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October 15, 2024

Navigating Buying and Adoption Journeys for AI Cybersecurity Tools

More and more security teams are adopting AI-powered cybersecurity solutions, but first-time buyers may not know how to evaluate new vendors and tools. This blog covers questions to consider at each stage of the AI adoption journey to ensure return on investment.
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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.
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15
Oct 2024

Enterprise AI tools go mainstream

In this dawning Age of AI, CISOs are increasingly exploring investments in AI security tools to enhance their organizations’ capabilities. AI can help achieve productivity gains by saving time and resources, mining intelligence and insights from valuable data, and increasing knowledge sharing and collaboration.  

While investing in AI can bring immense benefits to your organization, first-time buyers of AI cybersecurity solutions may not know where to start. They will have to determine the type of tool they want, know the options available, and evaluate vendors. Research and understanding are critical to ensure purchases are worth the investment.  

Challenges of a muddied marketplace

Key challenges in AI purchasing come from consumer doubt and lack of vendor transparency. The AI software market is buzzing with hype and flashy promises, which are not necessarily going to be realized immediately. This has fostered uncertainty among potential buyers, especially in the AI cybersecurity space.  

As Gartner writes, “There is a general lack of transparency and understanding about how AI-enhanced security solutions leverage AI and the effectiveness of those solutions within real-world SecOps. This leads to trust issues among security leaders and practitioners, resulting in slower adoption of AI features” [1].  

Similarly, only 26% of security professionals report a full understanding of the different types of AI in use within security products.

Given this widespread uncertainty generated through vague hype, buyers must take extra care when considering new AI tools to adopt.  

Goals of AI adoption

Buyers should always start their journeys with objectives in mind, and a universal goal is to achieve return on investment. When organizations adopt AI, there are key aspects that will signal strong payoff. These include:  

  • Wide-ranging application across operations and areas of the business
  • Actual, enthusiastic adoption and application by the human security team  
  • Integration with the rest of the security stack and existing workflows
  • Business and operational benefits, including but not limited to:  
  • Reduced risk
  • Reduced time to response
  • Reduced potential downtime, damage, and disruption
  • Increased visibility and coverage
  • Improved SecOps workflows
  • Decreased burden on teams so they can take on more strategic tasks  

Ideally, most or all these measurements will be fulfilled. It is not enough for AI tools to benefit productivity and workflows in theory, but they must be practically implemented to provide return on investment.  

Investigation before investment

Before investing in AI tools, buyers should ask questions pertaining to each stage of the adoption journey. The answers to these questions will not only help buyers gauge if a tool could be worth the investment, but also plan how the new tool will practically fit into the organization’s existing technology and workflows.  

Figure 1: Initial questions to consider when starting to shop for AI [2].

These questions are good to imagine how a tool will fit into your organization and determine if a vendor is worth further evaluation. Once you decide a tool has potential use and feasibility in your organization, it is time to dive deeper and learn more.  

Ask vendors specific questions about their technology. This information will most likely not be on their websites, and since it involves intellectual property, it may require an NDA.  

Find a longer list of questions to ask vendors and what to look for in their responses in the white paper “CISO’s Guide to Buying AI.”

Committing to transparency amidst the AI hype

For security teams to make the most out of new AI tools, they must trust the AI. Especially in an AI marketplace full of hype and obfuscation, transparency should be baked into both the descriptions of the AI tool and the tool’s functionality itself. With that in mind, here are some specifics about what techniques make up Darktrace’s AI.  

Darktrace as an AI cybersecurity vendor

Darktrace has been using AI technology in cybersecurity for over 10 years. As a pioneer in the space, we have made innovation part of our process.  

The Darktrace ActiveAI Security Platform™ uses multi-layered AI that trains on your unique business operations data for tailored security across the enterprise. This approach ensures that the strengths of one AI technique make up for the shortcomings of another, providing well-rounded and reliable coverage. Our models are always on and always learning, allowing your team to stop attacks in real time.  

The machine learning techniques used in our solution include:

  • Unsupervised machine learning
  • Multiple Clustering Techniques
  • Multiple anomaly detection models in tandem analyzing data across hundreds of metrics
  • Bayesian probabilistic methods
  • Bayesian metaclassifier for autonomous fine-tuning of unsupervised machine learning models
  • Deep learning engines
  • Graph theory
  • Applied supervised machine learning for investigative AI  
  • Neural networks
  • Reinforcement Learning
  • Generative and applied AI
  • Natural Language Processing (NLP) and Large Language Models (LLMs)
  • Post-processing models

Additionally, since Darktrace focuses on using the customer’s data across its entire digital estate, it brings a range of advantages in data privacy, interpretability, and data transfer costs.  

Building trust with Darktrace AI

Darktrace further supports the human security team’s adoption of our technology by building trust. To do that, we designed our platform to give your team visibility and control over the AI.  

Instead of functioning as a black box, our products focus on interpretability and sharing confidence levels. This includes specifying the threshold of what triggered a certain alert and the details of the AI Analyst’s investigations to see how it reached its conclusions. The interpretability of our AI uplevels and upskills the human security team with more information to drive investigations and remediation actions.  

For complete control, the human security team can modify all the detection and response thresholds for our model alerts to customize them to fit specific business preferences.  

Conclusion

CISO’s are increasingly considering investing in AI cybersecurity tools, but in this rapidly growing field, it’s not always clear what to look for.  

Buyers should first determine their goals for a new AI tool, then research possible vendors by reviewing validation and asking deeper questions. This will reveal if a tool is a good match for the organization to move forward with investment and adoption.  

As leaders in the AI cybersecurity industry, Darktrace is always ready to help you on your AI journey.  

CISOs guide to buying AI white paper cover

How to evaluate an AI cybersecurity vendor

Download the white paper to learn how buyers should approach purchasing AI-based solutions. It includes:

  • Key steps for selecting AI cybersecurity tools
  • Questions to ask and responses to expect from vendors
  • Understand tools available and find the right fit
  • Ensure AI investments align with security goals and needs

References

  1. Gartner, April 17, 2024, “Emerging Tech: Navigating the Impact of AI on SecOps Solution Development.”  
  1. Inspired by Gartner, May 14, 2024, “Presentation Slides: AI Survey Reveals AI Security and Privacy Leads to Improved ROI” and NHS England, September, 18, 2020, “A Buyer’s Guide to AI in Health and Care,” Available at: https://transform.england.nhs.uk/ai-lab/explore-all-resources/adopt-ai/a-buyers-guide-to-ai-in-health-and-care/  
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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.
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June 3, 2026

Stopping Stealth Attacks with Precision: How Núclea Prevented a Breach Without Disruption

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Núclea is a Brazilian data and technology company that supports the country’s financial system by delivering digital services exclusively to banks and financial institutions. Operating in an environment where trust, availability, and data integrity are critical, the company faces a threat landscape that has evolved rapidly—particularly with the rise of AI-driven cyberattacks.

Brazil has experienced a wave of successful cyber incidents targeting financial institutions, many of them enabled by insiders or compromised credentials. The result was a noticeable shift in attacker strategy: instead of focusing on end customers, threat actors began targeting the institutions and platforms that underpin the financial ecosystem itself.

“Attacks became far more directed and contextual,” explains Guilherme, who leads incident response within Núclea’s security platform engineering team. “They weren’t noisy or obviously malicious—they were precise, patient, and designed to blend into normal operations.”

That precision was on full display in January 2026, when Núclea faced one of the most convincing phishing attacks the team had seen.

A real attack, built on trust and context

The attack began with a seemingly routine email.

It was sent from a real Brazilian government institution, using legitimate infrastructure and valid credentials that were later confirmed to have been compromised. Núclea had an established, ongoing relationship with this organization, and the email’s language, tone, and subject matter aligned perfectly with the type of communication the recipient team handled every day.

Attached to the email was a PDF document containing content that looked entirely legitimate.

The problem? A single URL embedded inside that PDF.

“The message itself was correct. The sender was real. The context was familiar. Even the document content made sense,” Guilherme explains. “There was just one small element that didn’t belong.”

That small detail was enough to initiate a full attack chain.

What the attackers were trying to do

If clicked, the URL would have downloaded a malicious payload designed to:

  • Collect information about the user and device
  • Identify where the system was located within the financial ecosystem
  • Install remote access tools to maintain control
  • Deploy an infostealer to extract sensitive data
  • Execute anti-forensic scripts to erase traces of the intrusion

In other words, it was a carefully engineered operation designed for persistence and stealth, not immediate disruption.

The attack also employed urgency—a classic social engineering technique. When the link didn’t open as expected, employees requested assistance from the security team, insisting the document was important and needed to be accessed quickly.

This is precisely the kind of scenario where traditional security tools struggle: almost everything about the interaction is legitimate.

Where Darktrace made the difference

Instead of blocking the entire message or relying on known indicators of compromise, Darktrace focused on behavioral context.

Darktrace recognized:

  • That the sending organization was normally trusted
  • That the communication pattern matched historical behavior
  • That the PDF content itself was not suspicious

But it also identified that the URL embedded within the document deviated from established behavioral patterns.

Rather than disrupting business operations, Darktrace took precise action: it rewrote the URL, preventing the malicious download while leaving the rest of the email untouched.

“When we analyzed it afterward, it became clear how dangerous the attack would have been,” says Guilherme. “But it never progressed—because Darktrace acted at exactly the right point.”

Subsequent forensic analysis confirmed the payload’s malicious intent. The attack never succeeded.

Precision over disruption

For Núclea, this incident reinforced a critical lesson: modern attacks don’t always look malicious—they hide within normal activity.

“What stands out to me is the precision,” Guilherme says. “Darktrace doesn’t rely on big, obvious signals. It’s effective in situations that fall outside the standard patterns we all know.”

Building resilience in a high trust ecosystem

For Núclea, cybersecurity is not just a defensive measure—it’s a business enabler.

Availability failures or successful breaches in the financial ecosystem can have immediate, large-scale consequences, from financial loss to reputational damage. Preventing those outcomes protects not just Núclea, but its partners and customers as well.

“Cyber resilience means keeping the business running—even under attack,” Guilherme explains. “And that requires people, processes, and technology working together.”

As AI continues to accelerate both attacks and defenses, the role of security is evolving. Precision, behavioral understanding, and intelligent automation are no longer optional—they’re essential.

“The easy days were yesterday,” Guilherme says. “The challenges ahead are bigger. We need to be prepared—internally and with partners that help us build resilience.”

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June 1, 2026

Defend What You Trust: Stories from the Front Lines of Modern Cyber Defense

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Modern attacks don’t always announce themselves, follow obvious patterns, or rely on known malware. Often, they move quietly inside trusted systems, authenticated sessions, and everyday behavior.

They don’t break in. They blend in.

That’s why an AI-powered defense is essential. It turns invisible signals into actionable insights at a scale neither analysts nor traditional tools can achieve alone.

Confidence is creating risk

One of the most dangerous assumptions in cybersecurity today is that strong controls equal strong protection.

Multi-factor authentication (MFA), for example, is widely viewed as a foundational safeguard. But as the CISO for a professional sports organization explains, that confidence can be misplaced. “A lot of organizations assume that once you have MFA, those accounts are safe. That’s not true.”

In one instance, his team identified a sophisticated attack where a threat actor bypassed MFA entirely, not by breaking it, but by going around it. A user’s authenticated session was hijacked and re-used, allowing the attacker to impersonate them without triggering traditional controls.

“Darktrace picked up that a session had been re-injected by the hacker, and we were able to block it right away,” he explains.

Attackers anticipate what we miss

Even well-trained users can become entry points.

“An email bypassed our existing security tools,” shares the VP of IT at a U.S.-based risk management services provider.  “The user missed one signal and entered their credentials into a malicious site. That’s what the bad guys count on.”

The organization responded quickly, but not before damage was done. Crucially, this occurred while Darktrace was in “watch mode,” before autonomous response was fully enabled. “Darktrace would have seen that and shut it down immediately,” he notes.

Mistakes and oversights like misconfigurations, forgotten machines, and missed patches can create serious vulnerabilities.

The CIO of a utility services organization shares an instance when Darktrace detected a breach to a client’s network via their ZTNA VPN due to misconfigured MFA. “Darktrace alerted us and autonomously blocked the scanning, preventing what could have been a ransomware-type incident.”  

The most dangerous threats are already inside

The Head of Security at a global business services provider knows firsthand how blind spots can persist inside environments. His team uncovered evidence of dormant ransomware artifacts sitting unnoticed within a company’s environment ¬¬– long before modern detection was in place.

“During a routine file transfer, Darktrace flagged the suspicious activity, identified the ransomware, and immediately quarantined the server,” he recalls.  While the attack was never executed, the implication was significant: the risk existed long before it was finally detected.

Cyber threats are also successful because they take advantage of normal human behavior, exploiting moments of cognitive overload, urgency, and trust.

The Executive Director of IT and Business Applications at a pharmaceutical lab describes the time Darktrace flagged an employee logging into Microsoft 365 from Singapore, despite him being physically located in the U.S. Darktrace immediately cut off his access and within minutes revealed that the employee’s son was using a VPN to play a video game.

While the threat was benign, it demonstrated the strength of AI to use contextual information to detect threats other tools miss. The information also saved security analysts hours of investigation and minimized downtime for the employee. “That level of precision and speed isn’t just convenient, it’s game changing.”

“Unusual” behavior is the new red flag

Detecting modern threats requires an understanding of what “normal” looks like and recognizing when something subtly deviates.

One security leader  at an AI technology enterprise described a scenario in which an employee connected to a proxy service in China. The service itself was legitimate, and although traditional tools didn’t flag it, the behavior was unusual for that user specifically.

“That’s what Darktrace picked up on. The activity turned out to be benign, but without visibility into behavioral deviations, it could just as easily have been something more serious.”

AI shifts defense from reaction to anticipation

These stories point to a fundamental shift by cyber attackers, both tactically and strategically. Because traditional security tools were built to detect what’s already known, modern attacks are often:

  • Credential-based, not malware-based
  • Behavioral, not signature-based
  • Subtle, not overt

They may operate within the boundaries of what appears normal, exploiting what organizations trust, not what they block:

  • Trusted sessions
  • Legitimate services
  • Human error

This is where AI is changing the equation. Rather than relying on predefined rules or known threat signatures, AI can:

  • Establish a baseline of normal behavior
  • Detect subtle anomalies in real time
  • Act autonomously to contain potential threats

Resilience, not perfection, is the new security standard

As these frontline experiences show, the organizations that lead are those that move beyond reactive defense and embrace AI as a core part of their strategy.

It eliminates the blind spots and uncertainty, says the CISO of a professional sports organization. “If you lack visibility, you’re not managing risk, you’re assuming it. AI gives you the actionable insights needed to turn uncertainty into control.”

And it provides the speed and agility that are vital when seconds matter, says the Executive Director of IT and Business Applications. “When Darktrace alerted us at 3:00 am to a ransomware attack, it had already quarantined the affected systems, blocked the attacker’s access, and provided us with the critical details and time needed to investigate. That action likely saved us hundreds of thousands, if not millions, of dollars.”

The modern SOC has become a cornerstone of enterprise resilience, responsible for protecting data and operational continuity while enabling digital growth and innovation. For today’s security professional, that means success is no longer measured by what they keep out, but by what they protect: revenue, reputation, and trust.

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