Microsoft is taking a new approach to fighting cybercrime, targeting the cyberattack supply chain, not just individual services. In a case unsealed today, we are simultaneously targeting two widely used cybercrime tools, Amadey and StealC, after AI-assisted analysis revealed they rely on the same infrastructure.
This action goes after the cybercrime “assembly line,” where coordinated tools drive ransomware, financial fraud, and disruptions to public services. Amadey and StealC are often used alongside each other: Amadey helps attackers gain access to devices, while StealC steals passwords and sensitive information. Together, they form a critical link in the chain. In the first two weeks of May alone, Amadey and StealC were linked to more than 140,000 infected computers globally, highlighting how widely they are used.
Working with Europol and industry partners, we targeted both tools at once. The goal: break the chain. Since the start of the operation, Microsoft has identified more than 18,000 victim computers, severed criminal control of those devices, and is working with telecommunications providers to help protect affected customers globally.
When multiple parts of an operation are disrupted together, attacks are harder to launch, scale, and recover from. The result: fewer disrupted services, fewer opportunities for cybercriminals to profit, and more friction when they try to rebuild.
It’s no longer enough to go after threats one by one.We need to interrupt how the attacks are put together.
What’s new is how we’re combining AI analysis with an expanded use of that law.
Amadey and StealC were developed by separate cybercriminals, but they relied on the same infrastructure. To understand how they worked, investigators used AI, including Copilot, to quickly analyze the malware, asking questions in plain English instead of manually combing through complex code. That helped surface key details, uncover hidden data, and test findings in a fraction of the time, turning what would have taken hours or days into minutes and enabling the team to spot connections faster.
Those insights allowed the legal team to treat both malware families as part of a single conspiracy. Instead of going after each tool separately, as we have done in the past, we used RICO to charge multiple complicit enablers involved across the operation. In total, Microsoft’s Digital Crimes Unit disrupted over 200 command-and-control servers—the systems criminals use to control infected devices, steal data, and keep attacks running.
By targeting tools together, we can disrupt the cybercrime chain more efficiently and more effectively, in a way that better reflects how these networks actually operate today.
Cybercrime now runs like an assembly line
Cybercrime is no longer a series of isolated attacks—it’s a coordinated system.
Specialized tools handle each step: one gains access, another steals credentials, and others sell or exploit that access for fraud, ransomware, espionage, or other nefarious purposes. Different actors may be involved at each stage, but together they turn access into profit, quickly and at scale.
How cybercrime tools are built to be modular
That structure also creates a point of vulnerability. The people behind these cybercriminal tools may never interact directly, but their tools are designed to work together. If those connections can be identified, multiple stages of an attack can be disrupted at once.
How these attacks play out in the real world
Most people will never hear the names Amadey or StealC, but they feel the effects. A hospital locked out of critical systems. A city unable to deliver essential services. A small business losing access to accounts overnight. A retiree who lost their life savings.
These attacks don’t happen all at once. They unfold step by step: attackers get in, passwords are stolen, access is reused or sold, and sometimes repurposed for more targeted operations. For example, Microsoft has observed Russian-affiliated actor Secret Blizzard leveraging Amadey infections to deploy custom malware against targets in Ukraine.
By targeting multiple points in that chain at once, we reduce the chance that a single compromise turns into widespread harm. Put simply: fewer attacks succeed and fewer people feel the impact when they do.
No one organization can do this alone
Actions like this underscore a fundamental reality: we’re successful when we collaborate. No single organization, whether government or industry, has full visibility into how cyber threats operate across borders and sectors. What makes this effort effective is the combination of perspectives and data.
Bringing those efforts together expanded our collective datasets and made it possible to identify the connections between the two tools and act on them quickly. That shared understanding enabled a coordinated response that went further than any single organization could achieve alone.
This shows why partnerships matter. Industry shares technical insight, government brings visibility, and we need trusted ways to exchange that information. Only by working from the same picture can we stay ahead of attackers, disrupting not just individual tools but also the systems that make cybercrime possible.
Creating sustained pressure on cybercrime
This work doesn’t end with a single action. Cybercriminals adapt quickly, which is why we continue tracking how these operations evolve and working with partners to disrupt them.
Microsoft’s court-authorized disruption in this case is paired with ongoing efforts to track how cybercriminals rebuild, identify new infrastructure, and work with partners to disrupt the services they rely on to operate. It also includes incorporating the findings from this disruption into initiatives like Microsoft’s Statutory Automated Disruption program, which helps accelerate the removal of malicious domains and infrastructure.
The goal is not just to stop one operation but to slow the system itself—making attacks harder to launch, scale, and recover from. By combining AI-driven insight, legal action, and strong partnerships, we can continue to raise the cost of cybercrime and reduce its impact.
For more than a decade, Microsoft’s Digital Crimes Unit (DCU) has worked to disrupt cybercrime and nation-state threats, filing around 40 cases since 2008 and partnering with law enforcement to take down criminal networks. Learn more about the team’s efforts here.
You've watched the demos. Whether it's Claude Cowork, ChatGPT Enterprise, GitHub Copilot, Cursor, or internally developed agents, AI systems are no longer answering questions. They are connecting to enterprise data, invoking tools, making decisions, and executing multi-step workflows across applications without human intervention. The capability is real, and organizations are rapidly moving from experimentation to deployment.
Teams are no longer asking if they should use this, they have accepted agentic tools as the reality. But the board and the infosec team are asking a different question: can this capability be secured and controlled at enterprise scale? Can security teams prevent sensitive company data from being exchanged without oversight?
Anthropic built meaningful access controls into Cowork — role-based permissions, group spend limits, usage analytics and connector restrictions — so the answer is a qualified yes. Those controls handle who can use the tool and what they can connect to, but they don't answer whether a specific action inside a given session is safe. That gap is the one standing between a successful pilot and a successful org-wide rollout.
The Gap That a Demo Doesn’t Expose
The organization’s admin assigns roles, sets spend ceilings per user group and restricts which connectors have access to write to your database. Anthropic's OpenTelemetry support even lets your team pipe session events into your SIEM. These controls cover real ground, but they operate at the permissions level — answering whether a person is authorized to use the tool rather than whether what's happening inside a session is safe.
Consider what that gap looks like in practice. Let’s consider two scenarios. Your finance analyst has full Cowork access and uploads a quarterly forecast containing unannounced acquisition figures. The access controls confirm she is authorized to use the tool, but nothing evaluates whether that information should be exposed to a model. That's an AI data loss prevention risk, and access controls are blind to it.
The risk becomes greater when agents move beyond information retrieval and begin taking actions. Let’s say a scheduled Cowork automation is set up to pull weekly competitor pricing from the web. A target site embeds hidden instructions in its page content. The agent, running unattended, reads them as legitimate commands and begins modifying local files and triggering actions your team never authorized. By the time anyone notices, the agent has already acted.
The first scenario exposes a governance problem because your security team has no visibility into what data is flowing through AI tools across the organization. The second is a runtime security problem as there is nothing evaluating whether an action in progress is safe, regardless of whether the user was authorized to start it. Neither gap is addressed with the predefined controls in Cowork; both need to be solved before you can say yes to Cowork adoption in the whole organization.
Why Traditional Controls Break Down
Traditional enterprise software behaves predictably. Access controls work because administrators can reasonably anticipate what an authorized user or application will do once access is granted.
AI systems operate differently. Agents combine models, tools, data sources, and reasoning paths dynamically at runtime. An authorized user may start with a simple request, but the resulting chain of actions may evolve in ways that were never explicitly programmed or anticipated. The challenge is no longer controlling who can access a system. The challenge is securing and governing what happens after access has been granted.
The Missing Layer is Runtime Security
Anthropic's access controls establish who can use Cowork and what they can connect to. But as the examples above show, they don't protect against what happens inside a session: a finance analyst uploading sensitive acquisition data to the model, or a scheduled automation being hijacked by a malicious instruction embedded in a webpage it was directed to visit. What organizations working with Cowork need is a layer that enforces data and security controls and gives complete visibility at runtime across all Cowork agents in the enterprise every interaction boundary.
An AI runtime security layer that sits between your teams and the model providers such as Anthropic, AWS Bedrock, Google Vertex or any combination, and evaluates risk in every interaction. It inspects every request, every tool call and detects sensitive data like client names, financial projections, internal pricing and contract terms. It enforces agent identity controls, so every automated action is traceable to a specific workflow and owner.
Your CISO gets the audit trail and your Infosec team gets the evidence.
The AI Enterprise Needs a Control Plane
The CIO needs the observability for all Cowork activity and costs. An AI control plane allows the CIO to set spending limits per team and use case across every AI tool from a single console. Procurement asks for a quarterly forecast across all AI spend, and you pull it from one place instead of aggregating reports from four different vendor dashboards. If you need to move providers for cost or compliance, the gateway reroutes traffic without disrupting your teams or breaking your workflows.
Claude Cowork may be where organizations begin scaling their AI journey, but it won't be the only AI tool your teams use. Developers will use coding assistants, business teams will leverage the AI built into SaaS applications and data science teams will deploy custom agents for their workflows. New models, new providers and new workflows will continue to appear.
The challenge isn't just governing one AI application; it’s governing AI activity across the entire AI enterprise.
Everyone looks to secure each tool individually: configure Cowork's controls, configure your coding assistant's controls, configure your internal agents separately. But this approach doesn't scale.This is the sole purpose of the control plane. It sits above individual tools, applications and models and enforces security policies, across every AI interaction.
Prisma AIRS AI Gateway provides that centralised control plane. Organizations that deploy Cowork behind our gateway get runtime security, data protection, agent identity controls, and full visibility, applied consistently, without changing how teams use the tool. The same gateway secures every other AI tool in your environment on the same terms.
Cowork may be where the journey begins, the gateway is what allows it to scale and secure the AI Enterprise.
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.
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.
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.
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.
Artificial intelligence (AI) is changing the enterprise faster than most security models were built to handle. In just a fewyears, it has become part of everyday enterprise work. And soon, AI agents will do much more than provide assistance. They will act autonomously across applications, workflows, data stores and infrastructure.
This shift is already changing the security conversation – as it should. When agents can act on behalf of users, systems and business processes, identity is no longer a supporting layer of cybersecurity. It becomes the control plane for deciding who or what can act, what they can access, how much privilege they should have and when that access should be removed. Fragmented tools weren’t built to support this level of real-time visibility and control. It requires a unified identity security platform.
Palo Alto Networks recent acquisition of CyberArk reflects our conviction that identity is a core platform pillar for securing the future of AI. Identity security is now a foundational layer across our portfolio, building on CyberArk's trusted privileged access management (PAM) heritage and extending it to address the complexity of hybrid, cloud-native, and AI-driven environments. It also advances Palo Alto Networks broader platformization strategy, driven by customer demand for integrated, AI-powered security solutions that reduce complexity and close gaps created by disparate point products.
For partners, the launch of Idira™, our next-generation identity security platform, represents a significant opportunity to help customers secure access, privilege and identity risk through a more unified platform approach. More than ever, our customers need knowledgeable, trusted advisers to help them rethink how identity connects to the rest of their security architecture across network security, cloud, security operations (SecOps) and the broader AI-enabled enterprise.
Identity Security is No Longer Human-Centered
Research for our 2026 Identity Security Landscape report found that 96% of organizations have human identities operating with access far beyond what is required for their roles. That finding is unsettling enough, but also consider how modern identity security must account for far more than human users and privileged administrators. It includes machine identities and AI agent identities, ranging from service accounts, workloads and APIs to secrets and certificates and to agents operating across multiple systems.
Our recent report on identity security also notes that there are now roughly 109 machine identities for every human identity. Each identity can carry privilege, create risk and expand the attack surface. That scale makes real-time discovery, governance and control of identities essential. Yet many organizations are still managing privilege in ways that weren’t built for the AI era. When identities can act across systems and attacks can move faster, standing privilege (i.e., always-on access rights granted to users or machines) becomes harder to defend.
The premise of Idira is that every identity within an enterprise is privileged. The platform helps enterprises move from the traditional operating model of human-centered identity architectures and static access tools to embrace one platform that secures every identity – human, machine and AI agent. Idira discovers identities, entitlements and access paths, dynamically applies privileges through just-in-time controls and continuously governs identity lifecycles.
These capabilities become even more crucial as customers work to reduce fragmentation across their security environments. They want better visibility, faster time to value, stronger controls and a simpler way to manage risk across the enterprise. They still need advisory, implementation and managed services expertise, but the conversation is no longer limited to firewalls, privileged access, cloud workloads or SOC operations in isolation. Customers want expert help in connecting these areas into a unified strategy that reflects how their environments actually operate, especially with AI in the mix.
The Identity Security Opportunity for Partners
My message to partners following our launch of Idira is simple but direct: Now is the time to seize this defining moment in identity security. The speed of business is accelerating, as is the speed of attacks. And we know many of our customers around the world are already trying to understand what AI means for their security architecture, operating model and risk posture.
Partners can help lead those conversations with customers. For specialized and regional partners, this might mean expanding the advisory conversation beyond a single domain of cybersecurity. For global systems integrators, it might involve creating a more scalable delivery model by reducing the cost and complexity of stitching together multiple vendor environments. We are also actively welcoming partners into the broader Palo Alto Networks ecosystem, creating new opportunities for identity-focused partners to expand their role across the full platformization strategy.
Across partner types, the identity security opportunity is both strategic and economic. By connecting identity security to the broader Palo Alto Networks platform strategy, partners can expand services offerings, deepen customer relationships and build a stronger model for helping customers reduce complexity, improve visibility, strengthen controls and get to value faster.
But first, sales teams, technical teams, solution consultants and managed service teams need to understand how Idira fits into the Palo Alto Networks platformization strategy and where identity security connects to customer priorities. That means taking full advantage of the sales demos, AI role plays, technical enablement and other active learning resources in Palo Alto Networks newly evolved NextWave program.
I encourage you to move quickly to build your understanding of Idira’s role in securing human, machine and AI agent identities and the shift from standing privilege to dynamic access. Be prepared to talk with customers about identity security in the context of cloud, network, SASE and SOC transformation, as you can be assured questions will be coming. Also, think about the services and offerings you can build around this opportunity. Identity security assessments, privilege modernization, machine identity protection, AI agent identity readiness and broader platformization road maps can all help customers take practical steps toward strengthening security in the rapidly evolving AI era.
Our partners play a frontline role in driving Palo Alto Networks platformization strategy and enabling our shared success. To help your teams educate customers about AI-related identity risk and how Idira can help them secure every identity in the enterprise, human or not, explore the latest resources, enablement and partner tools available through theNextWave Partner Portal.
Key Takeaways
With the launch of Idira, identity security became a core pillar of Palo Alto Networks platformization strategy for the AI era.
Idira helps organizations secure every identity – human, machine and AI agent – with dynamic access, continuous governance and real-time control.
Partners have a timely opportunity to help customers reduce complexity, improve visibility and connect identity security to broader cloud, network, SASE and SecOps priorities.
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.
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.
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.
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 rise of Agentic AI is rapidly reshaping the enterprise, yet its deployment opens a complex new frontier for cyber threats. As organizations race to harness the power of enterprise agents, the "Data Estate" has become the new perimeter. CISOs today face a high-stakes trade-off: enabling developers to build at the speed of AI while keeping proprietary data visible, governed, and secure across the entire AI lifecycle. This requires meticulously checking user inputs, agent outputs, and tool calls for threats like prompt injections, sensitive data loss, and malicious code, while simultaneously preventing autonomous agents from performing destructive actions.
Securing the AI-driven enterprise requires a fundamental shift from reactive measures to proactive runtime protection. Palo Alto Networks and Databricks are delivering on that vision. Our partnership will integrate the Prisma AIRS API with Databricks Unity AI Gateway, embedding seamless security at runtime. This collaboration will enable organizations to innovate with AI agents, applications, models and MCP Servers at scale while maintaining a robust, policy-driven security posture. By combining the centralized AI governance and control capabilities of the Databricks platform with the runtime security protections of Palo Alto Networks, organizations can scale AI innovation without sacrificing visibility, compliance, or security.
The Context: Why AI Security is Different
AI security represents a fundamental departure from traditional defense. Legacy tools are designed for structured threats, leaving them incapable of parsing the intent behind complex, conversational attacks. Furthermore, the integration of Retrieval-Augmented Generation (RAG) and autonomous workflows creates a dynamic attack surface that goes far beyond traditional data loss. Without AI-native oversight, organizations can face severe risks from prompt injections, custom topics, and toxic content manipulating model logic, to tool misuse, malware execution, and malicious URLs hijacking agent actions.
Modern AI development requires more than just a perimeter; it requires contextual intelligence. By integrating Prisma AIRS directly into Databricks Unity AI Gateway, we will evolve security from a reactive layer into a native pillar of the AI architecture.
The Joint Solution: Centralized Security at the Gateway
The most effective way to secure an entire AI environment is at the governance layer. Our integration focuses on Databricks Unity AI Gateway, which serves as the centralized interface for all AI activity within the Databricks environment. Unity AI Gateway is designed for managing, governing, and monitoring access to all models, agents and MCP Servers—whether they are open-source models deployed within Databricks or external proprietary models. As organizations deploy more agents, applications, and models, centralized governance becomes critical. Unity AI Gateway provides a single control plane for AI usage, enabling teams to apply consistent policies, monitor activity, and manage access across AI workloads.
Through this integration, Unity AI Gateway will make real-time calls to the Prisma AIRS Runtime Security API for security inspection. Instead of managing fragmented security policies across dozens of individual applications, SecOps teams will be able to enforce consistent guardrails across the entire Agentic AI estate from one location, providing a single, unified enforcement point for all AI workloads.
Figure 1: Centralized AIRS guardrail configuration delivers instant protection across all applications, agents and MCP Servers without requiring client-side code refactoring
Mechanism: API Intercept for AI Runtime Security
Prisma AIRS operates as an advanced inspection layer, leveraging its API Intercept capability to provide real-time security embedded directly into the application flow. By embedding Prisma AIRS directly into the workflow, we offer a seamless 'Security-as-Code' experience that unifies development and defense. Prisma AIRS intercepts AI prompts, responses, and MCP calls—inspecting them in real time to enforce security policies with an immediate Go/No-Go verdict or by sanitizing the data in transit. Prisma AIRS uses deep learning classifiers to detect data exfiltration risks, such as the presence of PII (Personally Identifiable Information), PHI, or PCI data. If sensitive data is found, it can be dynamically redacted or blocked based on corporate policy.
Key Benefits for the Enterprise
This integration isn't just about blocking threats—it’s about accelerating your AI roadmap. By removing the "security friction" that often slows down production deployments, we enable teams to move faster with confidence. Key benefits include:
Zero-Friction Governance: Developers continue working within their familiar Databricks environment. Security is enforced via the Unity AI Gateway API, meaning there are no bulky agents to install and no complex architectural re-wiring required.
Prevention of Data Leakage: Leverage Prisma AIRS’s data classifiers to automatically protect sensitive intellectual property, preventing data leaks to public models and unauthorized users.
Resilience Against AI-Specific Attacks: Protect your Unity AI Gateway deployments from emerging threats that standard network security tools cannot see, including prompt injection, toxic content, custom topics, malware detection and malicious URL detection.
Key Takeaway
Ease of use and unified Policy Management: Enable runtime security through the Unity AI Gateway to gain centralized control over security enforcement.
Audit-Ready Compliance: Every transaction mediated by the Unity AI Gateway is logged with detailed security metadata, delivering enriched insights in Strata Cloud Manager. This provides the forensic trail required for regulatory compliance in highly governed industries like finance and healthcare.
Protection for Agentic Workflows: Future-proof your multi-step AI agents against sophisticated Agentic Threats by inspecting function and tool calls within the runtime.
Looking Ahead
As agentic workflows and multi-step model interactions become the standard, a 'fail-closed' runtime security posture is no longer optional; it is foundational. The integration of Prisma AIRS API and Databricks Unity AI Gateway marks a definitive shift toward a future where enterprise AI is secure by default. By integrating Prisma AIRS API with the Databricks platform through Unity AI Gateway, organizations can centrally govern AI across models, agents, applications, and MCP servers while enforcing consistent runtime security policies. Together, Databricks and Palo Alto Networks are helping customers scale AI innovation with the control, visibility, and protection required for the agentic era.
Are you ready to secure your AI workloads and agentic applications? check out the latest Databricks blog and stay tuned for technical deep-dive sessions coming soon.
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.
We’ve been thinking deeply about enterprise security. The operating model that served us for the past decade (collect telemetry, store it, query it, build dashboards to watch it) is no longer keeping pace. We need to shift to the new world: telemetry, context, reasoning, and actions. An approach that produces outcomes. The latest cybersecurity frontier models further made this shift urgent. Models like Claude Mythos can now find software vulnerabilities and reason through complex attack paths at machine-speed, leading to an exponentially increasing backlog of vulnerabilities.
Introducing AWS Continuum for code vulnerabilities
Today, we’re announcing AWS Continuum for code vulnerabilities, now available in gated preview. Continuum for code vulnerabilities addresses the full lifecycle of a code vulnerability at machine speed: from discovery through actions. It reasons over your environment, confirms what is real, and drives toward resolution. It’s model agnostic, using multiple frontier models where each performs best, and is built to incorporate the latest and most capable models as they emerge.
Continuum is built on lessons learned from running security across AWS and Amazon.com. Securing businesses that operate in different industries required a system that understands business context rather than applying generic rules uniformly.
How it works
Continuum for code vulnerabilities reasons over your full environment. This context includes structured data already living in Amazon Web Service (AWS) (your infrastructure, permissions, network topology, code) and the unstructured data that captures how your organization operates and your risk profile (your documents, communications, business priorities).
Continuum for code vulnerabilities operates in four continuous phases.
Discovery: Security teams tackle a backlog of vulnerabilities, and many are already using frontier models to find more. Continuum starts by ingesting that existing backlog and performing its own vulnerability scan of your environment. This creates a more comprehensive view of vulnerabilities and the associated attack paths.
Prioritization: Continuum uses context to evaluate, enrich, and prioritize every finding. Is the affected component deployed, is it reachable, is it in a production path, and what would the business impact be if exploited? The result is an evidence-backed list of priorities, allowing Continuum and your team to focus on what’s most important.
Validation: Continuum validates findings to surface false positives before they waste your team’s time. It contextualizes vulnerabilities against your environment. It then constructs working exploit examples in a sandboxed environment that provide concrete, reproducible evidence of the issue.
Mitigation and remediation: Continuum assesses existing defenses around a validated issue, including blocking and compensating controls along with detection mechanisms. It then draws on its understanding of the codebase, context, and findings to recommend mitigation or remediation of the vulnerability with a network change, policy change, or code patch. The patch recommendation is validated using the same system that confirmed the vulnerability. It also provides blast radius visibility and rollback paths where feasible.
This is just the beginning. We’re starting with code (1st and 3rd party) and then expanding to other aspects of security.
Trust is graduated
Continuum starts in learn mode with a human in the loop. Every recommendation includes the reasoning behind it. As you gain confidence, you can graduate Continuum to enforce mode, enabling remediation that can be increasingly automated based on categories and risk profiles you define.
Continuum capabilities
In addition to Continuum for code vulnerabilities, Continuum includes capabilities you might already know. The AWS Security Agent penetration testing and code scanning functionality is now part of Continuum as Continuum pen testing and Continuum code scanning (Preview). We’re also launching Continuum threat modeling in preview, which automatically generates comprehensive threat models from design documents or source code and outputs results in STRIDE format. These capabilities serve as detection and analysis sources that feed into the broader Continuum loop of discovery, prioritization, validation, and remediation.
Getting started
We’re working with customers across financial services, automotive, and technology to shape AWS Continuum. Customer feedback confirms the direction: security teams want tools that earn trust and take action.
AWS Continuum for code vulnerabilities is available in gated preview. Sign up to request access at AWS Continuum.
If you have feedback about this post, submit comments in the Comments section below.
AI security is getting attention because AI has stopped being a side experiment. It is now part of how work gets done. Employees use copilots to write, research, code, and analyze. Product teams are adding AI into customer experiences. Developers are building applications on top of foundation models. Business teams are experimenting with agents that can read email, summarize documents, query data, and trigger workflows. That is a very different world from the one many AI review processes were designed for. An AI system can pass a benchmark and still fail in production. It can behave safely in a clean test environment and then encounter real […]
In this blog post you’ll learn how to detect and prevent subdomain takeover – a tactic where threat actors exploit dangling DNS records to redirect traffic to attacker-controlled resources. We’ll explain the issue, how the situation arises, and how you can use various AWS features and services to help mitigate the impact of this tactic.
Under the shared responsibility model, securing configurations in the cloud is your responsibility. AWS supports you through strong defaults, guidance in the Security Pillar of the Well-Architected Framework, and security services to help you meet that responsibility. The AWS Customer Incident Response Team (AWS CIRT) also monitors for new and trending tactics that threat actors use to exploit specific customer configurations, so that you can make informed design decisions and improve your response plans.
AWS CIRT has observed threat actors actively scanning for public DNS CNAME records that point to resources that no longer exist, looking for subdomain takeover opportunities.
Note: The subdomain takeover tactic does not leverage vulnerabilities of AWS services. It exploits a dangling DNS record to redirect traffic to an attacker-controlled resource.
Quick DNS Primer
CNAME Records: A CNAME (Canonical Name) record is a DNS entry that points one domain name to another. For example, api.example.com can be configured to point to api.example.s3-website-us-east-1.amazonaws.com. This feature of DNS enables users to configure a memorable, human-friendly domain name while the actual resource lives at a longer, machine-generated AWS hostname. A security issue emerges when the target resource is deleted but the CNAME record pointing to it remains – creating a “dangling” record.
Dangling Records: When a resource (like an S3 bucket) is deleted but the DNS record pointing to it is left behind, that DNS record becomes “dangling”, pointing to a resource that no longer exists. For resources in globally shared namespaces, threat actors can potentially reclaim the name of your deleted resource and serve malicious content through your DNS record.
What is subdomain takeover?
A subdomain is a prefix added to a domain that allows you to organize access to your resources. A subdomain takeover occurs when you delete the underlying resource and a threat actor creates a new resource with the same name to take advantage of the DNS records still pointing to it.
A subdomain takeover is possible when a CNAME record points to an AWS resource that uses a globally shared DNS namespace where the resource name can be chosen by any AWS customer. The following AWS resources meet these criteria:
Amazon S3 (global namespace): Bucket names like mybucket.s3.amazonaws.com are globally unique and can be claimed by any account if the bucket is deleted. Note: S3 buckets created with account regional namespaces (launched March 2026) are scoped to your account and are not subject to this issue.
Amazon CloudFront: Distribution domain names like d111111abcdef8.cloudfront.net are assigned by AWS and cannot be chosen by an attacker. However, if you delete a distribution and another customer creates one that happens to receive the same domain name, a dangling CNAME could resolve to their content.
AWS Elastic Beanstalk: Environment names like myapp.elasticbeanstalk.com are globally unique and can be claimed by any account if the environment is terminated.
Resources like Amazon VPC, Amazon EC2 instances, or private hosted zones are not subject to this tactic because they do not expose globally claimable DNS namespaces.
You create a DNS CNAME record pointing to your S3 website endpoint. The subdomain subdomain.example.com now resolves to subdomain.example.s3-website-us-east-1.amazonaws.com, which serves content from the S3 bucket named subdomain.example. If your team deletes the bucket and forgets to delete the DNS record, users that navigate to the site will see an error stating that the bucket doesn’t exist. However, at this point, if a threat actor sees this error and moves in to claim the bucket name, they will be able to set up their own site that users will see when they navigate to the subdomain.example.com site.
Figure 1 shows an S3 bucket named subdomain.example (a globally unique bucket name) configured to host a static website, with the S3 website endpoint subdomain.example.s3-website-us-east-1.amazonaws.com.
Figure 1: S3 bucket configured as a static website
As shown in Figure 2, we use Amazon Route 53 to create a CNAME record to resolve to our Amazon domain name; to give users a friendly name and so they do not have to remember the long S3 website name in URLs.
Figure 2: DNS Resolver configured with CNAME record pointing to origin bucket
The customer’s AWS administrator decides to stop serving content from the S3 bucket and deletes it, as shown in Figure 3.
Figure 3: Resource deleted without removing the CNAME record
With the S3 bucket deleted and the CNAME record still in place, the DNS record is now dangling. A threat actor identifies this situation and creates a new S3 bucket with the same global name subdomain.example in an AWS account that the threat actor controls, as shown in Figure 4. The threat actor can now serve content from this new bucket, including potentially malicious content. End users remain unaware of this switch and continue to access subdomain.example.com, trusting the content because it appears to originate from a URL they recognize.
Figure 4: Subdomain takeover happens
Potential impacts of a sub-domain takeover
Consider these potential impacts:
Reputation risk: There is a potential risk to your organization’s reputation, because you don’t control the content being served from the threat actor’s site that your DNS record points to.
Potential exposure to phishing campaigns: Users within your organization might have the subdomain bookmarked in their browser, not knowing the resource is no longer available, then unsuspectingly navigate to the site that now hosts malware or is used to phish user credentials.
Blocking: If the subdomain is flagged by security vendors for malicious activity, it could impact your business operations.
Financial loss: Subdomain takeover incidents can result in a financial impact due to the potential disruption to service delivery as you deal with the event.
Proactive detection
AWS Config for proactive detection
For proactive detection, you can use AWS Config to continuously monitor your Route 53 CNAME records and verify that the target resources exist in your account.
Prerequisite: This approach requires AWS Config recorder to be enabled for the resource types you want to monitor (S3 buckets, CloudFront distributions, Elastic Beanstalk environments). If Config isn’t recording a resource type, it won’t appear in the inventory check. For more information, see Setting up AWS Config with the console.
Why use AWS Config inventory instead of DNS resolution checks?
A common approach is to check whether a CNAME resolves to a valid endpoint. However, this method has a critical flaw: if an attacker has already claimed the resource, DNS resolution will succeed – to their resource, not yours. You would have no indication that you don’t own what’s responding.
By querying AWS Config’s recorded configuration items, you’re checking whether the resource exists in your account inventory, not just whether something responds at that DNS name. This approach correctly identifies dangling CNAMEs even after a takeover has occurred.
Implementation approach:
Account-level vs. organization-level scope
The reference implementation queries AWS Config inventory within a single account. This means that if a CNAME record in Account A points to a resource that legitimately exists in Account B within the same AWS organization, the rule will flag it as NON_COMPLIANT.
For organizations that share resources across accounts, you can modify the solution to use an AWS Config Aggregator, which queries resource inventory across all accounts in your organization. This is similar to how IAM Access Analyzer supports both account-level and organization-level scopes. To use this approach, you need an organization-level Config Aggregator already configured, and the Lambda function’s IAM role needs the config:SelectAggregateResourceConfig permission.
We recommend starting with account-level scope for simplicity, then expanding to organization-level if your environment includes cross-account resource sharing.
The main idea is to create a custom AWS Config rule that queries your Route 53 hosted zones for CNAME records, then parses each CNAME target to determine whether it points to a known AWS resource pattern such as S3, CloudFront, or Elastic Beanstalk. For each match, the rule cross-references the target against your AWS Config inventory to verify that the resource actually exists in your account. If the resource isn’t found, the rule marks the CNAME record as NON_COMPLIANT, surfacing it for review.
The Config rule should focus on known AWS resource patterns:
Note: CNAME records pointing to external third-party services are outside the scope of this detection mechanism, as those resources won’t appear in your AWS Config inventory.
NON_COMPLIANT findings from your Config rule can be routed to AWS Security Hub for centralized visibility, or trigger SNS notifications to alert your security team.
Figure 5: Dangling DNS Detection Solution
Reference implementation:
We’ve published a complete implementation of this detection approach as an open-source solution. The solution deploys a Lambda function that discovers CNAME records across all your Route 53 hosted zones and uses pattern matching to identify targets pointing to S3, CloudFront, and Elastic Beanstalk. It then queries your AWS Config inventory to verify whether each target resource still exists in your account. When a dangling record is detected, the solution generates a HIGH severity finding in Security Hub and can optionally send SNS notifications to alert your security team. A CloudWatch metrics dashboard is also included for ongoing compliance tracking.
Deployment:
# Clone the repository
git clone https://github.com/aws-samples/sample-dangling-dns-detection
cd sample-dangling-dns-detection
# Build the Lambda deployment package
./scripts/package.sh
# Upload to S3
aws s3 cp dist/dangling-dns-detection.zip s3://YOUR_BUCKET/
# Deploy the CloudFormation stack
aws cloudformation deploy \
--template-file infrastructure/template.yaml \
--stack-name dangling-dns-detection \
--parameter-overrides \
LambdaCodeS3Bucket=YOUR_BUCKET \
EvaluationFrequency=TwentyFour_Hours \
--capabilities CAPABILITY_NAMED_IAM
The stack creates an AWS Config custom rule that runs on your specified schedule (default: every 24 hours), evaluating all CNAME records and reporting compliance status.
Mitigating the effects
Mitigating subdomain takeover requires both preventive procedures and responsive capabilities.
Prevention: Standard operating procedure
The most effective mitigation is a standard operating procedure for resource deprovisioning that ensures DNS records are removed before the underlying resource:
Within your DNS zone, delete the CNAME record that points to the fully qualified domain name (FQDN) of the resource that you plan to deprovision.
Wait for the DNS TTL to expire before deleting the resource. DNS resolvers cache records for the duration of the TTL (for example, a TTL of 3600 means resolvers may serve the old record for up to one hour). If you delete the resource before the TTL expires, a threat actor could claim the resource name while cached CNAME entries are still directing traffic to it.
Deprovision the resource that you no longer want to use.
Run a DNS check of the CNAME record that you removed to verify that the resource is no longer resolving.
Key principle: Always delete DNS first, wait for the TTL to expire, then delete the resource. This order eliminates the window where a dangling record could be exploited.
Prevention: S3 account regional namespaces
As mentioned earlier, AWS introduced account regional namespaces for Amazon S3 general purpose buckets in March 2026. While this is a meaningful step toward mitigating the S3-specific takeover vector, there are important operational limitations to be aware of:
Existing buckets are unaffected. Buckets already created in the global namespace cannot be migrated to an account regional namespace. The bucket names remain globally unique and claimable by anyone if the bucket is deleted.
Global namespace is still the default. When creating a new bucket through the console, CLI, or SDK, the global namespace remains the default selection. Users who aren’t aware of the new option will continue creating globally-scoped buckets.
Existing IaC templates require updates. Existing infrastructure-as-code templates (CloudFormation, CDK, Terraform) that don’t explicitly opt in to the account regional namespace will continue provisioning buckets in the global namespace. For CloudFormation, this means setting the BucketNamespace property to account-regional. For other IaC tools, consult their documentation for the equivalent configuration. Organizations need to audit and update their templates to opt in.
For these reasons, the dangling DNS detection approach described in this post remains critical – particularly for organizations with existing S3 infrastructure, and for CloudFront, and Elastic Beanstalk resources where no equivalent namespace scoping exists.
Response: Notification and remediation
When a dangling DNS record is detected, the reference solution described in the Detection section automatically creates a HIGH severity finding in AWS Security Hub and reports the CNAME record as NON_COMPLIANT in AWS Config. If you provide an SNS topic ARN during deployment, the solution also sends notifications to alert your security or operations team via email, Slack, or other channels. For production environments, consider a human-in-the-loop workflow where these notifications are reviewed by a team member who approves the DNS record deletion before it’s executed. This prevents accidental deletion of legitimate records during transient issues.
The reference solution also includes a CloudWatch dashboard for tracking compliance status and evaluation metrics over time, giving your team ongoing visibility into DNS health across your hosted zones.
Note: Fully automated remediation (auto-deleting DNS records) carries risk – a false positive could disrupt legitimate services. We recommend starting with detection and notification, then evaluating automation based on your detection accuracy and operational maturity.
Conclusion
Subdomain takeover is a preventable misconfiguration that can have significant impact on your organization. A layered defense approach provides the best protection:
Prevention: Implement a standard operating procedure that deletes DNS records before deprovisioning the underlying resource.
Detection: Use AWS Config custom rules to proactively identify CNAME records pointing to resources that no longer exist in your account.
Response: Configure notifications through SNS or Security Hub so your team can respond quickly when dangling records are detected.
Monitoring: Maintain ongoing visibility through CloudWatch dashboards to track DNS health and compliance status.
The key insight is that good DNS hygiene – knowing when your CNAME records point to a nonexistent resource – is your first line of defense. Automated detection through AWS Config provides a safety net when operational procedures fail. And if you detect an issue, having a playbook ready to enact your response can lower the impact and your mean time to recovery.
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There is a moment every security analyst knows well. It’s 2am, an alert fires, and you’re staring at a console trying to make sense of what just happened—fast. You need context, scope, and impact: What’s being targeted? Where is it coming from? Is it getting worse? What should we do next?
That moment is exactly what we built the Imperva AI Assistant to improve, starting with Cloud WAF (cWAF) investigations, where speed and clarity matter most.
Security teams are under pressure to investigate threats faster, with fewer resources
Modern application security environments generate a constant stream of signals across events, trends, attack patterns, and security posture. But turning that data into meaningful insight still takes effort. Analysts often move between dashboards, filter logs, and stitch together context across multiple tools to understand what’s happening.
At the same time, teams are expected to do more with less. A persistent skills gap and increasing alert volume mean even routine investigations can take longer than they should, slowing response times and adding pressure to already stretched teams.
The industry’s traditional response has been more dashboards, more saved reports, and more training. We think there’s a better answer: let your team ask the question in plain English and get a structured, security-relevant answer back immediately, grounded in Imperva platform data.
Introducing the AI Assistant.
What is an AI security assistant?
An AI security assistant is a natural-language tool that lets security teams investigate threats by asking questions in plain English, instead of building queries or navigating dashboards, and returns fast, ranked, security-relevant answers grounded in their own platform data. The Imperva AI Assistant brings this capability directly into the Imperva platform, starting with Cloud WAF investigations.
Protect with AI: Making security work faster, simpler, and more accessible
To address this, we’re bringing the power of AI directly into Thales’s Imperva platform.
It builds on AI ExplAIn, the one-click, plain-language explanations we introduced for Imperva Cloud WAF, extending that same clarity from individual blocked requests to full, cross-product investigations.
Our goal is simple: help security teams get answers faster, reduce manual effort, and improve day-to-day productivity.
What the AI Assistant does?
The AI Assistant is designed around three key goals:
Increase productivity
Instead of navigating dashboards or writing complex queries, users can simply ask a question and get an answer immediately.
Make AppSec more accessible
You don’t need deep expertise in Thales or Cloud WAF. The assistant uses natural language, making it easier for more team members to investigate and understand security data.
Support a wide range of use cases
Security questions don’t follow a fixed script. Our assistant can handle a variety of queries, from investigations to trend analysis, without requiring predefined workflows.
Instead of being limited to predefined dashboards or reports, teams can explore questions as they arise, using plain language to surface insights that would be impractical to design into a traditional UI. Because the assistant can draw on signals across the Imperva AppSec platform, it doesn’t just retrieve data – it connects it.
For example, an analyst might ask: “Was the IP that triggered a WAF block also behaving like automated traffic in the same session, and what changed compared to previous activity?”, and get a clear, unified answer in seconds, without having to pivot across tools or manually stitch the data together.
Security investigations, simplified with an AI security assistant
The AI Assistant is a natural-language experience built into the Imperva platform to help security teams investigate faster.
Instead of navigating dashboards or building filters, teams can simply ask:
“What are the top attack source IPs over the last 48 hours?”
“Which URLs are most targeted right now?”
“What types of attacks were blocked on site XYZ.com?”
“What changed between yesterday’s baseline and today’s spike?”
“Are these patterns concentrated in a single source or distributed across multiple locations?”
The assistant responds with a concise, ranked answer, along with a Critical Finding that highlights the security -relevant insight, not just raw data. The assistant can also access all Imperva documentation, so teams can ask “How do I configure…? Or “Where can I find…?” to easily find the information they need.
A real-world investigation, simplified.
Imagine a security analyst investigating a sudden spike in application traffic.
Today, that process often involves switching between dashboards, filtering logs, and piecing together data from multiple sources to understand what’s happening.
With the AI Assistant, the workflow is much simpler.
The analyst can ask:
“What’s driving the spike in traffic today?”
“Are these requests coming from the same source or multiple locations?”
“What has changed compared to yesterday’s baseline?”
Within seconds, the assistant provides a clear, summarized answer, highlighting key trends, identifying the most relevant signals, and surfacing a Critical Finding that explains what matters. Instead of manually connecting the dots, the analyst can quickly understand the situation, prioritize next steps, and respond faster.
Why this matters for security teams
When investigating potential threats, teams need more than confirmation that “something triggered.” They need fast, clear answers that help them understand what’s happening and what to do next.
What’s the pattern? (Is activity concentrated, distributed, or repeating?)
What’s the scope? (Which applications, URLs, geographies, or time windows are affected?)
What’s the severity? (How significant is the signal, and how quickly is it evolving?)
What’s the next best action? (Where should they focus, and what should they mitigate?)
The AI Assistant is designed to answer these questions directly, reducing investigation friction and helping teams move from data to insight, faster.
In practice, this means security teams can move from alert to understanding faster—without adding complexity or changing existing workflows.
Easy to get started
The AI Assistant is built directly into the Imperva AppSec platform, there’s nothing new to install or manage.
It’s available through the Ask AI experience and works within your existing environment, using the same data, workflows, and permissions you already rely on.
Because it’s permission-aware by design, users only see the data they’re authorized to access.
AI capabilities are always optional, customers can choose whether to enable or disable them at any time, ensuring full control over how AI is used in their environment.
Available today
The AI Assistant is currently available under controlled availability for a select group of customers. This phase allows us to refine quality, guardrails, and workflows based on real-world feedback before broader rollout.
Why it matters
AI in security has been discussed for years, often focused on detection and tuning. But the real pressure point has always been the moment of investigation, when teams need to quickly understand what’s happening and decide what to do next.
That’s where the AI Assistant is different. It focuses on turning security data into clear, actionable insight – faster. It doesn’t replace expertise, but it makes effective investigation workflows easier to access across the team.
When fewer people are bottlenecks for interpreting signals, response times improve, escalations reduce, and teams spend less time on repetitive analysis.
The impact is simple: faster decisions, fewer handoffs, and more time spent on the issues that matter most.
The bottom line
Security investigations get faster when teams can turn security data into explanations they trust. The Imperva AI Assistant is designed to shorten the path from alert to decision, starting with Cloud WAF, by helping analysts quickly pull the right data, spot what’s changed, and decide what to do next.
It starts with a question, and an answer you can defend.
Frequently asked questions about the AI security assistant
What is an AI security assistant?
An AI security assistant is a natural-language interface that lets security teams ask questions in plain English and get fast, ranked, security-relevant answers drawn from their own platform data, instead of manually building queries or pivoting across dashboards. The Imperva AI Assistant delivers this inside the Imperva platform, starting with Cloud WAF investigations.
How is the Imperva AI Assistant different from AI ExplAIn? AI ExplAIn gives one-click, plain-language explanations of individual blocked requests in Cloud WAF. The AI Assistant goes further, answering open-ended investigation and trend questions across the Imperva AppSec platform and connecting signals, such as a WAF block and automated-traffic activity, within the same session.
What questions can the AI Assistant answer?
Teams can ask investigative and trend questions such as “What are the top attack source IPs over the last 48 hours?” or “What changed between yesterday’s baseline and today’s spike?” Because it can also read the Imperva documentation, analysts can get configuration and “how do I…” answers in the same place.
Will an AI security assistant replace SOC analysts?
No. The AI Assistant is designed to speed up investigations, not replace expertise. It removes the manual work of pulling and correlating data so analysts can focus on judgment, prioritization, and response.
Is the data the AI Assistant sees kept private and under our control?
Yes. The assistant is permission-aware, so users only see data they are authorized to access, and AI capabilities are optional; customers can enable or disable them at any time.
The major enterprise WAAP solutions evaluated in this guide are Akamai, Cloudflare, F5, Fastly, Fortinet, Imperva, and Radware. In the most recent independent benchmarks, Akamai, Cloudflare, and Imperva were named Leaders in the Forrester Wave: Web Application Firewall Solutions, Q1 2025, while Akamai, Fortinet, and Imperva placed in the Leader category of the AMTSO-certified SecureIQLab Cloud WAAP v4.0 validation. The sections below compare these vendors on security efficacy, API protection, bot defense, operational efficiency, and total cost of ownership so you can match the right platform to your environment.
Web applications and APIs now sit at the center of nearly every digital business, and the threat surface has grown in step. Independent industry analysis estimates that API traffic represents more than 70% of all web traffic, that API related security incidents have climbed to roughly one third of reported data breaches, and that more than a third of recent API breaches trace back to Broken Object Level Authorization (BOLA) flaws.
At the same time, the latest AMTSO-certified SecureIQLab Cloud WAAP v4.0 validation found that average complete-security efficacy across the leading enterprise WAAP solutions declined year over year, even as operational efficiency improved slightly. The takeaway for security leaders is straightforward: WAAP capabilities are diverging across the market, and shortlist decisions made in 2022 or 2023 may no longer reflect current efficacy or operational fit.
This guide focuses on the major WAAP vendors that most frequently appear on enterprise shortlists. It draws on independent SecureIQLab testing, recent Forrester, Gartner, KuppingerCole, and IDC research, and verified peer reviews to help security and risk leaders evaluate platforms across modern, multi-cloud, API-heavy environments without reducing the decision to a generic ranked list.
1. Scope and methodology
This comparison focuses on the major WAAP vendors most commonly evaluated by enterprise buyers: Akamai, Cloudflare, F5, Fastly, Fortinet, and Radware, alongside Imperva. It uses three categories of independently sourced evidence:
Certified independent testing: the 2025 SecureIQLab Cloud WAAP v4.0 CyberRisk Validation, conducted under AMTSO Test ID AMTSO-LS1-TP097, which evaluated 11 enterprise WAAP solutions across more than 1,360 attacks aligned to the OWASP Top 10, OWASP API Security Top 10 2023, MITRE ATT&CK, and the Lockheed Martin Cyber Kill Chain.
Analyst recognition: the Forrester Wave for Web Application Firewall Solutions (Q1 2025), the Gartner Market Guide for Cloud Web Application and API Protection, the KuppingerCole 2025 Leadership Compass for WAAP, the IDC MarketScape for WAAP, and Gartner Peer Insights ratings as of the date of this article.
Verified customer reviews: Gartner Peer Insights, PeerSpot, G2, and TrustRadius user ratings, used as a sentiment signal rather than as a ranking input.
Of the seven platforms covered here, four (Akamai, Cloudflare, Fortinet, and Imperva) completed the public SecureIQLab v4.0 cycle, while three of the competitors (F5, Fastly, and Radware) are listed in the SecureIQLab comparative report as “Contact SecureIQLab” rather than appearing with published v4.0 results. For those three vendors, the profiles below rely on Forrester, Gartner, and verified customer review sources, and head-to-head efficacy comparisons should be confirmed through buyer-led testing.
Other WAAP vendors (for example hyperscaler-native services and specialized API-security vendors) may be relevant for specific buyer needs, but they fall outside the major-vendor scope used here. Buyers should treat this guide as one input among several and validate every vendor claim against their own application portfolio during a proof of value.
2. What is WAAP?
Web Application and API Protection (WAAP) is a category defined by Gartner to describe cloud-delivered services that protect web applications and APIs against runtime attacks. Core capabilities typically include a Web Application Firewall (WAF), distributed denial-of-service (DDoS) protection, advanced bot management, API security, and increasingly client-side script protection.
In practical terms, a WAAP platform sits in front of an application (or a portfolio of applications and APIs) and inspects every request, blocking exploits aligned to the OWASP Top 10 and OWASP API Security Top 10, distinguishing legitimate users from automated abuse, absorbing volumetric and Layer 7 denial-of-service traffic, and providing the visibility security teams need to investigate and tune.
For a foundational explainer, see Imperva’s What is a WAAP? Learning Center article at imperva.com/learn/application-security/web-application-and-api-protection-waap/ (set as an internal link on publish).
3. Why WAAP matters now
Three forces are reshaping WAAP buying decisions in 2026:
API growth is outpacing API security. Independent reporting indicates that API related breaches have moved from a niche concern to roughly a third of all data breaches, while only about one in five organizations rate themselves as highly capable of detecting attacks at the API layer.
Bots and AI-enabled automation are escalating. Public industry data shows AI-enabled bot activity rising sharply year over year, with credential stuffing, scraping, and inventory hoarding increasingly difficult to separate from legitimate users without sophisticated behavioral analytics.
Cloud-native deployment is the new default. As more workloads move inside hyperscale clouds, development teams increasingly prefer security that runs natively within the cloud environment rather than alongside it through external routing that can add latency and operational overhead.
Regulatory pressure is compounding. Frameworks such as PCI DSS 4.0 (client-side protection requirements), DORA, NIS2, and sector-specific rules on operational resilience are pushing application security from a best practice into a documented control requirement.
For security leaders, the business outcomes a modern WAAP must support include reduced breach risk and downtime, faster time to protection for new applications and APIs, audit and compliance readiness, and predictable cost as application portfolios scale.
4. WAAP vendor comparison at a glance
Use the table below to narrow the vendor set based on architectural focus and primary deployment use case. Then validate efficacy, API coverage, bot defense, and operational fit through your own proof of value. The order is alphabetical, not a ranking.
Vendor
Primary architectural focus
Core deployment use case
Independent 2025 recognition
Akamai
Edge-delivered WAAP on a globally distributed CDN; integrated DDoS, WAF, bot, and API security.
Large enterprises and content-heavy properties needing edge scale and integrated bot defense.
Unified WAF, Advanced Bot Protection, API Security, DDoS, Client-Side Protection, and CDN, delivered as SaaS, on-premises, or natively inside AWS, Azure, and Google Cloud.
Enterprises needing unified, multi-cloud and hybrid WAAP with deep bot, API, and DDoS coverage, including cloud-native deployment.
The Forrester Wave groups vendors into Leaders, Strong Performers, and Contenders, a single published designation that reflects the combined strength of each vendor’s current offering, strategy, and customer feedback. Rather than restate Forrester’s underlying sub-scores, the table below shows each covered vendor’s official tier, with a short note on what Forrester emphasized. This analyst recognition complements security-efficacy testing because it weighs roadmap, innovation, integrations, and customer feedback alongside current capabilities.
Vendor
Forrester tier
What Forrester emphasized
Cloudflare
Leader
Strongest current offering of any vendor evaluated; efficiency-focused features; reference customers flagged support as an area to improve.
Akamai
Leader
Strong detection and automation; broad edge and DDoS scale; noted to lag in DevOps and scanning integrations.
Imperva
Leader
Standout Layer 7 DDoS, CISA Secure by Design Pledge signatory, and a unifying platform roadmap; room to improve in DevOps and scanning integrations and UI consistency.
F5
Strong Performer
Built-in web application scanning and a strong API security story; fewer security operations integrations and a steeper learning curve.
Fastly
Strong Performer
Developer- and business-focused vision and pre-deployment rule testing; still building out API security.
Radware
Strong Performer
AI-assisted SOC tooling and tunable detection; fewer out-of-the-box integrations and less flexible reporting.
Fortinet
Contender
Strong API security capabilities and competitive pricing; roadmap less extensive than others, no rule versioning, and rule testing limited to logging mode.
Source: Forrester Wave: Web Application Firewall Solutions, Q1 2025 (published tier designations and findings). Among the seven vendors covered here, three were named Leaders, three Strong Performers, and one a Contender.
A note on tier equivalence: within Forrester’s methodology, vendors positioned in the same tier hold equivalent standing in the evaluation. The three Leaders (Cloudflare, Akamai, and Imperva) are designated by Forrester as Leaders together; vendor-specific sub-criterion scores within the tier do not change the tier-level designation.
Verified peer feedback (G2)
Independent customer ratings on G2 are a useful third complement to certified testing and analyst evaluation, because they reflect the day-to-day operational experience of paying customers. The table below shows the current G2 standing for each covered vendor’s flagship WAF product profile. Review-base sizes vary widely across vendors, so the rating is best read alongside the volume of reviews supporting it; vendors that have not actively claimed and managed their G2 product profile may show smaller review bases and older reviews.
Vendor product (G2 profile)
G2 rating (of 5)
Review base
Notes
Imperva Web Application Firewall (WAF)
4.7
41
Highest G2 rating among the flagship WAF profiles of the seven covered vendors; primarily enterprise reviewers.
F5 BIG-IP Advanced WAF
4.6
24
Strong rating with a focused enterprise review base.
Radware Cloud WAF
4.6
141
Strong rating with the second-largest review base among the seven.
Cloudflare Application Security and Performance
4.5
595
Largest review base in the category overall; review mix skews toward small business segments.
FortiAppSec Cloud
4.4
33
Solid mid-market G2 standing; reflects Fortinet’s consolidated WAAP profile launched after the Forrester Wave Q1 2025 cutoff.
Fastly Next-Gen WAF
4.2
30
Solid mid-market rating; vendor profile noted on G2 as having limited features (managed but not upgraded).
Akamai App & API Protector
4.0
2
G2 explicitly notes that there are not enough reviews to provide buying insight; the product profile is unclaimed by the vendor.
Source: G2 verified user reviews (most recent rating snapshots at time of writing). G2 product profiles do not always cover a vendor’s full WAAP suite, and review bases vary widely; the table compares each vendor’s flagship WAF product profile. See references.
Looking for the best WAAP solution?
Choosing the right WAAP platform depends on your organization’s unique security and operational needs. Contact our team to discuss your requirements and see how Imperva can help you achieve your application security goals. Get in touch with our team.
5. Key criteria to evaluate when comparing WAAP solutions
The framework below combines the SecureIQLab v4.0 evaluation model (security efficacy, operational efficiency, Secure by Design and Secure by Default ratings, false positive avoidance) with capability themes emphasized by Gartner and Forrester.
Capability
What to evaluate
Security efficacy
Independently measured coverage of OWASP Top 10 (web), OWASP API Security Top 10 2023, and advanced threats including bots and Layer 7 DDoS. Look for AMTSO-certified results.
API and microservice protection
API discovery (including shadow and undocumented endpoints), schema enforcement, BOLA and broken authentication detection, support for REST, GraphQL, SOAP, WebSockets, and gRPC.
Bot and abuse mitigation
Ability to distinguish legitimate automation from malicious bots, behavioral analytics, device and TLS fingerprinting, defenses against account takeover, scraping, and inventory hoarding.
Runtime and cloud integration
Support for major public clouds, native in-cloud deployment, Kubernetes and service-mesh ingress, edge versus centralized models, multi-cloud and hybrid coverage, CI/CD integration.
Operational efficiency and FP avoidance
Time to protection, tuning effort, automation, analytics, and false positive avoidance under real traffic. In the latest SecureIQLab v4.0 cycle, false positive avoidance ranged from near-perfect at the top of the group to noticeably weaker at the bottom.
Performance and reliability
Latency impact, scalability under load, behavior of failure modes (fail-open vs fail-closed), out-of-path versus inline architecture, published service-level commitments for availability and mitigation time.
TCO and commercial fit
Licensing model (per app, per request, per Mbps), predictability under traffic spikes, alignment with portfolio growth, marketplace availability, integration with existing security and developer toolchains.
Ecosystem and roadmap
Vendor stability, innovation pace, AI assistance, hyperscaler partnerships, SIEM and SOAR integrations, partner ecosystem, support quality reflected in verified customer reviews.
6. Five buyer questions to guide WAAP evaluation
Use these five questions as a lightweight evaluation framework. Each maps to one or more of the capability themes above.
1. How well does the platform stop the threats my applications actually face?
Look beyond generic OWASP coverage claims. Ask for AMTSO-certified third-party test results, and verify both web (OWASP Top 10) and API (OWASP API Security Top 10 2023) efficacy. In the latest SecureIQLab v4.0 testing, complete-security results spanned an extremely wide range, from near-complete coverage at the top to less than half of attacks blocked at the bottom, so the spread within a single shortlist can be very large.
2. How deep is the API protection, across all my protocols?
APIs are no longer just REST. SecureIQLab v4.0 testing measured coverage separately across REST, GraphQL, SOAP, WebSockets, and gRPC, and found that coverage varied widely by protocol even within a single vendor, with WebSockets generally the weakest area across the group. Confirm vendor coverage protocol by protocol, not just by headline API score.
3. How effective is bot defense against modern automation and AI-enabled abuse?
Ask vendors how they detect headless browsers, residential proxy traffic, and AI-driven scraping, and how those decisions are made without harming legitimate traffic. In the SecureIQLab bot suite, only a small number of the tested vendors blocked every attack type, so perfect bot defense is a genuine differentiator rather than a baseline.
4. How quickly can my team get to a tuned, low false-positive state?
Operational efficiency and false positive avoidance are tightly linked. In the latest cycle, the strongest vendors avoided essentially all false positives, while the weakest let through enough to translate into meaningfully more alerts per day and substantially more tuning effort for security operations teams. A few points of difference here can mean a very different daily workload.
5. How does the deployment and licensing model align with how my portfolio is growing?
Native in-cloud deployment, edge delivery, and traditional reverse-proxy models produce very different latency, resilience, and onboarding profiles, and per-request, per-Mbps, and per-application licensing produce very different cost curves as traffic scales. Walk through a 24 to 36 month projection with each shortlisted vendor, ideally informed by your own traffic baseline.
7. WAAP Vendor profiles
Each vendor profile below uses the same schema: a neutral summary, a list of capabilities verified from public documentation and independent sources, and a “Consider when” statement. Profiles are presented alphabetically. Capabilities should be re-validated against your specific environment during a proof of value.
Akamai — App & API Protector
Current market status: Publicly traded (NASDAQ: AKAM). Recognized as a Leader in the Forrester Wave: Web Application Firewall Solutions, Q1 2025, and placed in the Leader category of the SecureIQLab 2025 Cloud WAAP v4.0 validation.
Summary
Akamai delivers WAAP from one of the world’s largest edge networks, combining WAF, DDoS, bot management, API security, and client-side controls in its App & API Protector product. In SecureIQLab v4.0, the tested cloud-based deployment was among the strongest in the group on both complete security and operational efficiency, comfortably above the group averages, and avoided essentially all false positives. In the Forrester Wave Q1 2025, Akamai was named a Leader, strong on both current offering and strategy, with reference customers citing strong detection and automation; Forrester noted that Akamai lags in DevOps and scanning integrations and that some prospects weigh its pricing carefully.
Key capabilities
Edge-delivered WAAP integrated with Akamai’s global CDN and DDoS scrubbing capacity.
Behavioral bot detection that blocked every attack type in the SecureIQLab v4.0 bot suite.
API discovery and schema-aware protection for REST and modern protocols.
Layer 7 DDoS coverage with a perfect result in SecureIQLab v4.0 Layer 7 DoS testing.
Integration with Akamai’s broader Zero Trust and AI security portfolio.
Consider when
Consider Akamai when your organization needs edge-delivered protection at very large scale, has significant CDN and DDoS requirements alongside WAAP, and wants a vendor with an established global footprint and analyst-recognized leadership.
Current market status: Publicly traded (NYSE: NET). Recognized as a Leader in the Forrester Wave: Web Application Firewall Solutions, Q1 2025, with the strongest current-offering position of any vendor evaluated. Placed in the Visionary category of the SecureIQLab 2025 Cloud WAAP v4.0 validation; rated Secure by Default.
Summary
Cloudflare delivers WAAP from a globally distributed programmable network, with strong developer experience, rapid feature velocity, and integrated DDoS, bot management, API gateway, and Page Shield (client-side protection). In SecureIQLab v4.0, Cloudflare’s complete-security result landed around the group average, but it blocked every bot and Layer 7 DoS attack type and avoided nearly all false positives; API coverage was uneven, with strength in SOAP and gRPC and notable weakness in REST and WebSockets in the tested configuration. In the Forrester Wave Q1 2025, Cloudflare was named a Leader and posted the strongest current offering of any vendor evaluated; Forrester credited an efficiency-focused feature set and noted that reference customers flagged customer support as an area to improve.
Key capabilities
Cloud-native WAF integrated with Cloudflare’s CDN, DDoS scrubbing, and developer platform.
Programmable security policies and edge workers for custom logic.
Bot management that blocked every attack type in the SecureIQLab v4.0 bot suite.
Page Shield client-side protection aligned to PCI DSS 4.0 requirements.
Strong developer experience and rapid product release cadence.
Consider when
Consider Cloudflare when your organization values developer-led security, rapid time to deploy, and a unified edge platform across CDN, DDoS, and application protection. Plan to validate API coverage by protocol against your specific traffic mix during a proof of value.
F5 — Distributed Cloud WAAP
Current market status: Publicly traded (NASDAQ: FFIV). Named a Strong Performer in the Forrester Wave: Web Application Firewall Solutions, Q1 2025. Not part of the public 2025 SecureIQLab v4.0 published cycle (listed as Contact SecureIQLab in the comparative report).
Summary
F5 brings deep WAF heritage from BIG-IP Advanced WAF and a multi-acquisition portfolio (Volterra, Shape Security), assembled into the Distributed Cloud (XC) WAAP service. F5 is often shortlisted by organizations with significant existing F5 application delivery and security investments and a need to span data center, multi-cloud, and SaaS-delivered WAAP. In the Forrester Wave Q1 2025, F5 was named a Strong Performer, solid on both current offering and strategy; Forrester credited built-in web application scanning (via its Heyhack acquisition) and a strong API security story, while noting fewer security operations integrations and a steep learning curve cited by reference customers. Because F5 did not appear in the public SecureIQLab v4.0 dataset, comparative efficacy claims should be validated through buyer-led testing.
Key capabilities
Distributed Cloud WAAP delivered as a SaaS layer across multi-cloud and edge.
Behavioral bot defense lineage from Shape Security.
API security including discovery and schema validation.
Hybrid deployment alongside BIG-IP Advanced WAF appliances and virtual editions.
Strong fit for hybrid enterprises with existing F5 footprints.
Consider when
Consider F5 when your environment already standardizes on F5 application delivery and security infrastructure, when hybrid (data center plus SaaS) WAAP is required, and when buyer-led testing can fill the absence of comparable public SecureIQLab v4.0 data.
Fastly — Next-Gen WAF
Current market status: Publicly traded (NYSE: FSLY). Recognized as a Strong Performer in the Forrester Wave: Web Application Firewall Solutions, Q1 2025 (vision described by Forrester as developer- and business-focused). Not part of the public 2025 SecureIQLab v4.0 published cycle (listed as Contact SecureIQLab in the comparative report).
Summary
Fastly’s WAF is built on the Signal Sciences engine and is closely integrated with Fastly’s programmable edge platform. The product appeals to developer-led organizations that want deep observability into request decisions, the ability to test rules before deployment, and tight CI/CD integration. The absence of Fastly from the SecureIQLab v4.0 public cycle means head-to-head efficacy comparison against the 11 tested vendors must come from internal testing.
Key capabilities
Signal Sciences detection engine with detailed signal-based decisioning.
WAF Simulator for testing rules prior to production deployment.
Native integration with Fastly’s programmable CDN.
API security features that have continued to expand in 2024 and 2025.
Consider Fastly when application security is closely coupled to a developer-first delivery culture, when observability and pre-deployment rule testing are priorities, and when the lack of public SecureIQLab v4.0 data can be supplemented by internal validation.
Fortinet — FortiWeb
Current market status: Publicly traded (NASDAQ: FTNT). Named a Contender in the Forrester Wave: Web Application Firewall Solutions, Q1 2025, and placed in the Leader category of the SecureIQLab 2025 Cloud WAAP v4.0 validation.
Summary
FortiWeb is Fortinet’s WAAP, available as VM, AMI, container, and SaaS, and integrated with the broader Fortinet Security Fabric. The two independent sources frame Fortinet differently. In SecureIQLab v4.0, FortiWeb posted the strongest complete-security result among the tested platform vendors, with high operational efficiency and near-perfect false positive avoidance (its bot defense blocked three of the four attack types). In the Forrester Wave Q1 2025, Fortinet placed in the Contender tier, the only covered vendor below the Strong Performer band, with developing positions on both current offering and strategy. Forrester noted a roadmap less extensive than others in the evaluation, an absence of rule versioning, rule testing limited to logging mode, and limited compliance and performance reporting, while crediting strong API security capabilities and competitive pricing.
Key capabilities
WAAP available as virtual machine, AMI, container, and SaaS.
Integration with Fortinet Security Fabric (FortiGate, FortiAnalyzer, FortiSIEM).
Machine learning models for traffic profiling and threat detection.
API security capabilities including anomaly detection, PII labeling, and gRPC support (per Forrester).
April 2024 Google Cloud Technology Partner of the Year award in application security.
Strongest complete-security result among the SecureIQLab v4.0 tested platform vendors.
Consider when
Consider FortiWeb when your organization is standardized on the Fortinet Security Fabric, when integrated network and application security is a priority, and when a competitively priced option within a large security platform is the goal. Buyers prioritizing rule lifecycle management (versioning, safe rule testing outside logging mode) or breadth of strategy and roadmap should weigh the Forrester findings and validate these areas during a proof of value.
Imperva (part of Thales) — Web Application and API Protection
Current market status: Now part of Thales (acquired December 2023). Recognized as a Leader in the Forrester Wave: Web Application Firewall Solutions, Q1 2025, and the KuppingerCole 2025 Leadership Compass for WAAP. Placed in the Leader category of the SecureIQLab 2025 Cloud WAAP v4.0 validation (the fourth consecutive cycle) and awarded the Secure by Default rating.
Summary
Imperva delivers a unified WAAP combining Cloud WAF, Advanced Bot Protection, API Security, DDoS Protection, Client-Side Protection, Account Takeover Protection, and CDN under one platform, available as SaaS, on-premises, or deployed natively inside hyperscale clouds. In SecureIQLab v4.0, Imperva was among the strongest in the group on both complete security and operational efficiency, well above the group averages, and notably achieved perfect 100% results in bot defense, Layer 7 DoS, and false positive avoidance, a combination of high efficacy and full false-positive discipline that few vendors matched. In the Forrester Wave Q1 2025, Imperva was named a Leader, strong on strategy and solid on current offering. Forrester highlighted Imperva’s Layer 7 DDoS, its signing of the CISA Secure by Design Pledge, and a roadmap that integrates its application security offerings into a unified platform, while noting room to improve in out-of-the-box DevOps and scanning integrations and in some UI consistency.
Key capabilities
Unified WAAP platform across SaaS, on-premises, and cloud-native deployment.
Native in-cloud deployment for AWS, Microsoft Azure, and Google Cloud, with Imperva for Google Cloud (available on Google Cloud Marketplace) inspecting traffic inside the Google Cloud network via Service Extension and Private Service Connect, and onboarding without DNS, SSL, or routing changes.
Advanced Bot Protection with behavioral analytics and fingerprinting; blocked every bot attack type in SecureIQLab v4.0 testing.
API Security with discovery, schema-based protection, and BOLA detection; API protocol coverage well above the tested-group average.
DDoS Protection with industry SLA commitments; perfect result in SecureIQLab v4.0 Layer 7 DoS testing.
Client-Side Protection aligned to PCI DSS 4.0 magecart and script-protection requirements.
Perfect 100% results in bot defense, Layer 7 DoS, and false positive avoidance in the SecureIQLab v4.0 cycle; Secure by Default rating per CISA-aligned criteria.
Consider when
Consider Imperva when your organization needs unified WAAP across multi-cloud and hybrid environments, when deep API security and bot defense are required alongside core WAF and DDoS, when low operational burden and very high false-positive avoidance are priorities, and when cloud-native deployment inside AWS, Azure, or Google Cloud is on the roadmap.
Radware — Cloud Application Protection Service
Current market status: Publicly traded (NASDAQ: RDWR). Recognized as a Strong Performer in the Forrester Wave: Web Application Firewall Solutions, Q1 2025. Not part of the public 2025 SecureIQLab v4.0 published cycle (listed as Contact SecureIQLab in the comparative report).
Summary
Radware’s Cloud Application Protection Service combines WAF, bot management, API protection, and DDoS, with continued investment in AI-driven detection and SOC automation tooling. Radware’s heritage in DDoS protection makes it a frequent shortlist option for organizations whose risk profile is heavily weighted to availability attacks. In the Forrester Wave Q1 2025, Radware was named a Strong Performer, strong on strategy and solid on current offering; Forrester credited its AI SOC Xpert tool and tunable detection models, while noting fewer out-of-the-box integrations and reference-customer feedback that reporting could be more flexible. Comparable SecureIQLab v4.0 data is not publicly available for this cycle.
Key capabilities
Cloud Application Protection Service combining WAF, bots, API, and DDoS.
Strong DDoS protection heritage.
AI-assisted SOC tooling for application protection.
Hybrid and cloud deployment options.
Forrester recognition for detection models and pricing transparency in Q1 2025.
Consider when
Consider Radware when DDoS exposure is a primary driver, when AI-assisted SOC tooling is valued, and when the absence of public SecureIQLab v4.0 data can be addressed through internal testing.
8. Why Imperva stands out for unified, cloud-native WAAP
Imperva’s differentiation is grounded in four architectural realities that buyers can verify in their own environments and through independent testing.
Unified WAAP rather than assembled WAAP. Imperva’s Cloud WAF, Advanced Bot Protection, API Security, DDoS Protection, Client-Side Protection, Account Takeover Protection, and CDN are delivered as one platform rather than a portfolio of acquired and integrated products. The result is consistent policy, telemetry, and analytics across the entire application protection surface.
Validated efficacy with very low operational burden. In the latest AMTSO-certified SecureIQLab v4.0 cycle, Imperva paired among the strongest complete-security and operational-efficiency results in the group with perfect 100% results in false positive avoidance, bot defense, and Layer 7 DoS. Few vendors in the tested set combined top-tier efficacy with that level of false-positive discipline.
Deployment flexibility, including native cloud integration. Imperva can be deployed as SaaS, on-premises, or natively inside hyperscale clouds. Imperva for Google Cloud, available on Google Cloud Marketplace, inspects traffic inside the Google Cloud network using Service Extension and Private Service Connect, and onboards without DNS, SSL, or routing changes. This native, in-cloud direction extends across AWS, Azure, and Google Cloud, and reflects a broader roadmap of running enterprise-grade WAAP inside hyperscale infrastructure rather than alongside it through external routing.
Aligned to CISA Secure by Design. Imperva earned the SecureIQLab Secure by Default rating in the same cycle, reflecting hardened defaults and the ability to protect newly deployed applications without extensive manual tuning.
No single platform is the right answer for every environment. Buyers whose dominant requirement is a single edge platform unifying CDN, application protection, and a developer-centric workflow, or whose primary driver is the deepest possible DDoS scrubbing capacity, will want to weigh those needs explicitly. The most reliable approach is to validate any shortlist, including Imperva, against your own threat model, traffic patterns, and cloud footprint during a proof of value.
9. How to choose the right WAAP platform
Choosing a WAAP platform should start with your operating reality, not the vendor list. The matrix below maps the most common dominant security gap to the WAAP capabilities buyers should prioritize during evaluation.
If your biggest gap is…
Prioritize…
API exposure and BOLA-style abuse
API discovery (including shadow APIs), schema enforcement, behavioral analytics, BOLA detection, broad protocol coverage (REST, GraphQL, SOAP, WebSockets, gRPC).
Bot abuse and account takeover
Behavioral bot detection, device and TLS fingerprinting, real-time risk scoring, integration with fraud and identity controls.
Client-side protection that inventories scripts, detects unauthorized modification, and produces auditable evidence.
Operational overhead and tuning effort
High Secure by Default scores, high independent false positive avoidance scores, automated policy generation, and analyst-recognized ease of management.
Multi-cloud, hybrid, and cloud-native coverage
Consistent policy and telemetry across AWS, Azure, GCP, and on-premises; native in-cloud deployment options; CDN-agnostic delivery; marketplace availability.
There is no single best WAAP for every organization; the right platform depends on your threat profile, API footprint, and cloud architecture. Among the major vendors most often shortlisted by enterprises, Akamai, Cloudflare, and Imperva were named Leaders in the Forrester Wave: Web Application Firewall Solutions, Q1 2025, while Akamai, Fortinet, and Imperva placed in the Leader category of the AMTSO-certified SecureIQLab Cloud WAAP v4.0 validation. In that cycle, Imperva combined among the strongest security efficacy in the group with perfect 100% results in bot defense, Layer 7 DoS, and false positive avoidance. Validate any shortlist against your own traffic during a proof of value.
What is the difference between a WAF and a WAAP?
A Web Application Firewall (WAF) inspects and filters HTTP traffic to block common web exploits such as those in the OWASP Top 10. Web Application and API Protection (WAAP) is the broader, cloud-delivered category defined by Gartner that pairs a WAF with additional runtime defenses, typically DDoS protection, advanced bot management, API security, and client-side script protection. In other words, the WAF is one component inside a modern WAAP platform.
Which major WAAP vendors were named Leaders in the most recent Forrester Wave for WAF Solutions?
In the Forrester Wave: Web Application Firewall Solutions, Q1 2025, which evaluated 10 providers across 22 criteria, the vendors covered in this guide were placed as follows: Akamai, Cloudflare, and Imperva were named Leaders; F5, Fastly, and Radware were named Strong Performers; and Fortinet was named a Contender.
Which of the vendors covered here completed the most recent SecureIQLab Cloud WAAP testing?
Of the seven platforms covered here, four completed the public SecureIQLab v4.0 cycle: Akamai, Cloudflare, Fortinet, and Imperva. Akamai, Fortinet, and Imperva were placed in the Leader category. F5, Fastly, and Radware are listed as Contact SecureIQLab in the comparative report and did not appear with published v4.0 results.
Why does API protocol coverage matter so much in 2026?
API traffic now accounts for more than 70% of all web traffic, and independent industry reporting links roughly a third of recent data breaches to APIs, with about 35% of API breaches tied to Broken Object Level Authorization (BOLA). Modern WAAPs need to cover REST, GraphQL, SOAP, WebSockets, and gRPC; independent testing has shown wide variance across protocols even within a single vendor’s product.
What does native cloud deployment add over traditional WAAP delivery?
Native in-cloud deployment lets a WAAP inspect traffic inside the cloud provider’s own network rather than routing it externally, which can reduce latency and operational overhead and avoid changes to DNS, SSL, or routing. Imperva for Google Cloud, for example, uses Google Cloud Service Extension and Private Service Connect to operate inside the Google Cloud network, and Imperva offers native deployment across AWS, Azure, and Google Cloud.
What independent WAAP testing standards should I trust?
Look for testing conducted under the Anti-Malware Testing Standards Organization (AMTSO) framework. The SecureIQLab Cloud WAAP v4.0 methodology used in this guide is AMTSO-certified (AMTSO-LS1-TP097). Pair it with analyst evaluations (Forrester, Gartner, KuppingerCole, IDC) and verified peer reviews.
How should I treat vendor-supplied competitive content during evaluation?
Treat vendor-produced competitive comparisons as marketing inputs rather than evidence. Anchor evaluation on AMTSO-certified independent testing, recent analyst reports, and verified peer reviews, and confirm specific claims through your own proof of value.
11. Choose your next step
Strong WAAP decisions combine three things: independent testing data, analyst guidance, and a proof of value run on your own traffic. As next steps, security leaders typically benefit from running a quick application portfolio baseline (top 20 apps and APIs by risk), executing an internal red-team exercise against current controls, and shortlisting two to three vendors for parallel proof of value testing across the dimensions outlined above.
To explore Imperva’s WAAP capabilities, including native deployment for AWS, Azure, and Google Cloud, or to request a technical evaluation, contact the Imperva team.
12. References and appendix
All claims in this guide are supported by independent third-party sources or by vendor public documentation for descriptive facts. The full reference list is below.
Independent testing
[1] SecureIQLab, 2025 Cloud WAAP CyberRisk Comparative Validation Report v4.0, AMTSO Test ID AMTSO-LS1-TP097, https://www.secureiqlab.com.
[2] SecureIQLab, 2025 Cloud WAAP CyberRisk Validation Reports (individual vendor reports, including Akamai, Cloudflare, Fortinet, and Imperva).
[4] Forrester, The Forrester Wave: Web Application Firewall Solutions, Q1 2025 (Sandy Carielli, et al., March 20, 2025). Tier placements and composite scorecard scores cited here are from Figures 1 and 2 of the report.
[5] Gartner, Market Guide for Cloud Web Application and API Protection, most recent edition, https://www.gartner.com.
[6] Gartner Peer Insights, Cloud Web Application and API Protection market reviews, https://www.gartner.com/reviews/market/cloud-web-application-and-api-protection.
[7] G2, Web Application Firewall (WAF) category, verified user reviews and product ratings, https://www.g2.com/categories/web-application-firewall-waf.
[8] KuppingerCole, Leadership Compass: Web Application and API Protection (WAAP), 2025.
[9] IDC, IDC MarketScape for Web Application and API Protection (WAAP).
Industry standards and frameworks
[10] OWASP Top 10 (2021), https://owasp.org/Top10/.
[11] OWASP API Security Top 10 (2023), https://owasp.org/API-Security/.
Shadow AI is no longer a theoretical risk. Employees are adopting AI tools faster than security teams can track them, often without IT’s knowledge, and frequently on devices and surfaces that traditional security tools simply can’t see. If you asked your security team right now how many AI tools are active across your organization, on which surfaces, and what’s being shared, could they answer? For most organizations, the honest answer is no. And that gap, between what your employees are doing with AI and what your security team can actually see, is where enterprise risk lives today. AI adoption in the enterprise didn’t slow down and wait for governance to catch […]
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.
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.
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