Transforming Real-Time Protection with Cloud-Delivered Security Services

Discover how unified prevention provides IT leaders with real-time protection across every attack surface.

The line between innovation and exposure has never been blurred in today’s hyperconnected digital world. Every new device, application and cloud workload expands the modern attack surface, creating endless opportunities for adversaries who are scaling faster and becoming more sophisticated than ever before. The threat landscape is no longer defined by isolated malware or phishing emails. The modern attack surface has evolved into a dynamic, adaptive ecosystem, driven by automation and artificial intelligence. Traditional security is no longer enough against AI-powered adversaries; protecting the modern attack surface demands a unified, intelligent Cloud-Delivered Security Services (CDSS) platform.

Attackers have learned to weaponize the same innovations that once gave defenders an advantage. Generative AI now enables them to craft convincing phishing messages, generate polymorphic malware that changes with every delivery, and automate reconnaissance at an unprecedented scale. Ransomware groups operate with the speed and agility of modern startups, using AI to identify weaknesses while staying one step ahead of detection. The result is an era where breaches unfold in minutes rather than days. Organizations are left with little room for error, underscoring the urgent need for security that goes beyond traditional approaches.

The Power of a Unified, Cloud-Delivered Security Service Platform

The power of our Cloud-Delivered Security Services lies in our ability to bring together every layer of protection into a single, intelligent, connected system. This unified platform combines Advanced Threat Prevention, Advanced WildFire^® (AWF), Advanced DNS Security (ADNS) and Advanced URL Filtering (AURL) into a single AI-powered fabric that operates at the speed of the cloud.

Powered by Precision AI^®, this framework delivers real-time contextual awareness across every stage of the attack lifecycle. It continuously analyzes billions of signals across networks, users and applications to transform raw data into actionable insights. This capability enables organizations to move from reactive detection to proactive prevention, stopping threats before they can disrupt operations.

Every day, our CDSS services analyze up to 5.43 billion new events, detect nearly 8.95 million never-before-seen attacks, and block up to 30.9 billion threats inline. This scale of visibility is strengthened by AI that’s trained on shared threat data from more than 70,000 customers, creating a powerful network effect that delivers patient-zero prevention everywhere. This depth of intelligence provides the visibility and context needed to understand and stop even the most sophisticated attacks as they evolve.

Shared telemetry flows naturally across services, helping ensure threats are detected and prevented without operating in silos. A phishing domain identified by Advanced DNS Security can immediately inform Advanced URL Filtering to block the malicious site. When Advanced WildFire uncovers a new zero-day technique or malicious artifact, that intelligence is shared instantly across the CDSS intelligence layer. Inline services, like Advanced Threat Prevention and Advanced URL Filtering, are enabled to strengthen protections in real time without manual intervention.

For IT leaders and security teams, this unified approach delivers comprehensive visibility and protection that keeps pace with their environment. Continuous intelligence adapts as conditions change, reducing complexity and improving operational efficiency. With consistent policy enforcement, faster decision-making and unified management across the enterprise, organizations can shift their focus from maintenance to innovation and growth.

The Moment Traditional Security Stopped Being Enough

There was a time when traditional network security was enough. Perimeter defenses and signature-based tools could reliably detect and block most threats before they caused harm. For years, this layered approach gave organizations a sense of confidence and control. But that moment has passed.

Our Unit 42® team has found that attacks are now faster, more sophisticated and more disruptive than ever, with 86% of major incidents in 2024 resulting in business disruption. This shift underscores how quickly traditional defenses are being outpaced and why yesterday’s security models no longer match today’s threat landscape.

Traditional, siloed architectures simply cannot keep up with modern attackers. What once served as a strong defense is now outmatched by adversaries who use AI to move faster and slip through the cracks of static security controls. Attackers no longer need to rely on predictable patterns or known exploits. They can use machine learning to probe defenses, mimic legitimate activity and disguise malicious activity within normal traffic, allowing them to bypass systems once they are considered unbreakable.

Older security products that depend on static signatures or manual policy updates cannot match this speed and scale. They respond to what has already happened, not to what is happening right now. By the time a new rule is written or a patch is applied, the threat has already evolved. Fragmented visibility and delayed response times give adversaries the upper hand, leaving IT teams defending blind against threats that adapt and shift faster than their defenses ever could.

In an effort to compensate, many organizations continue to add more tools: One for web filtering, one for DNS, one for malware analysis and one for data protection. While each solution provides value, they rarely work together. The result is an overcomplicated ecosystem of disconnected products that create visibility gaps, duplicate alerts, inconsistent policy enforcement and operational overhead. These gaps are exactly where attackers find their opportunity.

The moment traditional security stopped being enough was the moment attackers learned to think and move like machines. The rise of AI-powered threats marked the end of static defense and the beginning of a new kind of warfare, one that demands prevention and is predictive, adaptive and unified.

Today, enterprises don’t need more point products. They need a single, intelligent security fabric so they can see, understand and act across every vector, from DNS to SaaS to endpoint, in one coordinated motion. Attackers increasingly weaponize GenAI to craft more evasive phishing pages, malware and domain infrastructures. So, security teams must rely on defenses that can counter these techniques in real time by effectively battling AI with AI.

That is where cloud-delivered security services (CDSS) redefine the game, bringing AI-driven prevention to every corner of the network.

Your Defense Is Only as Strong as What’s Enabled

Having the proper security tools is only part of the equation. Real protection comes when those tools are fully enabled, integrated and working together to secure the organization. Cloud-delivered security services deliver their greatest value when they are live and continuously analyzing traffic, sharing intelligence and adapting in real time to support the business.

Too often, organizations have the right capabilities in place but leave them underutilized or inactive. Protection begins the moment each service is turned on and working in unison to deliver real-time prevention at scale. Ensuring that these capabilities are fully enabled and actively defending the network is what turns investment into impact.

Prevention is about readiness, not reaction. The most resilient organizations are those that activate early, integrate completely and allow automation to amplify what human oversight cannot. When IT leaders enable Advanced Threat Prevention, AWF, ADNS and AURL, prevention becomes continuous, intelligent and aligned with the pace of modern threats.

The power of our CDSS lies in both their advanced technology and the unity they create. Together, these services form an intelligent defense that connects detection, prevention and response into one seamless operation, all powered by Precision AI.

Now, with AI reshaping both innovation and risk, CDSS helps organizations stay confidently ahead. IT leaders who enable these capabilities strengthen visibility, simplify operations and elevate their overall security posture.

Fully enable your defenses and have them ready to prevent threats at each stage of the attack lifecycle. Learn more about activating CDSS through Strata™ Cloud manager or speak with your Palo Alto Networks representative to see how unified, AI-powered prevention can strengthen your organization’s security posture.

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Key Takeaways

1. Traditional Security Is Insufficient Against Modern Threats
   The rise of AI and automation has created an era in which attackers move faster and are more sophisticated than traditional, siloed security products can handle, leading to an increasing number of major incidents that disrupt business.
2. Unified Cloud-Delivered Security Services (CDSS) Are Necessary for Proactive Prevention
   Protecting the modern attack surface requires a single, intelligent, connected CDSS platform that unifies all layers of protection (e.g., Advanced Threat Prevention, AWF, ADNS, AURL) into an AI-powered fabric, enabling proactive, real-time prevention rather than reactive detection.
3. Real Protection Depends on Full Activation and Integration
   Having the right security tools is only part of the solution. The greatest value and protection are realized when your fully enabled CDSS is integrated and working in unison to continuously analyze traffic and share intelligence.

The post The Power of Unity appeared first on Palo Alto Networks Blog.

The transformative potential of artificial intelligence (AI) across industries is undeniable. But realizing AI's true value hinges on three cybersecurity imperatives: Understanding the AI-cybersecurity nexus, harnessing AI to supercharge cyber defense, and embedding security into AI tools from the ground up through Secure AI by Design.

Nowhere is this convergence more urgent than in financial services. Sitting at the center of our global economy, financial institutions face a dual mandate: Embrace AI for cybersecurity and cybersecurity for AI.

I was honored to cover these key principals in my testimony before the House Committee on Financial Services, led by Chairman French Hill. The hearing, entitled “From Principles to Policy: Enabling 21st Century AI Innovation in Financial Services” convened witnesses from Palo Alto Networks, Google, NASDAQ, Zillow and Public Citizen. Together, we examined AI use cases in the financial services and housing sectors, including those specific to cybersecurity. We assessed how existing laws and frameworks apply in the age of AI.

The Defense Advantage Is AI-Powered Security Operations

Attacks have become faster, with the time from compromise to data exfiltration now 100 times faster than four years ago. The financial sector bears disproportionate risk, given the value of its data and interconnected systems, while firms contend with evolving regulatory expectations, talent shortages and the persistent tendency to elevate cybersecurity only after an incident.

Generative and agentic AI intensify these pressures by accelerating every phase of the attack chain, from deepfake-driven fraud to tailored spear phishing campaigns. Our researchers at Unit 42^® have found that agentic AI, autonomous systems that can reason and act without human intervention, can compress what was once a multiday ransomware campaign into roughly 25 minutes.

To keep pace, financial institutions must pivot to AI-driven defenses that operate at machine speed.

Security operations centers (SOC) have long been overwhelmed by traditional alerts and fragmented data. Security teams, forced into manual triage across dozens of disparate tools, face an inefficient model that leaves vulnerabilities exposed, burns out analysts and makes it impossible to operate at the speed necessary to outpace modern attacks.

The average enterprise SOC ingests data from 83 security solutions across 29 vendors. In 75% of breaches, logging existed that should have flagged anomalous behavior, but critical signals were buried. With 90% of SOCs still relying on manual processes, adversaries have the clear advantage.

AI-driven SOCs flip this paradigm, acting as a force multiplier to substantially reduce detection and response times. To illustrate the scale of this necessity, consider our own security operations. Palo Alto Networks SOC analyzes over 90 billion events daily. Without AI, this would be an impossible task for human analysts. But by applying AI, we distill that down to a single actionable incident.

Financial institutions migrating to AI-driven SOC platforms are seeing transformative results:

• One customer reduced the Mean Time to Respond (MTTR) from one day to 14 minutes.
• Another prevented 22,831 threats and processed 113,271 threat indicators in less than 5 seconds.
• A large bank saved 180 hours per year by automating security information and event management reporting; 500 hours through automated data collection; 360 hours by automating four Chief Technology Officer playbooks; and 240 hours with automated threat intelligence enrichment.

These improvements are critical to stopping threat actors. But none of this would be possible without AI.

Securing the New AI Attack Surface

As AI adoption grows, it will further expand the attack surface, creating new vectors targeting training data and model environments. AI's rapid growth is outpacing the adoption of security measures designed to protect it. Nearly three-quarters of S&P 500 companies now flag AI as a material risk in their public disclosures, up from just 12% in 2023.

Traditional security tools rely on static rules that miss advanced attacks, like multistep prompt injections or adversarial manipulations. Autonomous AI agents can take unpredictable actions that are difficult to monitor with legacy methods.

Rapid AI adoption has exposed organizations' infrastructure, data, models, applications and agents to unique threats. Unlike traditional cyber exploits that target software vulnerabilities, AI-specific attacks can manipulate the foundation of how an AI system learns and operates.

A Secure AI by Design

Even with an understanding of the risks, many organizations struggle with the lack of clarity on what effective AI security looks like in practice. Recognizing the gap between intent and execution, Palo Alto Networks developed a Secure AI by Design policy roadmap that provides organizations with a comprehensive roadmap that integrates security throughout the entire AI lifecycle.

A proactive stance ensures security is a feature, not an afterthought, crucial for building trust, maintaining compliance and mitigating risks. The approach addresses four imperatives organizations most pressingly face in AI adoption:

1. Secure the use of external AI tools.

2. Secure the underlying AI infrastructure and data.

3. Safely build and deploy AI applications.

4. Monitor and control AI agents.

The Path Forward

For financial institutions, Secure AI by Design must be anchored in enterprise governance. Institutions should maintain risk-tiered AI inventories, enforce strict access controls and implement testing commensurate with risk. Governance structures should enable board oversight and align with established model risk practices.

Policymakers also have a critical role to play in promoting AI-driven security operations, championing voluntary Secure AI by Design frameworks, ensuring policies safeguard innovation, enabling controlled experimentation and strengthening public-private collaboration.

Ultimately, the financial institutions that will thrive will recognize cybersecurity as the foundation that makes innovation possible. By embracing AI-driven defenses and securing AI systems from the ground up, the sector can confidently unlock AI's transformative potential while safeguarding the trust and stability that underpin the global economy.

Read the full testimony to learn more about how cybersecurity can enable AI innovation in financial services.

The post From the Hill: The AI-Cybersecurity Imperative in Financial Services appeared first on Palo Alto Networks Blog.

From Fragmented Fences to Cohesive Control

The attack surface for today’s enterprises is incredibly heterogeneous and dynamic. Applications and data are in constant motion, spanning public clouds, private data centers and edge locations. Users connect from anywhere.

For security leaders, this environment has led to an explosion in not only operational complexity, but in many cases, uncertainty. ​​Together, Nutanix and Palo Alto Networks enable security to finally match the speed and scale of these dynamic hybrid cloud environments.

The security ecosystem has become vast and complex. Point solutions accumulate to address specific gaps, yet each adds another interface, another policy language and another integration to manage. However well intentioned, this sprawl can lead directly to fractured visibility, overlapping tools and operational fatigue.

Elevate Perimeter Protection to Defense-in-Depth

Enterprises today face unprecedented security complexity as hybrid and multicloud environments become the new normal. Currently, 94% of enterprises use some form of cloud service, while 89% report having a multicloud strategy in place. This distributed reality means security is paramount: while managing cloud spending is the number one operational challenge (82% overall), security remains a major concern, affecting 79% of all organizations.

Hybrid cloud adoption offers agility, but it also introduces distinct security challenges that strain traditional approaches. Adversaries have taken notice. Hybrid and multicloud environments are prime targets because they connect sensitive data, privileged accounts and critical systems across public, and on-premises infrastructure. Perimeter-based security models, built for static networks and centralized data centers, cannot keep pace in a world where apps and data continuously move between platforms.

Defense-in-depth has become essential for addressing the inherent dynamism of today’s environments. Network visibility is required to monitor and contain east-west traffic and lateral movement of threats inside cloud environments. Identity controls must verify every user, device and interaction across a distributed workforce. Data protection must follow sensitive information as it traverses multiple clouds, data centers and edge locations.

Yet managing these protections as distinct layers is no longer viable. Each cloud provider introduces its own native security controls. Each additional tool adds another interface and another policy set to maintain. Defense-in-depth only achieves its purpose when its layers are fully unified, providing consistent control enforcement from the edge to the core, comprehensive visibility across traffic, and essential data protections for all workloads, wherever they reside.

Freedom of Choice Without Fragmentation

Hybrid environments span public clouds, private infrastructure, SaaS ecosystems and legacy on-premises systems. No single vendor can realistically cover that entire landscape, and forcing security into a single closed ecosystem risks creating gaps where those environments meet.

The answer lies in an open ecosystem approach that allows organizations to assemble best-of-breed capabilities rather than being locked into a single provider’s stack.

This flexibility empowers security teams to adapt to the unique requirements of each environment while still operating through a unified security model. Policies can be applied consistently, intelligence can be shared across layers, and protections can move in step with workloads, regardless of platform. In short, this model can effectively support freedom of choice while relieving the operational burden of managing hybrid and multicloud security.

A Unified Security Layer Across Every Environment

Open ecosystems solve the problem of choice. What remains is the challenge of bringing those best-of-breed capabilities together into a solution that is coherent and scalable.

To transform defense-in-depth from a conceptual framework into a practical system aligned to the realities of hybrid and multicloud deployments, this unified layer should be built on core capabilities:

• Inline visibility for east-west traffic within virtualized and cloud environments, enabled by deploying next-generation firewalls directly inside virtual private networks:
  This approach inspects workload-to-workload traffic, identifies anomalous behavior and stops lateral movement before it spreads.
• Consistent policy enforcement across public cloud, private data centers and edge locations through a centralized management plane:
  A single set of policies should be authored once and pushed everywhere, assuring a consistent security posture across all clouds and environments.
• Abstraction of security intent from network coordinates through tag-driven automation, an approach that allows security policies to be expressed in terms of workload attributes (rather than IPs or locations):
  These protections follow workloads automatically as they move. Through integration with orchestration pipelines, this approach aligns controls with rapid application rollouts in CI/CD workflows, all without manual reconfiguration.

With these core capabilities, security can finally catch up to the fluidity promised by hybrid cloud operating models.

Explore how Palo Alto Networks and Nutanix, work together to make this unified vision a reality, including joint offerings, like Palo Alto Networks secured Nutanix clusters with VM-Series Firewalls for AWS^® and Microsoft^® Azure.

The post Untangling Hybrid Cloud Security appeared first on Palo Alto Networks Blog.