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November 21, 2018

How Black Hats Take Advantage of Black Friday

The retail industry must be willing to adapt its cyber defenses against an ever-evolving adversary, or it may end Black Friday firmly in the red.
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
Justin Fier
SVP, Red Team Operations
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21
Nov 2018

From Thanksgiving to Cyber Monday, shoppers across the globe will splurge tens of billions of dollars on everything from pillows to parkas to Pokémon pajamas.

U.S. consumers alone spent a record $19.62 billion last Black Friday weekend — on just online purchases. And while the number of customers at brick-and-mortar stores declined 4% from 2016, e-commerce sales were 18% higher in 2017, when for the first time more Americans shopped online than in person. There is every reason to suspect that a virtually unprecedented volume of virtual cash is about to change hands, presenting an equally unprecedented opportunity for a massive holiday cyber-heist. Here’s what such a heist might look like:

Proof of concept

While the incentive for cyber-crime during this Black Friday weekend is historically unparalleled, it has long been the holiday of choice for criminals. On Cyber Monday of 2014, for instance, a DNS provider was hit by a relatively rudimentary DDoS attack that nonetheless disrupted its clients’ websites. More advanced DDoS attacks launched by modern Mirai botnets — like the 2016 Dyn attack that crippled many of the Internet’s top websites — would be devastating on Black Friday, when companies like Amazon reel in upwards of a million dollars per minute. And for smaller retailers, a ransomware or DDoS attack this weekend poses existential risk, both because of lost revenue and because of reputational damage in such a highly competitive industry.

Prior to last year’s Black Friday weekend, experts anticipated more than 50 million attacks on businesses during peak shopping days, and cyber-criminals did not disappoint. Darktrace detected a 70% uptick in significant threats facing its retail clients during the holiday season, from November and December, compared to the previous two months, an uptick that helps explain why cyber-crime cost the world $600 billion last year. At least in the short term, it appears that online crime does pay — especially after Thanksgiving.

Mode of attack

As forensics continue to improve and CCTVs rapidly proliferate, the in-person criminal heist has largely been replaced by online robbery, which leaves no fingerprints and can be seen by no camera. One example: the annual amount of money stolen in U.S. bank robberies — the quintessential heist — has fallen by more than 60% since 2003, while cyber-crimes like credit card fraud have simultaneously skyrocketed. This transition to digital larceny makes financial sense as well, given that less than 10% of the world’s currency still exists as physical cash.

Indeed, identity theft is even more lucrative than bank robbery if done at scale, yet it entails far less risk for the perpetrators. Stolen credit card numbers can each sell for $100 on the Dark Web, rendering crimes like the Target breach — which took place during Black Friday weekend in 2013 and exposed 40 million debit and credit accounts — extremely profitable. With more than 100 million Americans and close to a billion global shoppers online during the holiday season, ’tis certainly the season for a large-scale assault on personal information.

But perhaps the most revolutionary aspect of cyber-heists is that they need not even steal anything to make off with loot. Faced with a well-timed ransomware attack, retailers often simply hand over their cash to remain operational: 70% of businesses paid the ransom after attacks in 2016, prompting criminals to quadruple their average demand. And on the busiest shopping day in history, there’s no telling how exorbitant these demands might be.

Cyber-threats that are specifically aimed at the retail sector make the challenge of security even more difficult for defenders, since much like a targeted traditional heist, they exploit their victims’ unique vulnerabilities. The numbers validate common sense here: insights from across Darktrace’s customer base reveal that these key retail threats — which include personalized phishing attacks, Cloud and SaaS attacks, as well as trojans — are more than twice as likely to become high-priority incidents as the average threat. With so much money on the line, every retailer should expect to confront targeted attacks throughout the weekend.

Bypassing the defenses

From ransomware to data exfiltration, one can make an educated guess about the kinds of threats facing retailers this Black Friday. But the truth is that no one knows exactly what the next global cyber-attack will look like, particularly given the enormous incentive for criminals to create an entirely new attack strain — or even a new type of attack altogether. Several recent, state-sponsored exploits have proven that the financial and technical backing exists to produce malware sophisticated enough to deliver a serious blow to the U.S. economy.

Innovative attacks pose a fundamental problem for traditional security tools, which rely on knowledge of past incidents to stop future ones. By updating their predefined notions of what constitutes a cyber-threat when a breach occurs, the best of these tools stop previously known attacks, but they are nonetheless blind to unknown threats. Many retailers have deployed Darktrace’s AI cyber security because it doesn’t presume to know what tomorrow’s attack will look like; rather, Darktrace learns on the job to differentiate between normal and abnormal behavior. But while such adaptive security is the only approach that stands a chance in today’s fast-changing threat landscape, most retailers have yet to make the switch.

In this era of DNA forensics and near-ubiquitous surveillance, the criminal heist has not disappeared — it’s digitized. And while retail companies prepare themselves for the generic cyber-threats of the past, very few are in a position to counter a never-before-seen attack that, like a physical heist, has been planned for months to exploit their unique security blind spots. As we inch closer to zero hour, the industry must be willing to adapt its cyber defenses against an ever-evolving adversary, or it may end Black Friday firmly in the red.

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
Justin Fier
SVP, Red Team Operations

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June 24, 2026

A New Security Challenge: The Curious Case of Prompt Language Analysis

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Why prompt analysis is emerging as a key AI security challenge

If securing AI has been one of the defining cybersecurity conversations of the past year, prompt analysis is quickly becoming one of its most interesting frontiers.

Security leaders are under pressure to understand how AI is being used across the business. In some organizations, that means governing employee use of chatbots. In others, it means overseeing copilots embedded into SaaS platforms, monitoring coding assistants, or assessing the growing footprint of autonomous agents. However different these use cases may appear on the surface, they share a common factor: humans and machines are usually interacting with enterprise systems through language.  

How prompt language differs from traditional security telemetry

For years, defenders have become used to working with familiar forms of telemetry: email traffic, network connections, API calls, endpoint processes, authentication events. Prompt language is different. It is not simply another log source. It is an expression of intent, instruction, curiosity, urgency, and sometimes manipulation. It reflects the end-goal of a user or agent, but not always with enough surrounding context to interpret the risk correctly.

Why existing security approaches only partially explain prompt risk

A growing number of vendors are approaching the task of securing AI from the angle they know best. Perimeter vendors are extending web or browser controls into AI usage. Identity vendors are emphasizing agent permissions and access governance. Data security and DLP providers are focusing on content inspection and exfiltration risk. All of these perspectives matter, but individually can’t fully explain the problem.

The challenge with securing AI is not just that a new application category has emerged. It is that language has become a new operating layer in the enterprise.

Employees now use prompts to summarize documents, generate code, analyze spreadsheets, query internal knowledge, and trigger multi-step actions through agents. In each case, prompt language acts as the interface between human intent and machine execution. That makes prompts incredibly valuable from a security perspective as they can hint at misuse, policy violations, data exposure, or attempts to circumvent controls. However, they can also be deeply ambiguous when viewed in isolation. That ambiguity is the heart of the issue.

Prompts as behavioral signals, not just text to classify

A prompt by itself tells you what was asked. It does not necessarily tell you whether the request is expected, risky, accidental, or entirely legitimate in context. Two nearly identical prompts can carry very different meanings depending on the role and function of who issued them, what systems they can access, and what actions followed. In other words, prompts are not just text to classify. They are behavioral signals to interpret.

Example: How context changes prompt risk entirely

Consider a common enterprise scenario. An employee is pulled into a new project with an aggressive deadline. Almost overnight, their use of AI tools spikes. They begin prompting more frequently, working across unfamiliar documents, querying new data sources, and interacting with more systems than usual to accelerate delivery. Viewed narrowly, this may look suspicious. Prompt volume increases, file access patterns change, API and SaaS activity rise. From some vantage points, it may resemble insider risk or unmanaged AI usage.

But now add context. Imagine that, earlier that day, the employee received instructions from a senior leader asking them to support a time-sensitive initiative. Their communication history shows that this leader is a legitimate reporting-line superior. Their recent collaboration patterns align with the new project team. Their subsequent activity, while unusual for that individual’s baseline, is consistent with the business task they were assigned.

What initially looked like a risk event may actually be a normal response to business pressure. Without the surrounding context of communication, organizational relationships, and broader behavioral patterns, prompt activity alone could generate more noise than insight.

The reverse is also true. A prompt may appear benign on the surface while the context around it suggests elevated risk. A request that seems routine could originate from a compromised user, a newly connected external agent, a shadow AI workflow, or a user acting outside their normal role. The language itself may not contain anything obviously malicious, but the surrounding conditions may tell a very different story.

What security teams need to analyze prompts effectively

The future of prompt analysis is not just about understanding language. It is about understanding language in context.

To do that well, security teams need more than prompt inspection. They need to understand:

  • Who is issuing the prompt, whether human or agent
  • How that identity normally behaves across the enterprise
  • What systems, data, and workflows are connected to the interaction
  • Which relationships and communications explain the surrounding activity
  • Whether the downstream actions align with expected business behavior

When those layers are absent, prompt analysis can become another isolated control surface: useful in theory, but limited in practice. Security teams may detect unusual wording but miss the operational function behind it, overreact to benign changes in behavior, or miss subtle misuse because the prompt itself did not appear dangerous.

How organizations should think about prompt analysis going forward

Security teams have seen this pattern before. In the cloud, posture without runtime context left important gaps. In identity, access control without behavioral understanding missed misuse that looked legitimate on paper. In data security, content inspection without business context often created friction without resolving risk. AI is exposing the same lesson again: controls are strongest when they are coordinated, not isolated. As organizations work to secure AI and identify gaps across their security operations, prompt analysis will become an increasingly important source of insight, but only as part of a broader strategy.

Prompt analysis will undoubtedly become more common, as prompts are one of the clearest windows into how people and agents are using AI systems. However, what matters most is not simply collecting prompts or filtering dangerous phrases, but being able to place that language inside a wider behavioral and operational picture.

Organizations that already have a broader understanding of how work gets done across the enterprise will be better positioned to make sense of prompt language as this category matures. They will be better able to distinguish urgency from abuse, experimentation from exfiltration, and productive AI adoption from hidden risk.

Figure 1: Darktrace / SECURE AI reconstructs the full sequence of events, showing every user and agent interaction in context, with risky prompts highlighted and categorized, including PII, sensitive data, and other policy violations.

At Darktrace, this is the key lesson emerging from the market: prompt language does matter, but it does not stand alone. It is most valuable when treated as a new behavioral input that can enrich understanding across the enterprise, not as a self-contained source of truth.

Why prompts become less useful when analyzed in isolation

The curious case of prompt language analysis, then, is this: the more important prompts become, the less useful they are in a vacuum.

The real opportunity is not just to see what was asked. It is to understand why it was asked, what it meant in that moment, and what happened next.

For a deeper look at how organizations are approaching this challenge from the strengths of prompt analysis to its limitations in isolation see Prompt Security in Enterprise AI: Strengths, Weaknesses, and Common Approaches, which expands on the role prompt-level controls play within a broader, context-driven security strategy.

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About the author
Nabil Zoldjalali
VP, Field CISO

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June 23, 2026

Advancing the Use of Frontier AI in Cybersecurity: Darktrace Joins the OpenAI Daybreak Cyber Partner Program to Explore Defensive AI Integrations

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Darktrace joins the OpenAI Daybreak Cyber Partner Program

Today, we announced that Darktrace is joining the OpenAI Daybreak Cyber Partner Program. We’ll be partnering with OpenAI to explore how their cyber capabilities can be integrated within Darktrace products and services to bring new capabilities to our customers.

This partnership is an exciting opportunity to bring together Darktrace’s behavioral AI modelling of the organization with OpenAI’s advanced contextual capabilities to create a new level of understanding for security teams. To understand the impact, it’s helpful to start with how we think about the problem.  

At Darktrace, we built our AI in support of the core belief that cybersecurity needs to understand the business it is defending. That's why our Self-Learning AI is designed to help organizations understand normal and abnormal behavior for each organization across their digital environment, including users and identities, networks and cloud, email and collaboration tools, and now AI systems and agents with the rollout of Darktrace / SECURE AI™.  

Our goal was never simply to spot known attacks faster. It was to help defenders understand how their organization behaves, potential risks and impact, and where disruption could take hold so they could prepare for the unknown threats that they may not have seen or even imagined before.  

That’s exactly what is happening across the threat landscape today. Attacks keep changing; techniques shift, infrastructure evolves, and attackers move with more speed, precision, and context. And now they have even more AI and automation on their side. Attackers are exploiting identities, trusted services, SaaS applications, and business workflows. They are not always breaking in; often, the threat may come from within the organization in the form of insider threat or even rogue agents.  

In this reality, defenders need a combination of deep AI modelling of the organization and AI that can connect identified threats to concrete business context, translating this information into real world value, and allow action before risk becomes disruption.

That is the opportunity we see in partnering with OpenAI.  

What is the OpenAI Daybreak Cyber Partner Program and why is Darktrace joining

The OpenAI Daybreak Cyber Partner Program is focused on advancing the safe use of AI for cybersecurity. As part of the program’s next phase, OpenAI is working with a select group of trusted partners including Darktrace on scoped product integrations, managed services, and partner-delivered defensive capabilities. We’ll be exploring how OpenAI’s advanced frontier AI capabilities can support defenders in the tools and workflows they already use each day.

For Darktrace, this is a natural extension of our expertise and the work we have been doing for a decade: safely and securely applying the most effective AI techniques in combination to understand organizations, detecting malicious activity at the earliest indicators, and helping cyber defenders act faster.  

By using the advanced models and more precise safeguards available in the OpenAI Daybreak Cyber Partner Program, Darktrace and OpenAI will combine Darktrace’s real-time behavioral understanding of an organization's digital estate with OpenAI's ability to interpret wider business context.  

This is a unique and powerful combination of insights that could give organizations deeper context on technical risk and help them prioritize workloads and investigations based on potential impact to revenue, operations, and resilience. It can also provide security teams and executives with intelligence into which events matter most to the business, why they matter, and what action to take. Not just finding, for instance, that an agent is compromised, but highlighting that the compromised agent could shut down order fulfilment within the next three hours.  

Why the Darktrace and OpenAI partnership matters for defenders

Security teams today have more attack surface, more complex environments to protect, and an increasing volume of threats. The ability to act quickly is critical, but they also need to be able to focus on the risks that could have the greatest business impact.

That is especially important as attackers use AI to scale phishing, automate reconnaissance, find weaknesses, and blend into normal business activity. At the same time, organizations and their employees are using AI to innovate, which introduces an even broader attack surface and new set of risks. Defenders need AI that can operate across the same complexity, but safely, transparently, and in service of building more resilience. And they need a way to safely adopt, govern, and defend AI across their organizations.

Joining the OpenAI Daybreak Cyber Partner Program is another step in that direction. We are still early in this work, and we will take a careful, disciplined approach. But the direction is clear: protecting organizations requires AI that understands the business, not just the attack.

At Darktrace, that is exactly where we remain focused and why we are so excited about this partnership with OpenAI.  

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