Palo Alto Networks is proud to enter a strategic partnership with the RAF Association.

For over 90 years, the Royal Air Forces Association (RAFA) has championed a simple yet profound belief: No member of the RAF community should ever be left without the help they need. Serving personnel, veterans and their families, the RAF Association provides crucial welfare support, responding to increasingly complex needs in an era of operational changes and challenges, including persistent global deployment.

Delivering on their mission today requires not only compassion and expertise but also resilient digital foundations. To strengthen and future-proof its operations, RAFA has entered into a strategic partnership with Palo Alto Networks. Together, we are modernising the Association's cyber security posture through a secure-by-design, zero trust architecture to enhance organisational resilience, secure sensitive beneficiary data, and improve operational agility. This helps ensure they can focus on their mission of support, not security management.

As Nick Bunting OBE, Secretary General at the RAF Association, puts it:

Cybersecurity is essential to safeguarding the trust people place in our organisation. This transformation will give us greater protection for our data and systems, ensuring that our services remain dependable and that our organisation is secure, resilient and ready for the future. Strong digital security is not just a technical requirement, it is a fundamental part of how we uphold our duty of care to every individual who relies on us.

Securing the Mission

The RAF Association operates in a distributed environment comprising headquarters’ functions, remote caseworkers, and more than 20 RAFAKidz nursery sites, supported by a growing portfolio of cloud-based services. In this context, cybersecurity is not simply an IT concern. It is a safeguarding imperative.

Disruption to systems or a compromise of sensitive beneficiary data could directly impact RAFA’s ability to deliver services and maintain the trust of the communities it supports. By consolidating fragmented legacy tools into a unified platform, this partnership ensures the Association’s digital evolution aligns security controls with GDPR obligations and safeguarding requirements.

Digital Resilience with a Unified Platform for Visibility and Control

To support RAFA's lean IT operational model, this transformation will move them away from fragmented legacy tools toward a unified platform approach. The deployment of Prisma^® SASE (secure access service edge) and Cortex XDR^® will provide RAFA with consistent visibility and control across users, devices, applications and data, regardless of location. This consolidation replaces complexity with clarity, allowing the organisation to inspect traffic for threats in real-time. Security policies are now enforced continuously, threats are detected and contained faster, and access to critical systems is governed by zero trust principles without compromising the user experience.

As Phil Sherwin, Chief Information Officer, at the RAF Association states:

Our data is one of our most valuable assets and the protection of that data, as we continue to provide life-changing support to members of the RAF community, is our most important priority. This partnership will move us into the next generation of security tools that adopt zero trust principles and is a crucial step on our journey to providing a layered approach to data protection.

One of the most critical aspects of this modernisation is supporting RAFA’s diverse workforce, particularly within the RAFAKidz nursery sites. These environments rely on nondesk-based staff using iPads and mobile devices to get their critical work done.

Using zero touch provisioning and the Prisma Browser™, we are enabling secure, seamless connectivity for unmanaged devices. This ensures that nursery staff can access necessary SaaS applications safely without complex login hurdles or manual configuration, improving their agility and allowing them to focus on caring for children rather than troubleshooting technology.

Creating Operational Advantage by Scaling Operations with AI and Automation

As a charity, RAFA has a responsibility to ensure resources are used efficiently. A critical goal of this partnership is to improve productivity and allow the organisation to scale its services without increasing the IT burden.

By adopting Strata™ Cloud Manager with AIOps (artificial intelligence for IT operations), RAFA is shifting from reactive security operations to proactive, automated management. Machine learning helps identify configuration risks and performance issues before they affect users, while standardized policies enable the secure, consistent onboarding of new sites. This shift is projected to significantly reduce operational overhead, enabling RAFA to scale its support network cost-effectively. This shift is projected to reduce operational overhead by 40–50%.

A Resilient Future

This partnership is about more than deploying technology. It is about ensuring RAFA remains resilient, trusted and capable of supporting the RAF community for decades to come.

As Darren Bisbey, Head of Group Information Security for the RAF Association, puts it:

We live in an era where digital threats are accelerating in both scale and sophistication, creating unprecedented challenges for organisations. Our partnership with Palo Alto is a statement of intent, reflecting our unwavering commitment to building the most secure environments possible for our data.

At Palo Alto Networks, we are honored to support RAFA in this journey, providing the digital armour and operational advantage necessary to protect those who serve and have served.

As Alistair Wildman, Palo Alto Networks CEO for Northern Europe states:

For over 90 years, RAFA has been a lifeline for the RAF community; it is our privilege to ensure that legacy endures in a digital-first world. By embracing a unified, AI-driven platform, RAFA is moving beyond complex, fragmented security to a posture that is Secure by Design. This partnership allows them to navigate today’s threat landscape with confidence, ensuring their resources remain focused where they belong: on the families who need them.

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Key Takeaways

1. Digital Resilience – Strategic Shift to Zero Trust Architecture: RAFA is modernizing its cybersecurity posture by implementing a comprehensive zero trust architecture. This transition involves moving from fragmented legacy tools to a unified platform approach, deploying Prisma^® SASE and Cortex XDR for 360-degree visibility and complete control over access and traffic.
2. Interoperability – Secure, Seamless Access for Diverse Workforce: The partnership ensures operational agility by simplifying security for nondesk-based staff, particularly at the RAFAKidz nursery sites. Solutions like Zero-Touch Provisioning and the Prisma Access Browser enable secure, seamless connectivity for unmanaged devices, allowing nursery staff to focus on their critical work without complex login or configuration issues.
3. Creating Operational Advantage – Efficiency and Scalability through AI and Automation: RAFA is leveraging technology to scale services efficiently and reduce operational overhead. By using Strata Cloud Manager with AIOps (Artificial Intelligence for IT Operations), the organization can shift to proactive management and automating remediation, which is projected to reduce operational overhead by 40–50%.

The post Empowering the RAF Association with Next-Generation Cyber Resilience appeared first on Palo Alto Networks Blog.

How Ripley's Fight for Survival Became My Blueprint for SOC Transformation

I'll admit it. I wasn't planning to rewatch science fiction horror films when I sat down to write about modern cybersecurity challenges. But there I was, staring at yet another draft about SOC modernization when our content team threw out a wild idea: What if we explained threat actors through the lens of a Science Fiction movie like Alien?

Yo, Hicks. I think we got something here!

Against my better judgment, I queued up the original 1979 film. Somewhere between the chest-burster scene and Ripley's desperate attempt to purge the Nostromo's systems, it hit me: This crew had every problem a modern security operations center faces daily.

Stay with me here.

The Unknown Threat Aboard Your Ship

In the original Alien, the crew of the Nostromo responds to what they think is a distress signal. Spoiler alert: It's not. By the time they realize they've brought something deadly aboard, it's already loose in the ship's ventilation system, moving freely through areas they can't monitor.

Sound familiar? That's exactly how modern breaches unfold. Threat actors don't announce themselves with flashing lights and alarm bells. They exploit a vulnerability, establish a foothold, and move laterally through your environment while remaining undetected. According to recent Unit 42^® research, the mean time to exfiltrate has dropped from nine days in 2021 to just two days in 2023. Some incidents now occur in under 30 minutes. The xenomorph's (the alien’s) rapid lifecycle has nothing on modern ransomware operators.

The Nostromo crew's problem wasn't just the alien. It was that their ship's systems couldn't tell them where the threat actually was. Their motion trackers picked up movement, but couldn't distinguish between crew members, the cat or the xenomorph. Legacy SIEM systems have the same problem, generating thousands of alerts without the context to determine which ones represent actual threats.

"I Can't Lie About Your Chances, But You Have My Sympathies"

One of the most chilling moments in Alien comes when Ash, the science officer, reveals he's actually a synthetic programmed by the company to prioritize retrieving the alien specimen over crew survival. "I can't lie to you about your chances, but... you have my sympathies."

This is what alert fatigue feels like in a modern SOC.

Security teams face an overwhelming reality:

• Managing up to 45 different security tools on average.
• Coordinating responses across approximately 19 different consoles.
• Processing thousands of alerts daily, most of which are false positives.
• 66% of organizations use 25 or fewer security products yet still struggle with complexity.

Like the Nostromo crew discovering their systems were working against them, security analysts often find their tools generate more noise than signal. Traditional SIEMs bombard teams with redundant alerts while real threats slip through undetected. Analysts spend their days triaging false positives instead of hunting actual threats. Basically, they’re sorting through motion tracker pings while the xenomorph stalks the corridors.

The Company Knew (And Your Attack Surface Knows Too)

From Aliens (the 1986 sequel), we learn that the Weyland-Yutani Corporation knew about the xenomorph threat all along. They had information about LV-426, but that intelligence never reached the colonists who needed it. The result? An entire colony was lost because critical threat intelligence wasn't properly shared and acted upon.

This is the attack surface management problem in a nutshell.

You can't protect what you can't see. Like the colonial marines arriving at LV-426 with incomplete intelligence, security teams often lack comprehensive visibility across their cloud environments, hybrid infrastructures and sprawling IoT deployments.

Modern attack surface management addresses this:

• Providing continuous assessment of your external attack surface.
• Identifying abandoned, rogue or misconfigured assets before attackers find them.
• Monitoring for vulnerable systems proactively.
• Unifying visibility across network, endpoint, cloud and identity.

Think of it as having the schematics and sensor data Ripley desperately needed – a complete picture of where threats could hide and how they might move through your environment.

The Power Loader Moment: Amplifying Human Response with Automation

In the climactic scene of Aliens, Ripley straps into a power loader exosuit to fight the alien queen. She's still human, still making the decisions, but now she's augmented with technology that amplifies her capabilities and response speed.

This is exactly what AI-driven security operations should do.

Legacy SIEM is like facing the xenomorph queen with your bare hands. Modern AI-driven platforms are the power loader, they don't replace the human operator, but they dramatically amplify what that human can accomplish.

Platforms like Cortex XSIAM^® can process over 1 million events per second while reducing the number of incidents requiring human investigation to single digits per day. The technology handles the heavy lifting:

• Automated data integration and normalization across all security tools
• Machine learning models that detect anomalies in user behavior
• Intelligent alert correlation that groups related events into single incidents
• Automated response workflows that contain threats in minutes, not hours

Organizations using AI-driven SOC platforms report automating up to 98% of Tier 1 operations. Your analysts still make the critical decisions, they're just equipped with vastly better tools to execute those decisions at machine speed.

The Danger of Fragmented Systems

Throughout the Alien franchise, crew members are constantly struggling with fragmented information. The motion tracker shows movement, but not identity. The door controls are on a different system than life support. Communications are spotty. When seconds count, they're wasting precious time switching between systems and trying to piece together incomplete information.

This is the daily reality in most security operations centers.

The same attack generates alerts in multiple interfaces: your SIEM, EDR console, cloud security platform, identity provider. It’s like seeing the xenomorph's tail in one system, hearing its hiss in another, and detecting acid blood in a third, but never getting the full picture until it's too late.

The engineering challenge isn't just buying better sensors. It's creating a unified data foundation where security-relevant information is collected, stored and normalized together. When all your security data lives in a single data lake, AI models can recognize patterns that would never surface in siloed systems. It’s like understanding that the motion tracker ping, the door malfunctioning and the broken steam pipe are all connected to the same threat.

What this unified approach enables:

• Cross-data analytics that correlate threats across different data sources.
• Complete context of an attack from initial entry to lateral movement.
• Automated response that addresses root causes, not just symptoms.
• Seamless collaboration between SOC analysts, threat hunters and incident responders.

"Nuke It From Orbit! It's the Only Way to Be Sure"

In Aliens, the solution to an overwhelming infestation is drastic: orbital bombardment. While we don't recommend that approach for cybersecurity (your compliance team will object), there's a lesson here about the importance of decisive, automated response.

When the colonial marines discover the scope of the xenomorph infestation, their problem isn't just detection, it's that their response capabilities can't match the threat's speed and scale. By the time they've cleared one corridor, the aliens have flanked them through the ceiling.

Modern threats move at similar speeds. Attackers can pivot from initial compromise to data exfiltration faster than human analysts can investigate and coordinate responses across multiple tools. This is where automation becomes essential, not as a replacement for human judgment, but as the mechanism that executes decisions at the speed threats actually move.

The key is having the right response capabilities:

• Fast enough to outpace attacker movement.
• Comprehensive enough to address root causes.
• Automated enough to execute without human bottlenecks.
• Intelligent enough to avoid collateral damage.

You don't need to nuke your network from orbit. You need response automation that contains threats before they spread.

The Survivor (And Why Human Expertise Still Matters)

Ellen Ripley survives the Alien franchise through a combination of factors: technical competence, situational awareness, decisive action and refusal to give up. But here's what's critical. She's effective not because she's superhuman, but because she's highly trained, learns from experience, and adapts her approach as threats evolve.

The same principles apply to security operations.

AI and automation dramatically improve efficiency and response times, but skilled security professionals remain essential. The goal isn't to replace analysts. It's to free them from repetitive tasks so they can focus on what humans do best: creative problem-solving, threat hunting, strategic thinking.

The cybersecurity labor shortage continues to grow, and analysts experience burnout from manual processes that consume time better spent on high-value activities. Modern platforms address this by automating routine work while augmenting human decision-making. Instead of spending hours manually correlating events and switching between consoles, analysts receive high-fidelity incidents with complete context.

Ripley didn't survive because she had the best equipment (though the power loader helped). She survived because she understood the threat, adapted her tactics, and made smart decisions under pressure. Your security team needs the same combination: World-class tools that amplify their capabilities and free them to do the strategic thinking that actually stops sophisticated threats.

What Ripley Would Do With Modern SecOps

Imagine what the Nostromo crew could have done if they had access to modern security operations technology:

• Detected the alien's presence immediately through behavioral analytics instead of relying on motion trackers.
• Tracked its movement through integrated sensor data across the entire ship.
• Automatically sealed compartments and adjusted life support to contain the threat.
• Had complete visibility into every system, eliminating hiding spots and blind spots.

Your organization shouldn't face threats with 1970s technology while attackers use 2025 capabilities. The evolution from traditional log management to AI-driven security operations isn't just about buying new tools. It's about fundamentally transforming how your security team operates, moving from reactive alert management to proactive threat hunting, from fragmented tools to unified platforms, from manual response to intelligent automation.

The xenomorph was a perfect organism: efficient, deadly, focused solely on survival and reproduction. Modern threat actors are similarly evolved, using AI and automation to attack at machine speed. Your defenses need to match that evolution.

In Space, No One Can Hear You Scream, But Your SOC Platform Can

Modern security operations require more than collecting logs and hoping someone notices the anomalies. You need unified visibility, AI-driven analytics and automated response capabilities that can keep pace with threats that move at the speed of code.

Whether you're drowning in alerts, struggling with tool sprawl, or trying to defend against attackers moving faster than human reaction times, there's a better way forward. And unlike the Nostromo crew, you don't have to face it alone with outdated equipment and fragmented systems.

Just comprehensive security, delivered at the speed of AI.

Because in cybersecurity, everyone can hear you scream when your SIEM fails. The question is whether your security operations platform can stop the threat before it gets that far.

Take the Next Step

If you're ready to move from fragmented tools to unified security operations, download our whitepaper, Endpoint First: Charting the Course to AI-Driven Security Operations to break down the practical steps to get there.

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Key Takeaways

1. Stop Drowning in Alerts (AKA: Your SIEM Shouldn't Feel Like a Motion Tracker): Legacy Security Information and Event Management (SIEM) systems generate thousands of alerts without the necessary context. The modern approach requires moving past redundant alerts to a system that can accurately distinguish between noise and actual threats, a necessity driven by the rapidly decreasing time attackers take to exfiltrate data.
2. Get the Full Ship Schematics (Because You Can't Fight What You Can't See): Many organizations lack comprehensive visibility across their environments (cloud, hybrid, IoT). A unified approach, which includes continuous attack surface management and a single data foundation, is essential to connect disparate alerts and gain a complete picture of an attack across all security tools.
3. Give Your Analysts a Power Loader (Not a Pink Slip): AI-driven security operations (SecOps) platforms do not replace human analysts but dramatically amplify their capabilities and response speed, enabling automated data integration, intelligent alert correlation and rapid response workflows to contain threats at "machine speed" before human bottlenecks are reached.

The post What the Alien Franchise Taught Me About Cybersecurity 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.

The post Unified AI-Powered Security appeared first on Palo Alto Networks Blog.

Modernizing Vulnerability Sharing for a New Class of Threats

In cybersecurity, vulnerability information sharing frameworks have long assumed that conventional threats exploit flaws in software or systems, and they can be resolved with patches or configuration updates. AI and machine learning (ML) models upend that premise as adversarial attacks, like poisoning and evasion, target the unique way AI models process information. Consequently, the risks for AI systems include tactics like model poisoning (from evasion attacks) in datasets and training, which are not conventional software vulnerabilities. These new vulnerabilities fall outside the scope of traditional cybersecurity taxonomies like the Common Vulnerabilities and Exposures (CVE) Program.

There is a need to bridge the gap between the existing cybersecurity vulnerability sharing structure and burgeoning efforts to catalog security risks to AI systems. Provisions in the White House AI Action Plan, which Palo Alto Networks supports, call for the creation of an AI Information Sharing and Analysis Center (AI-ISAC), reinforcing the importance of addressing that disconnect. This integration is essential, as leveraging the existing, widely adopted cybersecurity infrastructure will be the fastest path to ensuring these new standards are accepted and operationalized.

Established Construct for Vulnerability Management and Disclosure

The global cybersecurity community relies on a mature infrastructure for sharing standardized vulnerability intelligence. Central to this ecosystem is the CVE List, established in 1999 as the authoritative catalog of cybersecurity vulnerabilities. Through CVE IDs and a network of CVE Numbering Authorities (CNAs), this framework enables consistent vulnerability documentation and disclosure.

Similarly, the Common Vulnerability Scoring System (CVSS) provides standardized severity assessments, allowing security teams to prioritize responses. Together with resources like the National Vulnerability Database (NVD) and CISA’s KEV Catalog catalog, these tools form the backbone of global vulnerability management, information sharing and coordinated disclosure.

Why AI Breaks the Traditional Model

While this infrastructure has served the cybersecurity community effectively for over two decades, it was designed around traditional threat models that AI systems substantially upend. Attacks on AI systems represent a critical departure from traditional cybersecurity threats as they operate insidiously, subtly corrupting core reasoning processes, causing persistent, systemic failures, some of which only become evident over time. Most traditional cybersecurity tools are not equipped to recognize those breakdowns because they assume deterministic behavior and rules-based logic. AI systems defy those assumptions because AI is probabilistic, not deterministic. Consequently, attacks on AI models may remain hidden for extended periods.

Unlike traditional cybersecurity threats that target code, adversarial AI attacks target the underlying data and algorithms that govern how AI systems learn, reason and make decisions. Consider the following predominant adversarial attack methodologies on machine learning:

• Poisoning attacks inject malicious data into training datasets, corrupting the model's learning process and creating deliberate vulnerabilities or degraded performance.
• Inference-related attacks exploit model outputs to extract sensitive information or learn about its training data. This includes model inversion, which reconstructs sensitive data from the model's outputs, as well as membership inference, which identifies whether specific data points were used in training.

The expansion of existing security frameworks and programs is necessary to cover the enumeration, disclosure and downstream management of security risks to AI systems.

Advancing AI Security Through the AI Action Plan

In July, the Administration unveiled the AI Action Plan, an innovation-first framework balancing AI advancement with security imperatives. The Plan prioritizes Secure-by-Design AI technologies and applications, strengthened critical infrastructure cybersecurity and protection of commercial and government AI innovations.

Notably, it recommends establishing an AI Information Sharing and Analysis Center (AI-ISAC) to facilitate threat intelligence sharing across U.S. critical infrastructure sectors and encourages sharing known AI vulnerabilities, “tak[ing] advantage of existing cyber vulnerability sharing mechanisms.” These provisions affirm that AI security underpins American leadership in the field and, where possible, should be built upon existing frameworks.

Redefining Boundaries for AI Threats

To position the CVE Program for the AI-driven future, Palo Alto Networks is engaging directly with industry and program stakeholders to chart the path forward. Traditionally, the CVE Program serves as an ecosystem-wide central warning system. It provides a unified source of truths for security risks. A security risk catalog and identification system are needed for AI systems, as they currently fall outside the traditional scope of the CVE Program that has focused exclusively on vulnerabilities rather than on malicious components. The historical aperture of the current CVE Program excludes harmful artifacts, such as backdoored AI models or poisoned datasets, which represent fundamentally different attack vectors, in turn creating security blind spots.

Securing AI’s Promise

The United States leads in AI innovation and must equally lead in securing it. As momentum builds behind the AI Action Plan and the establishment of the AI-ISAC, we have a critical window to shape information sharing frameworks of the future. The goal is to ensure that cybersecurity and AI security infrastructure advance in unison with the technology itself. Integrating new AI vulnerability standards into trusted frameworks like the CVE Program aligns with industry focus and needs. Through proactive, coordinated action, we can unlock AI’s full promise while safeguarding the models that are embedded in the critical systems on which our nation depends.

The post Bridging Cybersecurity and AI appeared first on Palo Alto Networks Blog.

If 2025 proved anything, it’s that no one wins alone in cybersecurity. AI-driven threats accelerated, and environments grew more complex while enterprises pushed hard for simplicity, integrated protection and security outcomes that deliver measurable results and meaningful value.

In response, we saw our partners around the globe lean into integration, treat AI as a built-in advantage and use the strength of our ecosystem as a force multiplier. The result: What could have been a disruptive year instead became one defined by growth and learning across our partner community.

Now, those lessons are guiding how Palo Alto Networks plans to partner with even greater precision in 2026. We remain a channel-first company that’s all-in on our ecosystem and united with our partners in a shared purpose to protect our customers’ digital future. But we also intend to double down in several areas in the year ahead, and we’re asking our partners to join us in doing the same.

1. Simplifying Security Through Integration

One message from customers that came through loud and clear in 2025 is that complexity is the enemy of resilience. Many enterprises are grappling with tool sprawl – multiple consoles, disconnected policies and overlapping investments that slow down their teams when speed and agility matter most.

The partners who delivered some of the most transformative results for organizations this year were those who chose integration over complexity and collaboration over siloed tools. With a laser focus on simplifying security, they were able to help customers:

• Consolidate fragmented point tools onto a unified security platform.
• Align visibility across the network, cloud and security operations center (SOC), so teams can respond faster.
• Build architectures with zero trust and AI-powered detection at the core.

We saw this simplifying-security trend through integration across our ecosystem. Partners unified cloud security and detection workflows through Cortex^® Cloud™ and Cortex. Teams modernized network architectures with tighter integration across our platform. We expect this activity to only accelerate in the coming year as our cloud security offerings continue to evolve.

When we innovate together, customers gain stronger defenses and a faster time-to-value. That’s why Palo Alto Networks has invested so heavily in platformization. When you connect our capabilities across network security, cloud security and security operations (wrapping them with your consulting, delivery and managed services) customers can experience something fundamentally better. With fewer gaps and clearer signals, they can build a security posture that’s built for the speed of modern threats.

In 2026, deep integration will remain a cornerstone of how we partner with precision. We’ll continue aligning our portfolio, programs and joint engagement model, so you can build offerings that reduce complexity for customers and create stronger differentiation for your business.

2. Making AI a Built-in Advantage

At Palo Alto Networks, our approach to AI in cybersecurity is straightforward. We believe AI must be embedded, not bolted on. It has to live in the data, analytics and workflows your teams rely on every day. That’s the thinking behind Precision AI^®, and it’s why we built AI capabilities into our platform’s core.

Partners who treated AI as a platform capability rather than a standalone tool delivered some of the strongest outcomes for customers in 2025. They were able to meet customers’ needs and deliver business outcomes in a single, unified approach. They helped organizations:

• Detect and respond to threats faster with AI-assisted analytics.
• Use automation to streamline change, investigation and response workflows.
• Tie AI to tangible outcomes, such as reduced risk, higher productivity and a better user experience.

In 2026, we’ll double down on AI across the platform and invest in the tools, content and enablement you need to bring those capabilities to life. Our focus is on making it easier for you to build AI-powered services that are repeatable and aligned to the outcomes customers expect.

Upcoming program changes reflect that intent. We’ll promote next-generation security as a growth engine and invest in ways that strengthen partner profitability across consulting services, resale, quality delivery, technical support and managed security services.

3. Ensuring Our Ecosystem Can Be a Growth Engine for Everyone

As AI raised the bar for both attackers and defenders in 2025, the partners who leaned into platformization and outcome-driven services were the ones who helped customers stay ahead of the curve. Those successes are now shaping how we strengthen and scale the partner ecosystem in 2026.

Our ecosystem isn’t just a route to market; it’s intended to be an economic engine for everyone involved. This year, many partners grew their business by building practices around our platform and aligning their services with where customers needed the most support: strategy, implementation, optimization, ongoing operations. We saw especially strong momentum from partners’ expansions:

• Consulting and advisory services around zero trust and AI-driven transformation.
• Resale opportunities centered on platform consolidation and next-generation security.
• Quality delivery and technical support that keep deployments reliable and current.
• Managed security services that give customers 24/7 protection and expert oversight.

These achievements reflect the value exchange at the heart of our ecosystem. Palo Alto Networks invests in platformization, AI and enablement, while our partners bring delivery expertise, regional insight and service innovation. Together, we create outcomes neither of us could deliver alone.

In 2026, we plan to build on that momentum and drive even greater partner profitability. Program evolutions will focus on growth across the full lifecycle, from initial design and implementation to long-term operation and optimization. We’re also expanding collaboration with our technology alliances to build new joint offerings and solution plays that the ecosystem can take to market together.

When we combine our platform, your expertise and the capabilities of our Alliance partners, then customers gain more paths to adopt next-generation security with confidence, and you gain more opportunities to develop differentiated, high-value practices.

Keeping Customers at the Center

At the heart of every partner collaboration is the customer, of course. Everything we build, integrate and advance together starts and ends with protecting them. This year, ecosystem alignment delivered measurable impact for our customers across industries. When partners lead with integrated solutions anchored in our platform, organizations saw visible improvements:

• Faster deployment of secure solutions.
• Reduced complexity with unified visibility.
• Greater confidence in defending against today’s AI-driven threats.

We saw this firsthand in joint wins across cloud security transformations, zero trust modernization and AI-assisted threat detection. When our ecosystem moves together, customers can move faster, operate more securely and achieve meaningful outcomes. Customer success is the foundation of everything we do as a partner-led organization, and it will remain our North Star in 2026.

Partnering with Precision in 2026 and Beyond

What we learned and achieved together in 2025 points us toward a clear focus for 2026 to advance ecosystem-led innovation, so we can deliver outcomes that matter most to our customers.

With that mission in mind, we will focus on the following four priorities:

• Deeper Integration – Expanding API partnerships and strengthening interoperability across the platform.
• Co-Innovation – Enabling partners to build solutions tailored to industry needs and use cases.
• Empowered Enablement – Investing in learning, automation and AI capabilities that fuel differentiated, profitable services.
• Simplified Engagement – Streamlining programs and tools, so that partnering with us is faster and more rewarding.

These priorities highlight the real strength of our ecosystem: How platformization, AI and partner expertise come together to enable what we could not build alone.

Finally, to our partners and customers, thank you. Your trust, collaboration and commitment push us to innovate boldly and continuously. As we enter the new year, I’m excited about what we’ll build together. When we align our AI-powered platform, our partner programs and your expertise in delivery, services and managed security, we can deliver something far greater than a set of solutions.

We’re a powerful team that’s not just defending against what’s next; we’re defining the future of cybersecurity. And together, we’re unstoppable.

Partners, join us in shaping the next chapter of secure, AI-powered innovations. Connect with your Channel Business Manager to align on 2026 opportunities, upcoming program updates and ways we can elevate customer outcomes together. Visit the partner portal to learn more.

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Key Takeaways

• Integration beats complexity.
  Unifying technology, data and expertise drove the strongest outcomes in 2025, helping partners reduce risk and accelerate time-to-value for customers.
• AI is a built-in advantage.
  By tapping into AI embedded across our cybersecurity platform, partners can address security and business outcomes simultaneously and deliver repeatable, profitable, AI-powered services.
• The partner ecosystem is a growth engine, and together, we’re unstoppable.
  Our 2026 priorities focus on deeper integration, coinnovation, empowered enablement and simplified engagement that drive partner profitability and stronger customer outcomes.

The post Partnering with Precision in 2026 appeared first on Palo Alto Networks Blog.

Every CIO and CISO we speak with describes the same paradox: AI is now central to their transformation agenda, yet the fastest way to derail that agenda is to lose control of AI. As generative AI, agentic systems and embedded AI features spread across the enterprise, leaders are no longer asking if they need AI security; they’re asking what kind of AI security strategy will actually scale.

Gartner^® has published two recent reports that validate this reality and outline the strategic direction enterprises must take to secure their AI:

• GMs: Win the AI Security Battle With an AI Security Platform (available as a complimentary reprint from Palo Alto Networks).
• AI Vendor Race: Palo Alto Networks Is the Company to Beat in AI Security Platforms, published December 8, 2025.

Why AI Security Is a Platform Game

Point products can plug individual gaps, but they can’t keep up with the speed, complexity and interconnected nature of AI adoption. And more importantly, they struggle to deliver the trust, consistency or scale AI transformation requires.

Many organizations are already experiencing AI adoption outpacing traditional security tools. Security teams are under pressure on three fronts:

• Risk – Shadow AI, unmanaged agents and custom LLMs create new pathways for data loss, intellectual property exposure and model misuse.
• Cost – Each new AI use case brings yet another tool, driving up license, integration and operations costs.
• Complexity – Fragmented controls across network, data, identity and application stacks create blind spots exactly where AI is moving fastest.

From a CIO or CISO’s perspective, this isn’t just a technical concern but the fault line beneath their entire AI agenda. CIOs are under pressure to deliver productivity gains, cost efficiencies and new AI-powered capabilities faster than ever before.

CISOs, on the other hand, see a parallel reality: custom-built AI applications that may be insecure by default, agents that can act unpredictably, and a constant risk that company secrets or customer data could leak into third-party GenAI tools.

If AI moves forward without security, the enterprise is exposed. If AI slows down because security can’t keep up, the business misses its transformation goals. This is why AI security isn’t a feature; it’s the determining factor in whether AI becomes a competitive advantage or a strategic setback.

Gartner recommends the path forward as “an integrated modular AI security platform (AISP) with a common UI, data model, content inspection engine and consistent policy enforcement.”

Gartner further recommends prioritizing investments in two phases.

Phase 1

Start with AI usage control to secure the consumption of third-party AI services.

Phase 2

Expand into AI application protection to securely develop and run AI applications.

Phase 1: Securing Generative AI Usage Is the “Right Now” Challenge

Before enterprises can secure how AI is developed, they must first understand how it is already being used across the organization. The earliest risks often emerge not from the AI-enabled apps built in-house, but from the external generative AI tools and copilots employees adopt, and often without the IT teams’ knowledge.

That’s why we think the report identifies AI usage control as phase one and why we recommend IT leaders start with these immediate questions to assess their organization’s AI usage.

• Where is AI actually being used in my organization?
• Which tools, copilots and agents are in play, and on what data?
• How do I enable productivity without losing control?

Phase 2: Securing AI Development Early Into the AI Lifecycle

Once public generative AI use is understood, the harder challenge emerges: Securing the AI apps and tools that your organization creates for itself. As models, agents and pipelines move into production, the questions shift from visibility to integrity, safety and scale.

Key questions that organizations must answer in phase two include:

• What AI applications, models and agents are my teams building, and where do they live?
• How do I manage the integrity, safety and compliance of AI apps before they reach production?
• How do I protect models and AI applications from prompt injection, misuse or agentic threats?
• How do I scale AI innovation without creating security bottlenecks for developers?

Palo Alto Networks Delivers the AI Security Platform

Although organizations can separate the work around securing AI usage and AI development, they are not two separate problems. The same organization that needs visibility into employees using public GenAI apps also needs to protect the AI applications and agents they’ve built as they move into production. A platform approach is what allows shared policies, shared guardrails and shared context across both sides of the AI usage and development equation.

That is exactly the philosophy behind our Secure AI by Design approach:

• Secure how GenAI is used with Prisma^® Browser and Prisma SASE to discover AI tools in use, govern access and prevent sensitive data from flowing into public models, all while keeping users productive with GenAI and enterprise copilots.
• Secure how AI is built with capabilities of Prisma AIRS, such as model and agent security, AI security posture management, runtime protection, automated testing with AI Red Teaming, as well as coverage for agentic protocols, like MCP, securing custom AI applications, agents and pipelines.

Gartner identifies Palo Alto Networks as “the company to beat” in their newly released report as of December 8, 2025: “AI Vendor Race: Palo Alto Networks Is the Company to Beat in AI Security Platforms.”

We believe we are the AI Security Platform to beat because:

• Palo Alto Networks product portfolio across network, edge, cloud and data provides a strong foundation for AI usage visibility and control.
• The acquisition of Protect AI integrated industry-leading AI talent and products resulting in the recently announced Prisma AIRS 2.0, which delivers comprehensive end-to-end AI security, seamlessly connecting deep AI agent and model inspection in development with real-time agent defense at production runtime. The platform, continuously validated by autonomous AI red teaming, secures all interactions between AI models, agents, data and users. This gives enterprises the confidence to discover, assess and protect their entire AI ecosystem, accelerating secure innovation.
• Complementing the platform, Unit 42^®’s deep expertise and Huntr’s bug bounty program, provide security thought leadership that directly improves product effectiveness and threat intelligence. These programs help us continuously uncover new attack patterns, misconfigurations and supply chain risks unique to AI systems, as well as feed those insights directly back into the product roadmap.
• Our large installed base and distribution channels create a flywheel for AI security platform adoption and learning from our customers and partners.

We also believe that underneath the technical requirements is a deeper truth: CIOs and CISOs want to move fast on AI, but they only feel safe doing so with a partner who has the scale, signal and staying power. This is where our breadth, research depth and ecosystem matter.

Leading Responsibly Means Listening, Innovating and Evolving

Being early is an advantage, but staying ahead requires humility and continuous learning. Leading means seeing what comes next, and Gartner’s insights accelerate our own roadmap as we continue to evolve.

• Simplifying the Experience: We are integrating capabilities across Prisma AIRS, Prisma SASE and Prisma Browser to make AI security easier to adopt, operate and scale through Strata Cloud Manager as the single entry point.
• Going Deeper into the AI Engineering Pipeline: We recognize that securing AI must start early in the developing environment and ML pipeline, not just at runtime. Our integrations with AI development tools and code repositories will continue to expand.
• Keeping Pace with a Fast-Moving Market: We are investing in open standards, partnerships and research, so our customers don’t have to chase every point solution that appears. Palo Alto Networks is also a contributing member to OWASP Standards and Threat analysis to help create an industry standard on AI security.
• Working Along Native AI Controls: Cloud providers and AI platforms are adding their own security features. We aim to complement, not replace, those controls, providing unified visibility, advanced protection and consistent policies across a fragmented AI landscape.

For us, being “the company to beat” is not a finish line. It’s a responsibility to listen carefully to customers, adapt as AI evolves, and keep delivering practical, integrated outcomes rather than isolated features.

If you are a GM, CIO, CISO or AI leader trying to make sense of a rapidly crowding AI security landscape, we believe “GMs: Win the AI Security Battle With an AI Security Platform”​​ is essential reading.

In the end, the real race isn’t about features; it’s about who helps enterprises accelerate transformation safely, reduce risk and compete better with AI they can trust.

 

Disclaimer: Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner’s business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose.

Gartner, AI Vendor Race: Palo Alto Networks is the Company to Beat in AI Security Platforms, By Mark Wah, Neil MacDonald, Marissa Schmidt, Dennis Xu, Evan Zeng, 8 December 2025. 

Gartner, GMs: Win the AI Security Battle With an AI Security Platform, By Neil MacDonald, Tarun Rohilla, 6 October 2025.

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

The post Winning the AI Race Starts with the Right Security Platform appeared first on Palo Alto Networks Blog.

What It Means and How to Counter Autonomous Offensive Cyber Agents

For years, we've anticipated this day. With the release of Anthropic's landmark report (detailing the disruption of a cyberespionage operation orchestrated by AI agents with minimal human intervention), the reality of autonomous offensive cyber agents has moved from speculation to an active, machine-speed threat. The report covers their internal identification and analysis of artifacts from the GTG-1002 campaign, which was conducted against over 30 different enterprise targets. This event is independently being tracked in the AI Incident Database as incident 1263. To have a successful defense in the age of AI, we need an immediate shift from human-led, reactive security to a proactive, machine-driven security paradigm.

The GTG-1002 campaign is the first open report of an AI agent, powered by Claude Code, targeting multiple enterprise environments. Using Claude Code as the primary orchestration framework, the agent was effective in all key phases of the attack:

• Mapping attack surfaces without human guidance.
• Exploit vulnerabilities using custom code generation.
• Moving laterally by autonomously harvesting and testing credentials.
• Conducting an intelligence analysis to identify and prioritize high-value data, rather than just exfiltrating raw dumps.

It was a watershed moment for several key reasons:

• Stealth – Traffic analysis of the inputs and outputs to Claude Code were the initial indicators of this attack, however, the attack was only observable in aggregate.
• Self-Configuration – The agent autonomously adapted its attack strategy to achieve actions on an objective.
• Machine-Speed – The agent both orchestrated AND executed the campaign across all attack vectors.
• Autonomous Context and Persistence – Using structured markdown files, the execution agent maintained a persistent state of the attack, providing context and autonomous continuity between distributed sub-actions and attack phases.

This campaign, executed at “multiple operations per second,” marks the end of the necessity for the "human-in-the-loop” attacker and the arrival of the "human-on-the-loop" supervisor. Transitions between attack phases were controlled by the human to validate sufficient completion of the current phase before progressing. It was a thin layer of supervisory human control. With the whiplash pace of AI, defenders should anticipate the necessity of any human control to fade.

In the reported attack campaign, “commodity tools” were leveraged by the threat actor, which at first glance, may not seem particularly novel. However, the autonomous orchestration of these tools across multiple attack phases by Claude Code, using Model Context Protocol (MCP) servers, represents a sophisticated technical advancement in offensive agents. Critically, this method improved more than just the speed of the attack, it also introduced the concept of autonomy with negligible human supervision, supporting dynamic and contextual reasoning in attack path planning across multiple target systems (even beyond typical human analyses, particularly for non-intuitive/interpretable event logging). Custom tools can bring very targeted actions within the same or similar offensive agent architectures, and defenders should be ready for this inevitable evolution.

We Need Agents to Fight Agents

With the debut of real-world offensive agent operations, it is now crystal clear: Defenders cannot combat autonomous, offensive AI with manual, static human driven security operations. Defenses must blend machine-speed responses with on-the-fly adaptability to maintain effectiveness against the self-optimizing campaigns now being observed. The pivot to autonomous agent-driven security operations will require transforming many elements of the traditional security operations lifecycle. All stages from preparation to response processes need to be resilient and robust to changes in adversary speed, stealth, evasion, orchestration frameworks and indicators of compromise.

Meeting the Challenges of Machine-Speed Defense Head-On

A new defense paradigm must be adopted to effectively combat AI attacks that are both orchestrated AND executed beyond human reaction time. To transform security operations and outpace AI-driven threats, organizations need to employ the following core principles:

• Precision of AI for Cybersecurity: Operating at machine speed requires precision and accuracy. Security systems must be capable of ingesting the right data, at the right time, and understanding the system context to detect and block threats in real-time, thwarting AI-generated attacks without generating erroneous alerts. Producing false positives is problematic at human speeds, and the problem compounds at machine speed.
• Proactive Cybersecurity for AI Systems: We must safeguard AI systems with real-time security solutions, preventing the models and applications from being directly or indirectly co-opted for malicious use. This demands a deep and continuous understanding of how AI agents might be abused via their application interfaces, permissions, provenance, identity and wider interactions across organizations.
• Transform Visibility into Observability: Visibility only encompasses a direct presence or absence. Observability is the combination of visibility plus some degree of cognitive and contextual reasoning. The visibility of a traffic sign does not guarantee a driver will observe and respond to it. The GTG-1002 attack evaded detection by splitting and distributing small, seemingly benign fragments of the full campaign across numerous sessions. The requests were visible, but the scope of the malicious campaign was not observed from the isolated requests. To identify and help stop such techniques, defenses need distributed observability, which can only be achieved from context-aware agents that understand the nature and impact of disparate events and can disrupt such attacks when they are identified.
• Agentic Security Operations: As an industry, we must also acknowledge the difference between autonomous and automated systems. The industry has been integrating elements of automation for years. Scripting, decision trees and playbooks are mechanisms for speeding up the response in specific context, but do not necessarily generalize or work across different phases. If the attacker is using an agentic system for 90% of the attack lifecycle, security operations centers (SOCs) must also implement an agentic system for 90% of their triage, investigation, remediation and threat hunting workflows. This must be the rule, rather than the exception. By combining observability with dynamic AI agents capable of coordinated decision making and task execution, SOCs can deliver proactive autonomous protection at scale.

The Future Is Now. Are You Ready?

The GTG-1002 campaign is a clear signal that offensive AI agents are being used in the wild. The adoption of AI agents by threat actors will accelerate and demand a decisive transformation of defensive security operations to include agent orchestration tools customized to respond to the uniqueness of offensive AI agents.

At Palo Alto Networks, our platformization strategy was built precisely for this moment. This interconnectivity between tools and systems transforms visibility into observability necessary for AI agent orchestration.

In light of GTG-1002, there is an unequivocal need for the security community to accelerate the pivot from automated to autonomous security operations. AI agents can quickly find and exploit vulnerabilities, moving stealthily across the attack chain. We must shift from human-led, reactive defense to fast, proactive machine-driven security to ensure cyber resilience in the age of AI.

Are you ready? Learn about securing AI agents and how to create a trustworthy AI ecosystem.

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Key Takeaways

• Autonomous Orchestration and Execution: The GTG-1002 campaign was a watershed event because the AI agent, powered by Claude Code, autonomously orchestrated and executed all key phases of the attack, from mapping surfaces and exploiting vulnerabilities to moving laterally and conducting intelligence analysis at machine speed.
• Shift to Machine-Driven Security Paradigm: The emergence of autonomous offensive cyber agents, as demonstrated by the GTG-1002 campaign, demands an immediate pivot from human-led, reactive security to a proactive, machine-driven security defense model.
• Distributed Observability is Essential to Agentic Defenses: To counter new attack techniques like GTG-1002, which evade detection by splitting the campaign into small, distributed, and seemingly benign fragments, defenses must adopt distributed observability to connect disparate events using context-aware agents.

Further Reading:

• Lohn, Andrew, et al. "Autonomous Cyber Defense." A roadmap from lab to ops. Online. Centre for Emerging Technology and Security (CETaS) at The Alan Turing Institute (2023).
• Principles for the Secure Integration of Artificial Intelligence in Operational Technology

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Posted by Google GenAI Security Team