ASPM in the AI Era Part 1: Unified Visibility Across Your Stack

Frontier AI models and agentic development have fundamentally changed the demands on application security. 

On one hand, AI models can autonomously discover vulnerabilities and generate working exploits, shrinking the window from discovery to exploitation from days to minutes. On the other, AI-assisted development is helping teams ship code faster than ever, amplifying existing risks and expanding the attack surface.

This dual acceleration breaks traditional AppSec workflows. A process that once allowed teams time to manually review scanner alerts, track down code owners, and assign tickets is no longer viable in an era of machine-speed detection and exploitation. 

It’s why Application Security Posture Management (ASPM) is even more important today than it was in the past. But, it can’t just be a layer that aggregates risk signals. To drive real security outcomes, ASPM needs to help teams prioritize exploitable risks by drawing on context across the entire application lifecycle. 

In this blog series, we’re taking a deep dive into how organizations can operationalize ASPM with Wiz Code. Over the next few weeks, we will cover: 

• Part 1: Visibility and Coverage: How to connect your existing scanners, correlate and deduplicate your resources, and identify coverage gaps across your codebases.

• Part 2: Context and Prioritization: How Wiz enriches third-party findings, removes duplicate alerts, and uses the Security Graph to identify true attack paths.

• Part 3: Remediation and Automation: How to systematically group findings for developers using Posture Policies and leverage the Green Agent for AI-generated fixes.

Why Context is the Foundation of ASPM 

To drive security outcomes, ASPM needs a strong foundation of context. 

Let’s take a practical example with React2Shell (CVE-2025-55182), the critical remote code execution vulnerability impacting Next.js applications from late last year. For an enterprise heavily invested in Next.js, a flaw in a core component does not just trigger one alert. It cascades across micro-frontends, internal tools, and public applications, instantly generating thousands of isolated findings across hundreds of repositories and container images. 

Without context, AppSec teams would be left staring at a massive backlog of vulnerable packages, with no way to tell which instances were actually exploitable. 

With the right context, organizations could detect every instance of the vulnerable component and immediately prioritize the ones tied to internet-facing applications or workloads with access to sensitive data.

Wiz Code delivers this exact capability by connecting your existing AppSec scanner findings with cloud exposure, runtime insights, and even adversarial testing to prioritize critical risks. The foundation of context is also what enables security teams to achieve broad visibility into application risk across their enterprise footprint and empower developers to remediate at machine speed. 

Let’s dive into how organizations can get set up with ASPM in Wiz. 

Maximize the Investment on your Existing Scanners 

The first step is bringing your existing AppSec tools into Wiz. Whether you standardize entirely on Wiz Code’s native scanners (for SAST, SCA, IaC, and Secrets) or operate a hybrid ecosystem, Wiz provides the flexibility to ingest and contextualize all your application security findings without forcing a rip-and-replace.

Traditionally, building a unified risk dashboard across multiple third-party tools requires massive integration overhead. But with the Wiz Integration Network (WIN) we provide out of the box support for popular AppSec solutions like Snyk, Checkmarx, GitHub Advanced Security, and more. 

You can deploy these Wiz-managed connectors with read-only API access and configure them to automatically fetch relevant findings. Wiz handles the API connection, data normalization, and enrichment. This gives your team immediate visibility into SAST, SCA, DAST, and Secret risks without writing or maintaining custom integration scripts.

Custom Integrations 

If you use a homegrown scanner or a tool without a native connector, you can still bring that data into Wiz via SARIF file ingestion. Static Analysis Results Interchange Format, or SARIF for short, is a standard, JSON-based file format used to store and share the output of static code analysis tools in a normalized structure. So if your security team is running a custom solution for code analysis, they can still benefit from the enrichment, prioritization, and lifecycle management in Wiz. 

Correlate Application Security with Cloud Resources  

Once your connectors are active, Wiz begins ingesting the data your scanners generate. You can review this on the Imported Assets page in your inventory.

Each row in this table represents your third-party scanner's perspective of an asset. For example a repository branch scanned by Semgrep or Checkmarx, or Container Image scanned by Snyk. The table shows the asset name, origin scanner, classification, and correlation status.

Crucially, AppSec tools often use completely different naming conventions for the same repository. This is where Wiz asset correlation comes in to serve as your first layer of deduplication. Instead of creating disparate resources for each branch for each scanner, Wiz automatically correlates them to existing resources in Wiz, and adds the third party information as an enrichment on the existing graph entity. If Wiz does not already know of the resource, a new graph resource is created from the scanner’s asset. This cleans up your inventory and prevents unnecessary noise, while allowing you to take your normal action on graph resources such as putting them in Wiz Projects or running Workflows.

This mechanism is the foundation for true code-to-cloud analysis. Traditional AppSec scanners focus on the code. They cannot tell you if a vulnerable repository generates a container image deployed in your environment and is exposed to the internet.

Wiz advances this model. It takes an isolated finding on a repository branch, regardless of the scanner source, traces it to the container image it was built into, linking it to the exact workload where the finding is currently running. Security teams gain immediate context on where vulnerable code lives in reality without any manual searching.

Crucially, this correlation is the engine that allows Wiz to enrich external findings with live cloud context. It sets the stage for the automated prioritization and finding-level deduplication we cover in Part 2 of this series.

Map Coverage and Eliminate Blindspots in Coverage

Enterprise AppSec teams often struggle to answer a fundamental question: Are all of our repositories actually being scanned? In complex environments with multiple development teams, blind spots lead to unmitigated risk, while redundant scanning creates unnecessary noise and wastes resources.

Once your connectors are active and assets are correlated, the Code Repositories inventory gives you a unified view of scanner coverage.

Instead of guessing, you get a clear, per-repository view of exactly what is happening across your codebase. 

For each repository, you can see:

• Active Scanning Tools: Which AppSec tools are actively scanning each repo (such as Snyk, SonarQube, Checkmarx, Wiz Code native scanners, or VCS-native tools).

• Coverage & Gaps: Which finding types are covered (SAST, SCA, Secrets, IaC) and where critical gaps exist.

• Finding Volume: The exact number of open findings per category from each scanner.

You can use this view to surface repositories where no SAST scanning is active or where secret scanning exists from one tool but is missing elsewhere. By mapping your coverage, your team can eliminate blind spots, identify redundant tools on the same repository, and ensure consistent security standards across every development project.

Up Next: Prioritizing Critical Risk with Context 

Getting your existing AppSec data into one platform and mapping your coverage is the crucial first step. However, visibility alone does not solve the vulnerability fatigue caused by AI-accelerated development. Security teams need context to know what to fix first.

In Part 2 of this series, we will dive into how Wiz enriches your third-party findings, automatically removes duplicate alerts across different scanners, and uses the Security Graph to trace isolated flaws into true, exploitable attack paths.