Palo Alto Networks announces that Unit 42® Continuous Frontier AI Defense and Prisma AIRS are now on the newly launched OpenAI Marketplace, making them directly available to OpenAI’s enterprise customers. Threat actors are deploying artificial intelligence to find and exploit vulnerabilities at unprecedented speed, compressing breach cycles by almost 97%—from weeks down to mere hours. Human-speed defense can no longer keep pace with adversaries executing automated, continuous attacks.

AI Investments: The OpenAI Marketplace Advantage

For enterprise organizations holding OpenAI spend commitments, this milestone offers a compelling 2-for-1 financial and strategic advantage. Security teams can now deploy machine-speed, proactive defense while retiring their pre-committed OpenAI spend.

Palo Alto Networks offers two flagship solutions available for procurement through the OpenAI Marketplace.

• Unit 42® Continuous Frontier AI Defense: An always-on, expert-led agentic offensive security service that uses defender-grade models to discover, validate, and accelerate the remediation of exposures across applications and network assets before weaponization.
• Prisma® AIRS: A comprehensive AI security platform designed to provide complete discovery, risk assessment, runtime protection, identity and data governance, and observability for AI applications, agents, models, and artifacts across enterprise cloud platforms, SaaS environments, and endpoints.

Machine-Speed Defense with Unit 42 Continuous Frontier AI Defense

Unit 42 Continuous Frontier AI Defense is an expert-led, agentic offensive security service engineered to identify, validate, and remediate enterprise exposures as an organization’s environment changes.

This always-on, agentic service combines our offensive security experts with our proprietary multi-model harness, which uses defender-grade frontier models to discover vulnerabilities, validate real-world exploitability, and accelerate remediation across applications, identities, cloud infrastructure, and network assets as an organization’s environment changes. At the core of this capability is our proprietary multi-model software harness that dynamically routes security tasks to the optimal AI model, maximizing efficacy and coverage while managing the cost of frontier AI at scale.

The harness integrates defender-grade models, including OpenAI’s GPT-5.6-Cyber, and other commercial models alongside open-weight models and Unit 42 threat intelligence. By executing non-destructive adversary simulations across first- and third-party environments, the system proves actual exploitability and delivers prioritized remediation guidance including actionable fixes, code-level changes, and virtual patches. Organizations can pair this with Frontier Virtual Patching to block exploits long before official patches exist or CVEs are publicly disclosed.

The real-world impact of this proactive methodology was validated over six months of in-house testing and across more than 75 customer engagements backed by a $17 million R&D investment. During internal deployment within Palo Alto Networks, the service uncovered over two years’ worth of exposures in just three weeks. In customer assessments, the underlying analysis identified exposures in 100% of assessed organizations, with 37% rated high or critical severity. Crucially, over two-thirds of exposures found in third-party applications had no known CVE, proving the urgent necessity of continuous, AI-driven discovery.

Unit 42 Continuous Frontier AI Defense is available worldwide today on an annual subscription basis. Register for our upcoming Virtual Threat Briefing to see how we apply Frontier AI, our proprietary multi-model harness, and offensive security expertise to protect Palo Alto Networks and our customers.

To learn more about Unit 42 Continuous Frontier AI Defense, register for the upcoming Virtual Threat Briefing here.

Scale Enterprise AI Adoption Safely with Prisma AIRS

As OpenAI customers rapidly scale their use of powerful AI models, AI coding assistants, and autonomous agents, the enterprise attack surface is expanding faster than traditional security teams can manage. The transition to autonomous AI breaks traditional security boundaries, creating shadow AI blind spots, supply chain risks in open-source base models, unsafe actions from malicious inputs, and uncontrolled AI agents executing tasks with excessive permissions.

Prisma AIRS: Secure Every AI Ambition

Prisma AIRS is the Palo Alto Networks unified AI security platform, enabling enterprises to accelerate AI adoption while maintaining control over sensitive data, agent identities, autonomous actions and AI costs. Recognized by Gartner as a Market Shaper in the September 2026 Emerging Market Quadrant for AI Application Security – Established Vendors, Palo Alto Networks brings together discovery, continuous risk assessment, real-time protection and centralized governance to secure AI applications and agents across enterprise environments.

• Gain Visibility Across Enterprise AI: Discover and inventory AI applications, coding assistants, autonomous agents and associated assets across endpoints, cloud and enterprise environments. Identify shadow AI and gain visibility into the AI systems operating across the organization.
• Identify Risks Before They Become Threats: Continuously assess AI security posture, scan models and agent artifacts—including skills and MCP servers—for vulnerabilities and supply chain risks, and proactively red team AI applications and agents to uncover exploitable weaknesses before deployment.
• Secure AI Interactions, Data and Agent Identities: Enforce real-time protection against prompt injection, malicious interactions and sensitive data exposure. Verify agent identities, enforce least-privilege access and prevent unauthorized actions as agents interact with enterprise systems and data.
• Centralize AI Policy, Access and Spend: Use AI Gateway to govern connections to LLMs, MCP servers, APIs and enterprise services. Centralize policy enforcement, control model and provider access, monitor consumption and manage AI usage and costs across teams and applications.

Together, these capabilities help OpenAI enterprise customers secure AI-powered workflows, maintain accountability for autonomous actions and scale AI adoption with consistent security and governance.

Book a demo to see our AI Security solution in action.

The post Palo Alto Networks Brings Continuous AI Defense and Prisma AIRS to the OpenAI Marketplace appeared first on Palo Alto Networks Blog.

Two critical vulnerabilities in PHP (CVE-2026-109618 and CVE-2026-109619) have been published. Both vulnerabilities carry a severe CVSS score of 9.2 (more technical details are in the Unit 42 Threat Brief). 

This is not just another high-severity vulnerability disclosure, it marks the opening chapter in a massive acceleration of cyberthreats that will define the foreseeable future. Because PHP is widely used globally (by some estimates, more than half of all websites), the sheer scale of this is massive. Navigating this new reality demands immediate imperatives, including continuous, proactive vulnerability discovery before adversaries weaponize code, and a modern defense strategy that pairs traditional patching with real-time virtual patching. At a footprint of 22 million exposed instances, relying on manual remediation cycles alone is not a viable defense.

For context, exposures are typically in the thousands, for example around 50,000 potentially vulnerable exposed instances for recent NetScaler vulnerabilities, and about 16,000 exposed instances of BeyondTrust, potentially vulnerable to CVE-2026-1731. Pervasive open-source software introduces an exposure footprint on an entirely different order of magnitude. 

This situation illustrates what I shared in Defender’s Guide to the Frontier AI Impact on Cybersecurity. We’re officially in a new reality, and this is going to be an ongoing cycle.

An Accelerating Cycle

The latest frontier AI models are extraordinarily capable at finding vulnerabilities in code. We’ll see these models continue to surface critical issues at a pace faster than ever before.

But here’s the challenge: As soon as patches for vulnerabilities are available, attackers will reverse engineer the patch, locate the root flaw, and target them in near real time. It simply takes too long to apply patches to every system. This vulnerability deluge demands urgency and new technologies, such as virtual patching, are needed.

What Organizations Should Do Now

(1) Assess Your Open Source Inventory

Given the unprecedented speed at which new, critical vulnerabilities are being found with frontier AI, organizations need the ability to understand their true exposure at a moment’s notice. Attack surface management solutions have never been more critical for finding these blind spots across your entire codebase and supply chain. You can’t protect what you can’t see.

Additionally, services like Unit 42 Continuous Frontier AI Defense put defender-grade AI models in the hands of defenders to find and fix vulnerabilities before attackers can weaponize them.

(2) Prioritize Remediation Based on Reachability

You have to reduce what is reachable by attackers. You can't instantly patch everything everywhere, so prioritize what needs to be fixed first based on attack-path reachability. Secure what must be accessible to the public internet, and evaluate your environments to understand which of those exposed PHP instances carry the most immediate risk. For example, Cortex Xpanse and exposure management are great tools for determining reachability and automating remediation.

(3) Secure your AI deployments

While not the main focus for these PHP vulnerabilities, rapid deployment of AI across organizations is expanding the attack surface. All AI deployments must be secure AI deployments.

(4) Mitigate and Ensure Attack Protections

While you coordinate patching with your development teams, ensure best-in-class protections are in place to block the actual exploits. Mitigate against potential attacks immediately through proactive virtual patching and reducing overall exposure. Deploying high-fidelity virtual patches across your network and cloud security provides the mitigation layer necessary to give your teams the time they need to update the actual software safely.

Our new Frontier Virtual Patching capability delivered preemptive coverage for these PHP vulnerabilities ahead of today’s public disclosure. Additionally, Palo Alto Networks customers are protected from exploitation of these vulnerabilities by Advanced Threat Prevention available on our next-generation firewalls and Prisma Access.

(5) Deploy Real-Time Security Operations

Autonomous AI-driven attacks will drive attack lifecycles to minutes requiring every SOC to achieve single-digit mean time to detect (MTTD) and mean time to respond (MTTR).

The Path Forward: Institutionalize Defenses

This isn’t a one-and-done situation. With frontier AI compressing the patch-to-exploit window to minutes, assessing exposure, prioritizing reachability, mitigating and ensuring attack protections must become a continuous, automated motion.

This is a pivotal moment. While the scale of the challenge presented by frontier AI is real, I’m confident in our ability to solve it. Take the steps to secure your organization today, and build the foundation needed to ensure the advantage remains with the defender.

The post Millions of PHP Instances Exposed - What Organizations Need To Do Right Now appeared first on Palo Alto Networks Blog.

Enterprises spent the last two years racing to capture the vast potential of AI, authorizing AI agents to touch production code, internal databases, customer tickets and financial ledgers. Because these agents operate non-deterministically with broad capabilities, they can easily be manipulated into unexpected or malicious behavior. The result is agents breaking out of isolation, shifting AI risk from a hallucinating chatbot to an operational liability. 

The standard fixes, such as software containers or prompt-level guardrails, aren't sufficient to prevent malicious agent behavior. And traditional endpoint security was not designed to secure agents, which operate with real user access. Just as we pioneered XDR to include network, identity and cloud, we must now expand protection to secure agents in the enterprise. 

Cortex XDR One brings together XDR and Koi Agentic Endpoint Security to protect both traditional system processes and AI agents, delivering layered enforcement across an agent’s execution path. XDR One is designed to control an agent’s actions at the source, enforce hard boundaries at the operating system level, and spot rogue behavior through an AI-driven layer of defense.

An Emerging Security Blind Spot

Endpoints have evolved from controlled execution environments into complex ecosystems of AI coding agents, AI co-pilots, MCP servers and personal agents with access to sensitive data and systems. These artifacts can bypass traditional controls and operate in critical blind spots. 

When an agent ingests an untrusted input, connects to a compromised enterprise app or executes an unauthorized command, it transforms from a productivity tool into an active risk vector. Because agents operate with real user permissions and non-deterministic behavior, security teams face a compounding set of enterprise challenges that extend far beyond simple prompt injections.

Employees are adopting personal AI agents and browser tools that bypass IT oversight, spreading shadow AI across endpoints. At the same time, attackers are exploiting connected systems to manipulate these agents. By poisoning the external data, databases, or SaaS applications an agent relies on, adversaries can alter its behavior indirectly without ever touching the AI model itself. Without hard boundaries, an agent can be tricked into escalating host privileges, bypassing local containers or executing arbitrary system commands. In short, the agent escapes its intended sandbox and becomes an unwitting insider threat.

Adversaries are already exploiting this new vulnerability. In the ClawHavoc supply chain attack, adversaries targeted agents by uploading hundreds of malicious skills to OpenClaw's marketplace; once installed, these rogue skills broke runtime isolation to give remote attackers direct command-line access on the host. In a separate incident, Unit 42 research showed how agents can be tricked into revealing secret system prompts or sensitive information through indirect data poisoning from connected applications. Additionally, agents can bypass system and access controls when tricked into issuing unauthorized API calls or executing system tools under the guise of legitimate user permissions. Compounding these risks is the rise of shadow AI, as ungoverned, unmonitored agents deployed by employees silently inherit elevated system privileges without IT visibility.

When agentic AI was just emerging, we saw the potential risks it would bring and immediately sought out a solution to secure our internal AI workloads. Our InfoSec team found and deployed Koi while the startup was still in stealth mode. Impressed by Koi’s unique ability to secure new agentic endpoint behavior, we welcomed the talented Koi team into the Palo Alto Networks family to deliver this protection directly to our customers.

Cortex XDR One: Securing Every Endpoint and Agent from a Single Platform

XDR One integrates Cortex XDR and Cortex Agentic Endpoint Security with a single user interface and sensor, providing centralized visibility, management and investigation.

From sanctioned agents to shadow AI, XDR One gives teams a real-time inventory of every AI artifact the moment it appears on an endpoint. Armed with visibility into all the agent activity in the enterprise, security teams can control what packages, extensions, agents and AI artifacts are allowed to be installed or used. For example, a CISO can evaluate which vibe coding agents are actually being used by engineering teams and make an informed decision about the productivity impact of removing access to a specific agent. 

Securing the modern endpoint requires unified defense across both the AI agent lifecycle and the underlying operating system. XDR One delivers this protection, from software installation to live execution. Within the agent layer, it enforces runtime guardrails to help stop prompt injections and destructive commands. Simultaneously at the OS layer, XDR One continuously monitors runtime process chains to block zero-day exploits and living-off-the-land attacks in real time without affecting performance. To complement these defenses, optimized small language models run directly on the endpoint sensor to guard against evasive, fileless threats even while offline and without sending sensitive code to the cloud. By stitching cross-domain telemetry into clear, end-to-end attack chains, XDR One cuts false positives by up to 95% and drives automated remediation in minutes.

Ultimately, consolidating this security telemetry onto a single sensor eliminates fragmented point tools and establishes a powerful operational foundation, equipping Cortex XSIAM with the critical data needed to better govern AI risk across the enterprise.

Flexible Protection with Standalone Agentic Endpoint Security or Native Integration

Cortex Agentic Endpoint Security (AES) specifically governs AI tools, MCP servers and agentic workflows running on those hosts. Organizations have the flexibility to deploy AES alongside existing third-party EDR environments using the Cortex targeted sensor.

However, organizations can simplify operations when AES and XDR come together natively in Cortex XDR One. By unifying agentic defense and extended detection and response into a single sensor and platform, XDR One bridges the gap between traditional host security and AI risks, delivering seamless visibility, management and real-time investigation.

Setting a New Baseline for Endpoint Security

The era of standalone EDR has passed. Just as XDR moved beyond siloed endpoint detection and response to encompass network, identity and cloud, securing the modern enterprise now demands native protection for autonomous AI workloads. EDR without integrated agentic security is incomplete and fundamentally legacy. Disconnected point solutions lack visibility into OS execution, while bolt-on EDR offerings fail to correlate the agent’s prompt and tool context with subsequent system behaviors. Relying on a bird of prey may seem like high-end security, until you discover it only swoops in after the wolf has already attacked the flock.

XDR One sets the new standard for endpoint security, providing unmatched visibility and preemptive control across both the OS and AI layers within a single sensor.

Scaling Enterprise AI with Confidence

While XDR One delivers complete standalone protection, security leaders grappling with this complex new attack surface can augment their team’s capabilities with Unit 42 MDR, which will now include Managed Agentic Endpoint Security. By combining XDR One telemetry with elite threat intelligence, Unit 42 experts deliver proactive threat hunting, incident investigation, and AI risk governance to strengthen overall resilience.

Securing the Agentic Frontier

As organizations race to adopt AI agents, security teams face a pivotal transition. The expansion of agentic capabilities across enterprise endpoints demands a security posture that treats agents with the same rigor and control as traditional system processes.

By unifying agentic endpoint defense and XDR into a single sensor and platform, XDR One sets a new standard for endpoint security in the agentic era. Whether deployed independently or backed by Unit 42 expertise, XDR One gives security leaders the visibility and control needed to eliminate shadow AI, enforce operational guardrails and accelerate their AI transformation.

 

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Forward-Looking Statements
This blog contains forward-looking statements that involve risks, uncertainties and assumptions, including, without limitation, statements regarding the benefits, impact, or performance or potential benefits, impact or performance of our products and technologies or future products and technologies. Any unreleased services or features (and any services or features not generally available to customers) referenced in this or other press releases or public statements are not currently available (or are not yet generally available to customers) and may not be delivered when expected or at all. Customers who purchase Palo Alto Networks applications should make their purchase decisions based on services and features currently generally available.

The post Reinventing Endpoint Security with Cortex XDR One appeared first on Palo Alto Networks Blog.

AI agents and AI-enabled tools are fundamentally changing how work gets done. From coding assistants to Model Context Protocol (MCP) servers, autonomous tools now access sensitive data, execute commands, and modify local workflows directly from the endpoint. Traditional endpoint security models fail to offer the visibility or governance required to manage these autonomous actions.

The security gap is already significant. Only 6% of organizations have an advanced AI security strategy. And the fastest attacks can move from initial access to data exfiltration in just 72 minutes, according to the 2026 Unit 42 Global Incident Response Report. As AI adoption grows, teams need context to prioritize risk and experts ready to respond so the business can continue adopting AI with confidence.

Today, we are announcing Unit 42 Managed Agentic Endpoint Security (Managed AES). We built the service on Cortex AES, our AI-native endpoint security platform that provides visibility, contextual risk intelligence and protection for AI agents and artifacts. Managed AES adds 24/7 Unit 42 expertise to help organizations put those capabilities into action. Backed by Unit 42 threat intelligence, our experts provide AI governance, threat hunting, investigation and response, and AI-related cyber hygiene. They apply human judgment to turn contextual intelligence into policy recommendations and prioritized actions as the environment evolves.

Continuous Expert Defense for the AI Environment

Managed AES brings continuous Unit 42 expertise to four areas of AI endpoint security.

• Govern AI Adoption with Greater Confidence
  AI adoption often moves faster than security teams can assess it. Our experts help identify AI tools and associated risks, evaluate exposure and recommend improvements to policies and controls. Security leaders gain a clearer view of AI use across their environment.
• Hunt for Emerging and Zero-Day Threats
  AI-related threats can emerge before they trigger a known alert. Our threat hunters use frontline threat intelligence and Cortex AES signals to proactively hunt across the customer’s AI environment. They evaluate findings, recommend action and refine policies and correlation rules to strengthen protection over time.
• Investigate and Respond 24/7
  Our analysts continuously monitor activity, investigate suspicious behavior and take permitted actions on the customer’s behalf to contain AI-related threats. Security teams gain specialized support to understand what happened, determine the potential impact and prioritize next steps.
• Continuously Strengthen AI-Related Cyber Hygiene
  Unit 42 assesses the customer’s AI security posture as adoption evolves. AI Security Posture Reports identify policy and control improvements, while Threat Impact Reports detail threats, potential impact, response actions taken and recommended next steps. These insights help teams prioritize improvements.

Expert Protection Across Your AES Environment

Organizations can choose the Cortex AES deployment model that best fits their environment while receiving the same 24/7 Unit 42 expertise.

• Managed AES with Standalone Cortex AES
  Organizations can deploy Cortex AES alongside their existing endpoint security solution for AI-native visibility, contextual risk intelligence, governance and protection for AI agents and AI-enabled tools. Managed AES adds Unit 42 experts who help customers act on that visibility and risk intelligence.
• Managed AES with Cortex XDR One
  Cortex XDR One brings together Cortex AES and Cortex XDR into a single sensor and console experience. It combines endpoint detection and response with AI-native security for AI agents and artifacts. Unit 42 experts provide 24/7 governance, threat hunting, investigation and response across the entire endpoint attack surface.

Securely Scale AI Adoption

Unit 42 Managed AES helps security teams understand how AI is being used, address risk before it escalates and respond quickly when threats emerge. By combining Cortex AES context with frontline threat intelligence and expert analysis, Managed AES helps businesses adopt AI with confidence.

Register for our upcoming webinar, The Next Era of Endpoint Security, to learn how Cortex AES and Unit 42 experts help your team govern AI risks, strengthen visibility and protect the agentic endpoint.

The post Introducing Unit 42 Managed Agentic Endpoint Security appeared first on Palo Alto Networks Blog.

Are organisations becoming so reliant on third party space assets that they would face severe disruption if the assets were impacted by a cyber attack?

When most people think of space technology, they imagine routine weather forecasts or blue-dot navigation on a smartphone map. But behind those quiet satellite signals lies an invisible digital thread holding modern society together. From crop harvesting schedules to international flight routes and supermarket supply chains, daily life on Earth is deeply dependent on data from space.

Yet space security remains the cyber risk that very few in executive boardrooms are addressing. As the space economy surges toward a $1.01 trillion valuation by 2034, a dangerous blind spot has emerged. Cyber threats to orbital infrastructure are no longer a theoretical hazard—they are happening now.

Privatization Outpacing Security

Historically, space operations were the exclusive domain of governments operating in strictly air-gapped environments with near-zero tolerance for risk. Today, rapid commercial privatization has slashed launch costs, but speed to market is dangerously outstripping security by design. Commercial operators inherit standard enterprise IT vulnerabilities, complex supply chain risks, unpatched APIs, and operational technology gaps.

The systemic disconnect is stark:

• According to data from the Organisation for Economic Co-operation and Development (OECD), space-based systems now support more than 50% of all critical services and infrastructure across modern economies.
• The European Commission’s latest assessment is that 10% of the EU’s GDP is enabled directly or indirectly by satellite navigation signals. This equates to around €1.88 trillion based on the EU’s GDP for 2025.
• Yet 85% of organisations aren’t factoring space assets into their cyber risk mitigation strategy, according to the World Economic Forum.

Physical Consequences on the Ground

Unlike typical corporate breaches, orbital cyber attacks can trigger immediate physical impacts on Earth. Tampering with satellite telemetry can destabilize regional crop yields by altering planting schedules or paralyze commercial aviation by injecting false data into flight-navigation networks.

Crucially, these risks are not limited to assets in orbit. Ground-based power substations, telemetry command hubs, and downlink facility infrastructure have become primary cyber-physical targets. A coordinated cyber attack on local energy substations supporting satellite ground operations could sever communication links and ground control just as effectively as an in-orbit compromise.

A study commissioned by the European Space Agency (ESA) modeled the impact of a hypothetical 7-day satellite communications outage across ESA member states and Canada. The potential cost reaches up to €20 billion ($21.8 billion) in total economic losses. This includes €19 billion in maritime logistics and port bottlenecks, €558 million in direct aviation losses (canceling ~4,000 transatlantic flights), €352 million in lost connectivity for emergency services and remote communities, and €89.8 million from stalled offshore energy operations.

Aging Tech Meets Advanced Threat Actors

Geostationary satellites carry mission lifespans of 10 to 15 years, locking critical communications into legacy hardware designed before modern cyber threats existed. Nation-states and cybercriminals are exploiting these gaps; Palo Alto Networks Unit 42 threat intelligence currently tracks multiple state-sponsored groups actively targeting space-sector systems.

What Leaders Must Do Now

Governments and enterprise boards must recognize space-based timing, navigation, and observation as core national critical infrastructure. Leadership teams should execute four priorities immediately:

1. Map Space Dependencies: Audit third-party services, cloud links, and automated logistics relying on satellite telemetry.
2. Establish Terrestrial Backups: Build manual redundancies—including ground-based radio networks and offline inventory controls—for scenario planning when space signals go dark.
3. Elevate Supply Chain Audits: Evaluate whether key vendors rely on single-point-of-failure commercial satellite constellations or unfortified ground substations.
4. Update Risk Registers: Formally integrate space dependencies into corporate cyber risk registers.

Translating these action items into real-world operational resilience requires moving beyond static compliance policies. To protect complex ecosystems—where ground stations, power substations, cloud environments, and orbital data streams converge—organizations need a unified, platformized approach to security that provides continuous visibility across every link in the space supply chain.

In the modern threat landscape, business resilience, national sovereignty, and space security are inseparable. It is time for leaders to look up before an orbital breach brings ground operations to a standstill.

The post The Blind Spot in Orbit: Why Space Could Be the Next Infrastructure Crisis appeared first on Palo Alto Networks Blog.

The NHS has set an ambitious goal of achieving cyber resilience across healthcare organisations by 2030. Delivering on that vision requires technology, expertise and close collaboration across the public and private sectors.

This is clearly a highly complex task, but one we're delighted to help deliver in partnership with IBM. Through this partnership, Palo Alto Networks will provide advanced cloud-based perimeter technology, alongside IBM Consulting’s specialist guidance, implementation support and tailored onboarding for NHS organisations.

As health and care services continue to modernise, maintaining resilient, secure digital infrastructure has never been more important. Healthcare organisations are operating in an increasingly complex environment, with growing digital dependencies, expanding supply chains, evolving cyber threats and new technologies such as AI reshaping the landscape.

According to IBM's Cost of a Data Breach Report, healthcare continues to be one of the most impacted sectors globally when it comes to the financial consequences of cyber incidents. This highlights the importance of taking a proactive, long-term approach to cyber resilience across critical public services.

Palo Alto Networks' continued work with the NHS demonstrates the scale and complexity of securing modern healthcare environments. As organisations balance innovation, operational demands and evolving security requirements, there is a growing need for solutions that provide both strong protection and the flexibility to meet local needs.

Introducing the Next Generation of the NHS Secure Boundary Programme

Palo Alto Networks will deliver next-generation, cloud-based security solutions through the next iteration of the NHS Secure Boundary programme. The service has been designed to help strengthen cyber resilience across UK health and social care organisations while supporting the safe and reliable delivery of services.

Secure Boundary provides the capability to support a network spanning more than 1.5 million NHS staff, over 200 NHS trusts, more than 55,000 organisations handling health data and approximately 2 million devices under national cyber monitoring. The nationally integrated and centrally funded service embodies a "Defend as One" approach, helping organisations benefit from shared protection while retaining local control.

Secure Boundary supports NHS organisations through:

• An AI-enabled cybersecurity capability designed to strengthen resilience and support the safe, reliable delivery of healthcare services.
• Enhanced visibility and protection for internet traffic across the Health and Social Care Network.
• Improved security for infrastructure and clinical applications operating across multiple service providers.
• Increased protection for information shared across NHS organisations and trusted third parties.
• Greater privacy and security for staff accessing web-based services, whether on-site or remotely.
• A "Defend as One" approach that complements existing local security measures while allowing organisations to tailor policies to their specific requirements.
• Reduced complexity through the consolidation of security tools and management processes.
• Improved efficiency through a centrally funded model that helps reduce duplication of technology and investment.

The new Secure Boundary service represents a significant step forward in strengthening the NHS's digital resilience. By providing a more secure foundation for NHS services, it helps support operational continuity, safeguard sensitive information and enable healthcare teams to continue delivering high-quality care in communities across the UK for years to come.

If you would like to find out more about Secure Boundary and how it can help your organisation, please contact ukpubsec@paloaltonetworks.com. 

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Forward-Looking Statements

This blog contains forward-looking statements that involve risks, uncertainties and assumptions, including, without limitation, statements regarding the benefits, impact, or performance or potential benefits, impact or performance of our products and technologies or future products and technologies. These forward-looking statements are not guarantees of future performance, and there are a significant number of factors that could cause actual results to differ materially from statements made in this blog. We identify certain important risks and uncertainties that could affect our results and performance in our most recent Annual Report on Form 10-K, our most recent Quarterly Report on Form 10-Q, and our other filings with the U.S. Securities and Exchange Commission from time-to-time, each of which are available on our website at investors.paloaltonetworks.com and on the SEC's website at www.sec.gov.  All forward-looking statements in this blog are based on information available to us as of the date hereof, and we do not assume any obligation to update the forward-looking statements provided to reflect events that occur or circumstances that exist after the date on which they were made.  

 

The post NHS England evolves its cybersecurity strategy with Palo Alto Networks and IBM appeared first on Palo Alto Networks Blog.

Hope is not a strategy. Neither is nostalgia.

Mark Carney, Prime Minister of Canada

 

Business leaders cannot respond to AI-era cyber risk by longing for a simpler technology stack, slower decision-making or a security model built around a trusted internal network. AI is changing how organisations operate—and how adversaries identify and exploit weaknesses—faster than many leadership teams can anticipate.

Cybersecurity has therefore evolved from a “coconut strategy”, built around a hardened perimeter and trusted interior, to what I call a “mango strategy”. The modern enterprise and its digitally connected ecosystem have a porous, continuously changing edge, but it must place its strongest protection around the core: its data, identities, code repositories, applications, digital essentials and critical operations.

What is the CEO’s role in AI governance and cybersecurity?

This shift makes cybersecurity a CEO-level business priority. CEOs do not need to oversee every AI deployment, but they must define how the organisation adopts, governs and secures AI while maintaining resilience, accountability and trust. That means setting risk thresholds, assigning accountability, protecting critical data and identities, and ensuring that security can operate at the same machine-speed as autonomous systems.

Why autonomous AI agents require workforce-level oversight

Given this dual nature, business leaders cannot afford to ignore AI. Like water, AI adoption will find its way and follow the path of least resistance as a senior cybersecurity leader from a large European bank put it. Without clear governance, it can expose weak controls, while AI-enabled attackers can exploit those weaknesses at unprecedented speed and scale.

Some have suggested that CEOs should double as Chief AI Officers. However, as executive responsibilities expand, expecting a CEO to oversee day-to-day AI implementations while setting broader corporate vision is unrealistic. While the CEO may not manage specific AI initiatives, they must actively shape the overarching strategy, the “AI surround and framework”.

This leadership starts with developing and hiring highly capable talent to execute the vision. The CEO’s true value lies in ensuring that AI is embraced across every business unit, integrated into risk models, and governed by robust safeguards. Proper administration and oversight are no longer secondary concerns—they are core executive functions.

A critical dimension of this responsibility is governing the use of agentic AI. Autonomous agents function effectively as "authorized insiders." Custom-built for specific workflows, they leverage elevated privileges to access critical applications, databases, and proprietary tools around the clock.

In practice, these agents represent a new class of virtual employees. Though non-human, their operational impact is comparable to their human counterparts, yet they operate 24/7. CEOs must ensure that autonomous agents are deployed, monitored, and evaluated with the same rigors applied to the rest of the workforce.

How can leaders build resilience against AI-driven instability?

Translating this new operational reality into steady organizational resilience requires recognizing AI's broader societal impact. While the technology holds vast potential for good, it can also accelerate systemic and geopolitical instability when misused. For instance, recent developments in frontier AI models demonstrating advanced exploit-generation capabilities highlight the immediate necessity of defense-in-depth.

Palo Alto Networks CEO Nikesh Arora highlighted this shift in this article - Weaponised Intelligence -  “These are not incremental improvements. Imagine a horde of agents methodically cataloging every weakness in your technology infrastructure, constantly. Over the next six months, the barrier to entry for sophisticated attacks will continue to diminish. A hacker’s dream weapon will be available to anyone with a credit card and computer.”

To counter these emerging risks, leading AI developers and security organizations are actively collaborating. Through initiatives like Project Glasswing, partners across technology and financial services are stress-testing defender-grade models to harden critical software and establish proactive defenses before threats reach the wild.

These collaborative initiatives address the exact questions executive boards are asking today: Where are our exposure points, how severe are they, and how quickly can we contain them?

Answering these questions requires a strong security culture. Defining how an organization adopts and governs AI is now a core mandate for executive leadership. Even with specialized AI leadership in place, the CEO must drive the culture to align AI implementation with business values and strategic priorities.

Ultimately, executive leadership must set clear parameters: defining operational boundaries, establishing accountability, tracking key progress metrics, and encouraging responsible innovation within controlled risk thresholds.

Four cybersecurity priorities for the agentic AI era

The cybersecurity landscape has reached an inescapable inflection point: we have entered the "Agentic Era," where autonomous AI agents drive attacks at machine speed. In this environment, manual, reactive patching is no longer just slow—it is a mathematical dead end that can leave enterprises effectively unprotected.

Navigating this shift requires a deliberate transition from reactive measures to proactive architecture built on four strategic pillars:

1. Fight Machine with real-time machine speed: Because automated adversaries can scan millions of endpoints and chain multiple low-severity vulnerabilities into catastrophic exploit paths, human-led response is a guaranteed failure. Organizations must move to a prevention-first posture, using AI-driven systems that natively integrate across network, cloud, and endpoint telemetry to block threats in real-time.
2. The "Customer Zero" Mandate: The time between a model's release and its weaponization is shrinking to zero. Palo Alto Networks acts as "Customer Zero" by stress-testing frontier models during their development phase, hardening the security stack against specific autonomous logic capabilities well before they are public.
3. Move Beyond "Find-and-Fix": Finding vulnerabilities is only half the battle. The new imperative is to prioritize remediation based on exploitability and reachability—identifying which vulnerabilities can be chained together by an attacker—rather than just severity. This requires shifting operations to machine-speed defense via unified platforms and services like Unit 42 Frontier AI Defense or virtual patching, allowing you to safely patch your digital essentials when real-time agentic attacks are happening.
4. Prioritize Platformization: Fragmented security architectures—where point solutions cannot communicate—are an open invitation to automated lateral movement. A unified, data-driven architecture is a prerequisite for security, enabling a threat blocked at the endpoint to harden an organization’s perimeter.

How CEOs can create the defender’s advantage

For the C-suite, the takeaway is clear: Digital transformation and cybersecurity transformation are now inextricably linked. The organizations that adapt by rebuilding their architecture around unified data and autonomous prevention will hold the "defender's advantage," while those relying on legacy, manual workflows remain exposed to a rapidly accelerating threat landscape.

Nostalgia offers no protection against the speed and complexity of the modern threat landscape. Operating under the assumption that perimeters remain secure is a legacy mindset. 

As executive leaders refine their strategy for the AI era, two core principles should guide their approach:

• Cybersecurity is a data issue, not a technology issue. The goal is to protect data, not just to harden infrastructure.
• Many of our core best practices in cybersecurity, such as Zero Trust and modular platformization, are more appropriate than ever in the era of AI and automated agents. 

Helmut Reisinger is CEO for Europe, Middle East and Africa at Palo Alto Networks.

The post The Mango Strategy: A CEO’s Guide to AI Cybersecurity appeared first on Palo Alto Networks Blog.

For decades, industrial cybersecurity rested on a comfortable assumption: operational technology (OT) was protected by physical isolation. The "air gap" guaranteed that power grids, manufacturing lines, and water systems remained safely disconnected from the chaos of the public internet.

That assumption is no longer just outdated - it is a strategic liability.

Driven by the imperative for real-time efficiency, predictive maintenance, and AI-led automation, industrial operations are integrating with enterprise IT and cloud environments at an unprecedented scale. Telemetry from Palo Alto Networks reveals a 332% surge in unique internet-exposed OT devices and services, bringing nearly 20 million OT-related assets onto the public internet.

Digital transformation has fundamentally redrawn the perimeter. What was once an engineering challenge managed on the plant floor has transformed into an existential risk that demands board-level oversight.

Every Industrial Asset Is Now a Digital Asset

Modernizing critical infrastructure is rarely framed as a security initiative; it is an operational mandate. Heavy machinery engineered to last thirty years is now instrumented with IoT sensors, managed through cloud-native platforms, and remotely monitored.

This connectivity creates tight dependencies between core business IT and physical operations. Modern industrial facilities rely on enterprise identity management, cloud telemetry, and continuous software updating to function day to day.

Consequently, a threat actor does not need to breach the factory floor to stop production.

When an enterprise IT network suffers an incident, executive leadership often initiates a manual shutdown of operational lines out of caution or because shared authentication mechanisms become unavailable. The business processes linking enterprise IT and OT have become functionally inseparable.

The Anatomy of Modern Industrial Threats

Attackers no longer require sophisticated, state-sponsored zero-day exploits to disrupt physical infrastructure. As seen in recent cyber incidents targeting municipal water systems in the US and the breach of a Polish power plant, threat actors continuously exploit basic internet exposure, unpatched vulnerabilities, weak default credentials, and unsegmented remote connections.

Threat dynamics across critical infrastructure have shifted toward two major vectors:

• Low-Friction Initial Access: Basic internet discovery tools allow threat actors to identify exposed control systems and programmable logic controllers (PLCs) in minutes. Weak factory default passwords or unsegmented cellular modems provide direct entry points into physical operations.
• Operational Blindness: Modern attacks deliberately target the reporting layer - such as HMI and SCADA interfaces - to suppress alarms and present "normal" operational telemetry to engineers, even while underlying physical processes operate dangerously out of specification.

Operational Realities and the Zero Trust Imperative

The integration of artificial intelligence and automated workflows into industrial environments accelerates this challenge. Beyond human engineers logging into control networks, automated software pipelines, third-party monitoring platforms, and autonomous AI agents are executing commands within OT environments.

Data from recent identity landscape research reveals that machine identities outnumber human identities by 109 to 1 across EMEA organizations.

In an environment populated by millions of interconnected human, machine and AI actors, implicit trust based on network location is dangerous. Applying Zero Trust to OT requires moving away from traditional perimeter defense toward continuous, explicit verification:

• Verify Explicitly: Authenticate and authorize every access request - human or machine - regardless of where the request originates.
• Enforce Least-Privilege Access: Limit access strictly to the assets and commands necessary for a specific operational role or process.
• Assume Breach: Design networks under the assumption that enterprise systems are compromised, preventing lateral movement into physical control layers.

The Industrial "Red Button": Engineering for Containment

While IT security prioritizes data confidentiality, OT security prioritizes human safety, system availability, and operational continuity. Halting a processing facility or energy grid carries immediate financial, environmental, and regulatory consequences. Security controls designed for corporate office networks cannot simply be retrofitted onto plant floors.

Cyber resilience is measured not merely by prevention, but by limiting the blast radius when a breach occurs.

Leading industrial organizations are establishing a programmable "Red Button" capability - a combination of architectural micro-segmentation and automated playbooks. This architecture allows security teams to rapidly isolate critical physical operations from compromised IT networks or cloud dependencies without bringing production to a complete halt.

Five Strategic Actions for Executive Boards

With regulatory frameworks like NIS2 increasing direct accountability for senior leadership, OT cybersecurity requires strategic governance centered on comprehensive visibility, robust micro-segmentation, operational risk scoring, and virtual patching:

• Establish Complete Asset Visibility: Eliminate dark corners across physical environments. Organizations must maintain a continuous, real-time inventory of every connected industrial asset, controller, and external dependency.
• Embed Security by Design and Virtual Patching: Integrate cybersecurity requirements directly into industrial modernization programs from initiation. Deploy virtual patching mechanisms - such as Frontier Virtual Patching - to shield unpatchable legacy systems against rapidly evolving AI-driven threats.
• Architect for Degraded Mode: Design critical infrastructure to maintain safe, baseline operations even if cloud access, enterprise IT, or external network connections are severed.
• Practice Operational Recovery: Develop and stress-test incident response playbooks specifically designed for physical environments, including offline configuration backups and manual operational overrides.
• Unify Risk Governance: Align executive leadership, security operations, and plant engineering around operational-based risk scoring and shared business metrics: physical safety, system uptime, and operational continuity.

Accelerating digital transformation should not mean compromising physical safety or operational stability. Palo Alto Networks provides an integrated platform built to address the unique constraints of operational environments. By combining AI-driven asset discovery, granular micro-segmentation, continuous risk assessment, and virtual patching across both enterprise IT and physical control networks, Palo Alto Networks empowers industrial organizations to modernize with confidence - securing operations, protecting revenue, and safeguarding national infrastructure.

Further interesting reading:

• ‘Complexity at the intersection of IT and OT’ – Executive Edge Peer Guide  
• A CISO’s guide to navigating OT & IT convergence in the manufacturing industry

The post Why OT Resilience Is Now a Boardroom Imperative appeared first on Palo Alto Networks Blog.

Cybersecurity is in the middle of a generational shift. AI has disrupted a 30-year balance of power between defenders and adversaries.

Armed with agentic AI tools and open-weight models stripped of safety guardrails, threat actors are discovering, validating, and chaining exposures at machine speed. In a recent Unit 42 investigation, the attacker used more than 50 MITRE ATT&CK techniques to reduce weeks of methodical intrusion tradecraft into less than 10 hours—97% faster than a skilled red team could have done. Time-to-exfiltration has compressed to under an hour in real-world attacks. And when new CVEs are publicly disclosed, automated adversary scanners are weaponizing them within 15 minutes.

Defending at human speed is no longer viable. Organizations must close years of accumulated exposure while securing the AI they are rapidly adopting. That demands action on five fronts: continuously find and fix vulnerabilities, reduce exposure, secure AI infrastructure, unify attack prevention, and automate detection and response at machine speed.

Today, we are announcing Unit 42 Continuous Frontier AI Defense to put the first two priorities into practice. Powered by Anthropic's Mythos models and OpenAI's latest GPT cyber models, this always-on, agentic service combines our offensive security experts with proprietary multi-model harnesses to discover vulnerabilities, validate real-world exploitability, and accelerate remediation across applications, identities, cloud infrastructure, and network assets.

Led by our offensive security experts, this service discovers, validates and remediates exposures before they can be exploited. We use proprietary AI harnesses and gated capability models—powerful models restricted from public use—to discover vulnerabilities, prove real-world exploitability, and accelerate remediation across applications, identities, cloud infrastructure, and network assets as an organization’s environment changes.

Continuous Frontier AI Defense builds on Unit 42’s Frontier AI Defense, which launched in April and introduced Frontier AI Exposure Analysis, a point-in-time exposure analysis, and a security blueprint that benchmarks current capabilities to help organizations modernize their cybersecurity systems. In August, Unit 42 expanded the list of frontier AI models to include  OpenAI’s GPT-5.6-Cyber and Anthropic's Claude Mythos 5, giving organizations access to additional AI capabilities.

A Single AI Model Is Not a Security Strategy

Frontier models are powerful, but no single AI model is a cybersecurity silver bullet and the models require equally powerful AI scanning harnesses.

Unit 42 research evaluation of model performance across enterprise codebases and live environments revealed two stark operational realities:

• Coverage caps: No single AI model catches more than 40% of vulnerabilities in a complex environment.
• Visibility: Leading cyber models such as Anthropic Claude Mythos 5 and OpenAI GPT-5.6-Cyber have less than 10% overlap in the exposures they identify.

To solve the single model gaps, Continuous Frontier AI Defense runs on proprietary multi-model harnesses. These harnesses act as an intelligent orchestration layer, routing specific offensive testing tasks to the model best suited for the job. This approach aligns model strengths, eliminates individual gaps, and keeps compute spend economical.

We combine these frontier models with Unit 42 threat intelligence, and frontline security expertise to turn raw vulnerability data into verified, actionable protection. Zero Data Retention (ZDR) architectures protect enterprise source code and telemetry, so customer data is never retained or used to train public models.

What Happens When AI Meets Real Enterprise Architecture

We did not build this service on theoretical assumptions. We built and validated it internally  across Palo Alto Networks and across more than 100 customer engagements.

During our internal deployment, continuous Mythos-based scanning achieved over a year’s worth of traditional penetration testing results in just three weeks. The harness identified 3.2 times more high and critical vulnerabilities per product than legacy testing methods, and helped engineering teams cut mean time to remediate by 51%.

When we executed the service across customer environments, the frontline data delivered a clear warning:

• Hidden exposures: In third-party applications, two out of three validated exposures had no known CVE. Vulnerability-only scanners will never see them.
• High severity: 37% of identified exposures rated high or critical in severity.
• Chained attack paths: Flaws rarely existed in isolation. In one financial sector engagement, our harness identified a sequence of individually minor flaws: an application payment link that failed to re-verify identity, a skipped one-time password check, and a session routing flaw. Chained together, an attacker could achieve complete account takeover and payment fraud without any victim action.

Moving from Discovery to Validated Protection

Finding weaknesses without fixing them only creates noise. And, security teams do not lack findings; they already have more alerts than they can act on. The bigger challenge is knowing which weaknesses an attacker can actually exploit and chain into a viable path to compromise, and then remediating them.

Unit 42 Continuous Frontier AI Defense translates findings directly into risk reduction:

• Continuous Testing Engine: Provides a full-estate baseline scan followed by always-on testing as an organization’s environment changes.
• Multi-Model AI Harness: Unit 42 deploys proprietary multi-model harnesses, the software architecture to route work to the model best suited for the task, improving efficacy and coverage while managing the cost of frontier AI at scale.
• Leading Cyber Models: The harnesses are built around gated capability models, including Anthropic Claude Mythos 5 and OpenAI GPT-5.6-Cyber, as well as open weight models. 
• Advanced Adversary Simulation: Proves real-world exploitability by validating end-to-end attack paths across first- and third-party web apps, APIs, cloud infrastructure, source code repositories, and network assets.
• Accelerated Remediation: Delivers actionable and prioritized fixes, code-level guidance, and virtual patch recommendations. To implement virtual patches before vulnerabilities are publicly disclosed or official patches exist, organizations can pair this with Frontier Virtual Patching. 

Unit 42 Continuous Frontier AI Defense is available worldwide today on an annual subscription basis. Register for our upcoming virtual Threat Briefing to see how we apply Frontier AI, our proprietary multi-model harness, and offensive security expertise to protect Palo Alto Networks and our customers.

To learn more about Unit 42 Continuous Frontier AI Defense, register for the upcoming Virtual Threat Briefing here.

The post Introducing Unit 42 Continuous Frontier AI Defense appeared first on Palo Alto Networks Blog.

As artificial intelligence (AI) adoption surges and organisations move from the ‘should we?’ phase to the ‘how do we?’ phase, it’s natural to evaluate the likelihood of positive returns on AI investments. That’s always been the case with the onset of each new technology paradigm: C-suite executives, guided by their boards and aided by technical and business teams, remain keenly focused on traditional metrics such as return on investment, shareholder equity, developing and extending competitive advantage, and ensuring superior customer relationships.

This time is different, however. I recently experienced that firsthand when I went to visit a major customer. My contact, a senior decision maker, gave me a pointed piece of advice about how to talk about AI with his boss, the CEO: “Please don’t say anything negative about AI.” The subtext was clear: The company was fully committed to AI and didn’t want any cognitive dissonance to dissuade them from their mission.

It's hard to imagine a CEO taking such an absolutist stance on previous technology waves, such as cloud, bring your own device, or the internet of things. CEOs, board members, and technical leaders would be pragmatic in evaluating the benefits of investments and put mileposts in place to gauge progress – and to determine if and how to proceed.

AI is certainly a different kind of paradigm, though. While no one is casting aside careful evaluation and monitoring of AI investments, the underlying assumption is that we’re stepping on the accelerator. We’re all enthused not only by its potential for transformation and innovation, but also by how this technology can be leveraged for remarkable societal good.

However, while the accelerating momentum toward AI and agentic systems is undeniable, it is vitally important to set aside the fervour around AI and take a sober look at how to deliver safe, secure, and tightly governed systems at enterprise scale. 

Many organisations are underestimating the challenges of AI governance, in large part because they think they’ve been here before. They already have many experiences of ensuring robust cybersecurity and strict governance for new technologies, as they’ve done for remote systems, cloud computing, the internet of things, and more. They already have a corporate commitment to doing governance correctly and a sound governance model. 

But this new era of AI and agentic systems is different. New challenges abound, and AI strategy, build-out, and governance must be in alignment from the start to ensure proper operational, ethical, and regulatory outcomes. 

Our intention with this Peer Insights guide is to raise what we believe are existential issues around governance for this powerful, complex, and unprecedented technology wave. Few technologies have merited the often overused phrase ‘inflection point’ more than AI. The speed of AI adoption is nothing short of breathtaking; however, today’s runaway embrace of AI is far stronger than our current ability to govern it. That’s because AI represents a fundamental shift in how organisations do their business, interact with customers, make vital decisions, and execute their plans. This isn’t just a technology play: It’s a strategy for success and survival for entire industries and our global economy. The stakes have never been higher.

CEOs care so passionately about AI because they see it changing nearly everything we’ve learned and believed to be true about organisational success and failure. CEOs are in their positions for one purpose: to grow the business. AI can do that by transforming their processes and sparking new ideas. When that customer representative forewarned me, I really wasn’t surprised to hear his CEO felt so strongly about AI: Research from BCG indicates that more than 94% of CEOs say they still plan to deploy AI irrespective of demonstrated business value, even if there is a lack of tangible ROI or financial benefits from the start. 

Which brings us to the central role of AI governance. As we all know, there are many fundamental elements to any governance strategy, starting with robust, scalable, and intelligent cybersecurity. Cybersecurity - the foundation of governance - also includes the twin imperatives of accountability (‘rogue AI’ being a real thing, after all) and regulatory compliance.

But good AI governance has to go even further. Operational integrity is key to good governance because so much sensitive and even proprietary data is poured into AI models and accessed through powerful agentic AI systems. Now more than ever, organisations have to be transparent with customers and trading partners about how their AI systems operate, what kind of data is accessed, and how it is protected. And that doesn’t just mean being upfront with customers by telling them when they are interacting with an AI agent. Let’s take a typical retail use case: Imagine you’re on a website looking at clothing, and the agent recommends specific styles of clothing in specific colours. True operational integrity would allow you to discover why and when the agent made those recommendations. Was it based on your prior purchasing history, or on your browsing patterns on a recent web session? AI and agentic governance take the guesswork out of the equation for those interacting with the system and help breed greater confidence and trust.

It's critically important for decision makers to view AI governance holistically, rather than through a series of narrow lenses. For instance, even though cybersecurity is the foundation of good AI governance, it’s a mistake to treat AI governance primarily as a cybersecurity problem. If asked about ownership of AI governance, CEOs cannot and should not reply, “Oh yeah, the CISO has that covered.”

AI governance is fundamentally an enterprise risk problem, which means everyone must be involved in creating, deploying, managing, evaluating, and adjusting AI governance guardrails on a real-time basis. Again, AI is a different kind of risk environment than any we’ve previously encountered. For the most part, organisations are simply not adequately prepared to apply the right level and right type of governance to AI and agentic systems. I’ve spent much of the past 15 years of my career building governance frameworks, and while it has never been easy, we have had the advantage of being able to control many of the variables – such as infrastructure and network access – impacting governance decisions. With AI and agentic, we no longer have that advantage.

To explore the critical and complex issues of AI governance, we’ve enlisted five leading voices to bring their real-world experience to the discussion. Together, our five authors help lay out the new rules of the road for governing AI and agentic systems at scale.

Just as my customer gave me a heads up about the realities of speaking with his boss about AI, I’d like to offer you a heads up about the realities of AI governance challenges before you read this Peer Insights guide. 

1. Visibility is paramount for successful AI governance. As we learned during the growth of trends such as cloud, bring your own device, and remote work, our employees will push the envelope with a do-it-yourself mindset. These tech-savvy and resourceful users are already making rogue AI a reality, so organisations need more visibility than ever into where AI ‘science projects’ and sandboxes are operating without anyone’s knowledge.
2. AI governance must reflect the stunning velocity of change in AI development and deployment. Not only does AI have its own never-imagined rate of change, but the technology is changing everything else faster – product development, supply chains, marketing programmes, and more. AI governance has to evolve just as rapidly. Governance in the AI world must be a living system, constantly evolving with new technology use cases.
3. Trust boundaries are incredibly different and difficult to manage in AI governance. AI represents a new class of identity that simply didn’t exist before. That means AI doesn’t fit neatly into your existing identity management framework, making things like application whitelists and zero trust network access less effective.

Unfortunately, many CEOs, board members, and business executives simply don’t understand the profound importance and complexity of these issues. They may have been heartened by how they integrated generative AI into their technology frameworks and their business processes, but GenAI was pretty familiar territory for CIOs, CTOs, and CISOs. Agentic AI is different for several reasons, including its automation and self-learning capabilities. Don’t be lulled into a false sense of security: Agentic AI is not simply a refresh of GenAI.

As you get ready to dive into the following chapters, rethink how you define governance when applying it to AI systems and agentic AI. Most traditional governance models are imagined, constructed, and deployed as gates, preventing people from doing things or going places they shouldn’t. Instead, think of AI governance as a guardrail to guide and direct people to get the most out of AI without creating problems. With so much excitement and investment around AI, organisations – and their employees – want to get the most out of their AI and agentic systems. We all know people don’t want to hear “no, you can’t do that”, so an effective governance system should use guardrails to drive proper, responsible, and safe usage of the technology.

Finally, as complex as AI and agentic governance are and will continue to be, don’t overthink things in hopes of creating the perfect model – it doesn’t exist. My advice is to start now, even if the model and framework are imperfect, and then bring the business along with you.

We at Palo Alto Networks are excited to give you insights, ideas, and actions you can take away from the chapters of this guide. We encourage you to share what you learn with your colleagues, peers, and team members – and to take prudent steps to build an AI governance model that rewards innovation without allowing your organisation to drift into dangerous waters.

 

Click here to download the guide today. Visit Executive Edge, our C-level thought leadership platform, for more insights for EMEA CXOs.

Haider Pasha is VP & Chief Security Officer, EMEA, Palo Alto Networks

The post It Might Feel Like We’ve Been Here Before, But We Haven’t appeared first on Palo Alto Networks Blog.

The White House Executive Order on securing the nation against advanced cryptographic attacks accelerates the mandatory timeline for post-quantum readiness.

For years, post-quantum cryptography has been discussed as an important, yet abstract future technical migration. Because of the uncertain timeline for quantum computing, it has been difficult for most organizations to prioritize quantum readiness against more immediate security demands.

That is changing.

Signed on June 22, 2026, the Executive Order mandates the transition of federal information systems to post-quantum cryptography and establishes a national policy to migrate them to NIST-approved standards. It also extends the urgency beyond government by directing support for critical infrastructure owners and operators, advancing requirements for federal contractors, and calling for cryptographic bill of materials guidance.

The order directly addresses harvest now, decrypt later risk and sets transition milestones for federal high-value assets and high-impact systems: 2030 for key establishment and 2031 for digital signatures.

While the order directly applies to U.S. Federal civilian agencies, it should be seen as a signal of broader policy and procurement momentum. Organizations that do business with the government, support critical infrastructure, or operate in regulated industries such as energy, financial services, and healthcare should expect post-quantum readiness expectations to accelerate.

Quantum risk has shifted from a long-term research concern to a national cybersecurity priority tied to sensitive data, critical infrastructure, federal systems, procurement, and the broader digital economy. For security teams, the challenge now is turning that urgency into an operational plan.

Operationalizing the quantum mandate

As quantum computing advances, widely used public-key cryptography will become vulnerable to future attacks. Even before a cryptographically relevant quantum computer exists, adversaries can capture encrypted data now with the goal of decrypting it later.

This “harvest now, decrypt later” risk is especially concerning for organizations that protect sensitive information with a long shelf life. The response cannot wait until the threat fully materializes.

The broader ripple effect matters because compliance alone will not equal readiness. As requirements flow into federal acquisition rules and contractor obligations, the vendor ecosystem will be pushed to support quantum-safe capabilities in the products and services that enterprises, critical infrastructure organizations, and regulated industries rely on.

Adding support for post-quantum algorithms is not the same as safely migrating to them. Support means a system can use new algorithms. Readiness means the organization knows where cryptography exists, which systems are exposed, which dependencies matter most, and how to execute changes without creating disruption or new risk.

That matters because post-quantum migration can affect more than cryptographic libraries. Larger cryptographic objects, new protocol behaviors, hybrid modes, hardware acceleration requirements, interoperability constraints, and legacy system limitations can create real performance, availability, and compatibility challenges if changes are made blindly.

This is why cryptographic visibility must lead to actionable migration planning.

Security teams cannot migrate what they cannot see. But visibility by itself is not enough. They also need to classify exposure, prioritize high-value systems and long-lived data, understand operational dependencies, and plan changes in a way that avoids disruption, downgrade risk, or incomplete migration.

Cryptographic bill of materials guidance will be an important step toward mapping cryptographic assets. But a CBOM should be the starting point, not the finish line. An inventory can show where cryptography exists, but readiness requires understanding business impact, migration complexity, interoperability risk, ownership, and the order in which changes should happen.

Post-quantum readiness is not just an algorithm swap. It is an operating model for managing cryptographic change at scale.

Five actions for post-quantum readiness

The path forward starts with five practical actions.

• First, see cryptographic exposure. Organizations must gain visibility into cryptographic usage across all environments to mitigate the risks associated with undocumented encryption.
• Second, prioritize what matters most. Cryptographic exposure varies in urgency. Organizations should prioritize protecting authentication, high-value assets, and long-lived sensitive data based on risk and business impact.
• Third, modernize trust infrastructure. Existing systems rely on fixed cryptographic assumptions. Post-quantum readiness demands flexible infrastructure and trust services that support evolving standards.
• Fourth, automate cryptographic change. Manual tracking with spreadsheets provides an incomplete, point-in-time snapshot that quickly becomes outdated and is insufficient for the coming changes. Automation allows organizations to manage cryptographic updates and trust operations in a consistent, controlled manner.
• Fifth, govern readiness over time. Post-quantum migration requires continuous governance to track progress, align ownership, and adapt to evolving threats and standards.

These actions help security leaders move from awareness to readiness.

What this means for cybersecurity now

The Cryptographic Reset is already underway, driven by post-quantum risk, shorter certificate lifecycles, machine identity growth, fragmented cryptographic ownership, CA distrust events, and expanding digital infrastructure.

The organizations that move first will not simply be the ones that adopt new algorithms the fastest. They will be the ones that build the visibility, operating model, and governance needed to manage cryptographic change continuously.

Take the next step

Read the guide: The Post-Quantum Readiness Race Is On: Five Actions Security Leaders Can Take to Accelerate Crypto Agility.

More resources

• Blog: The Cryptographic Reset Has Begun
• Watch: Palo Alto Networks Quantum
• Blog: Palo Alto Networks Leads the Way with Quantum and Multicloud Security
• Blog: Introducing Palo Alto Networks Quantum-Safe Security
• Blog: Palo Alto Networks Announces New Quantum Security Innovations
• Press Release: Palo Alto Networks Delivers Enterprise Wide Quantum Security Readiness for All Customers

The post New Executive Order Accelerates Post-Quantum Readiness Amid the Cryptographic Reset appeared first on Palo Alto Networks Blog.

Anyone who has seen the impressive frame of Stonehenge against the morning’s sunrise cannot help but be struck by its resilience, how it has withstood time and the unpredictable impact of nature and humans. And partly because of this, a recent conversation I had with the CIO of a large healthcare technology company made me realize that it was a fitting metaphor for cybersecurity.

As our conversation wove through familiar topics — the challenges and breakthroughs in enterprise IT architecture — we recognised and discussed a recurring pattern throughout most EMEA and multinational enterprises. Those organisations have gradually but surely evolved into a mosaic of vendor fragmentation, ‘micro-platforms’ across vendor-specific technologies, and rapidly developing data silos that no single IT architecture can solve on its own. 

The increased heterogeneity of hardware, operating systems, and cloud architectures now comes with a dizzying mix of cybersecurity tools and services, often optimised for Vendor X’s platform. This has led to the situation that a large organisation typically has more than 30 cybersecurity point solutions in place to protect their digital assets. And now that we have thrown AI into that mix, designing the right cybersecurity solution is as confusing as it is imperative.

That’s when I was reminded of Stonehenge. Its lintel-and-joinery design is strikingly simple and elegant, and it stands as a brilliant monument to long-term resilience. Just as Stonehenge has endured against natural and human threats, so organisations must build a cybersecurity architecture that endures a revolutionary rate of change and threat diversity, including geopolitical turbulence and AI entering the value chain. 

For CISOs, CIOs, board members, C-suite executives and line-of-business leaders concerned with operational resilience, cybersecurity architecture matters—deeply. 

And we should not forget that cybersecurity is a data problem. The more telemetry data you have, the more effectively you can execute security algorithms and protect your digital essentials across all your enterprise IT pillars, i.e., IT, OT, Clouds, Networks, Workplace, Endpoints, etc. We at Palo Alto Networks are able to combine relevant telemetry data from networks, firewalls, clouds, browsers, endpoints and the internet. 

Stonehenge was built from massive, self-reinforcing pillars and platforms of stone. The lintels and joinery help hold together the overall structure as a cohesive unit, and they have striking similarities to how IT architects are now thinking about cybersecurity. In today’s technology architecture, Stonehenge’s vertical pillars are an IT organisation’s specialised, vendor-specific IT domains—sometimes with its own security tools and capabilities rather than as a strategically integrated zero-trust cybersecurity framework across your enterprise IT pillars.

Now, Stonehenge’s with its unique resilience, can also serve in its own construction as a model for modern cybersecurity architecture. Like our evolution towards modular platformisation evolved deliberately and assuredly over time and it spans all key domains of cybersecurity, ie network, cloud, AI,  identity security and all key building blocks for an AI-driven SOC, the last line of defense that has to be real-time. In other words, it is the linchpin of our strategy for enterprise security built upon such key areas as Identity, the Autonomous SOC, and Network Security. 

Stonehenge’s lintel is analogous to cybersecurity platformization, a growing trend rapidly replacing the now-outdated best-of-breed point solution mindset. This employs a modular approach that gives flexibility and control to the security architect looking to add security domain capabilities as needs evolve. The mortise-and-tenon joinery of Stonehenge works because the parts fit together rather than being stacked as an afterthought, in much the same way modern cybersecurity frameworks are built upon the concept of embedded functionality rather than being bolted on. 

An important example here is Palo Alto Networks’ decision to power the cybersecurity platform core with Precision AI, rather than its technology being added as a separate tool. This approach enables Precision AI to power data, analytics, and workflows, making it an omnipresent resource for smarter and faster prevention, detection and response.

Another important element of any enduring architecture is its ability to provide stability to the overall framework. In cybersecurity architecture, this is the all-important cyber data layer across an integrated zero trust framework. As organisations continue to struggle with data silos across networks, cloud environments, security operations centres, and edge systems, the cybersecurity data lake takes on a heightened role of importance for the resilience of the entire cyber framework. Again, let’s not forget, cybersecurity is a data problem, a domain in its own right across all vertical IT pillars.

Now, Stonehenge with its unique resilience, can also serve in its own construction as a model for modern cybersecurity architecture. Like our evolution towards modular platformization evolved deliberately and assuredly over time and it spans all key domains of cybersecurity, i.e.  network, cloud, AI, endpoints, identity security and all key building blocks for an AI-driven SOC, the last line of defense that has to be real-time. In other words, it is the linchpin of our strategy for enterprise security built upon such key areas as Identity, the Autonomous SOC, and Network Security/SASE. 

Another critical element of the cyber platform is something even Stonehenge hasn't had to face: securing AI itself, especially the opportunity and threat represented by agentic AI. AI security must become part of the platform design and implementation, as we have done with our Prisma AIRS (AI Runtime Security) platform for enabling an organisation's growing AI portfolio to remain a vital asset and not an inviting attack vector. Agents now are not just another non-human identity; they are an entirely new class of identity, with a striking mismatch in speed between agent decision-making and human governance. The inside-out attack paths taken by hackers' ill-intentioned agents represent a major threat to under-protected AI supply chains. The same pressure now also comes from geopolitics and from AI moving into the value chain itself, such as in the case of the Factory of the Future.

Similarly, our recent acquisition of CyberArk gives us what we believe is the industry’s strongest identity security platform, Idira, positioning it as yet another vertical pillar connected to the overall cybersecurity platform lintel. Cortex XSIAM and its security data lake are deliberately open — ingesting and correlating third-party telemetry alongside our own, over 17 petabytes of telemetry data each day — to form a secure data layer that is accessible to users based on policy management and credentials validation. Palo Alto Networks leverages this mountain of data, along with around-the-clock scanning of more than 5 billion daily security events, to feed Precision AI in order to detect and block potentially devastating attacks. Currently, we detect about 9,6m new attacks per day that have not been there the day before. The use of automated AI in attack vectors has been accelerating the time of exfiltration of data from the compromise of an organization. This delay was 9 days about 3 years ago, now data is exfiltrated in most cases in less than a day, sometimes already within less than one hour!

In this context, it's also important to highlight the importance of an Autonomous SOC pillar, particularly since compliance reporting windows are continuously contracting from days to mere hours calling for real-time, highly automated defence. Today, mean-time-to-detect and mean-time-to-respond are board-level imperatives commanding more conversation and attention at an organisation’s highest levels. The Autonomous SOC pillar is a vital element in helping enterprises achieve even faster detection and remediation, ideally down into single minutes. If it also integrates the historic enterprise SIEM you can further simplify your SOC operations and gain solid financial benefits by platformization of your security relevant data.

Finally, keep in mind the use of supply chains to build the actual platform. For Stonehenge, that was an impressive physical supply chain: The bluestones used in the structure were hauled about 250 kilometers from Wales without the benefit of air, rail, or truck transport. For Palo Alto Networks’ cybersecurity platform, the supply chain was no less impressive, but more virtual than physical, often faced with attacks on third-party interdependencies such as SaaS applications, APIs and in times of Frontier AI models, the Open Source components. 

Like the pyramids, the Great Wall of China, and the Roman road system, the most remarkable aspect to Stonehenge isn’t just its engineering elegance, but its ability to withstand changing conditions and threats over time. Whether you’re a CEO, board member, CIO, CISO or security engineer, the decisions you make about cybersecurity carry significant impact and implications. In order to achieve Stonehenge-like resiliency, technical and business leaders should commit to an architectural model designed not only for today’s needs, but for what those needs are likely to be over the long term. 

Therefore, cybersecurity should be architected as a horizontal, dedicated platform across all your IT domains and businesses. With this you are able to provide real-time and platformized cybersecurity for tomorrow. And tomorrow is going to be a more and more AI-driven business world. 

 

Helmut Reisinger is CEO for Europe, Middle East, and Africa at Palo Alto Networks.

The post Built to Last: What Stonehenge Teaches us About IT Architecture & Cyber Resilience appeared first on Palo Alto Networks Blog.

When a major cyber incident hits, all eyes are on the CISO.

They become the invisible CEO of crisis, steering the entire enterprise through the storm, managing stakeholders and making major decisions under immense pressure. The clock is ticking. Every minute can mean more systems affected, more data exposed, greater operational disruption and a growing risk to customer trust and corporate reputation.

And this on top of an already expanded day-to-day role, where they are expected to make decisions with incomplete information, brief the board, support legal and communications teams, manage technical response and reassure the business, all while knowing that any delay could increase the damage.

But a troubling pattern often emerges once the smoke clears. The CISO may find themselves held responsible for the incident that just happened, and in some cases personally liable, while still being expected to prevent the next one. Yet, at the same time, their influence over the strategic decisions that shape cyber risk can quickly diminish. 

This cycle takes a toll. Across EMEA, we are seeing the personal and organisational impact of that pressure, from burnout and leadership turnover to growing concerns about long-term resilience.

That pressure often comes at a demanding stage of life too. Many security leaders reach the CISO role when career responsibility is peaking at the same time as responsibilities outside work, from ageing parents and family commitments to their own health.

With an average CISO tenure now reduced to between 18 and 26 months, and nine out ten reporting feeling moderate to high stress, a more sustainable model is needed for structural and personal resilience.

Cybersecurity is far more complex than it was a decade ago. AI-powered attacks and autonomous agents are increasing the speed and scale of threats. At the same time, the CISO has never had more potential influence over business strategy. The challenge is ensuring the support around the role evolves as quickly as the threat landscape.

That is why it’s time to stop treating cybersecurity as a technical function alone and recognise the CISO as a strategic business leader.

Structural equity - breaking the cycle of isolation

The burden of cyber resilience should not rest on one individual. Yet too often, organisations place responsibility on the CISO without providing the support, influence or measures of success needed to help them thrive.

Part of the problem is how the role is measured. CISOs are judged by whether incidents happen, rather than by the quality of preparation, resilience planning, risk reduction and secure business enablement.

And preparation can really help reduce the pressure. Regular red teaming, tabletop exercises and incident simulations mean the CISO is not carrying the crisis alone when a breach happens. The organisation has rehearsed its roles, decision points and escalation paths before the stakes are at their highest. 

But after a crisis, organisations also often fall back into day-to-day survival mode, undoing the progress made when security was treated as a critical part of business planning rather than a technical function. Strong resilience requires the CISO to have a permanent seat at the table for all strategic decisions, from M&A to digital transformation.

That influence only comes with strong foundations. This includes visibility of critical assets and risks, security controls that are fit for purpose and the operational discipline to maintain them over time.

• Invest in leadership as much as certifications: The modern CISO needs diplomacy, judgement and the ability to translate risk into business terms. Different backgrounds can strengthen that role, bringing fresh perspective when solving problems that are no longer purely technical
• The ‘Shared CISO’ model: Cyber resilience should not rest on one pair of shoulders. The most resilient organisations embed responsibility for cybersecurity across the business, while creating stronger support structures around the CISO through deputies, shared ownership of cyber risk and clear succession planning. This reduces pressure on individual leaders and helps ensure resilience is built into the organisation itself

Strategic diplomacy - aligning people and purpose

Cyber resilience depends on people as much as technology, and a CISO’s success depends on building alliances across the business. The strategic diplomat CISO focuses on moving the conversation from ‘no’ to ‘how?’ by building deep relationships with other leaders, every team and every department across the organisation.

By understanding the business’ growth drivers, the CISO can align security goals with the board’s priorities. That means agreeing meaningful measures of risk and readiness, preparing for difficult questions and giving the business a clear view of where it is exposed. 

Security and growth must be seen as a single strategic fabric. Integrating security into the development of internal AI tools and customer-facing products helps ensure innovation is secure by design, rather than being a hurdle to overcome later.

The post The Invisible CEO of Crisis: Breaking the Cycle of CISO Burnout appeared first on Palo Alto Networks Blog.

Palo Alto Networks is pleased to announce the successful completion of a new Cloud Medium security assessment conducted by the Canadian Centre for Cyber Security (Cyber Centre), significantly expanding the number of Palo Alto Networks cloud services assessed for Protected B / Medium Integrity / Medium Availability (PBMM) environments. This assessment includes a broad range of capabilities across our Cortex®, Cortex Cloud and Strata™ platforms. By achieving this milestone, Palo Alto Networks enables  organizations handling Canada’s most sensitive data to leverage a unified, AI-driven security architecture without compromising on compliance or operational resilience.

For years, many organizations viewed PBMM as something that only mattered to the Canadian federal government. It was often seen as a procurement requirement—a framework tied to public sector cloud adoption, relevant for departments handling Protected B information, but not necessarily for the private sector.

That assumption is changing.

The reality is that the challenges driving PBMM are no longer unique to government environments. Banks, energy providers, transportation networks, healthcare organizations, crown corporations, and other critical infrastructure operators are now facing many of the same pressures:

• Expanding attack surfaces across hybrid and multi-cloud environments.
• Increased regulatory scrutiny and privacy obligations.
• Greater operational dependence on cloud and AI technologies.
• Increased reliance on third-party providers and software supply chains.
• The need to maintain operational resilience during cyber incidents and disruptions.
• A growing expectation that organizations can demonstrate—not just claim—security maturity.

That is why PBMM matters far beyond Ottawa. At its core, PBMM represents a rigorous approach to validating whether enterprise-grade security platforms can operate securely in environments where trust, resilience, and operational continuity are critical.

Increasingly, that level of assurance matters to everyone.

What PBMM Really Represents

PBMM, a rigorous cybersecurity and data classification standard used by the  Canadian Centre for Cyber Security, stands for Protected B / Medium Integrity / Medium Availability. While often associated with federal cloud security requirements, PBMM is not simply a checkbox exercise. It is a comprehensive assessment framework aligned to Canadian cybersecurity guidance and operational security expectations.

What makes PBMM important is that it evaluates whether platforms and services can securely support sensitive and mission-critical workloads in real-world environments.

Palo Alto Networks meeting these rigorous PBMM requirements through three core pillars:

• Strata (Network Security): Secures data resiliency and zero trust connectivity, driving robust perimeter and cloud edge protection.
• Cortex Cloud (Cloud Security): Provides complete visibility, security governance, and data protection across complex cloud-native architectures.
• Cortex (Security Operations): Powers the agentic SOC, combining unified data, AI, and automation to detect and respond to threats in real time.

These are not theoretical requirements. They are practical operational expectations designed for environments where downtime, visibility gaps, or security failures can have significant consequences.

Organizations today are no longer evaluating cybersecurity solely based on features. They are evaluating whether platforms can be trusted to support critical operations at scale.

Why Security Expectations Are Changing

The cybersecurity landscape has evolved dramatically. Infrastructure is distributed across cloud providers, SaaS applications, remote users, third-party integrations, operational technology (OT), AI platforms, and interconnected supply chains. At the same time, attacks have become faster, more automated, and more disruptive.

In this environment, security can no longer be treated as a compliance exercise. Organizations need confidence that their platforms, operational processes, and security controls can function effectively under pressure.

This is why Palo Alto Networks has undertaken independent PBMM assessments across its portfolio, providing customers with greater assurance and trust. By meeting these rigorous standards into Strata and Cortex, we enable non-government entities—like financial institutions and utility providers—to deploy the same defensive rigor used to protect national security systems.

Transforming Critical Infrastructure with a Unified Platform

To effectively manage risk, critical infrastructure operators require a platform approach that helps eliminate security silos, reduce manual intervention, and accelerate threat mitigation.

Key Portfolio Advantages for Critical Infrastructure & Enterprise:

• AI-Driven Threat Detection & Response: Cortex XSIAM® and Cortex XDR® unify telemetry across endpoints, network, and cloud to deliver unparalleled visibility and automated threat stitching, neutralizing advanced cyberthreats before they disrupt operations.
• Comprehensive Cloud Native Protection: Cortex Cloud secures applications from code to cloud to SOC, offering posture security, data protection, and continuous compliance monitoring tailored to stringent Canadian data standards.
• Zero Trust Network Security: Strata enables secure access and consistent policy enforcement across campus, branch, and data center environments, protecting critical OT and IT systems from lateral threat movement.
• Elite Incident Response: Backed by Unit 42®, organizations gain access to threat intelligence and rapid incident response services to augment their teams and build long-term cyber resilience.

Operational Resilience Is Becoming a Strategic Requirement

One of the most significant shifts occurring across industries today is the growing focus on operational resilience. Organizations are increasingly asking questions that extend beyond traditional cybersecurity controls:

• Can we maintain critical services during a cyber attack?
• Do we have visibility across our cloud environments and supply chain dependencies?
• Can we rapidly detect, respond to, and recover from disruptions?
• Are our governance processes keeping pace with cloud adoption and AI innovation?

As organizations adopt cloud-native architectures, AI-driven technologies, and interconnected digital ecosystems, resilience has become a board-level concern. The ability to prevent incidents remains important, but organizations are equally focused on their ability to withstand, respond to, and recover from them.

This is where frameworks like PBMM provide value. Beyond evaluating security controls, PBMM assesses the governance, operational processes, monitoring capabilities, and risk management practices that help organizations operate securely.

For critical infrastructure operators, resilience is no longer simply an IT objective—it is a business imperative. Increasingly, the organizations that earn trust are those that can demonstrate they are prepared to operate effectively when disruption occurs.

Final Thoughts: PBMM Reflects the Future of Trust

PBMM may have started solely as a government assessment framework, but its relevance now extends far beyond federal environments. It represents something universal: the ability to operate securely, reliably, and transparently in environments where trust matters most.

By expanding our PBMM-assessed offerings across Cortex and Strata, Palo Alto Networks underscores its commitment to securing Canada's digital future. We provide the validated foundation organizations need to innovate with confidence, protect sensitive data, and maintain operational continuity under any circumstance.

Read the Assessment Summary Report

To learn more about the Palo Alto Networks Cloud Medium security assessment, review the publicly available assessment summary report issued by the Canadian Centre for Cyber Security.

Ready to modernize your defenses with PBMM-assessed solutions? Schedule a demo with our team or contact Unit 42 to learn how we can help elevate your organization's resilience against emerging cyber threats.

The post Securing Canada’s Digital Future: Why PBMM Matters Beyond Government appeared first on Palo Alto Networks Blog.

Frontier AI is moving faster than most governance and response systems were designed to handle.

The corporate landscape across the Japan and Asia-Pacific (JAPAC) region is facing an unprecedented regulatory and operational reckoning. The rise of hyper-autonomous ‘frontier’ AI models is pushing cyber security out of human hands and into a real-time war of machine against machine. This shift has triggered a highly coordinated enforcement wave cascading through JAPAC’s premier digital hubs, where regulators and enterprises are moving in lockstep to address machine-speed threats. 

With corporate watchdogs Australian Prudential Regulation Authority (APRA) and Australian Securities and Investments Commission (ASIC) firing warning shots via urgent market letters, and neighbouring authorities like the Monetary Authority of Singapore and South Korea’s central government enacting strict new AI safety rules, organisations are being forced to completely overhaul their defensive architecture. Decades of relying on slower, committee-based governance are being shattered by new threat intelligence showing that autonomous AI agents can now exploit vulnerabilities and exfiltrate critical data within minutes—turning traditional 72-hour regulatory reporting windows into mere post-mortems.

The warning comes as the gap between corporate readiness and technological reality widens right across the JAPAC corridor. Much of the region’s current governance and cyber risk architecture still reflects a legacy system engineered for predictable, slower-paced environments. We have spent years building risk models where vulnerability discovery, incident escalation, and defensive response unfold gradually enough for traditional executive oversight and committee structures to remain effective. But that comfortable pace has officially vanished.

The Machine-Speed Reality

The sheer velocity of this shift was highlighted during restricted testing of Anthropic’s advanced frontier model, Claude Mythos, under an initiative known as Project Glasswing. Palo Alto Networks was among a select group of technology and cyber security organisations chosen to evaluate the implications of the model before its broader release. Mythos demonstrated an unprecedented capability to identify and exploit vulnerabilities across major operating systems at a level matching or exceeding advanced human experts.

During combined testing involving Mythos, Claude Opus 4.7, and OpenAI’s GPT-5.5-Cyber, the real-world impact of machine speed became starkly visible. In a single month, Palo Alto Networks disclosed 26 Common Vulnerabilities and Exposures (CVEs) representing 75 distinct issues, a massive surge compared to a typical monthly volume of fewer than five CVEs.

While discovering flaws at that scale would historically have raised uncomfortable questions around software quality, the landscape has fundamentally shifted. In this new era, radical transparency, paired with the ability to reflect and act instantly, has emerged as a critical corporate superpower. Frontier AI is accelerating both sides of the digital chessboard simultaneously: while attackers are gaining unprecedented speed, defenders are gaining a level of visibility that simply did not exist a few years ago. Real-time warfare between AI defenders and AI attackers is rapidly becoming the standard operating model.

AI Agents: The New Corporate ‘Insiders’

This shift introduces a profound dilemma for corporate leadership. Recent regulatory guidance repeatedly emphasises the necessity of human supervision, and for good reason—ultimate accountability must always remain with people. Boards must still set risk appetite, Chief Information Security Officers (CISOs) must determine operational thresholds, and security teams must decide how much authority autonomous systems should hold inside critical environments.

However, organisations must now look a step further. Autonomous AI agents—operating on behalf of employees, suppliers, or automated workflows—are quickly becoming the new corporate ‘insiders’. If not managed with extreme care, they represent massive, systemic blind spots.

Current identity and access frameworks are starting to buckle under the strain because they were never built to distinguish between human users and autonomous agents acting on their behalf. Traditional identity systems assume a predictable human pattern: a user authenticates, requests access, and operates within set boundaries. Autonomous agents, by contrast, interact continuously with APIs, generate code on the fly, move fluidly across workflows, and operate with delegated authority from trusted users.

When these agents begin operating deep inside critical infrastructure, financial services, or government workflows, the risk profile changes entirely. Security teams are no longer just dealing with stolen passwords or human misuse; they are managing autonomous systems capable of acting at machine speed across highly interconnected environments, with potentially devastating consequences if control is lost.

The Failure of the 72-Hour Window

This acceleration has effectively broken traditional regulatory reporting timelines. Recent threat observations from Unit 42 reveal that in approximately 20 percent of modern breaches, attackers successfully exfiltrate data within the very first hour of a compromise.

When data theft occurs inside 60 minutes, a 72-hour reporting window ceases to function as an effective defense mechanism. Instead, it becomes a post-mortem.

For example Australia’s current reporting obligations—including those under the SOCI Act, CPS 234, and the Privacy Act—were largely designed for static environments where defenders had sufficient time to investigate, escalate internally, and coordinate remediation before damage spread. Today, many CISOs quietly acknowledge the immense operational strain created by overlapping reporting frameworks during a live crisis. In the chaotic early stages of a compromise, security teams frequently find themselves managing compulsory reporting requirements from different regulators while their engineering teams are still actively trying to contain a fast-moving incident.

A Region-Wide Regulatory Reckoning

Australia is far from alone in this challenge. The regulatory anxiety echoing through the halls of APRA and ASIC is part of a highly coordinated, region-wide crackdown across the Japan and Asia-Pacific (JAPAC) tech corridor. As frontier models shrink the ‘time-to-exploit’ to near zero, neighbouring digital economies are rapidly realising that their legacy frameworks are equally vulnerable.

In Singapore, the regulatory response has been immediate. The Cyber Security Agency (CSA) recently issued a stark advisory warning that advanced frontier models can examine complex codebases and automate attacks faster than human developers can write patches. In lockstep, MAS finalised its Guidelines on AI Risk Management. Under these new rules, financial institutions are now mandated to perform continuous ‘AI Cyber Stress Testing’— requiring boards to prove that complex, autonomous AI-to-AI interactions within their systems won't trigger an unmanageable domino effect.

Meanwhile, South Korea has shifted from guidelines to hard law. The nation's landmark AI Basic Act (Framework Act on Artificial Intelligence) has officially entered into force, creating strict compliance mandates, mandatory data audits, and extraterritorial penalties for any enterprise deploying high-impact AI systems without ironclad human guardrails.

Across JAPAC, a uniform regulatory shift is underway: voluntary AI ethics frameworks are being replaced by proactive, real-time enforcement measures. 

Moving with Discipline

Organisations broadly acknowledge that AI demands a distinct approach, yet implementation gaps remain. Businesses must move away from managing AI like standard software and instead commit the significant defensive resources needed to protect complex AI supply chains. 

The language coming from regulators reflects these exact challenges. ASIC Commissioner Simone Constant warned that frontier AI capability could expose vulnerabilities at unprecedented speed and scale, creating systemic consequences across entire sectors. Her message to corporate Australia was direct: do not wait for perfect clarity to address the threat posed by new AI models. Instead, organisations must act now, and act with discipline, to strengthen the cyber resilience fundamentals that underpin their businesses.

The testing conducted within Project Glasswing ultimately proved that while frontier models can expose weaknesses at terrifying speed, that exact same capability can be weaponised defensively. By deploying AI to reduce exposure and identify vulnerabilities before adversaries can operationalise them, organisations can effectively level the playing field.

The most resilient organisations over the next few years will be those that combine real-time frontier AI defensive capabilities with disciplined human supervision, rather than treating the two as separate priorities. In the era of machine-speed warfare, you cannot successfully have one without the other.

To learn more about how we are securing the frontier of technology, visit the Palo Alto Networks Trust Center and explore the latest threat insights from Unit 42.

The post Beyond Human Oversight: Adapting to the Frontier AI Era appeared first on Palo Alto Networks Blog.

Modern phishing campaigns are no longer trying to convince users. They are trying to outrun them. By forcing an automatic progression from click to download, attackers eliminate the moment of hesitation entirely by forcing files to download instantly using trusted cloud platforms like Dropbox and Google Drive.

Detecting when these legitimate SaaS auto-download features are being weaponized is an immense challenge for traditional defenses. This is exactly where Cortex^® Email Security steps in. By combining deep static analysis with advanced behavioral intelligence, the module can distinguish in this attack between a benign file share and a malicious, forced-momentum trigger.

This technical detection is vital because while the autodownload method is the primary cause of infection, its effectiveness relies on a clever strategy, using a wide range of changing social engineering lures. By alternating between lures like 'Invoices' or 'Quotes,' attackers rotate their themes to catch a wider variety of victims. This strategy allows attackers to convert trusted email links into rapid, dangerous file executions that effectively evade standard security measures.

How Forced Momentum Drives Auto-Downloads

The core of this attack leverages the infrastructure of real SaaS providers to eliminate the user's preview buffer. Typically, cloud sharing directs users to a webpage for file examination. In this campaign, however, forced-download parameters (such as ?dl=1 on Dropbox) are used instead. To ensure the victim executes the file once it lands on their machine, attackers hide the danger behind "visual anchors." By using double extensions like PDF and .EXE, the threat actor exploits default settings in certain operating systems that hide known extensions. The user's eyes stop at the familiar ".PDF" or ".ZIP," leading them to believe the file is a harmless document rather than a malicious executable.

When the targeted victim clicks the link in the email, it triggers an immediate file download in the browser, effectively bypassing any intermediary steps.

Attack Flow: From Email to Execution

• The Bait: A highly personalized email arrives, using a trusted cloud link (like Dropbox) to lower the victim's guard.
• The Trap: Clicking the link skips the usual "preview" screen and instantly drops a file onto the victim's computer.
• The Disguise: The file is cleverly named to look like a safe PDF or document, hiding its true identity as a harmful program.
• The Lock: In many cases, the attacker ensures only the intended victim can open the file, preventing security tools from scanning it first.
• The Takeover: Once the victim opens the file, the attacker gains remote access to the system.

The Library of Lures Strategy

To fuel the autodownload machine, attackers employ a flexible strategy by switching between various social engineering themes. This spear phishing campaign targets specific inboxes, such as "Orders," to exploit professional routines. Some common lures found in this campaign include:

• Financial Urgency – Fake "Invoices" or "Receipts" that induce anxiety. These often set close-day payment deadlines, pressuring recipients to click quickly.
• Business Operations – "Quote Requests" or "Purchase Orders" that exploit professional habits.
• Deceptive Naming – Concealing the download as a safe document, using display text like "invoice.pdf" in the email body to hide the underlying Dropbox URL.

Government Domain Impersonation

Attackers often leverage high-authority lures designed to paralyze a user's critical thinking. In one sophisticated wave, we observed threats impersonating a government entity by exploiting the high-reputation, official government domain. By borrowing the reputational authority associated with official infrastructure, the attacker successfully maneuvered an "Unidentified Payment Notice" past standard "Untrusted Sender" filters. To the recipient, the email carries the weight of a sanctioned document. Fearing legal or financial ramifications, they feel a heightened sense of urgency to click "View Invoice" to resolve the issue immediately.

Employee Impersonation

When government authority isn’t the angle, attackers shift to impersonating internal staff. In one case, the sender’s display name was spoofed to match a real employee in the target organization. Attackers rely on a “Momentum of Trust” tied to familiar names to overwhelm user judgment. Even when a generic Gmail address is used, users, especially those on mobile devices, rarely pause to check the underlying headers.

Internal Trust Amplification ("Human Relay")

The most effective aspect of this campaign occurs through Internal Laundering, where the threat shifts from external suspicion to a trusted internal message. This was observed when a Finance Department employee received a "Quote Analysis" file and, believing it to be a valid inquiry, mistakenly forwarded the link to the Procurement department.

At that stage, the attack no longer depended on deception, it propagated through trusted human workflows. These various tactics illustrate the sophistication and adaptability of phishing campaigns and highlight the importance of vigilance in email security.

How We Uncovered a Single Threat Actor

Although the lures appeared diverse, a deeper technical analysis revealed that they were all orchestrated by a single, coordinated threat actor.

By mapping the campaign, we uncovered a significant pattern: Each autodownload link pointed to a different file hash to evade signature detection, but all unique executables were ultimately associated with the same parent installer hash.

The file was identified as a specific Remote Monitoring and Management (RMM) executable, an administrative software used to manage computers remotely. Because RMM tools are legitimate, they often trigger fewer alerts than traditional Trojans. This allows the attacker to maintain persistent access under the guise of “authorized” system activity.

How Cortex Email Security Addresses the Threat

To defend against a campaign that emphasizes speed and rotation, behavioral analysis is essential.

The Cortex^® Email Security Module addresses this threat:

• Advanced URL Analysis – Detection of forced-download parameters, combined with delivery of high-risk files via URLs.
• Deep Metadata Correlation – Correlating sender identity with behavioral anomalies to flag threats that traditional scanners might overlook.
• LLM-Based Intent Analysis – Classifying phishing themes (invoice, payment, quote) despite variation.

The security engine triggers an alert by synthesizing LLM analysis with real-time email telemetry, global threat intelligence and behavioral signals.

Securing the Click

The combination of autodownload links and rotating lures is crafted to exploit user momentum and the "psychology of trust."

This campaign represents a shift from deception to acceleration. Attackers no longer need perfect lures, they only need to remove friction. Defenders must evolve accordingly, focusing not only on what a link is, but on what it forces a user to do.

Palo Alto Networks Cortex Advanced Email Security was built for this evolution. By moving beyond static file analysis to identify the behavioral "red flags" of autodownloads and forced-momentum URLs, we provide the visibility needed to stop these attacks before they reach the device.

The module examines email metadata, content, and behavior to uncover hidden malicious intent and sophisticated impersonation, including AI-crafted threats. By assigning precise risk scores to every detection, the system filters out the noise, allowing analysts to move past alert fatigue and focus on the most critical threats first.

Indicators of compromise discovered during this research are detailed on Unit 42’s GitHib instance.

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FAQs

1. Why is the "Auto-Download" parameter so effective? It removes the "moment of doubt." By bypassing the preview page, the attacker forces the file onto the computer instantly, prompting the user to "Open" it out of habit.
2. How does the use of rotating lures benefit the attacker? It maximizes both psychological and technical success. People have different "blind spots" (e.g., finance professionals are likely to click on invoices), and variety increases the chances of finding a template that can bypass specific customers' security filters.
3. Why might a sandbox fail to catch the malicious file? Because the link was "Identity-Bound." To the scanner, the link appeared to lead to a harmless error page (cloaking), resulting in a false negative.

Cloaking involves showing different content to security scanners than what is presented to the victim. By using Identity-Bound access, the file only reveals itself to the intended target.

The post The Dangerous Momentum of Autodownload Phishing appeared first on Palo Alto Networks Blog.

Palo Alto Networks recently joined the DNS-OARC community as a Platinum Member. Together, our organizations share a commitment to advancing collaboration in research and operational excellence across the global DNS ecosystem. DNS is critical to both internet infrastructure and security, and this collaboration facilitates the sharing of real-world insights among researchers and practitioners.

Our Contribution

We help organizations secure their digital environment with a comprehensive portfolio of cybersecurity solutions spanning Network, Cloud, Security Operations, AI and Identity. Trusted by more than 70,000 customers worldwide and informed by Unit 42^® Threat Intelligence, their AI-driven platforms help organizations reduce complexity, modernize with confidence, and securely enable innovation.

As a Platinum Member, our subject matter experts will actively participate in the DNS-OARC community by engaging in discussions and contributing to research on evolving DNS threats and network challenges. The growing intersection of DNS and security makes access to intelligence and experience increasingly important. It strengthens the community’s ability to respond to emerging challenges and improves resilience across the internet.

Through our participation, our customers will gain stronger protection informed by community-driven intelligence and real-world operational insight. These learnings are continuously integrated into our threat intelligence and security capabilities. Our participation signals our support for DNS-OARC’s mission of fostering open dialogue and shared learning across the DNS ecosystem. This collaboration helps bridge DNS operations with broader security practices, improving coordination between operators, researchers and security practitioners.

Our Commitment to the DNS-OARC and Global Communities

Collaboration between our organizations strengthens the connection among DNS operations and modern security practices by bringing together operational insight and a global community dedicated to advancing the internet’s resilience.

For the DNS-OARC community, our commitment enhances knowledge sharing around evolving DNS threats, large-scale network operations and practical approaches to emerging challenges.

For organizations and customers, it reinforces a stronger alignment between DNS infrastructure and security, expands access to community-driven intelligence and supports more resilient, well-informed defenses.

Tong Zhao, Senior Manager of DNS Security Engineering, Palo Alto Networks:

We recognize the critical role of DNS-OARC in DNS operations and research. The teams from Palo Alto Networks believe that our DNS-OARC membership aligns perfectly with our goals. We are eager to participate in and contribute to the DNS community.

Our partnership with the DNC-OARC highlights the value of open collaboration in helping both the community and its participants stay ahead of an increasingly complex threat landscape. To learn more about how our expertise and insights support DNS-OARC’s mission to improve the security and stability of the internet’s DNS, visit DNS-OARC.

The post Palo Alto Networks Joins DNS-OARC as a Platinum Member appeared first on Palo Alto Networks Blog.

In the race to digitise public services, the UK’s digital estate has grown into a vast, borderless ecosystem that manual audits can no longer track. For UK Government departments, local authorities and NHS trusts, it is a sprawling, shifting landscape of cloud workloads, legacy infrastructure, shadow IT and third-party supplier connections.

This complexity creates blind spots that modern threats exploit. Recognising this vulnerability, the UK Government is moving toward a secure-by-design digital infrastructure, with the 2026 Government Cyber Action Plan (GCAP) setting a high bar for resilience. A central theme of the GCAP is the urgent need for the government to have better visibility of cyber security and resilience risk. Fundamentally, organisations cannot secure what they cannot see. As the GCAP explicitly states, the Government will use “data sources from across the government to truly understand government-wide and departmental cyber risks.”

The Challenge: Visibility in a “Landscape”

Many public sector organisations rely on a complex web of spreadsheets, data calls, legacy tools and manually curated lists to create an inventory of their internet-connected assets. But attackers do not look at an organisation's internal lists; they scan the internet for what they have forgotten to secure. Whether it is an unpatched server from a legacy project or a misconfigured database in a department, these "unknown unknowns" are the primary entry points for attackers.

The Strategic Mission: Empowering the Public Sector and Critical Industries

Palo Alto Networks Cortex Xpanse® is an active external attack surface management (EASM) solution that provides an outside-in view of organisations' entire digital footprint. It helps leaders meet national resilience goals:

• Comprehensive, Continuous Visibility: Xpanse scans the global internet space continuously and identifies every asset associated with an organisation, without requiring software agents to be installed on your systems.
• Accelerate Response: Leveraging automation, the solution streamlines response processes and enhances collaboration across dispersed teams from the sharing of findings to tracking actions and remediation.
• Supply Chain Integrity: Inline with the new Cyber Security and Resilience Bill (bringing managed service providers and critical third parties into scope), Xpanse allows organisations to assess the internet-facing security posture of third-party partners and suppliers, ensuring a weak link elsewhere doesn't compromise the broader mission.
• Alignment with GovAssure: Xpanse provides a consolidated risk profile and inventory for all internet-facing and cloud assets required for GovAssure assessments, turning a manual, months-long audit process into a continuous, data-driven cycle.
• Investment prioritisation: Xpanse provides that much needed visibility to help executive committees and boards prioritise investment decisions on legacy IT and technical debt.

Aligning to National Cybersecurity Centre (NCSC) Guidance

Palo Alto Networks Cortex Xpanse aligns with the National Cyber Security Centre (NCSC) external attack surface management (EASM) buyer's guide by providing automated discovery, continuous monitoring and risk prioritisation of internet-facing assets. It replaces manual, point-in-time audits with a proactive, agentless solution. By automating the discovery of all internet-accessible assets (including shadow IT and unmanaged cloud operations) the platform fulfills the NCSC’s core requirement for continuous global monitoring and rapid attribution. This data-driven approach allows for the automated prioritisation of critical exposures, such as RDP, and integrates seamlessly with multiple third-party automation and visualisation tools, including Cortex XSOAR® and XSIAM, to accelerate remediation with national incident response standards.

In fact, with Palo Alto Networks deployment of Cortex Xpanse, we were able to achieve a 95% reduction in external vulnerability management spending across more than 700,000 cloud instances, while improving coverage and outcomes.

Palo Alto Networks Cortex Xpanse Capabilities

• Discover Assets: Leveraging organisations' known asset inventory and other data points, Xpanse performs continual, automated discovery of all internet-accessible assets, effectively eliminating blind spots created by shadow IT and unmanaged cloud operations.
• Obtain Information: Always-on, continuous monitoring of an organisation's entire attack surface through daily scans of the global IP address space, ensuring that newly exposed services are identified quickly and accurately.
• Perform Analysis: Xpanse automates and prioritises alerts on all identified risks by severity, enabling organisations to optimise resolution and risk management, allowing teams to properly allocate resources and focus on the most critical risks to the organisation.
• Display Information and Provide Advice: Leveraging a unified view of the internet facing and cloud-based estate, Xpanse provides specific resolver guidance for every identified issue, supporting and monitoring automated resolution through multiple native integrations.
• Monitor Risk: Always on, discreet continual monitoring provides an independent real time status of the digital estate. Leveraging the threat intelligence capabilities of Palo Alto Networks, Xpanse is uniquely positioned to provide rapid coverage for newly discovered vulnerabilities, exploits or misconfigurations.

Securing the public sector requires a move from manual, point in time assessments to data-driven intelligence. Cortex Xpanse provides the foundations to remove blind spots, secure the supply chain and prevent unknown vulnerabilities in the face of sophisticated threats.

For further information and case studies, visit the links below, or schedule a demo.

• Palo Alto Networks: Slash false positives, remediation time budget with Cortex attack surface management.
• U.S. Pentagon: Palo Alto Networks Cortex Xpanse supercharge the Cyber Defences for the Department of Defense.
• Accenture: Secure rapid growth with Cortex Xpanse.

The post Closing the Gap by Enhancing Visibility and Mitigating Risks appeared first on Palo Alto Networks Blog.

Why the GSA OneGov Agreement Is a Game-Changer for Federal Cybersecurity

The mission to modernize government IT is accelerating at lightning speed, largely thanks to the transformative power of artificial intelligence (AI). Federal agencies are strategically leveraging AI to boost efficiency, enhance citizen services, and strengthen national security – a vision fully supported by the administration’s AI Action Plan.

At Palo Alto Networks, we are all-in on helping agencies deploy AI bravely and securely. Because the challenge isn't just about using AI for cyberdefense, but also about defending AI itself. We appreciate the U.S. General Services Administration (GSA) recognizing the critical need for scalable, efficient solutions.

That is precisely why the GSA OneGov Initiative is a massive, game-changing step forward. We are proud to be the first pure-play cybersecurity vendor to secure a OneGov agreement with the GSA. This strategic alliance simplifies and standardizes the process for agencies to access our world-class, AI-powered security platform, ensuring security is foundational to this crucial modernization mission.

The Wake-Up Call: The Silent Threat of AI Agent Corruption

If you needed a clear sign that AI has fundamentally shifted the cybersecurity landscape, our own Unit 42 research provides it. The new reality isn't just about hackers using AI in their attacks; it’s also about how internal AI provides another attack surface for threat actors.

The most insidious new threat we've observed is AI Agent Smuggling, where malicious attackers use AI agents to exploit other agents. Our Unit 42 research highlights two major vectors:

• Indirect Prompt Injection: A security risk in LLMs where a user crafts input containing deceptive instructions to manipulate the model’s behavior, which can lead to unauthorized data access or unintended actions.
• Agent Session Smuggling: Exploit vulnerabilities in agent-to-agent communication, injecting malicious instructions into a conversation, hiding them among otherwise benign client requests and server responses.

This confirms our core belief as stated in a recent secure AI by Design blog: The AI ecosystem (the models, data and infrastructure) is now a complex, expanding attack surface that traditional perimeter defenses were simply not designed to protect.

As I’ve said before, “If you’re deploying AI, you must deploy AI security.”

Secure AI by Design: A Strategic Alliance with GSA

The GSA’s OneGov Initiative aims to streamline procurement and drive down costs by leveraging the purchasing power of the entire federal government. This is more than an agreement; it’s a direct response to the call for a "secure-by-design" approach to federal AI adoption. This agreement simplifies and standardizes the process for agencies to access our world-class, AI-powered security platform, ensuring that security is foundational, not an afterthought. It provides industry leading AI security tools into the hands of our cyber defenders today.

Under the Hood: Technical Capabilities for the AI Ecosystem

To counter the autonomous threats we’re seeing, we provide a platform that protects the entire AI lifecycle, from the developer's keyboard to the data center.

1. Runtime Protection for AI Workloads

Securing the AI supply chain requires visibility across every stage, especially during runtime when models are processing sensitive data.

• Prisma^® AIRS delivers comprehensive security for the entire AI lifecycle, in one unified platform. It allows organizations to deploy traditional apps as well as AI applications, models and agents with confidence by reducing risk from misuse, data loss and sophisticated AI-driven threats. Prisma AIRS provides a clear, connected view of assets in multicloud environments, so teams can eliminate silos, accelerate responses, as well as scale cloud and AI apps securely.
• Our Cloud-Native Application Protection Platform (CNAPP) has achieved the FedRAMP High designation, making it the preferred Code to Cloud solution to secure the entire application lifecycle from development to runtime. Our industry-leading CNAPP eliminates silos to deliver comprehensive visibility and best-in-class protection across multicloud environments.

2. Protecting Users and Data at the Edge

Even the most advanced AI defenses are undermined if users accessing applications and data are left vulnerable outside corporate security boundaries. The explosive growth of generative AI tools and the unseen behavior of AI agents are amplifying data exposure risks.

• Prisma SASE (secure access service edge) secures all users, apps, devices and data, no matter where they are and no matter where applications reside.
  • Prisma Access (FedRAMP High Authorized) and Prisma Browser (FedRAMP-Moderate Authorized) integrate security capabilities, like zero trust network access (ZTNA), secure web gateway (SWG) and cloud access security broker (CASB), to provide a unified policy framework and a consistent user experience.
• This approach helps agencies outpace the speed of AI-driven threats, safeguarding critical data and simplifying operations for a frictionless user experience. It ensures that the human element interacting with the AI is protected by the most stringent security controls available.

Deploy AI Bravely

The GSA OneGov agreement is a pivotal moment that provides federal agencies with the cost-effective, streamlined access they need to deploy AI with confidence. By leveraging our unified, AI-powered platform, government organizations can stop reacting to threats and start building secure-by-design AI environments. We are committed to remaining a key partner in this strategic initiative and helping the government achieve its mission outcomes safely.

For more information and access to promotional offers for new contracts signed on or before January 31, 2028, federal agencies can visit the GSA OneGov website.

The post Securing the AI Frontier appeared first on Palo Alto Networks Blog.

Strengthening Cyber Resilience Across Northern Europe

Across Northern Europe, organizations are redefining how they work, innovate and compete. From the Netherlands’ smart logistics hubs to Finland’s AI-driven public services and the UK’s digital-first financial sector, this region is setting the global pace for responsible, data-driven transformation.

Yet behind this progress lies a growing challenge: security complexity.

According to the IBM Institute for Business Value (IBV), the average enterprise now manages 83 security tools from 29 vendors, leading to fragmented visibility, slower responses and rising risk exposure. In contrast, 96% of organizations that have unified their security platforms say they now view cybersecurity as a driver of business value, not a barrier to it.

That’s where the IBM and Palo Alto Networks partnership is making an impact. Together they are helping Northern European enterprises simplify, secure and accelerate their digital transformation with unified, AI-powered cybersecurity.

From Fragmented Tools to an Integrated Security Foundation

Northern Europe’s strength lies in its strong culture of trust and transparency, advanced digital infrastructure, as well as progressive regulatory frameworks. But as the EU NIS2 Directive, DORA and the AI Act come into force, achieving both compliance and cyber resilience require board-level oversight.

IBM and Palo Alto Networks are helping organizations lead this change. They combine IBM’s deep consulting and industry expertise with Palo Alto Networks market-leading security platforms and solutions, including Cortex XSIAM^®, Cortex^® Cloud™ and Prisma^® Access. This integrated approach protects innovation, enables compliance efforts, and enhances operational efficiency.

The partnership not only secures organizational estates, but empowers faster decision-making, measurable ROI and sustainable transformation.

Five Capabilities Powering Secure Transformation

Organizations want to strengthen cyber resilience without slowing innovation. IBM and Palo Alto Networks help them do just that, through five connected capabilities that turn complex challenges into measurable outcomes.

1. Unified Security Platform: Simplify and See More

The Challenge: Too many tools, too little visibility.
The Reality: Most enterprises run more than 80 security tools from nearly 30 vendors.

By consolidating with IBM’s unified security approach and the Palo Alto Networks platforms, organizations are cutting total product costs by up to 19.4% and gaining a single, trusted view of their security posture.

The Outcome: Streamlined operations, faster decision-making and improved compliance enablement for frameworks like NIS2, all while reducing the energy footprint of sprawling infrastructure.

2. Cloud Security: Innovate Without the Risk

The Challenge: Cloud transformation introduces new risks and blind spots.
The Reality: 82% of breaches now involve cloud data, and nearly 40% span multiple environments.

IBM and Palo Alto Networks secure the journey from code to cloud to SOC, embedding security early in design and automating protection across environments. IBM’s AI deployment accelerators slash rollout time, while Cortex Cloud™ provides continuous visibility and compliance enablement.

The Outcome: Faster innovation with cloud operations that are secure by design, from day one.

3. Security for AI: Build Trust in Every Algorithm

The Challenge: Rapid AI adoption without consistent oversight.
The Reality: 82% of executives say trustworthy AI is critical to success, yet few have the controls in place.

IBM and Palo Alto Networks help organizations govern and protect their use of AI, securing data pipelines, scanning models and preventing adversarial attacks.

The Outcome: Confident AI adoption aligned to the EU AI Act requirements, where innovation can move forward without compromising data integrity or customer trust.

4. Security Service Edge (SSE): Connect People Securely, Anywhere

The Challenge: Hybrid work models demand reliable secure access everywhere.
The Reality: Human risk, not technology alone, is now the dominant factor in breaches, with 95% of data breaches involving human error, such as insider missteps, credential misuse and careless actions, underscoring how remote and hybrid workers’ behaviors significantly expand exposure.

With Palo Alto Networks Prisma Access and IBM’s consulting expertise, enterprises across Europe are simplifying secure connectivity through a unified zero trust framework.

The Outcome: Simpler, more efficient policy management and stronger protection across hybrid environments, where risk exposure is reduced, visibility is enhanced, and a seamless user experience is delivered.

5. SOC Transformation: Detect Earlier, Respond Faster

The Challenge: SOC teams are overwhelmed, missing as many as two thirds of daily alerts due to alert fatigue and limited resources.
The Reality: Over half of organizations report they can’t hire or retain enough skilled analysts, leaving gaps in coverage and consistency.

By combining IBM’s Autonomous Threat Operations Machine (ATOM) with Palo Alto Networks Cortex XSIAM, organizations can streamline and automate core SOC workflows, reducing response times by more than half and enabling analysts to focus on the most critical incidents.

The Outcome: Faster detection, shorter resolution times and a more proactive, resilient security posture. AI-driven automation not only boosts accuracy but can also shorten breach lifecycles by more than 100 days, helping teams defend smarter.

Built for Northern Europe’s Next Decade of Growth

As Northern Europe is a leader in digital innovation, the stakes for cybersecurity have never been higher. Trust, transparency and compliance are not simply checkboxes, but are competitive advantages.

IBM and Palo Alto Networks are helping organizations across the region turn that reality into action. By uniting AI-powered automation, cloud-native security and deep industry expertise, they’re enabling enterprises to move faster, reduce complexity and strengthen resilience. This is achieved while enabling alignment with the region’s evolving frameworks, such as NIS2, DORA and the EU AI Act.

To stay ahead, security can no longer be a fragmented layer sitting outside transformation; it must be the foundation that powers it. With IBM and Palo Alto Networks, organizations gain a unified security platform built for the next decade of digital progress – one that protects every connection, every line of code and every moment of innovation.

Resilient. Compliant. Unified.

That’s the future of cybersecurity in Northern Europe.

Learn how IBM and Palo Alto Networks can help your organization simplify complexity and strengthen resilience.

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