A routine scan detects a low-severity code issue in a microservice — say, a parameter injection flaw with a CVSS score of 4.3. It’s correctly classified as ‘low priority’ and placed in the backlog to wait patiently for it to be fixed by the devs, sometime in the next round of housecleaning. No rush.
And yet, the next time the company CISO encounters it is the same night at 3:42 AM—with a call from the team that’s sitting red-eyed in boxer shorts, hunched over their laptops, puzzled by an unexpected spike in internal API traffic that is rapidly escalating into a severe security breach.
The AppSec team did everything by the book. And still, this seemingly harmless, non-urgent vulnerability is keeping everyone up, kicking themselves for letting it slip under the radar.
Scenarios like this are becoming increasingly common in enterprises delivering software across hybrid and multi-cloud environments. For CISOs, these aren’t just isolated incidents — they’re indicators that the current approach to managing application risk is flawed. But why does this happen? What are we missing here? And how can CISOs cope with this expanding threat landscape?
Why Security Gaps Form in Modern Cloud Environments – A Question of Context
Modern applications span code, clouds, and containers. They’re composed of different third-party libraries, developed across global teams, and deployed multiple times per day.
In this multidimensional world, traditional AppSec methodology can protect the separate parts and processes but simply doesn’t scale to capture the interactions between components in the cloud environment. It’s as effective as a beekeeper working with a patchwork suit.
CISOs and AppSec leaders can check all the boxes on the relevant scans: SAST, DAST, SCA, IaC. They’re building their AppSec program by the book.
But the book itself needs a rewrite. It doesn’t apply to a multi-faceted cloud environment: All the tools operate in silos. Each one produces its own findings. Each team reviews them independently. And when something slips through, no one sees the full picture, because they’re missing the context.
If we go back to the hypothetical we started with – the one that ruined a certain CISO’s good night’s sleep, here’s what happened: The code flaw was identified by the scan, and on its own, wasn’t much to look at and was classified as low-severity. But it was in an exposed API processing regulated customer data, running with elevated permissions, deployed via infrastructure with misconfigured access controls—and so in that context, it became a serious risk with implications for compliance, reputation, and financial exposure. None of the individual tools identified it as urgent because none had the full context.
How The Cloud Changed Everything About Application Risk
Most organizations have successfully transformed their development practices to embrace cloud-native approaches, but their security setup still operates in silos:
- Application security teams focus on SAST, DAST, and SCA, but lack visibility into how code vulnerabilities manifest in cloud environments.
- Cloud security teams monitor infrastructure configurations and runtime activity, but don’t understand how application code interacts with cloud services.
- DevOps teams are caught in the middle, receiving conflicting guidance from both groups.
The rapid evolution of cloud-native architecture—with its containers, Kubernetes, serverless functions, and proliferating APIs—has created an expanded attack surface that traditional security models weren’t designed to protect.
Most enterprises’ security approach failed to catch up to their development architecture. A 2023 survey of over 1,000 IT security professionals revealed that 90% of organizations operate with siloed risk and compliance data—and these organizations experienced breaches at nearly twice the rate of the 10% with integrated security approaches.
This siloed approach fails because in modern cloud environments, application risk isn’t determined solely by code quality. A seemingly minor vulnerability can become critical depending on:
- The cloud services the application interacts with
- The permissions and IAM configuration of the application’s service accounts
- The network exposure of vulnerable components
- Whether the application processes sensitive data
- The cloud provider’s shared responsibility boundaries
This new reality means traditional application security tools that focus purely on code analysis are missing half the picture. Similarly, cloud security tools that don’t understand application vulnerabilities miss critical context about what’s actually exploitable. For CISOs, this means that even a well-funded AppSec program can leave high-risk exposures unaddressed if the organization lacks visibility across this full matrix.
This is exactly where a new security model needs to be introduced: the “Fix–Find–Fuse” model, or 3xF for short.
What’s the 3xF Model, and How to Implement It
The Fix-Find-Fuse model is a practical framework for CISOs that helps security leaders evolve their program — not by replacing everything, but by weaving together what’s already in place. It surfaces the insights that matter most from the clutter, connects findings across domains, and equips teams with the live context they need to prioritize their focus and act upon it.
For enterprises investing in scalable, cloud-native application security platforms, this framework serves as a north star for what a modern AppSec operating model should look like—one that harmonizes today’s architectures, development velocity, and organizational structure to hone security processes, close coverage gaps and reduce DevSec frictions.
Let’s break it down and focus on each of its three parts.
1. Fix: Align Existing Tools to Modern Development
Most organizations already have the building blocks of a strong security program. But those tools must evolve to match today’s velocity and complexity. That means:
- SAST should be incremental, developer-native, and pipeline-integrated. It should scan code early and often—without slowing builds. After running a complete scan, you can run incremental scans on only changed code. Additionally, in the IDE itself, get real-time insights on security best practices before committing code.
- SCA should prioritize vulnerabilities in the context of usage, reachability, and exposure—not just list every CVE in the dependency tree or simply serve as an SBOM generating machine.
- DAST should shift from crawling web forms to testing APIs and cloud services based on OpenAPI specs. DAST can help identify shadow and zombie APIs which are then further tested using an API Testing tool.
- IaC scanning should happen before infrastructure is provisioned, identifying misconfigurations in Terraform, Helm, and Kubernetes.
As you scan a single application, you should be able to launch scans of multiple engines at the same time and correlate results across tools. By understanding context, you can better understand risk. The result enables more precise results, with fewer false positives and false negatives, and a better sense of where risk actually lies.
These adjustments make your tools more useful. But they also expose where they fall short: in context, prioritization, and coordination.
2. Find: Identify Your Gaps
Blind spots multiply with architectural complexity. As enterprises adopt microservices, containerization, and multi-cloud strategies, traditional boundary-based security models fail to capture the interconnected nature of modern applications.
Scale amplifies the cost of incomplete visibility – what appears as an acceptable gap in development environments becomes a critical risk when replicated across thousands of production instances and cloud regions.
That is why this second step in the 3xF model is perhaps the most crucial: to establish complete and continuous visibility—not just into vulnerabilities, but more importantly, into blind spots. True visibility requires mapping what exists before determining what’s vulnerable:
- Establish continuous attack surface discovery as your foundation: Before code scanning can be effective, you must regularly inventory all assets – including undocumented services, ephemeral workloads, and shadow IT that exist outside formal CI/CD pipelines. You can’t secure what you don’t know exists.
- Build API governance around data flows, not just endpoints: Look beyond API documentation to understand how data actually traverses your environment. Track sensitive information from ingestion to processing to identify exposure points that formal specifications miss. As mentioned above, use SAST and DAST to identify shadow and zombie APIs.
- Catch IaC misconfigurations before they reach production: Shift IaC security scanning left to catch misconfigurations during the design phase. Preventing problematic configurations from reaching production is exponentially more efficient than remediating them after deployment.
- Identify which third-party components are reachable from external traffic: Map dependency chains to understand where third-party code interacts with critical systems. Prioritize remediation based on actual application connectivity rather than isolated vulnerability scores.
Without this foundation, AppSec investments are misaligned with actual risk exposure—and the organization is flying blind.
3. Fuse: Create a Holistic Security Vision
The final step in the 3xF model is about meaningful integration rather than mere collection. While “Fix” updates your tools and “Find” identifies your gaps, “Fuse” transforms disconnected security data into a coherent security strategy that cuts through complexity to surface what truly matters. “Fuse” is what elevates AppSec from operations to strategy.
This fusion operates through several key mechanisms:
- Favoring integration over replacement: Rather than ripping out existing security tools that work, invest in platforms that connect and enhance what you’ve already built. Seek solutions that create a unified view across your security toolchain while leveraging open standards for data exchange. The goal isn’t a new dashboard—it’s revealing relationships between findings that remain hidden when viewed in isolation. Effective integration preserves your existing investments while multiplying their value through context.
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Prioritizing based on context, not CVSS: Modern risk isn’t defined by severity alone. The relevant questions here are: (1) How exploitable is this vulnerability in the context of our environment?; (2) Does it touch sensitive data? (3) Is it exposed to the internet?
The goal is smarter triage. Risk scoring must reflect exposure, cloud permissions, API protection, and runtime behavior—not just code flaws in isolation.
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Making security native to development: Security shouldn’t feel external to engineering. The best programs deliver feedback directly into the developer’s flow—whether that’s in an IDE, pull request, or pipeline. It should seamlessly integrate into their environment, be as frictionless as possible and work behind the scenes.
They shift scanning left, automate enforcement, and make remediation guidance clear and fast within the development environment – not external security tools. Security becomes a workflow accelerator, not a blocker.
- Breaking down silos between code and cloud: Siloed teams miss correlated risks. Unified security programs foster shared visibility across AppSec and CloudSec. They align risk models across teams, establish consistent metrics, and build cross-functional security squads that own end-to-end outcomes—from code to configuration to cloud.
- Finding the right metrics: Legacy metrics like “vulnerabilities found” don’t reflect posture. Modern programs track: (1) Mean time to remediate exploitable cloud-exposed risks; (2) Reduction in excessive cloud permissions; (3) Alignment of findings to critical business applications.
These metrics speak to business risk—not just security activity. These are board-ready KPIs—not vanity metrics.
Embedding Application Security Posture Management (ASPM): ASPM is not a scanner—it’s the layer that connects scanners to each other, and to business logic. It correlates code-level vulnerabilities with runtime context, identity configurations, cloud architecture, and sensitive data exposure. When implemented correctly, ASPM enables:
- A unified view of application assets across dev and cloud
- Contextual risk scoring that goes beyond CVSS
- Development and runtime context
- Routing of findings to the right teams based on ownership and impact
This is where security becomes more than just detection. It becomes direction.
What Does 3xF Look Like in Practice?
Here’s how a hypothetical might play out in a real-world enterprise that employs the 3xF model:
- Detection Phase: Multiple security tools identify what appear to be isolated issues:
- An incremental SAST scan flags a parameter injection issue in a Go microservice
- SCA identifies a vulnerable library reachable from an API endpoint
- IaC scanning finds default allow-all ingress rules in the environment
- DAST confirms the API lacks rate limiting and responds to malformed payloads
- Correlation and Prioritization: The AppSec manager receives a critical alert as these findings are correlated, recognizing that together they create an exploitable path to regulated customer data. The development lead is automatically notified via a Jira ticket enriched with contextual risk details and remediation steps.
- Response and Remediation: The security team implements temporary API gateway rules for immediate protection while developers address the root causes:
- Fixing the parameter injection using contextual guidance delivered in the IDE
- Upgrading the vulnerable library to a secure version
- Updating infrastructure code to enforce least-privilege access
- Implementing API rate limiting to prevent abuse
- Verification and Improvement: Post-remediation scans confirm the complete resolution of all issues. The incident is documented internally, feeding metrics like mean time to remediation and contributing to ongoing risk reduction.
In isolation, each tool might have marked its finding as low priority. Together, these interconnected vulnerabilities represented a high-risk situation that demanded immediate attention — highlighting the power of the 3XF approach.
The Road Ahead: Finding Clarity in the Cloud
The attack surface is expanding fast. APIs, multi-cloud workloads, ephemeral infrastructure, and AI-generated code are redefining how applications are built and breached in the cloud era.
In this new reality, security leadership isn’t about owning more tools. It’s about owning the model.
The 3xF framework offers a path forward. It equips CISOs to drive unity across teams, clarity across data, and prioritization across findings. But it’s only effective when implemented on a platform designed to bring application and cloud security together—unifying code, configuration, and context.
You don’t need to rip and replace your stack. You need to rearrange it and the process around it in a way that will provide your team with visibility into what’s deployed, insight into what’s vulnerable, and confidence that they fix what matters most – first.
Learn more about Checkmarx One’s comprehensive code-to-cloud security platform and how it can help you adopt the 3xF framework.