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November 27, 2025

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

Darktrace detected a surge in Black Friday phishing campaigns exploiting brand impersonation, urgency-driven language, and malicious redirects. Attackers leveraged newly registered domains and social engineering to mimic Amazon, Louis Vuitton, and luxury watch retailers. Learn how layered evasion tactics bypassed security and how Darktrace / EMAIL neutralized these threats.
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
Ryan Traill
Analyst Content Lead
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27
Nov 2025

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.

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.

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

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.

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

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].

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

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.

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

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”.

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

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].

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

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.

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

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)

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)  

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
Ryan Traill
Analyst Content Lead

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May 20, 2026

Prompt Security in Enterprise AI: Strengths, Weaknesses, and Common Approaches

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How enterprise AI Agents are changing the risk landscape  

Generative AI Agents are changing the way work gets done inside enterprises, and subsequently how security risks may emerge. Organizations have quickly realized that providing these agents with wider access to tooling, internal information, and granting permissions for the agent to perform autonomous actions can greatly increase the efficiency of employee workflows.

Early deployments of Generative AI systems led many organizations to scope individual components as self-contained applications: a chat interface, a model, and a prompt, with guardrails placed at the boundary. Research from Gartner has shown that while the volume and scope of Agentic AI deployments in enterprise environments is rapidly accelerating, many of the mechanisms required to manage risk, trust, and cost are still maturing.

The issue now resides on whether an agent can be influenced, misdirected, or manipulated in ways that leads to unsafe behavior across a broader system.

Why prompt security matters in enterprise AI

Prompt security matters in enterprise AI because prompts are the primary way users and systems interact with Agentic AI models, making them one of the earliest and most visible indicators of how these systems are being used and where risk may emerge.

For security teams, prompt monitoring is a logical starting point for understanding enterprise AI usage, providing insight into what types of questions are being asked and tasks are being given to AI Agents, how these systems are being guided, and whether interactions align with expected behavior. Complete prompt security takes this one step further, filtering out or blocking sensitive or dangerous content to prevent risks like prompt injection and data leakage.

However, visibility only at the prompt layer can create a false sense of security. Prompts show what was asked, but not always why it was asked, or what downstream actions were triggered by the agent across connected systems, data sources, or applications.

What prompt security reveals  

The primary function of prompt security is to minimize risks associated with generative and agentic AI use, but monitoring and analysis of prompts can also grant insight into use cases for particular agents and model. With comprehensive prompt security, security teams should be able to answer the following questions for each prompt:

  • What task was the user attempting to complete?
  • What data was included in the request, and was any of the data high-risk or confidential?
  • Was the interaction high-risk, potentially malicious, or in violation of company policy?
  • Was the prompt anomalous (in comparison to previous prompts sent to the agent / model)?

Improving visibility at this layer is a necessary first step, allowing organizations to establish a baseline for how AI systems are being used and where potential risks may exist.  

Prompt security alone does not provide a complete view of risk. Further data is needed to understand how the prompt is interpreted, how context is applied, what autonomous actions the agent takes (if any), or what downstream systems are affected. Understanding the outcome of a query is just as important for complete prompt security as understanding the input prompt itself – for example, a perfectly normal, low-risk prompt may inadvertently result in an agent taking a high-risk action.

Comprehensive AI security systems like Darktrace / SECURE AI can monitor and analyze both the prompt submitted to a Generative AI system, as well as the responses and chain-of-thought of the system, providing greater insight into the behavior of the system. Darktrace / SECURE AI builds on the core Darktrace methodology, learning the expected behaviors of your organization and identifying deviations from the expected pattern of life.

How organizations address prompt security today

As prompt-level visibility has become a focus, a range of approaches have emerged to make this activity more observable and controllable. Various monitoring and logging tools aim to capture prompt inputs to be analyzed after the fact.  

Input validation and filtering systems attempt to intervene earlier, inspecting prompts before they reach the model. These controls look for known jailbreak patterns, language indicative of adversarial attacks, or ambiguous instructions which could push the system off course.

Importantly, for a prompt security solution to be accurate and effective, prompts must be continually observed and governed, rather than treated as a point-in-time snapshot.  

Where prompt security breaks down in real environments

In more complex environments, especially those involving multiple agents or extensive tool use, AI security becomes harder to define and control.

Agent-to-Agent communications can be harder to monitor and trace as these happen without direct user interaction. Communication between agents can create routes for potential context leakage between agents, unintentional privilege escalation, or even data leakage from a higher privileged agent to a lower privileged one.

Risk is shaped not just by what is asked, but by the conditions in which that prompt operates and the actions an agent takes. Controls at the orchestration layer are starting to reflect this reality. Techniques such as context isolation, scoped memory, and role-based boundaries aim to limit how far a prompt’s influence can extend.  

Furthermore, Shadow AI usage can be difficult to monitor. AI systems that are deployed outside of formal governance structures and Generative AI systems hosted on unknown endpoints can fly under the radar and can go unseen by monitoring tools, leaving a critical opening where adversarial prompts may go undetected. Darktrace / SECURE AI features comprehensive detection of Shadow AI usage, helping organizations identify potential risk areas.

How prompt security fits in a broader AI risk model

Prompt security is an important starting point, but it is not a complete security strategy. As AI systems become more integrated into enterprise environments, the risks extend to what resources the system can access, how it interprets context, and what actions it is allowed to take across connected tools and workflows.

This creates a gap between visibility and control. Prompt security alone allows security teams to observe prompt activity but falls short of creating a clear understanding of how that activity translates into real-world impact across the organization.

Closing that gap requires a broader approach, one that connects signals across human and AI agent identities, SaaS, cloud, and endpoint environments. It means understanding not just how an AI system is being used, but how that usage interacts with the rest of the digital estate.

Prompt security, in that sense, is less of a standalone solution and more of an entry point into a larger problem: securing AI across the enterprise as a whole.

Explore how Darktrace / SECURE AI brings prompt security to enterprises

Darktrace brings more than a decade of AI expertise, built on an enterprise‑wide platform designed to operate in and understand the behaviors of the complex, ambiguous environments where today’s AI now lives. With Darktrace / SECURE AI, enterprises can safely adopt, manage, monitor, and build AI within their business.  

Learn about Darktrace / SECURE AI here.

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Jamie Bali
Technical Author (AI) Developer

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May 20, 2026

State of AI Cybersecurity 2026: 77% of security stacks include AI, but trust is lagging

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Findings in this blog are taken from Darktrace’s annual State of AI Cybersecurity Report 2026.

AI is a contributing member of nearly every modern cybersecurity team. As we discussed earlier in this blog series, rapid AI adoption is expanding the attack surface in ways that security professionals have never before experienced while also empowering attackers to operate at unprecedented speed and scale. It’s only logical that defenders are harnessing the power of AI to fight back.

After all, AI can help cybersecurity teams spot the subtle signs of novel threats before humans can, investigate events more quickly and thoroughly, and automate response. But although AI has been widely adopted, this technology is also frequently misunderstood, and occasionally viewed with suspicion.

For CISOs, the cybersecurity marketplace can be noisy. Making sense of competing vendors’ claims to distinguish the solutions that truly deliver on AI’s full potential from those that do not isn’t always easy. Without a nuanced understanding of the different types of AI used across the cybersecurity stack, it is difficult to make informed decisions about which vendors to work with or how to gain the most value from their solutions. Many security leaders are turning to Managed Security Service Providers (MSSPs) for guidance and support.

The right kinds of AI in the right places?

Back in 2024, when we first conducted this annual survey, more than a quarter of respondents were only vaguely familiar with generative AI or hadn’t heard of it at all. Today, GenAI plays a role in 77% of security stacks. This percentage marks a rapid increase in both awareness and adoption over a relatively short period of time.

According to security professionals, different types of AI are widely integrated into cybersecurity tooling:

  • 67% report that their organization’s security stack uses supervised machine learning
  • 67% report that theirs uses agentic AI
  • 58% report that theirs uses natural language processing (NLP)
  • 35% report that theirs uses unsupervised machine learning

But their responses suggest that organizations aren’t always using the most valuable types of AI for the most relevant use cases.

Despite all the recent attention AI has gotten, supervised machine learning isn’t new. Cybersecurity vendors have been experimenting with models trained on hand-labeled datasets for over a decade. These systems are fed large numbers of examples of malicious activity – for instance, strains of ransomware – and use these examples to generalize common indicators of maliciousness – such as the TTPs of multiple known ransomware strains – so that the models can identify similar attacks in the future. This approach is more effective than signature-based detection, since it isn’t tied to an individual byte sequence or file hash. However, supervised machine learning models can miss patterns or features outside the training data set. When adversarial behavior shifts, these systems can’t easily pivot.

Unsupervised machine learning, by contrast, can identify key patterns and trends in unlabeled data without human input. This enables it to classify information independently and detect anomalies without needing to be taught about past threats. Unsupervised learning can continuously learn about an environment and adapt in real time.

One key distinction between supervised and unsupervised machine learning is that supervised learning algorithms require periodic updating and re-training, whereas unsupervised machine learning trains itself while it works.

The question of trust

Even as AI moves into the mainstream, security professionals are eyeing it with a mix of enthusiasm and caution. Although 89% say they have good visibility into the reasoning behind AI-generated outputs, 74% are limiting AI’s ability to take autonomous action in their SOC until explainability improves. 86% do not allow AI to take even small remediation actions without human oversight.

This model, commonly known as “human in the loop,” is currently the norm across the industry. It seems like a best-of-both-worlds approach that allows teams to experience the benefits of AI-accelerated response without relinquishing control – or needing to trust an AI system.

Keeping humans somewhat in the loop is essential for getting the best out of AI. Analysts will always need to review alerts, make judgement calls, and set guardrails for AI's behavior. Their input helps AI models better understand what “normal” looks like, improving their accuracy over time.

However, relying on human confirmation has real costs – it delays response, increases the cognitive burden analysts must bear, and creates potential coverage gaps when security teams are overwhelmed or unavailable. The traditional model, in which humans monitor and act on every alert, is no longer workable at scale.

If organizations depend too heavily on in-the-loop humans, they risk recreating the very problem AI is meant to solve: backlogs of alerts waiting for analyst review. Removing the human from the loop can buy back valuable time, which analysts can then invest in building a proactive security posture. They can also focus more closely on the most critical incidents, where human attention is truly needed.

Allowing AI to operate autonomously requires trust in its decision-making. This trust can be built gradually over time, with autonomous operations expanding as trust grows. But it also requires knowledge and understanding of AI — what it is, how it works, and how best to deploy it at enterprise scale.

Looking for help in all the right places

To gain access to these capabilities in a way that’s efficient and scalable, growing numbers of security leaders are looking for outsourced support. In fact, 85% of security professionals prefer to obtain new SOC capabilities in the form of a managed service.

This makes sense: Managed Security Service Providers (MSSPs) can deliver deep, continuously available expertise without the cost and complexity of building an in-house team. Outsourcing also allows organizations to scale security coverage up or down as needs change, stay current with evolving threats and regulatory requirements, and leverage AI-native detection and response without needing to manage the AI tools themselves.

Preferences for MSSP-delivered security operations are particularly strong in the education, energy (87%), and healthcare sectors. This makes sense: all are high-value targets for threat actors, and all tend to have limited cybersecurity budgets, so the need for a partner who can deliver affordable access to expertise at scale is strong. Retailers also voiced a strong preference for MSSP-delivered services. These companies are tasked with managing large volumes of consumer personal and financial data, and with transforming an industry traditionally thought of as a late adopter to a vanguard of cyber defense. Technology companies, too, have a marked preference for SOC capabilities delivered by MSSPs. This may simply be because they understand the complexity of the threat landscape – and the advantages of specialized expertise — so well.

In order to help as many organizations as possible – from major enterprises to small and midmarket companies – benefit from enterprise-grade, AI-native security, Darktrace is making it easier for MSSPs to deliver its technology. The ActiveAI Security Portal introduces an alert dashboard designed to increase the speed and efficiency of alert triage, while a new AI-powered managed email security solution is giving MSSPs an edge in the never-ending fight against advanced phishing attacks – helping partners as well as organizations succeed on the frontlines of cyber defense.

Explore the full State of AI Cybersecurity 2026 report for deeper insights into how security leaders are responding to AI-driven risks.

Learn more about securing AI in your enterprise.

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