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July 31, 2024

CDR is just NDR for the Cloud... Right?

As cloud adoption surges, the need for scalable, cloud-native security is paramount. This blog explores whether Cloud Detection and Response (CDR) is merely Network Detection and Response (NDR) tailored for the cloud, highlighting the unique challenges and essential solutions SOC teams require to secure dynamic cloud environments effectively.
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
Adam Stevens
Senior Director of Product, Cloud | Darktrace
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31
Jul 2024

The need for scalable cloud-native security

The cybersecurity landscape is undergoing a rapid transformation driven by the accelerated adoption of cloud computing, compelling organizations to reevaluate their security strategies. According to Forrester’s Infrastructure Cloud Survey, 2023, cloud decision-makers who are moving to a cloud computing infrastructure estimated they have already moved 39% of their application portfolio to the cloud and intend to move another 53% in the next two years [1].

This explosive growth underscores not only the increased dependency on cloud services, but also the evolving sophistication of cyber threats targeting these platforms, and the critical need for dedicated security measures tailored to cloud infrastructures — thereby making cloud security a pivotal focus for Security Operations Center (SOC) teams.

As organizations increasingly migrate to cloud environments and their reliance on cloud infrastructures deepens, they encounter new security challenges that require reevaluating their security strategies. Traditional measures like Network Detection and Response (NDR) are being reassessed in favor of more dynamic, scalable cloud-native solutions.

However, can we truly say that cloud detection and response (CDR) is fundamentally different? Or is it simply an evolution of NDR tailored for the cloud?

Cloud Detection and Response (CDR) vs Network Detection and Response (NDR)

Cloud Detection and Response (CDR) has emerged as a pivotal technology in the race against threat actors targeting cloud assets. CDR is typically centered around the same foundational principles as NDR. As such, NDR providers are well placed to provide these capabilities within dynamic cloud environments – particularly those providers that are built upon the foundation of understanding your business, its digital footprint, and leveraging that understanding to detect subtle deviations and highlighting anomalies as opposed to pre training or relying on rules and signatures.

However, there are unique challenges within cloud environments that require a wider, richer, context-aware approach.

Why SOC Teams Care

Widespread UseThe shift towards cloud services is no longer a trend but a standard practice across industries. Organizations increasingly rely on cloud infrastructures for essential operations across IaaS, PaaS, and SaaS platforms. According to Gartner, worldwide end-user spending on public cloud services is forecast to grow 20.4% to total $678.8 billion in 2024, up from $563.6 billion in 2023 [2]. This widespread adoption necessitates a security approach that can operate seamlessly across varied cloud environments, addressing both the scalability and the agility that these platforms offer.

Sophisticated AttacksCyber threats have evolved in sophistication, specifically targeting cloud platforms due to their growing prevalence. Attackers exploit the dynamic nature of cloud services, where traditional security measures often fall short. The cloud has emerged as a major target for threat actors who want to control access to, manipulate, and steal that data. This makes cloud resources a bigger target than ever for attackers. According to the IBM Cost of a Data Breach 2023 report, 82% of breaches involved data stored in the cloud [3]. Examples include data breaches initiated through misconfigured storage instances or through the exploitation of incomplete data deletion processes, highlighting the need for cloud-specific security responses.

Dynamic EnvironmentsCloud environments are inherently dynamic, characterized by the rapid provisioning and de-provisioning of resources, this fluidity presents a significant challenge for maintaining continuous security oversight, organizations need to be able to see what individual assets in the cloud look like at any given moment, who or what can access those, but also to be able to detect and respond to changes in real time. Unlike traditional infrastructure, detection and response in the cloud is challenging because of the ephemeral nature of some cloud assets and the velocity and volume of new app deployment – traditional signature-based detections will often struggle to work with such data.

What SOC Teams Need

Centralized VisibilityEffective security management requires a comprehensive, unified view spanning all operational environments including multi-cloud platforms and on-premises datacenters. Furthermore, in today's complex IT landscape, where organizations operate across both on-premises and various cloud environments, the need for centralized visibility becomes paramount. This comprehensive oversight is crucial for detecting anomalies and potential threats in real time, allowing SOC teams to manage security from a single source of truth, despite the dispersed nature of cloud assets and the heterogeneity of on-premises resources. By integrating these views, organizations can ensure a seamless security posture that encompasses all operational environments, enhancing their ability to respond swiftly to incidents and reduce security gaps.

AutomationGiven the vast scale and complexity of cloud operations, automation in detection and response processes is indispensable. Automated security solutions can instantly respond to threats, or adjust permissions across the cloud, enhancing both the efficiency and effectiveness of security measures.

Containment and RemediationThe capability for swift containment and remediation of security incidents is vital to minimize their impact on business operations. Automated response mechanisms that can isolate affected systems, revoke access, or reroute traffic until the threat is neutralized are essential components of modern CDR solutions.

Unpacking the Essentials: What Sets CDR Apart from NDR

While CDR and NDR share similar goals of threat mitigation, the context within cloud environments brings additional complexities:

Who: The identification of user roles and access patterns in cloud environments is crucial for detecting insider threats or compromised accounts. For example, an account behaving irregularly or accessing unusual data points may indicate a security breach.

What: Understanding what resources are deployed in the cloud (such as VMs, containers, and serverless functions) and the types of data they handle helps prioritize security efforts. Protecting data with varying sensitivity levels requires different security protocols.

Where: The geographic distribution of cloud datacenters affects regulatory compliance and data sovereignty. Security measures must consider these factors to ensure that data storage and processing comply with local laws and regulations.

How: Monitoring the configuration and usage of cloud services helps in identifying misconfigurations and anomalous usage patterns, which are common vectors for attacks. Tools that can automatically scan and rectify configurations in real time are particularly valuable in maintaining cloud security.

Key takeaways and benefits of CDR

As cloud adoption continues to surge, the strategic importance of CDR becomes increasingly evident. However, NDR vendors are well-positioned to provide these capabilities, especially those who deeply understand customer environments by learning the pattern of life of resources rather than relying on static rules and signatures.

Cloud environments, at their core, are still comprised of networks for communication. Interactions between cloud resources need to be monitored in real time, and access to these resources needs to be tracked and managed. As the cloud changes dynamically, the understanding and visualization of what is deployed and where needs to be updated quickly. Above all effective and proportional cloud-native response needs to be provided to mitigate threats and avoid business disruption.

Moreover, the ideal solutions will not only monitor network interactions but also bring in cloud contextual awareness. By combining these insights, SOC teams can gain a deeper understanding of permissions, assess risk vulnerabilities, and integrate all these elements into a single, cohesive platform. Importantly, SOC teams need to go beyond detection and response to actively mitigate potential misconfigurations and stay preventative. After all, proactive security is much better than reactive. By leveraging such comprehensive solutions, SOC teams can better equip themselves to tackle the modern cybersecurity landscape, ensuring robust, responsive, and adaptable defenses.

Learn more about Darktrace / CLOUD

Darktrace / CLOUD is intelligent cloud security powered by Self-Learning AI that delivers continuous, context-aware visibility and monitoring of cloud assets to unlock real-time detection and response​,​ and proactive cloud risk management. Read more about our cloud security solution here.

References

[1]  Gartner Forecasts Worldwide Public Cloud End-User Spending to Surpass $675 Billion in 2024

[2]  Public Cloud Market Insights, 2023 | Forrester

[3]  IBM Cost of a Data Breach 2023 Report

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
Adam Stevens
Senior Director of Product, Cloud | Darktrace

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April 28, 2026

State of AI Cybersecurity 2026: 87% of security professionals are seeing more AI-driven threats, but few feel ready to stop them

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

In part 1 of this blog series, we explored how AI is remaking the attack surface, with new tools, models, agents — and vulnerabilities — popping up just about everywhere. Now embedded in workflows across the enterprise, and often with far-reaching access to sensitive data, AI systems are quickly becoming a favorite target of cyber threat actors.

Among bad actors, though, AI is more often used as a tool than a target. Nearly 62% of organizations  experienced a social engineering attack involving a deepfake, or an incident in which bad actors used AI-generated video or audio to try to trick a biometric authentication system, compared to 32% that reported an AI prompt injection attack.

In the hands of attackers, AI can do many things. It’s being used across the entire kill chain: to supercharge reconnaissance, personalize phishing, accelerate lateral movement, and automate data exfiltration. Evidence from Anthropic demonstrates that threat actors have harnessed AI to orchestrate an entire cyber espionage campaign from end to end, allegedly running it with minimal human involvement.

CISOs inhabit a world where these increasingly sophisticated attacks are ubiquitous. Naturally, combatting AI-powered threats is top of mind among security professionals, but many worry about whether their capabilities are up to the challenge.

AI-powered threats at scale: no longer hypothetical

AI-driven threats share signature characteristics. They operate at speed and scale. Automated tools can probe multiple attack paths, search for multiple vulnerabilities and send out a barrage of phishing emails, all within seconds. The ability to attack everywhere at once, at a pace that no human operator could sustain, is the hallmark of an AI-powered threat. AI-powered threats are also dynamic. They can adapt their behavior to spread across a network more efficiently or rewrite their own code to evade detection.

Security teams are seeing the signs that they’re fighting AI-powered threats at every stage of the kill chain, and the sophistication of these threats is testing their resolve and their resources.

  • 73% say that AI-powered cyber threats are having a significant impact on their organization
  • 92% agree that these threats are forcing them to upgrade their defenses
  • 87% agree that AI is significantly increasing the sophistication and success rate of malware
  • 87% say AI is significantly increasing the workload of their security operations team

These teams now confront a challenge unlike anything they’ve seen before in their careers, and the risks are compounding across workflows, tools, data, and identities. It’s no surprise that 66% of security professionals say their role is more stressful today than it was five years ago, or that 47% report feeling overwhelmed at work.

Up all night: Security professionals’ worry list is long

Traditional security methods were never built to handle the complexity and subtlety of AI-driven behavior. Working in the trenches, defenders have deep firsthand experience of how difficult it can be to detect and stop AI-assisted threats.

Increasingly effective social engineering attacks are among their top concerns. 50% of security leaders mentioned hyper-personalized phishing campaigns as one of their biggest worries, while 40% voiced apprehension about deepfake voice fraud. These concerns are legitimate: AI-generated phishing emails are increasingly tailored to individual organizations, business activities, or individuals. Gone are the telltale signs – like grammar or spelling mistakes – that once distinguished malicious communications. Notably, 33% of the malicious emails Darktrace observed in 2025 contained over 1,000 characters, indicating probable LLM usage.

Security leaders also worry about how bad actors can leverage AI to make attacks even faster and more dynamic. 45% listed automated vulnerability scanning and exploit chaining among their biggest concerns, while 40% mentioned adaptive malware.

Confidence is lacking

Protecting against AI demands capabilities that many organizations have not yet built. It requires interpreting new indicators, uncovering the subtle intent within interactions, and recognizing when AI behavior – human or machine – could be suspicious. Leaders know that their current tools aren’t prepared for this. Nearly half don’t feel confident in their ability to defend against AI-powered attacks.

We’ve asked participants in our survey about their confidence for the last three years now. In 2024, 60% said their organizations were not adequately prepared to defend against AI-driven threats. Last year, that percentage shrunk to 45%, a possible indicator that security programs were making progress. Since then, however, the progress has apparently stalled. 46% of security leaders now feel inadequately prepared to protect their organizations amidst the current threat landscape.

Some of these differences are accentuated across different cultures. Respondents in Japan are far less confident (77% say they are not adequately prepared) than respondents in Brazil (where only 21% don’t feel prepared).

Where security programs are falling short

It’s no longer the case that cybersecurity is overlooked or underfunded by executive leadership. Across industries, management recognizes that AI-powered threats are a growing problem, and insufficient budget is near the bottom of most CISO’s list of reasons that they struggle to defend against AI-powered threats.  

It’s the things that money can’t buy – experience, knowledge, and confidence – that are holding programs back. Near the top of the list of inhibitors that survey participants mention is “insufficient knowledge or use of AI-driven countermeasures.” As bad actors embrace AI technologies en masse, this challenge is coming into clearer focus: attack-centric security tools, which rely on static rules, signatures, and historical attack patterns, were never designed to handle the complexity and subtlety of AI-driven attacks. These challenges feel new to security teams, but they are the core problems Darktrace was built to solve.  

Our Self-Learning AI develops a deep understanding of what “normal” looks like for your organization –including unique traffic patterns, end user habits, application and device profiles – so that it can detect and stop novel, dynamic threats at the first encounter. By focusing on learning the business, rather than the attack, our AI can keep pace with AI-powered threats as they evolve.

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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April 24, 2026

Email-Borne Cyber Risk: A Core Challenge for the CISO in the Age of Volume and Sophistication

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The challenge for CISOs

Despite continuous advances in security technologies, humans continue to be exploited by attackers. Credential abuse and social actions like phishing are major factors, accounting for around 60% of all breaches. These attacks rely less on technical vulnerabilities and more on exploiting human behavior and organizational processes. 

From my perspective as a former CISO, protecting humans concentrates three of today’s most pressing challenges: the sheer volume of email-based threats, their increasing sophistication, and the limitations of traditional employee awareness programs in moving the needle on risk. 

My personal experience of security awareness training as a CISO

With over 20 years’ experience as an ICT and Cybersecurity leader across various international organizations, I’ve seen security awareness training (SAT) in many guises. And while the cyber landscape is evolving in every direction, the effectiveness of SAT is reaching a plateau.  

Most programs I’ve seen follow a familiar pattern. Training is delivered through a combination of eLearning modules and internal sessions designed to reinforce IT policies. Employees are typically required to complete a slide deck or video, followed by a multiple-choice quiz. Occasional phishing simulations are distributed throughout the year.

The content is often static and unpersonalized, based on known threats that may already be outdated. Every employee regardless of role or risk exposure receives the same training and the same simulated phishing templates, from front-desk staff to the CEO.

The problem with traditional SAT programs

The issue with the approach to SAT outlined above is that the distribution of power is imbalanced. Humans will always be fallible, particularly when faced with increasingly sophisticated attacks. Providing generic, low-context training risks creating false confidence rather than genuine resilience. Let’s look at some of the problems in detail.

Timing and delivery

Employees today operate under constant cognitive load, making lots of rapid decisions every day to reduce their email volumes. Yet if employees are completing training annually, or on an ad hoc basis, it becomes a standalone occurrence rather than a continuous habit.  

As a result, retention is low. Employees often forget the lessons within weeks, a phenomenon known as the ‘Ebbinghaus Forgetting Curve.’

The graph illustrates that when you first learn something, the information disappears at an exponential rate without retention. In fact, according to the curve, you forget 50% of all new information within a day, and 90% of all new information within a week.  

Simultaneously, most training is conducted within a separate interface. Because it takes place away from the actual moment of decision-making, the "teachable moment" is lost. There is a cognitive disconnect between the action (clicking a link in Outlook) and the education (watching a video in a browser). 

People

In the context of professional risk management, the risks faced by different users are different. Static learning such as everyone receiving the same ‘Password Reset’ email doesn’t help users prepare for the specific threats they are likely to face. It also contributes to user fatigue, driven by repetitive training. And if users receive tests at the same time, news spreads among colleagues, hurting the efficacy of the test.  

Staff turnover introduces further risk. In many organizations, new employees gain access to systems before receiving meaningful training, reducing onboarding to little more than policy acknowledgment.

Measuring success

In my experience, solutions are standalone, without any correlation to other tools in the security stack. In some cases, the programs are delivered by HR rather than the security team, creating a complete silo.  

As a result, SAT is often perceived as a compliance exercise rather than a capability building function. The result is that poor-quality training does little to reduce the likelihood of compromise, regardless of completion rates or quiz performance.

What a modern SAT solution should look like

For today’s CISO, email represents the convergence point of high-volume, high-impact, and human-centric threats. Despite significant security investments, it remains one of the most difficult channels to secure effectively. Given these constraints, CISOs must evolve their approach to SAT.

Success lies in a balanced strategy one that combines advanced technology, attack surface reduction, and pragmatic user enablement, without over-relying on human vigilance as the final line of defense.

This means moving beyond traditional SAT toward continuous, contextual awareness, realistic simulations, and tight integration with security outcomes.

Three requirements for a modern SAT solution

  • Invisible protection: The optimum security solution is one that assists users without impeding their experience. The objective is to enhance human capabilities, rather than simply delivering a lecture. 
  • Real-time feedback: Rather than a monthly quiz, the ideal system would provide a prompt or warning when a user is about to engage with something suspicious. 
  • Positive culture: Shifting the focus away from a "gotcha" culture, which is a contributing factor to a resentment, and instead empowers employees to serve as "sensors" for the company. 

Discover how personalized security coaching can strengthen your human layer and make your email defenses more resilient. Explore Darktrace / Adaptive Human Defense.

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About the author
Karim Benslimane
VP, Field CISO
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