protect them against advanced phishing, messaging, and account-level attacks.  

As a Leader, we believe we owe our positioning to our customers and partners for supporting our growth. In the upcoming years we will continue to innovate to serve the organizations who depend on Darktrace for threat protection.  

To learn more about Darktrace’s position as a Leader, view a complimentary copy of the Magic Quadrant report, register for the Darktrace Innovation Webinar on 9 December, 2025, or simply request a demo.

Gartner, Gartner® Magic Quadrant™ for Email Security Platforms, Max Taggett, Nikul Patel, 3 December 2025

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 is a registered trademark of Gartner, Inc. and/or its affiliates and is used herein with permission. All rights reserved.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Darktrace.

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Carlos Gray
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December 2, 2025

Protecting the Experience: How a global hospitality brand stays resilient with Darktrace

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For the Global Chief Technology Officer (CTO) of a leading experiential leisure provider, security is mission critical to protecting a business built on reputation, digital innovation, and guest experience. The company operates large-scale immersive venues across the UK and US, blending activity-driven hospitality with premium dining and vibrant spaces designed for hundreds of guests. With a lean, centrally managed IT team responsible for securing locations worldwide, the challenge is balancing robust cybersecurity with operational efficiency and customer experience.

Brand buzz attracts attention – and attacks

Mid-sized, fast-growing hospitality organizations face a unique risk profile. When systems go down in a venue, the impact is immediate: hundreds of disrupted guest experiences, lost revenue during peak hours, and potential long-term reputation damage. Each time the organization opened a new venue, the surge of marketing buzz attracted attention in local markets and waves of sophisticated cyberattacks, including:

Phishing campaigns leveraging brand momentum to lure employees into clicking on malicious links.

AI-enhanced impersonation using advanced techniques to create AI-generated video calls and deep-researched, contextualized emails  

Fake domains targeting leadership with AI-generated messages that contained insider context gleaned from public information.

“Our endpoint security and antivirus tools were powerless against these sophisticated AI-powered campaigns. We didn’t want to manage incidents anymore. We wanted to prevent them from ever happening.”  - Global CTO

Proactive, preventative security with Darktrace AI

The company’s cybersecurity vision was clear: “Proactive, preventative – that was our mandate,” said the CTO. With a lean and busy IT group, the business evaluated several security solutions using deep-dive workshops. Darktrace proved the best fit for supporting the organization’s proactive mindset, offering:

  • Autonomy without added headcount: Darktrace provided powerful AI-driven detection and autonomous response functions with minimal manual oversight required.
  • Modular adoption: The company could start with core email and network protection and expand into cloud and endpoint coverage, aligning spend with growth.
  • Partnership and responsiveness: “We wanted people we trust, respect, and know will show up when we need them. Darktrace did just that,” said the CTO.
  • Affordability at scale: Darktrace offered reasonable upfront costs plus predictable, sustainable economics as the company and IT infrastructure expanded.  

“The combination of AI capabilities, a scalable model, and a strong engagement team tipped the balance in Darktrace’s favor, and we have not been disappointed,” said the CTO.

Phased deployment builds trust

To minimize disruption to critical hospitality systems like global Point of Sales (POS) terminals and Audio-Visual (AV) infrastructure, deployment was phased:

  1. Observation and human-led response: Initially, Darktrace was deployed in detection-only mode. Alerts were manually reviewed.
  2. Incremental autonomous response: Darktrace Autonomous Response was enabled on select models, taking action on low-risk scenarios. Higher-risk subnets and devices remained under human control.
  3. Full autonomous coverage: With tuning and reinforcement, autonomous response was expanded across domains, trusted to take decisive action in real time. Analysts retained the ability to review and contextualize incidents.

“Darktrace managed the rollout through detailed, professional, and responsive project management – ensuring a smooth, successful adoption and creating a standardized cybersecurity playbook for future venue launches,” said the CTO.  

AI delivers the outcomes that matter  

Measurable efficiency replaces endless alerts

Darktrace autonomous response significantly decreased false alerts and noise. “If it’s quiet, we’re confident there isn’t a problem,” said the CTO. Within six months, Darktrace conducted 3,599 total investigations, detected and contained 320 incidents indicative of an attack, resolved 91% of those events autonomously, and escalated only 9% to human analysts. The efficiency gains were enormous, saving analysts 740 hours on investigations within a single month.  

Precision AI turns inbox chaos into calm

Darktrace Self-Learning AI modeled sender/recipient norms, content/linguistic baselines, and communication patterns unique to the organization’s launch cadence, resulting in:

  • Automated holds and neutralizations of anomalous executive-style messages
  • Rapid detection of novel templates and tone shifts that deviated from the organization’s lived email graph, even when indicators were not yet on any feed
  • Downstream reduction in help-desk escalations tied to suspicious email

Full visibility fuels real-time response

Darktrace gives IT direct visibility without extra licensing, and it surfaces ground truth across every venue, including:

  • Device geolocation and placement drift: Darktrace exposed devices and users operating outside approved zones, prompting new segmentation and access-control policies.
  • Guest Wi-Fi realities: Darktrace AI uncovered high-risk activity on guest networks, like crypto-mining and dark-web traffic, driving stricter VLAN separation and access hygiene.
  • Lateral-movement containment: Autonomous response fenced suspicious activity in real time, buying time for human investigation while keeping POS and AV systems unaffected.

Smarter endpoints for a smarter network

Endpoints once relied on static agents effective only against known signatures. Darktrace’s behavioral models now detect subtle anomalies at the endpoint process level that EDRs often miss, such as misuse of legitimate applications (commonly used in living-off-the-land attacks), unapproved application usage and policy violations. This increases the accuracy and fidelity of network-based investigations by adding endpoint process context alongside existing EDR alerts.

Autonomous response for continuous compliance

Across PCI, GDPR, and cross-border privacy obligations, Darktrace’s native evidencing is helping the team demonstrate control rather than merely assert it:

  • Asset and flow awareness: Knowing “what is where” and “who talks to what” underpins PCI scoping and data-flow diagrams.
  • Layered safeguards: Showing autonomous prevention, network segmentation, and rapid containment supports risk registers and control attestations.
  • Audit-ready artifacts: Investigations and autonomous actions produce artifacts that “tick the box” without additional tooling.  

Defining the next era of resilience with AI

With rapid global expansion underway, the company is using its cybersecurity playbook to streamline and secure future venue launches. In the near term, IT is focused on strengthening prevention, using Darktrace insights to guide new policy updates and infrastructure changes like imposing stricter guest-network posture and refining venue device baselines.

For tech leaders charting their path to proactive cyber defense, the CTO stresses success won’t come from sidestepping AI, but from turning it into a core capability.

“AI isn’t optional – it’s operational. The real risk to your business is trying to out-scale automated adversaries with human speed alone. When applied to the right use case, AI becomes a catalyst for efficiency, resilience, and business growth.” - Global CTO
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