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December 5, 2024

Protecting Your Hybrid Cloud: The Future of Cloud Security in 2025 and Beyond

In the coming years, cloud security will not only need to adapt to increasingly complex environments as ecosystems become more distributed, but also to rapidly evolving threats like supply chain attacks, advanced misconfiguration exploits, and credential theft. AI-powered cloud security tools can help security teams keep up.
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
Kellie Regan
Director, Product Marketing - Cloud Security
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05
Dec 2024

Cloud security in 2025

The future of cybersecurity is being shaped by the rapid adoption of cloud technologies.

As Gartner reports, “By 2027, more than 70% of enterprises will use industry cloud platforms to accelerate their business initiatives, up from less than 15% in 2023” [1].

As organizations continue to transition workloads and sensitive data to cloud environments, the complexity of securing distributed infrastructures grows. In 2025, cloud security will need to address increasingly sophisticated threats with innovative approaches to ensure resilience and trust.

Emerging threats in cloud security:

  1. Supply chain attacks in the cloud: Threat actors are targeting vulnerabilities in cloud networks, including third-party integrations and APIs. These attacks can have wide-spanning impacts, jeopardizing data security and possibly even compromising multiple organizations at once. As a result, robust detection and response capabilities are essential to identify and neutralize these attacks before they escalate.
  2. Advanced misconfiguration exploits: Misconfigurations remain a leading cause of cloud security breaches. Attackers are exploiting these vulnerabilities across dynamic infrastructures, underscoring the need for tools that provide continuous compliance validation in the future of cloud computing.
  3. Credential theft with evolving Tactics, Techniques, and Procedures (TTPs): While credential theft can result from phishing attacks, it can also happen through other means like malware, lateral movement, data breaches, weak and reused passwords, and social engineering. Adversarial innovation in carrying out these attacks requires security teams to use proactive defense strategies.
  4. Insider threats and privilege misuse: Inadequate monitoring of Identity and Access Management (IAM) in cloud security increases the risk of insider threats. The adoption of zero-trust architectures is key to mitigating these risks.
  5. Threats exploiting dynamic cloud scaling: Attackers take advantage of the dynamic nature of cloud computing, leveraging ephemeral workloads and autoscaling features to evade detection. This makes adaptive and AI-driven detection and response critical because it can more easily parse behavioral data that would take human security teams longer to investigate.

Where the industry is headed

In 2025, cloud infrastructures will become even more distributed and interconnected. Multi-cloud and hybrid models will dominate, so organizations will have to optimize workloads across platforms. At the same time, the growing adoption of edge computing and containerized applications will decentralize operations further. These trends demand security solutions that are agile, unified, and capable of adapting to rapid changes in cloud environments.

Emerging challenges in securing cloud environments

The transition to highly distributed and dynamic cloud ecosystems introduces the following key challenges:

  1. Limited visibility
    As organizations adopt multiple platforms and services, gaining a unified view of cloud architectures becomes increasingly difficult. This lack of visibility makes it unclear where sensitive data resides, which identities can access it and how, and if there are potential vulnerabilities in configurations and API infrastructure. Without end-to-end monitoring, detecting and mitigating threats in real time becomes nearly impossible.
  2. Complex environments
    The blend of public, private, and hybrid clouds, coupled with diverse service types (SaaS, PaaS, IaaS), creates a security landscape rife with configuration challenges. Each layer adds complexity, increasing the risk of misconfigurations, inconsistent policy enforcement, and gaps in defenses – all of which attackers may exploit.
  3. Dynamic nature of cloud
    Cloud infrastructures are designed to scale resources on demand, but this fluidity poses significant challenges to threat detection and incident response. Changes in configurations, ephemeral workloads, and fluctuating access points mean that on-prem network security mindsets cannot be applied to cloud security and many traditional cloud security approaches still fall short in addressing threats in real time.

Looking forward: Protecting the cloud in 2025 and beyond

Addressing these challenges requires innovation in visibility tools, AI-driven threat detection, and policy automation. The future of cloud security hinges on solutions that adapt to complexity and scale, ensuring organizations can securely navigate the growing demands of cloud-first operations.

Unsupervised Machine Learning (ML) enhances cloud security

Unlike supervised ML, which relies on labeled datasets, unsupervised ML identifies patterns and deviations in data without predefined rules, making it particularly effective in dynamic and unpredictable environments like the cloud. By analyzing the baseline behavior in cloud environments, such as typical user activity, network traffic, and resource utilization, unsupervised ML and supporting models can identify behavioral deviations linked to suspicious activity like unusual login times, irregular API calls, or unexpected data transfers, therefore flagging them as potential threats.

Learn more about how multi-layered ML improves real-time cloud detection and response in the data sheet “AI enhances cloud security.

Agent vs. Agentless deployment

The future of cloud security is increasingly focused on combining agent-based and agentless solutions to address the complexities of hybrid and multi-cloud environments.

This integrated approach enables organizations to align security measures with the specific risks and operational needs of their assets, ensuring comprehensive protection.

Agent-based systems provide deep monitoring and active threat mitigation, making them ideal for high-security environments like financial services and healthcare, where compliance and sensitive data require stringent safeguards.

Meanwhile, agentless systems offer broad visibility and scalability, seamlessly covering dynamic cloud resources without the need for extensive deployment efforts.

Together, a combination of these approaches ensures that all parts of the cloud environment are protected according to their unique risk profiles and functional requirements.

The growing adoption of this strategy highlights a shift toward adaptive, scalable, and efficient security solutions, reflecting the priorities of a rapidly evolving cloud landscape.

To learn more about how these technologies are reshaping cloud defenses, read the blog “Agent vs. Agentless Cloud Security: Why Deployment Methods Matter.”

Shifting responsibilities: security teams must get more comfortable with cloud mindsets

Traditionally, many organizations left cloud security to dedicated cloud teams. However, it is becoming more and more common for security teams to take on the responsibilities of securing the cloud. This is also true of organizations undergoing cloud migration and spinning up cloud infrastructure for the first time.

Notably, the usual approaches to other types of cybersecurity can’t be applied the exact same way to the cloud. With the inherent dynamism and flexibility of the cloud, the necessary security mindset differs greatly from those for the network or datacenters, with which security teams may be more familiar.

For example, IAM is both critical and distinct to cloud computing, and the associated policies, rules, and downstream impacts require intentional care. IAM rules not only govern people, but also non-human entities like service accounts, API keys, and OAuth tokens. These considerations are unique to cloud security, and established teams may need to learn new skills to reduce security gaps in the cloud.

Discover more about the teams that impact modern cloud security in the blog "Cloud Security Evolution: Why Security Teams are Taking the Lead."

The importance of visibility: The future of network security in the cloud

As organizations transition to cloud environments, they still have much of their data in on-premises networks, meaning that maintaining visibility across both on-premises and cloud environments is essential for securing critical assets and ensuring seamless operations. Without a unified security strategy, gaps between these infrastructures and the teams which manage them can leave organizations vulnerable to cyber-attacks.

Shared visibility across both on-premises and cloud environments unifies SecOps and DevOps teams, enabling them to generate actionable insights and develop a cohesive approach. This alignment helps confidently mitigate risks across the cloud and network while streamlining workflows and accelerating the cloud migration journey—all without compromising security or operational continuity.

Read more about the importance of end-to-end visibility in the modern threat landscape in the blog "Breaking Silos: Why Unified Security is Critical in Hybrid World."

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Ready to transform your cloud security approach? Download the CISO's Guide to Cloud Security now!

References:

[1] Gartner, June 5, 2024, “The Expanding Enterprise Investment in Cloud Security,” Available at: https://www.gartner.com/en/newsroom/press-releases/2024-06-05-the-expanding-enterprise-investment-in-cloud-security

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
Kellie Regan
Director, Product Marketing - Cloud Security

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Compliance

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November 25, 2025

UK Cyber Security & Resilience Bill: What Organizations Need to Know

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Why the Bill has been introduced

The UK’s cyber threat landscape has evolved dramatically since the 2018 NIS regime was introduced. Incidents such as the Synnovis attack against hospitals and the British Library ransomware attack show how quickly operational risk can become public harm. In this context, the UK Department for Science, Innovation and Technology estimates that cyber-attacks cost UK businesses around £14.7 billion each year.

At the same time, the widespread adoption of AI has expanded organisations’ attack surfaces and empowered threat actors to launch more effective and sophisticated activities, including crafting convincing phishing campaigns, exploiting vulnerabilities and initiating ransomware attacks at unprecedented speed and scale.  

The CSRB responds to these challenges by widening who is regulated, accelerating incident reporting and tightening supply chain accountability, while enabling rapid updates that keep pace with technology and emerging risks.

Key provisions of the Cyber Security and Resilience Bill

A wider set of organisations in scope

The Bill significantly broadens the range of organisations regulated under the NIS framework.

  • Managed service providers (MSPs) - medium and large MSPs, including MSSPs, managed SOCs, SIEM providers and similar services,will now fall under NIS obligations due to their systemic importance and privileged access to client systems. The Information Commissioner’s Office (ICO) will act as the regulator. Government analysis anticipates that a further 900 to 1,100 MSPs will be in scope.
  • Data infrastructure is now recognised as essential to the functioning of the economy and public services. Medium and large data centres, as well as enterprise facilities meeting specified thresholds, will be required to implement appropriate and proportionate measures to manage cyber risk. Oversight will be shared between DSIT and Ofcom, with Ofcom serving as the operational regulator.
  • Organisations that manage electrical loads for smart appliances, such as those supporting EV charging during peak times, are now within scope.

These additions sit alongside existing NIS-regulated sectors such as transport, energy, water, health, digital infrastructure, and certain digital services (including online marketplaces, search engines, and cloud computing).

Stronger supply chain requirements

Under the CSRB, regulators can now designate third-party suppliers as ‘designated critical suppliers’ (DCS) when certain threshold criteria are met and where disruption could have significant knock-on effects. Designated suppliers will be subject to the same security and incident-reporting obligations as Operators of Essential Services (OES) and Relevant Digital Service Providers (RDSPs).

Government will scope the supply chain duties for OES and RDSPs via secondary legislation, following consultation. infrastructure incidents where a single supplier’s compromise caused widespread disruption.

Faster incident reporting

Sector-specific regulators, 12 in total, will be responsible for implementing the CSRB, allowing for more effective and consistent reporting. In addition, the CSRB introduces a two-stage reporting process and expands incident reporting criteria. Regulated entities must submit an initial notification within 24 hours of becoming aware of a significant incident, followed by an incident report within 72 hours. Incident reporting criteria are also broadened to capture incidents beyond those which actually resulted in an interruption, ensuring earlier visibility for regulators and the National Cyber Security Centre (NCSC). The importance of information sharing across agencies, law enforcement and regulators is also facilitated by the CSRB.

The reforms also require data centres and managed service providers to notify affected customers where they are likely to have been impacted by a cyber incident.

An agile regulatory framework

To keep pace with technological change, the CSRB will enable the Secretary of State to update elements of the framework via secondary legislation. Supporting materials such as the NCSC Cyber Assessment Framework (CAF) are to be "put on a stronger footing” allowing for requirements to be more easily followed, managed and updated. Regulators will also now be able to recover full costs associated with NIS duties meaning they are better resourced to carry out their associated responsibilities.

Relevant Managed Service Providers must identify and take appropriate and proportionate measures to manage risks to the systems they rely on for providing services within the UK. Importantly, these measures must, having regard to the state of the art, ensure a level of security appropriate to the risk posed, and prevent or minimise the impact of incidents.

The Secretary of State will also be empowered to issue a Statement of Strategic Priorities, setting cross-regime outcomes to drive consistency across the 12 competent authorities responsible for implementation.

Penalties

The enforcement framework will be strengthened, with maximum fines aligned with comparable regimes such as the GDPR, which incorporate maximums tied to turnover. Under the CSRB, maximum penalties for more serious breaches could be up to £17 million or 4% of global turnover, whichever is higher.

Next steps

The Bill is expected to progress through Parliament over the course of 2025 and early 2026, with Royal Assent anticipated in 2026. Once enacted, most operational measures will not take immediate effect. Instead, Government will bring key components into force through secondary legislation following further consultation, providing regulators and industry with time to adjust practices and prepare for compliance.

Anticipated timeline

  • 2025-2026: Parliamentary scrutiny and passage;
  • 2026: Royal Assent;  
  • 2026 consultation: DSIT intends to consult on detailed implementation;
  • From 2026 onwards: Phased implementation via secondary legislation, following further consultation led by DSIT.

How Darktrace can help

The CSRB represents a step change in how the UK approaches digital risk, shifting the focus from compliance to resilience.

Darktrace can help organisations operationalise this shift by using AI to detect, investigate and respond to emerging threats at machine speed, before they escalate into incidents requiring regulatory notification. Proactive tools which can be included in the Darktrace platform allow security teams to stress-test defences, map supply chain exposure and rehearse recovery scenarios, directly supporting the CSRB’s focus on resilience, transparency and rapid response. If an incident does occur, Darktrace’s autonomous agent, Cyber AI Analyst, can accelerate investigations and provide a view of every stage of the attack chain, supporting timely reporting.  

Darktrace’s AI can provide organisations with a vital lens into both internal and external cyber risk. By continuously learning patterns of behaviour across interconnected systems, Darktrace can flag potential compromise or disruption to detect supply chain risk before it impacts your organisation.

In a landscape where compliance and resilience go hand in hand, Darktrace can equip organisations to stay ahead of both evolving threats and evolving regulatory requirements.

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November 20, 2025

Managing OT Remote Access with Zero Trust Control & AI Driven Detection

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The shift toward IT-OT convergence

Recently, industrial environments have become more connected and dependent on external collaboration. As a result, truly air-gapped OT systems have become less of a reality, especially when working with OEM-managed assets, legacy equipment requiring remote diagnostics, or third-party integrators who routinely connect in.

This convergence, whether it’s driven by digital transformation mandates or operational efficiency goals, are making OT environments more connected, more automated, and more intertwined with IT systems. While this convergence opens new possibilities, it also exposes the environment to risks that traditional OT architectures were never designed to withstand.

The modernization gap and why visibility alone isn’t enough

The push toward modernization has introduced new technology into industrial environments, creating convergence between IT and OT environments, and resulting in a lack of visibility. However, regaining that visibility is just a starting point. Visibility only tells you what is connected, not how access should be governed. And this is where the divide between IT and OT becomes unavoidable.

Security strategies that work well in IT often fall short in OT, where even small missteps can lead to environmental risk, safety incidents, or costly disruptions. Add in mounting regulatory pressure to enforce secure access, enforce segmentation, and demonstrate accountability, and it becomes clear: visibility alone is no longer sufficient. What industrial environments need now is precision. They need control. And they need to implement both without interrupting operations. All this requires identity-based access controls, real-time session oversight, and continuous behavioral detection.

The risk of unmonitored remote access

This risk becomes most evident during critical moments, such as when an OEM needs urgent access to troubleshoot a malfunctioning asset.

Under that time pressure, access is often provisioned quickly with minimal verification, bypassing established processes. Once inside, there’s little to no real-time oversight of user actions whether they’re executing commands, changing configurations, or moving laterally across the network. These actions typically go unlogged or unnoticed until something breaks. At that point, teams are stuck piecing together fragmented logs or post-incident forensics, with no clear line of accountability.  

In environments where uptime is critical and safety is non-negotiable, this level of uncertainty simply isn’t sustainable.

The visibility gap: Who’s doing what, and when?

The fundamental issue we encounter is the disconnect between who has access and what they are doing with it.  

Traditional access management tools may validate credentials and restrict entry points, but they rarely provide real-time visibility into in-session activity. Even fewer can distinguish between expected vendor behavior and subtle signs of compromise, misuse or misconfiguration.  

As a result, OT and security teams are often left blind to the most critical part of the puzzle, intent and behavior.

Closing the gaps with zero trust controls and AI‑driven detection

Managing remote access in OT is no longer just about granting a connection, it’s about enforcing strict access parameters while continuously monitoring for abnormal behavior. This requires a two-pronged approach: precision access control, and intelligent, real-time detection.

Zero Trust access controls provide the foundation. By enforcing identity-based, just-in-time permissions, OT environments can ensure that vendors and remote users only access the systems they’re explicitly authorized to interact with, and only for the time they need. These controls should be granular enough to limit access down to specific devices, commands, or functions. By applying these principles consistently across the Purdue Model, organizations can eliminate reliance on catch-all VPN tunnels, jump servers, and brittle firewall exceptions that expose the environment to excess risk.

Access control is only one part of the equation

Darktrace / OT complements zero trust controls with continuous, AI-driven behavioral detection. Rather than relying on static rules or pre-defined signatures, Darktrace uses Self-Learning AI to build a live, evolving understanding of what’s “normal” in the environment, across every device, protocol, and user. This enables real-time detection of subtle misconfigurations, credential misuse, or lateral movement as they happen, not after the fact.

By correlating user identity and session activity with behavioral analytics, Darktrace gives organizations the full picture: who accessed which system, what actions they performed, how those actions compared to historical norms, and whether any deviations occurred. It eliminates guesswork around remote access sessions and replaces it with clear, contextual insight.

Importantly, Darktrace distinguishes between operational noise and true cyber-relevant anomalies. Unlike other tools that lump everything, from CVE alerts to routine activity, into a single stream, Darktrace separates legitimate remote access behavior from potential misuse or abuse. This means organizations can both audit access from a compliance standpoint and be confident that if a session is ever exploited, the misuse will be surfaced as a high-fidelity, cyber-relevant alert. This approach serves as a compensating control, ensuring that even if access is overextended or misused, the behavior is still visible and actionable.

If a session deviates from learned baselines, such as an unusual command sequence, new lateral movement path, or activity outside of scheduled hours, Darktrace can flag it immediately. These insights can be used to trigger manual investigation or automated enforcement actions, such as access revocation or session isolation, depending on policy.

This layered approach enables real-time decision-making, supports uninterrupted operations, and delivers complete accountability for all remote activity, without slowing down critical work or disrupting industrial workflows.

Where Zero Trust Access Meets AI‑Driven Oversight:

  • Granular Access Enforcement: Role-based, just-in-time access that aligns with Zero Trust principles and meets compliance expectations.
  • Context-Enriched Threat Detection: Self-Learning AI detects anomalous OT behavior in real time and ties threats to access events and user activity.
  • Automated Session Oversight: Behavioral anomalies can trigger alerting or automated controls, reducing time-to-contain while preserving uptime.
  • Full Visibility Across Purdue Layers: Correlated data connects remote access events with device-level behavior, spanning IT and OT layers.
  • Scalable, Passive Monitoring: Passive behavioral learning enables coverage across legacy systems and air-gapped environments, no signatures, agents, or intrusive scans required.

Complete security without compromise

We no longer have to choose between operational agility and security control, or between visibility and simplicity. A Zero Trust approach, reinforced by real-time AI detection, enables secure remote access that is both permission-aware and behavior-aware, tailored to the realities of industrial operations and scalable across diverse environments.

Because when it comes to protecting critical infrastructure, access without detection is a risk and detection without access control is incomplete.

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About the author
Pallavi Singh
Product Marketing Manager, OT Security & Compliance
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