Phishing attacks surge by 620% in the lead-up to Black Friday
Black Friday continues to be a prime opportunity for threat actors, with early analysis from Darktrace showing a significant spike in attackers impersonating well-known brands, as well as the brands most frequently impersonated by scammers. Plus, check out our top tips to stay safe while filling your basket with deals.
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
Carlos Gray
Senior Product Marketing Manager, Email
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27
Nov 2025
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.
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.
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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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.
Darktrace / EMAIL Expands Behavioral Defense Across Email and Collaboration Workflows
New capabilities help employees understand suspicious content, give administrators more control over sensitive data, and show security teams where risky workflows sit across the organization.
Journey of a Threat: How Multi-Layered AI Works in Darktrace / EMAIL
Follow a malicious email as it moves through Darktrace / EMAIL’s multi-layered AI system, from raw data to final decision. Each layer works together to detect threats, understand intent, and take autonomous action.
Hiding in Plain Sight: Uncovering a Multi-Stage Ransomware Attack Through Behavioral Detection
Why ransomware has changed
Ransomware attacks have continued to increase globally, with 698 incidents reported in May 2026, representing a 48% rise compared to 472 incidents in May 2025 [1]. At the same time, the ransomware landscape is evolving. Several major ransomware groups, including LockBit [2], have been disrupted by successful joint law enforcement operations, resulting in a shift away from a small number of dominant actors towards a more fragmented and distributed ecosystem. This is increasingly composed of smaller groups who play a specialized role in the attack, such as initial access brokers, affiliates or developers.
As a result, ransomware tactics, techniques, and procedures (TTPs) are becoming more diverse and less predictable. On top of this, adversaries are leveraging native tools and legitimate penetration testing frameworks to evade detection. Anomaly-based detection is therefore critical to identify pre-ransomware activity, rather than relying on signatures associated with a handful of well-known ransomware groups.
As these attacks often unfold over several days, there is a critical window for defenders to act. In this context, behavioral-based detection plays a vital role in identifying suspicious pre-ransomware activity, and enabling early intervention before encryption or exfiltration occurs.
Inside a modern ransomware intrusion
In early 2026, Darktrace detected activity within a customer’s environment related to a multi-stage ransomware intrusion from the initial compromise. This activity does not appear to be attributable to a specific ransomware group, and no known ransomware payload was observed until the final stage.
The attack aligns with a broader industry trend in which compromised virtual private network (VPN) credentials are used as an entry point, followed by rapid internal reconnaissance and lateral movement using legitimate administrative tools. This growing preference for native tools and legitimate frameworks in cyber-attacks illustrates that it is increasingly unreliable to depend solely on traditional indicators of compromise such as known malware signatures or exploit detection.
The intrusion also involved the use of Sliver, an open-source adversary emulation framework, which is increasingly observed in real-world attacks. Originally designed for penetration testing and red teaming, Sliver has gained traction among threat actors as a stealthier alternative to more heavily signatured frameworks such as Cobalt Strike. As a legitimate framework, its use further complicates detection for security tools that rely on known malicious signatures.
Darktrace’s detection of a ransomware event in a customer’s environment
The initial compromise appears to have occurred via compromised credentials used over the VPN shortly before, or at the onset of the first indicators of suspicious activity. While it remains unclear as to how or when the threat actors gained access to these credentials, the use of initial access brokers (IABs) is a common feature of modern ransomware operations. This suggests that access to the environment may have been established several days or weeks beforehand.
The intrusion unfolded over three days, presenting multiple opportunities for early detection and intervention before ransomware deployment. The attack progressed through a compressed but structured sequence: initial access and reconnaissance were completed within hours, followed by privilege escalation and lateral movement the next day, and culminating in data exfiltration and encryption shortly thereafter. Throughout each stage, distinct behavioral anomalies emerged across the network providing clear indicators of malicious activity well before the ransomware was deployed.
While Darktrace’s Autonomous Response capability was enabled within the customer’s environment, it was not fully configured across the impacted devices, allowing the attack to progress to ransomware deployment. Had Autonomous Response been fully deployed across the affected systems, it could have taken targeted action against the earliest stages of malicious activity, potentially disrupting the intrusion before it escalated.
Figure 1: Timeline of the attack progression.
Day 1: Reconnaissance and privilege escalation
The threat actor gained access via compromised VPN credentials and initiated internal reconnaissance. Darktrace detected anomalous scanning behavior, including unusual port scanning activity and widespread network enumeration.
Specifically, Darktrace detected a high volume of east-west scanning activity across a broad range of ports, with TCP connections targeting ports 21, 80, 445, 4899 and 8080. Associated URIs suggested the use of Nmap, a widely used penetration testing tool. This highlights how attackers often leverage legitimate penetration testing tools for malicious reconnaissance, enabling them to blend into normal network activity and evade traditional signature-based detection methods.
Figure 2: Darktrace's detection of a sharp increase in anomalous internal connections, triggering multiple high-severity model alerts associated with reconnaissance activity.
Several devices were observed using administrative credentials to carry out privileged actions in a manner that was highly anomalous for the environment. This activity was accompanied by behavior consistent with SMB authentication scanning, suggesting efforts to identify and access additional systems. As the activity intensified, an increasing number of devices became involved, signalling lateral movement and further spread across the network.
Darktrace also identified privilege escalation through active directory (AD) replication abuse, specifically via the drsuapi::DRSGetNCChanges function. This technique allows an attacker with sufficient privileges to request directory replication data from a domain controller (DC), enabling them to extract credentials, including password hashes, without directly interacting with user accounts. Commonly associated with ‘DCSync’ attacks, this technique is frequently used to obtain highly privileged credentials and enable further escalation within an environment.
Figure 3: Darktrace’s detection of anomalous AD replication activity indicative of privilege escalation.
This activity was seen alongside the use of the now obsolete SMBv1, repeated NTLM authentication attempts using multiple variations of ‘Administrator’ credentials, reverse DNS scanning, and large-scale network scanning. Darktrace observed widespread use of SMBv1 across the customer’s environment, exposing a significant security weakness. As a legacy protocol with well-documented weaknesses, SMBv1 can be exploited to facilitate lateral movement, allowing the attackers to expand their access following initial compromise.
Day 3: Lateral Movement, Command & Control, and Exfiltration
Two days later, the attacker escalated privileges and expanded their foothold using living-off-the-land (LOTL) techniques such as PSExec, WMI, and RDP. Concurrently, Darktrace identified command-and-control (C2)-style communications consistent with the Sliver framework, alongside rare outbound connections to cloud infrastructure indicating potential data exfiltration. The volume and severity of observed activity increased as attack behavior intensified.
The device was observed conducting extensive lateral movement, leveraging LOTL techniques to evade detection. Activity included WMI execution (e.g. ExecQuery), DCE-RPC activity, SMB sessions and file writes, most of which were successful, as well as the deployment of PSEXESVC.exe via ADMIN$ shares and prolonged RDP sessions. Darktrace identified this behavior as highly anomalous for the environment. Such activity is commonly associated with the transfer of attacker tooling, remote command execution, and the establishment of persistent access across compromised systems.
Figure 4: Darktrace’s detection of a spike in RPC binding events indicative of potential lateral movement.
On the same day, Darktrace detected C2-style SSL communications originating from multiple internal devices to rare external endpoints. These connections exhibited anomalous characteristics, including invalid SSL certificates and repeated connection patterns resembling beaconing. Analysis of the observed JA3 fingerprint further linked the activity to Sliver, the adversary simulation framework referenced earlier, as the hash has previously been associated with Sliver-related infrastructure [3]. The use of this framework reflects a broader trend of attackers repurposing legitimate offensive security tools for stealthy C2 communications. Connections to 137[.]220[.]59[.]55 (ASN AS20473 AS-VULTR) indicated that the communications were likely routed via a virtual private server (VPS) hosted by Vultr. Attackers often utilize VPS infrastructure from legitimate cloud providers like Vultr to obscure their true origin, blend into benign traffic, and evade IP-based detection mechanisms [4].
Figure 5: Darktrace’s Cyber AI Analyst detection of two linked unusual connections to Vultr infrastructure.
Darktrace also observed a device initiating SSL connections to safedata.s3[.]wasabisys[.]com, an endpoint associated with Wasabi cloud storage. Darktrace recognized that neither the destination nor the associated IP address had previously been observed within the environment. More than 200 MB of data was subsequently uploaded externally to endpoints sharing the same JA3 client hash, indicating a sustained transfer session and potential data exfiltration to third-party storage. The apparent exfiltration prior to encryption is consistent with a double-extortion ransomware strategy.
Figure 6: Darktrace’s Cyber AI Analyst detection of more than 30 rare outbound connections to a Wasabi cloud storage endpoint, indicative of potential data exfiltration
Day 4: Encryption
The attack culminated in ransomware deployment, marking the transition from suspicious network activity to a business-impacting incident. Using SMB-based propagation, the threat actor encrypted thousands of files across the network, affecting multiple systems and disrupting normal operations. Throughout the encryption event, the legacy SMBv1 protocol was used extensively across multiple internal systems, resulting in a significant increase in newly encrypted files.
Figure 7: Darktrace’s detection of abnormal spikes in SMB activity and associated model alerts, indicative of ransomware encryption and propagation.
Darktrace’s Cyber AI Analyst automatically investigated and correlated the encryption activity and related events into a single incident narrative, providing the customer with real-time visibility into the attack while significantly reducing investigation time.
Figure 8: Darktrace’s Cyber AI Analyst’s investigation into the encryption activity. AI Analyst incident detailing example encryption activity in real time. Related events are automatically correlated and summarized into a clear narrative, reducing investigation time.
Defender action recommendations
What Could Have Stopped the Attack Earlier?
Although the attack ultimately resulted in ransomware deployment, there were multiple opportunities to detect, contain, and disrupt the intrusion before encryption occurred. The following actions could have significantly reduced the overall impact:
Detect and investigate indicators of reconnaissance and lateral movement
Unusual scanning
Active Directory replication anomalies consistent with DCSync activity
Anomalous use of native tools and processes indicative of LOTL attacks
Unusual use of common reconnaissance tools such as Nmap and NetScan
Contain compromised credentials and affected devices
Disable and reset compromised VPN credentials
Isolate devices performing anomalous scanning and lateral movement activity
Block suspicious external communications and data exfiltration
Use anomaly-based detection to detect and block repeated outbound connections to rare external infrastructure
Prevent data exfiltration to unauthorized cloud storage services such as Wasabi
Conclusion
The incident highlights the importance of anomaly-based detection, particularly against attacks that primarily use native or legitimate tools to evade traditional security measures. Darktrace identified suspicious activity from the first day of the compromise, providing multiple opportunities to disrupt the intrusion before it progressed to lateral movement and data exfiltration.
In this instance, detection was not the limiting factor; response time was. Prompt investigation and containment of devices exhibiting anomalous behavior could have prevented lateral movement, data exfiltration, and ultimately ransomware deployment.
As adversaries increasingly prioritize stealth over custom malware, relying instead on legitimate tools, valid credentials, and trusted infrastructure, traditional signature-based detection becomes less effective. Identifying subtle behavioral deviations early remains critical to disrupting attacks before they escalate into full-scale ransomware incidents.
Credit to Alexandra Evzona (Cyber Analyst), Priya Thapa (Senior Cyber Analyst) Edited by Ryan Traill (Content Manager)
Darktrace / EMAIL Expands Behavioral Defense Across Email and Collaboration Workflows
Email and collaboration tools do more than carry messages. They are where organizations approve payments, share sensitive data, reset credentials, and make thousands of everyday decisions. Increasingly, they are interfaces through which humans direct AI agents in their daily activity. Email, Slack and Teams are high volume, rich with sensitive data, and an easy place to hide malicious activity.
The opportunity isn’t lost on bad actors. Darktrace / EMAIL detected more than 32 million high-confidence phishing emails globally in 2025, and 70% of those messages passed DMARC authentication. Phishing is increasingly difficult to detect and familiar trust signals alone are not enough. People and security teams need to understand how a message fits the normal behavior of the sender, recipient, and organization. They also need to correlate activity across platforms to spot threats that span multiple channels.
To effectively secure against today’s evolved threats, security teams need to act at two levels: they need to help each employee make a safer decision ‘in the moment’, and they need to understand the wider patterns that may expose the business to risk.
Darktrace is introducing four new capabilities in Darktrace / EMAIL to address both challenges. The new features explain suspicious content more clearly to end users, strengthen the capabilities of Darktrace / Adaptive Human Defense with richer guidance, let organizations define their own patterns for detecting sensitive data in messages, and give security teams a process-level view of risk across email and collaboration workflows.
Darktrace / EMAIL Inbox Analysis highlights risky content within your emails
A warning is more useful when it explains what the user should look at. To help do that, we’ve expanded Darktrace / EMAIL’s Inbox Analysis Add-In to highlight potentially dangerous content within the body of emails that Darktrace / EMAIL flags as potentially suspicious or high risk.
The add-in can highlight language designed to create urgency, financial references, requests for payment, suspicious links, and content that is unusual for the sender. Each highlighted element includes a pop up that explains why it may be suspicious. Instead of asking an employee to accept a verdict without context, the analysis helps them examine the message and make a more informed decision.
Enhanced Just-In-Time Training Banners in Darktrace / Adaptive Human Defense
Enhanced Just-In-Time Training Banners build on the same principle. The banners now include a contextual header, actionable advice, and specific detection context. This gives employees more useful guidance at the point of risk without adding unnecessary information or cognitive load.
Together, the capabilities help turn a warning into a short learning moment. Employees can see what looks unusual, understand what action to take, and build their judgment.
Custom Sensitive Data Detection in Darktrace / EMAIL - Data Loss Prevention
Sensitive data is different for every business. Standard categories such as payment card details or government identifiers matter, but organizations also have their own customer codes, project names, research formats, account structures, and internal identifiers.
Custom Sensitive Data Detection in Darktrace / EMAIL - Data Loss Prevention allows administrators to write custom expressions for the data their organization needs to protect. Matched content can trigger existing model actions and data loss prevention (DLP) workflows, extending Darktrace's DLP capabilities.
This extends data loss detection beyond a fixed library of common data types. Security teams can apply controls to information that is sensitive in the context of their own organization and adapt those controls as the business changes.
Introducing Email and Collaboration Workflow Risk Posture Dashboards
Some of the most important risks are not isolated events. They are repeated ways of working that create an opening for error, misuse, or attack. For example, a payment request may be one suspicious message, but a recurring approval workflow that relies on weak verification is a business process risk.
The new Email and Collaboration Workflow Risk Posture Dashboard analyzes email and collaboration data across Email, Microsoft Teams, Slack and Zoom to provide a process-level view of risk in the organization. These may include financial authorization workflows, sensitive data sharing patterns, and activity that could expose credentials.
The dashboard brings these patterns into a view and provides actionable recommendations. This helps security teams determine where to investigate or strengthen controls, where ownership needs to be clarified, and where the business may need to change a risky process. It gives CISOs a clearer view of how human and communication risk is embedded in everyday operations, not only where individual alerts occur.
Behavior connects the individual decision to the wider risk
These capabilities build on Darktrace’s unique behavioral approach to security. We use Adaptive AI to learn how people and AI normally behave within an organization, creating the context needed to recognize when activity changes.
Within the Darktrace Behavioral Defense Platform, Darktrace / EMAIL helps protect people against phishing, account takeover, data exfiltration, and human risk across email and collaboration tools. The new capabilities extend that protection in both directions. They give employees clearer context for the decision in front of them, while giving security leaders a broader view of the workflows and behavior that create risk across the organization.
The result is not simply more alerts. It is a better understanding of why something is risky, what action to take, and where the organization can reduce risk before a familiar process becomes an easy route for an attacker.