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.

Written by

Sam Lister

Specialist Security Researcher

Written by

Shuh Chin Goh

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

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

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

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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

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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 119^th 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 14^th 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.

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

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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

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Written by

Sam Lister

Specialist Security Researcher

Written by

Shuh Chin Goh

Inside the SOC

Written by

Sam Lister

Specialist Security Researcher

Written by

Shuh Chin Goh

Senior Product Marketing Manager, Email

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November 28, 2025

From Amazon to Louis Vuitton: How Darktrace Detects Black Friday Phishing Attacks

Why Black Friday Drives a Surge in Phishing Attacks

In recent years, Black Friday has shifted from a single day of online retail sales and discounts to an extended ‘Black Friday Week’, often preceded by weeks of online hype. During this period, consumers are inundated with promotional emails and marketing campaigns as legitimate retailers compete for attention.

Unsurprisingly, this surge in legitimate communications creates an ideal environment for threat actors to launch targeted phishing campaigns designed to mimic legitimate retail emails. These campaigns often employ social engineering techniques that exploit urgency, exclusivity, and consumer trust in well-known brands, tactics designed to entice recipients into opening emails and clicking on malicious links.

Additionally, given the seasonal nature of Black Friday and the ever-changing habits of consumers, attackers adopt new tactics and register fresh domains each year, rather than reusing domains previously flagged as spam or phishing endpoints. While this may pose a challenge for traditional email security tools, it presents no such difficulty for Darktrace / EMAIL and its anomaly-based approach.

In the days and weeks leading up to ‘Black Friday’, Darktrace observed a spike in sophisticated phishing campaigns targeting consumers, demonstrating how attackers combine phycological manipulation with technical evasion to bypass basic security checks during this high-traffic period. This blog showcases several notable examples of highly convincing phishing emails detected and contained by Darktrace / EMAIL in mid to late November 2025.

Darktrace’s Black Friday Detections

Brand Impersonation: Deal Watchdogs’ Amazon Deals

The impersonation major online retailers has become a common tactic in retail-focused attacks, none more so than Amazon, which ranked as the fourth most impersonated brand in 2024, only behind Microsoft, Apple, Google, and Facebook [1]. Darktrace’s own research found Amazon to be the most mimicked brand, making up 80% of phishing attacks in its analysis of global consumer brands.

When faced with an email that appears to come from a trusted sender like Amazon, recipients are far more likely to engage, increasing the success rate of these phishing campaigns.

In one case observed on November 16, Darktrace detected an email with the subject line “NOW LIVE: Amazon’s Best Early Black Friday Deals on Gadgets Under $60”. The email was sent to a customer by the sender ‘Deal Watchdogs’, in what appeared to be an attempt to masquerade as a legitimate discount-finding platform. No evidence indicated that the company was legitimate. In fact, the threat actor made no attempt to create a convincing name, and the domain appeared to be generated by a domain generation algorithm (DGA), as shown in Figure 2.

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Although the email was sent by ‘Deal Watchdogs’, it attempted to impersonate Amazon by featuring realistic branding, including the Amazon logo and a shade of orange similar to that used by them for the ‘CLICK HERE’ button and headline text.

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Figure 1: The contents of the email observed by Darktrace, featuring authentic-looking Amazon branding.

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Darktrace identified that the email, marked as urgent by the sender, contained a suspicious link to a Google storage endpoint (storage.googleapis[.]com), which had been hidden by the text “CLICK HERE”. If clicked, the link could have led to a credential harvester or served as a delivery vector for a malicious payload hosted on the Google storage platform.

Fortunately, Darktrace immediately identified the suspicious nature of this email and held it before delivery, preventing recipients from ever receiving or interacting with the malicious content.

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Figure 2: Darktrace / EMAIL’s detection of the malicious phishing email sent to a customer.

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Around the same time, Darktrace detected a similar email attempting to spoof Amazon on another customer’s network with the subject line “Our 10 Favorite Deals on Amazon That Started Today”, also sent by ‘Deal Watchdogs,’ suggesting a broader campaign.

Analysis revealed that this email originated from the domain petplatz[.]com, a fake marketing domain previously linked to spam activity according to open-source intelligence (OSINT) [2].

Brand Impersonation: Louis Vuitton

A few days later, on November 20, Darktrace / EMAIL detected a phishing email attempting to impersonate the luxury fashion brand Louis Vuitton. At first glance, the email, sent under the name ‘Louis Vuitton’ and titled “[Black Friday 2025] Discover Your New Favorite Louis Vuitton Bag – Elegance Starts Here”, appeared to be a legitimate Black Friday promotion. However, Darktrace’s analysis uncovered several red flags indicating a elaborate brand impersonation attempt.

The email was not sent by Louis Vuitton but by rskkqxyu@bookaaatop[.]ru, a Russia-based domain never before observed on the customer’s network. Darktrace flagged this as suspicious, noting that .ru domains were highly unusual for this recipient’s environment, further reinforcing the likelihood of malicious intent. Subsequent analysis revealed that the domain had only recently registered and was flagged as malicious by multiple OSINT sources [3].

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Figure 3: Darktrace / EMAIL’s detection of the malicious email attempting to spoofLouis Vuitton, originating from a suspicious Russia-based domain.

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Darktrace further noted that the email contained a highly suspicious link hidden behind the text “View Collection” and “Unsubscribe,” ensuring that any interaction, whether visiting the supposed ‘handbag store’ or attempting to opt out of marketing emails, would direct recipients to the same endpoint. The link resolved to xn--80aaae9btead2a[.]xn--p1ai (топааабоок[.]рф), a domain confirmed as malicious by multiple OSINT sources [4]. At the time of analysis, the domain was inaccessible, likely due to takedown efforts or the short-lived nature of the campaign.

Darktrace / EMAIL blocked this email before it reached customer inboxes, preventing recipients from interacting with the malicious content and averting any disruption.

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Figure 4: The suspicious domain linked in the Louis Vuitton phishing email, now defunct.

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Too good to be true?

Aside from spoofing well-known brands, threat actors frequently lure consumers with “too good to be true” luxury offers, a trend Darktrace observed in multiple cases throughout November.

In one instance, Darktrace identified an email with the subject line “[Black Friday 2025] Luxury Watches Starting at $250.” Emails contained a malicious phishing link, hidden behind text like “Rolex Starting from $250”, “Shop Now”, and “Unsubscribe”.

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Figure 5: Example of a phishing email detected by Darktrace, containing malicious links concealed behind seemingly innocuous text.

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Similarly to the Louis Vuitton email campaign described above, this malicious link led to a .ru domain (hxxps://x.wwwtopsalebooks[.]ru/.../d65fg4er[.]html), which had been flagged as malicious by multiple sources [5].

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Figure 6: Darktrace / EMAIL’s detection of a malicious email promoting a fake luxury watch store, which was successfully held from recipient inboxes.

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If accessed, this domain would redirect users to luxy-rox[.]com, a recently created domain (15 days old at the time of writing) that has also been flagged as malicious by OSINT sources [6]. When visited, the redirect domain displayed a convincing storefront advertising high-end watches at heavily discounted prices.

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Figure 7: The fake storefront presented upon visiting the redirectdomain, luxy-rox[.]com.

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Although the true intent of this domain could not be confirmed, it was likely a scam site or a credential-harvesting operation, as users were required to create an account to complete a purchase. As of the time or writing, the domain in no longer accessible .

This email illustrates a layered evasion tactic: attackers employed multiple domains, rapid domain registration, and concealed redirects to bypass detection. By leveraging luxury branding and urgency-driven discounts, the campaign sought to exploit seasonal shopping behaviors and entice victims into clicking.

Staying Protected During Seasonal Retail Scams

The investigation into these Black Friday-themed phishing emails highlights a clear trend: attackers are exploiting seasonal shopping events with highly convincing campaigns. Common tactics observed include brand impersonation (Amazon, Louis Vuitton, luxury watch brands), urgency-driven subject lines, and hidden malicious links often hosted on newly registered domains or cloud services.

These campaigns frequently use redirect chains, short-lived infrastructure, and psychological hooks like exclusivity and luxury appeal to bypass user scepticism and security filters. Organizations should remain vigilant during retail-heavy periods, reinforcing user awareness training, link inspection practices, and anomaly-based detection to mitigate these evolving threats.

Credit to Ryan Traill (Analyst Content Lead) and Owen Finn (Cyber Analyst)

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Appendices

References

1. https://keepnetlabs.com/blog/top-5-most-spoofed-brands-in-2024

2. https://www.virustotal.com/gui/domain/petplatz.com

3. https://www.virustotal.com/gui/domain/bookaaatop.ru

4. https://www.virustotal.com/gui/domain/xn--80aaae9btead2a.xn--p1ai

5. https://www.virustotal.com/gui/url/e2b868a74531cd779d8f4a0e1e610ec7f4efae7c29d8b8ab32c7a6740d770897?nocache=1

6. https://www.virustotal.com/gui/domain/luxy-rox.com

Indicators of Compromise (IoCs)

IoC – Type – Description + Confidence

petplatz[.]com – Hostname – Spam domain

bookaaatop[.]ru – Hostname – Malicious Domain

xn--80aaae9btead2a[.]xn--p1ai (топааабоок[.]рф) – Hostname - Malicious Domain

hxxps://x.wwwtopsalebooks[.]ru/.../d65fg4er[.]html) – URL – Malicious Domain

luxy-rox[.]com – Hostname - Malicious Domain

MITRE ATT&CK Mapping

Tactic – Technique – Sub-Technique

Initial Access - Phishing – (T1566)

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About the author

Ryan Traill

Analyst Content Lead

Blog

Email

November 28, 2025

Phishing attacks surge by 620% in the lead-up to Black Friday

Black Friday deals are rolling in, and so are the phishing scams

As the world gears up for Black Friday and the festive shopping season, inboxes flood with deals and delivery notifications, creating a perfect storm for phishing attackers to strike.

Contributing to the confusion, legitimate brands often rely on similar urgency cues, limited-time offers, and high-volume email campaigns used by scammers, blurring the lines between real deals and malicious lookalikes. While security teams remain extra vigilant during this period, the risk of phishing emails slipping in unnoticed remains high, as does the risk of individuals clicking to take advantage of holiday shopping offers.

Analysis conducted by Darktrace’s global analyst team revealed that phishing attacks taking advantage of Black Friday jumped by 620% in the weeks leading up to the holiday weekend, with the volume of phishing attacks expected to jump a further 20-30% during Black Friday week itself.

First observation: Brand impersonation

Brand impersonation was one of the techniques that stood out, with threat actors creating convincing emails – likely assisted by generative AI – purporting to be from household brands including special offers and promotions.

The week before Thanksgiving (15-21 November) saw 201% more phishing attempts mimicking US retailers than the same week in October, as attackers sought to profit off the back of the busy holiday shopping season. It’s not just about volume, either – attackers are spoofing brands people love to shop with during the holidays. Fake emails that look like they’re from well-known retailers like Macy’s, Walmart, and Target were up by 54% just across last week¹. Even so, Amazon is the most impersonated brand, making up 80% of phishing attempts in Darktrace’s analysis of global consumer brands like Apple, Alibaba and Netflix.

While major brands invest heavily in protecting their organizations and customers from cyber-attacks, impersonation is a complicated area as it falls outside of a brand’s legitimate infrastructure and security remit. Retail brands have a huge attack surface, creating plenty of vectors for impersonation, while fake domains, social profiles, and promotional messages can be created quickly and at scale.

Second observation: Fake marketing domains

One prominent Black Friday phishing campaign observed landing in many inboxes uses fake domains purporting to be from marketing sites, like “Pal.PetPlatz.com” and “Epicbrandmarketing.com”.

These emails tend to operate in one of two ways. Some contain “deals” for luxury items such as Rolex watches or Louis Vuitton handbags, designed to tempt readers into clicking. However, the majority are tied to a made-up brand called Deal Watchdogs, which promotes “can’t-miss” Amazon Black Friday offers – designed to lure readers into acting fast to secure legitimate time-sensitive deals. Any user who clicks a link is taken to a fake Amazon website where they are tricked into inputting sensitive data and payment details.

Third observation: The impact of generative AI

The biggest shift seen in phishing in recent years is how much more convincing scam emails are thanks to generative AI. 27% of phishing emails observed by Darktrace in 2024 contained over 1,000 characters², suggesting LLM use in their creation. Tools like ChatGPT and Gemini lower the barrier to entry for cyber-criminals, allowing them to create phishing campaigns that humans find it difficult to spot.

Let’s take a look at a dummy email created by a member of our team without a technical background to illustrate how easy it is to spin up an email that looks and feels like a genuine Black Friday offer. With two prompts, generative AI created a convincing “sale” email that could easily pass as the real thing without requiring any technical skill.

A fake Black Friday deal email created using generative AI, with only two prompts. The image has been pixelated for marketing purposes.

Anyone can now create convincing brand spoofs, and they can do it at scale. That makes it even more important for email users to pause, check the sender, and think before they click.

Why phishing scams hurt consumers and brands

These spoofs don’t just drain shoppers’ bank accounts and grab their personal data. They erode trust, drive people away from real sites, and ultimately hurt brands’ sales. And the fakes keep getting sharper, more convincing, and harder to spot.

Though brands should implement email controls like DMARC to help reduce spoofing, they can’t stop attackers from registering new look-alike domains or using other channels. At the end of the day, human users remain vulnerable to well-crafted scams, particularly when the element of trust from a well-known brand is involved. And while brands can’t prevent all impersonation scams, the fallout can still erode consumer trust and damage their reputation.

In order to limit the impact of these scams, two things need to work together: better education so consumers know when to slow down and look twice, and email security (plus a DMARC solution and an attack surface management tool) that can adapt faster than the attackers – protecting both shoppers and the brands they love.

Tips to stay safe while Black Friday shopping online

On top of retailers implementing robust email security, there are some simple steps shoppers can take to stay safer while shopping this holiday season.

Check every website (twice). Scammers make tiny changes you can barely see. They’ll switch Walmart.com for Waimart.com and most people won’t notice. If something looks even slightly off, check the URL carefully and, if you’re unsure, search for reviews of that exact address.
Santa keeps the real gifts in the workshop. Don’t just click through from sales emails. Use them as a prompt to log in directly to the official app or site, where any genuine notifications will appear.
Look at the payment options. Real retailers usually offer a handful of recognizable ways to pay; if a site pushes only odd methods or upfront transfers, don’t use it.
Be skeptical of Christmas miracles. If a deal on a big-ticket item looks too good to be true, it usually is.
Leave the rushing to the elves. Countdown timers and “last chance” banners are designed to make you click before you think. Take a breath, double-check the sender and the site, and then decide whether to buy.

Email security you can trust this holiday season

The heightened holiday shopping season shines a spotlight on an uncomfortable reality: now that phishing emails are harder than ever to distinguish from legitimate brand communication, traditional spam filters and Secure Email Gateways struggle to keep up. In order to protect against communication-based attacks, organizations require email security that can evaluate the full context of an email – not just surface-level indicators – and stop malicious messages before they reach inboxes.

Darktrace / EMAIL uses Self-Learning AI to understand the behavior and patterns of every user, so it can detect the subtle inconsistencies that reveal a message isn’t genuine, from shifts in tone and writing style to unexpected links, unfamiliar senders, or off-brand visual cues. By identifying these anomalies automatically – and either holding them entirely, or neutralizing malicious elements – it removes the burden from employees to catch near-imperceptible errors and reinforces protection for the entire organization, from staff to customers to brand reputation.

Join our live broadcast on 9 December, where Darktrace will reveal new, industry-first innovations in email security keeping organizations safe this Christmas – from DMARC to DLP. Sign up to the live launch event now.

For a deeper dive into some specific Black Friday phishing campaigns surfaced by the Darktrace threat analysis team, read the follow-up blog here.

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A note on methodology

Insights derive from anonymous live data across 6,500 customers protected by Darktrace / EMAIL. Darktrace created models tracking verified phishing emails that:

Explicitly mentioned Black Friday
Impersonated US retailers popular during the holiday season (Walmart, Target, Best Buy, Macy's, Old Navy, 1800-Flowers)
Impersonated major global brands (Apple, eBay, Netflix, Alibaba and PayPal)

Tracking ran from October 1 to November 21.

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References

[1] Based on live tracking of phishing emails spoofing Walmart, Target, Best Buy, Macy's, Old Navy, 1800-Flowers across email inboxes protected by Darktrace.  November 15 – November 21, 2025

[2] Based on analysis of 30.4 million phishing emails between December 21, 2023, and December 18, 2024. Darktrace Annual Threat Report 2024.

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About the author

Carlos Gray

Senior Product Marketing Manager, Email

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MITRE ATT&CK Techniques Observed

References

From Amazon to Louis Vuitton: How Darktrace Detects Black Friday Phishing Attacks

Phishing attacks surge by 620% in the lead-up to Black Friday

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Blog

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From Amazon to Louis Vuitton: How Darktrace Detects Black Friday Phishing Attacks

Why Black Friday Drives a Surge in Phishing Attacks

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Brand Impersonation: Deal Watchdogs’ Amazon Deals

Brand Impersonation: Louis Vuitton

Too good to be true?

Staying Protected During Seasonal Retail Scams

Appendices

Blog

Email

November 28, 2025

Phishing attacks surge by 620% in the lead-up to Black Friday

Black Friday deals are rolling in, and so are the phishing scams

First observation: Brand impersonation

Second observation: Fake marketing domains

Third observation: The impact of generative AI

Why phishing scams hurt consumers and brands

Tips to stay safe while Black Friday shopping online

Email security you can trust this holiday season

A note on methodology

References