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December 4, 2024

Phishing Attacks Surge Over 600% in the Buildup to Black Friday

Black Friday and Cyber Monday are prime targets for cyber-attacks, as consumer spending rises and threat actors flock to take advantage. Darktrace analysis reveals a surge in retail cyber scams at the opening of the peak 2024 shopping period, and the top brands that scammers love to impersonate. Plus, don’t forget to check out our top tips for holiday-proofing your SOC before you clock off for the festive season.
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
Nathaniel Jones
VP, Security & AI Strategy, Field CISO
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04
Dec 2024

Defenders are accustomed now to an uptick in cyber-attacks around the holiday period. The festive shopping season creates ideal conditions for cybercriminals. Consumers are inundated with time-sensitive deals, while retailers handle record-breaking transaction volumes at speed. This environment makes it harder than ever to identify suspicious activity.

An investigation conducted by Darktrace’s global analyst team revealed that Christmas-themed phishing attacks leapt 327%1 around the world and Black Friday and Cyber Monday themed phishing attacks soared to 692% last week compared to the beginning of November2 (4th - 9th November), as threat actors seek to take advantage of the busy holiday shopping period.

The United States retail sector saw the most marked increase in threat actors crafting convincing emails purporting to be from well-known brands, mimicking promotional emails. Attacks designed to look like they came from major brands including Walmart – which was easily the most mimicked US brand – Macy’s, Target, Old Navy, and Best Buy3 increased by more than 2000% during peak shopping periods.

Darktrace analysis also highlighted a redistribution of scammers’ resources to take advantage of the festive shopping season, moving from targeting businesses to consumers. The impersonation of major consumer brands, dominated by Amazon and PayPal4, increased by 92% globally between analyzed periods, while the spoofing of workplace-focused brands, like Adobe, Zoom and LinkedIn, decreased by 9%.

Major retail brands invest heavily in safeguarding themselves and their customers from scams and cyberattacks, particularly during the holiday season. However, phishing and website spoofing occur outside the retailers' legitimate infrastructure and security controls, making it difficult to catch and prevent every instance due to their sheer volume. While advancements like AI are helping security teams narrow the gap, brand impersonation remains a persistent challenge.

Multiple attack methods exploit trust during holiday rush

Darktrace’s findings demonstrate some of the most common brand spoofing strategies used by attackers during the holiday season:

Domain spoofing, which sees attackers create near perfect replicas of retail websites, complete with lookalike domain names and branding, to trick consumers into handing over personal and payment details.  

Brand spoofing, where attackers send a phishing email designed to look like a favorite retailer, enticing their target to click a link for a discount, when in fact the link downloads malware to their device.  

Safelink smuggling, which involves an attacker intentionally getting their malicious payload rewritten by a security solution’s Safelink capability to then propagate the rewritten URL to others. This not only evades detection but also undermines trust in email security tools. Darktrace observed over 300,000 cases of Safelinks being included in unexpected and suspicious contexts over a period of 3 months.

Multi-stage attacks which combine these tactics into a single attack: brand spoofing emails lead unsuspecting shoppers directly to domain spoofed websites that harvest login or payment details, creating a seamless deception that hands personal and financial data directly to attackers. This coordinated approach exploits the chaos of holiday sales, when shoppers are primed to expect high volumes of retail emails and website traffic promoting significant savings.

A spike in cyber-criminal activity which extends beyond email

While email often serves as the front door to an organization and the initial avenue of attack, Darktrace frequently observes a surge in cyber-attacks during public holidays5. These “off-peak” attacks exploit common organizational practices and human vulnerabilities with greater ease.

When staff numbers are reduced, and employees mentally and physically disconnect from work, the speed of detection and response has the potential to slow. This creates opportunities for threat actors to infiltrate undetected. Without real-time autonomous systems in place, such attacks can have a far more severe impact on an organization’s ability to respond and recover effectively.

Ransomware is among the most common threats targeting organizations after hours. In 76% of cases, the encryption process begins during off-hours or on weekends6. For instance, Darktrace identified a ransomware attack launched in the early hours of Christmas Day on a client’s network, taking advantage of the period when most employees were offline.

Festive cheer: giving your SOC team the break they deserve

Staff burnout is increasingly top of mind, with 74% of cybersecurity leaders reporting that they’ve had employees resign due to stress7. And the numbers stack up – almost 60% of security analysts report feeling burnt out, and many are choosing to leave their jobs and even security altogether.8

At a human level, the holiday season should be a time of relaxation and merriment rather than anxiety. For SOC leaders, giving teams time to prioritize recharging during the holidays is crucial for sustaining long-term resilience and productivity, balanced with the importance of maintaining rigorous defenses with a reduced workforce.  

So… how can cybersecurity leaders ensure peace of mind during the holidays?

Step 1: Cover yourself from every angle. It’s no longer enough for your email solution to only catch known threats. Security leaders need to invest in multi-layered email defenses that can combat novel and advanced attacks – such as the multi-stage brand personation attacks that lead shoppers to domain-spoofed websites.  

Darktrace / EMAIL – the fastest growing email security solution – has been proven to detect up to 56% more threats than other email solutions.9  It is uniquely capable of catching novel attacks on the first encounter, rather than waiting the 13 days it takes for other solutions to take action10 – by which time your decorations might be coming down, along with your business.

Step 2: Avoid an overwhelming deluge of alerts raining (or snowing) down on your L1 SOC analysts. Lining up people to manage the grunt work over the holidays is an easy pattern to fall into, but consider technology that can automate that initial triage. For example, Darktrace’s Cyber AI Analyst automatically investigates every alert detected by Darktrace’s core real-time detection engine. It does an additional layer of AI analysis – establishing whether an alert is unusual but benign, or part of a more serious security incident. Rather than looking at hundreds of alerts, your team is presented with just a handful of overall incidents. They can use that new free time to do more strategic work, or take some much-needed time off.

Step 3: Make sure someone – or something – is keeping guard in those super off-peak hours. Enter Autonomous Response. Because it knows what normal looks like for your business it can take action to stop and contain only the unusual and threatening activity. Even if it doesn’t eliminate the threat entirely, it can buy your security team time and space, allowing them to enjoy their holiday in peace.

With Black Friday over and the festive shopping period looming, businesses should act now to protect their brand and ensure they have the cybersecurity measures are in place to enjoy the gift of a stress-free holiday season.  

Interested in how AI-driven email security can protect your organization? Check out the product hub to learn more. Or watch the demo video to see Darktrace / EMAIL in action.

References

[1] Based on analysis of 626 customer deployments and attempted phishing emails mentioning Christmas that were detected by Darktrace / EMAIL.

[2] Emails in the analysis mentioning ‘Black Friday’ or ‘Cyber Monday’.

[3] Walmart, Target, Best Buy, Macy's, Old Navy, 1800-Flowers

[4] Amazon, eBay, Netflix, Alibaba, Paypal, Apple

[5] In 2021, Darktrace observed a 70% average increase in attempted ransomware attacks in November and December compared to January and February. (Darktrace Press Release, 2021)

[6] https://www.zdnet.com/article/most-ransomware-attacks-take-place-during-the-night-or-the-weekend

[7] https://www.scworld.com/perspective/ciso-stress-levels-are-out-of-control

[8] https://www.informationweek.com/cyber-resilience/the-psychology-of-cybersecurity-burnout

[9] 56% of malicious phishing emails detected and analyzed across Darktrace / EMAIL customer deployments from December 2023 – July 2024 passed through all existing security layers. (Darktrace Half Year Report 2024)

[10] 13 days mean average of phishing payloads active in the wild between the response of Darktrace / EMAIL compared to the earliest of 16 independent feeds submitted by other email security technologies. (Darktrace Press Release, 2023)

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
Nathaniel Jones
VP, Security & AI Strategy, Field CISO

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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.

Sign up today to stay informed about innovations across securing AI.

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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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