What is Code-to-Cloud Security?

In cloud-native development, security can’t wait until deployment. Code-to-cloud security brings protection to every stage—from the first line of code to what’s running in production—so you catch issues early, fix what matters, and keep up with the speed of DevOps.

Aimed at enforcing security from development to deployment in the cloud, the main goals of this code security strategy are finding and addressing vulnerabilities early in development, preventing cloud infrastructure misconfigurations, and continuously monitoring against threats during runtime.

Unlike siloed AppSec scanners, code-to-cloud security aims to correlate issues identified in the repository with observed runtime behaviors in the cloud.

 For example, if a specific vulnerability is flagged in the source code, the system can help trace its manifestation in the live environment—enabling teams to prioritize remediation based on actual exposure. However, it is important to note that while this approach provides extensive SDLC coverage, supplemental runtime measures may be necessary to address advanced threats such as zero-day exploits or insider attacks.

In the rapidly evolving world of cloud-native applications, code-to-cloud security has emerged as an effective practice for automating the detection of vulnerabilities before and after deployment, reducing attack surfaces through end-to-end coverage, preventing data breaches, and ensuring compliance with industry standards.

 Let’s take a closer look. 

Why is code-to-cloud security necessary?

Cloud-native development has completely changed the software delivery lifecycle. Releases now happen on every commit. Infrastructure is spun up on demand using Terraform, CloudFormation, or Kubernetes manifests. Containers and serverless functions are deployed and destroyed in seconds. In this world, the old security playbooks don’t work.

Most security teams rely on CSPM tools to detect misconfigurations in production and IaC scanners to check for risks in code. But here’s the problem: these tools don’t talk to each other. CSPM surfaces a misconfigured S3 bucket but can’t tell you which Terraform file created it. Meanwhile, your IaC scanner flags a hardcoded secret—but can’t say whether that resource ever made it to production.

This disconnect creates critical challenges:

• Security teams can’t trace issues back to their root cause in code.

• Developers get noisy, low-context alerts they can’t act on.

• Fixes made directly in production break GitOps workflows, causing configuration drift and audit headaches.

High-profile incidents like SolarWinds and Log4j show how attackers exploit weaknesses early in the build process—knowing those flaws will ripple into every environment the code touches. And once a vulnerable artifact is live, tracing it back to a specific commit or pull request can be painfully slow.

Code-to-cloud security solves this fragmentation. It creates a unified view across the entire software development lifecycle—connecting issues found in production to the IaC files, build jobs, or pull requests that introduced them. Security teams gain full visibility, developers get precise, actionable feedback, and risky changes are stopped before they ever reach the cloud.

Secure Coding Best Practices [Cheat Sheet]

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How code-to-cloud security works

Implementing code-to-cloud security requires three core capabilities: shift-left security, infrastructure-as-code (IaC) security, and runtime protection.

Shift-left security

Shift-left security involves integrating security measures into the earliest stages of the SDLC to detect vulnerabilities as soon as possible. Identifying and addressing security flaws before they escalate minimizes both risk and remediation costs.

Key tools and practices include:

Infrastructure-as-code (IaC) security

After securing the application code, the next step is to secure your cloud infrastructure. Cloud resources defined using tools like Terraform, CloudFormation, Kubernetes manifests, or Helm Charts must adhere to security best practices. These include enforcing least-privilege IAM policies, encrypting data in transit and at rest, managing secrets through external vaults, and applying policy-as-code guardrails (like OPA) that fail builds when misconfigurations are introduced.

To control cloud resources before they’re provisioned, teams should rely on IaC scanners and policy-as-code frameworks. These tools catch misconfigurations, compliance violations, and insecure defaults early—before they reach runtime and put production environments at risk.

Mapping IaC to cloud resources

Even with well-secured templates, cloud deployments don’t always reflect the original intent. Misconfigurations can be introduced through overridden variables, reused modules, or environment-specific changes—issues that static scanners often miss.

Code-to-cloud mapping bridges this gap by tracing live cloud resources back to the exact IaC code that created them. Wiz builds this lineage automatically by ingesting Terraform state files, parsing modules and variables, and correlating infrastructure with real-time CSPM findings. This enables teams to:

• Pinpoint which IaC file and line introduced a misconfigured resource

• Determine whether flagged code actually made it to production

• Fix issues at the source to prevent misconfigurations from recurring

With full code-to-cloud visibility, developers and security teams can respond quickly, remediate confidently, and ensure fixes happen in the source of truth—not just in the cloud.

Runtime and post-deployment security

Even with rigorous pre-deployment checks, not every risk can be caught in code. Misconfigurations may be introduced manually, permissions can drift over time, and certain vulnerabilities only reveal themselves during runtime. That’s why runtime and post-deployment security are essential components of a complete code-to-cloud strategy.

Once an application is deployed, security shifts to monitoring and detection. This includes:

• Observing how cloud workloads behave during execution

• Detecting unauthorized access, lateral movement, or privilege escalation

• Continuously validating that deployed configurations still align with security policies

Cloud-native application protection platform (CNAPP) capabilities—such as Cloud Security Posture Management (CSPM), Cloud Infrastructure Entitlement Management (CIEM), and Cloud Detection & Response (CDR)—all come into play here. Together, they help maintain cloud security posture, reduce identity-based risks, and detect active threats like malware, crypto-mining, or remote code execution attempts.

Tools like dynamic application security testing (DAST) can also simulate attacks on live environments to surface flaws that static tools may have missed.

Importantly, runtime signals also feed back into the broader code-to-cloud pipeline—enriching risk prioritization, informing policy updates, and helping teams trace security events back to the source in version control.

When runtime protection is integrated with shift-left and IaC scanning efforts, organizations gain full lifecycle visibility—and the ability to respond to threats without patching over the problem in production.

Alignment with Industry Standards

Code-to-cloud security practices are closely aligned with established industry standards and frameworks, including:

• NIST Secure Software Development Framework (SSDF, SP 800-218): Shift-left security and CI/CD security gates directly address NIST’s requirements for early vulnerability detection, secure coding, and automated testing throughout the SDLC.

• ISO/IEC 27001: By enforcing continuous monitoring, least privilege, and automated controls, code-to-cloud security supports ISO/IEC 27001’s mandates for risk management, access control, and incident response.

• OWASP SAMM & CSA CCM: Integrating security into developer workflows and automating policy enforcement aligns with OWASP’s maturity models and the Cloud Security Alliance’s Cloud Controls Matrix.

How to achieve code-to-cloud security across the CI/CD pipeline

Code-to-cloud security in CI/CD pipelines starts with automating checks at every stage of the build and deployment process. These are often called “security gates”—enforcement points that code must pass through before reaching production. But securing modern pipelines also means maintaining consistency after deployment: preventing configuration drift, aligning with GitOps workflows, and enforcing policies continuously from code to cloud.

Below, we’ll walk through the key security gates—and the supporting practices that ensure misconfigurations don’t reappear later on.

1. The pre-commit security gate

This gate protects code before it’s pushed to an online repository. Security checks during the pre-commit stage rely on the shift-left tools and techniques we mentioned earlier, like SAST, SCA, and code reviews. 

The pre-commit security gate is all about alerting developers about potential security risks they may be introducing into the codebase. Now, imagine a developer attempts to commit this code with a hardcoded credential to connect to a database:

const DB_PASSWORD = "mYnorNIAntENTroLurbeI"

An automated tool should flag this line of code as a security risk and prevent the commit.

2. The pre-build security gate

In the pre-build phase, the focus is on checking that your application's dependencies are secure before the build process starts. That requires top SCA tools, like OWASP Dependency-Check, Retire.js, or FOSSA, to look for known vulnerabilities in third-party dependencies.

For example, assume an application relies on the following Log4j dependency:

<dependency>
    <groupId>org.apache.logging.log4j</groupId>
    <artifactId>log4j-core</artifactId>
    <version>2.14.1</version> <!-- Insecure version of Log4j affected by Log4Shell -->
</dependency>

Because that version of Log4j is vulnerable to Log4Shell, an automated security gate should flag it.

Build configurations should also be analyzed to confirm that the code secured before the commit in the previous stage will remain secure in the build bundle.

3. The pre-deployment security gate

Before deployment, you need to secure your infrastructure using IaC tools and PaC frameworks. 

For instance, consider this misconfigured Terraform script that accidentally allows public access to cloud storage:

resource "aws_s3_bucket" "ecommerce" {
  bucket = "ecommerce"
}

resource "aws_s3_bucket_ownership_controls" "ecommerce" {
  bucket = aws_s3_bucket.ecommerce.id
  rule {
    object_ownership = "BucketOwnerPreferred"
  }
}

resource "aws_s3_bucket_acl" "ecommerce" {
  depends_on = [aws_s3_bucket_ownership_controls.ecommerce]

  bucket = aws_s3_bucket.ecommerce.id
  acl    = "public-read"  # misconfigured for public access => sensitive data may be exposed
}

An automated security gate should flag this misconfiguration, preventing the deployment.

4. The post-deployment security gate

Even after code is deployed, security checks shouldn’t stop. Once applications are live in the cloud, new risks can emerge that static analysis tools won’t catch—such as misconfigurations introduced manually, runtime drift, or real-world attack activity.

This is where post-deployment security gates come in. These gates rely on runtime monitoring and threat detection tools—such as CNAPP platforms with cloud detection and response (CDR) capabilities—to continuously scan for unexpected behaviors across containers, VMs, serverless workloads, and APIs.

Runtime sensors may flag suspicious behavior—like containers reaching out to untrusted domains, lateral movement between cloud resources, or newly exposed storage buckets.

In this phase, dynamic application security testing (DAST) can also play a role by simulating real-world attacks on running applications to identify flaws that only appear in production.

By integrating runtime signals into the same security context used earlier in the pipeline, teams can respond quickly—while avoiding duplication or blind spots.

5. Preventing Drift and Preserving GitOps

When security teams apply fixes directly in the cloud—without updating the underlying code—they introduce configuration drift. This creates a mismatch between what’s defined in version control and what’s actually running, which breaks GitOps workflows and opens the door to regressions during redeploys.

Code-to-cloud security helps prevent drift by guiding teams to fix misconfigurations at the source: the IaC templates, not just the live infrastructure. By surfacing runtime issues with full code lineage, developers and security teams can collaborate on the root cause and resolve it in the repo—where it belongs.

Fix once, fix right—in the code, not the cloud.

6. Enforcing Policy Everywhere with a Unified Engine

To make this work at scale, security teams need a consistent way to enforce controls across every stage of the SDLC. That’s where a unified policy engine comes in.

Instead of juggling different tools and rule formats, this engine lets you define a policy once—like “no public S3 buckets”—and enforce it:

• In code via IaC scanning

• In CI pipelines through policy-as-code gates

• In production via CSPM monitoring

Whether you're using industry frameworks like CIS Benchmarks or building custom rules, the same policies apply from development to deployment. That means less duplication, fewer blind spots, and stronger alignment between developers, security, and compliance.

Wiz’s approach to code-to-cloud security

Wiz Code is engineered to provide a unified security perspective by leveraging its proprietary Security Graph. This robust feature correlates vulnerabilities identified in the code with cloud misconfigurations and runtime signals. 

By doing so, Wiz Code not only prioritizes remediation based on real-world risk exposure but also supports integrated workflows—enabling IDE integrations, pull request analysis, and seamless CI/CD pipeline incorporation. With capabilities such as secrets scanning, IaC misconfiguration detection, and adaptive guardrails, Wiz Code differentiates itself from traditional, siloed security solutions.

Wiz Code provides features like one-click remediation, real-time vulnerability detection, and the ability to trace risks in cloud environments back to the source code.

Ready to Secure Your Code-to-Cloud Journey?

With Wiz Code, integrate security seamlessly into your developers’ daily workflows—whether in the IDE, pull requests, or CI/CD pipelines. Leverage a unified policy engine that reduces false positives, accelerates remediation, and ensures compliance with industry standards.

Protect your applications from code to cloud with actionable insights, automated fixes, and end-to-end visibility.

Schedule a demo to see how Wiz Code unifies security across code, cloud, and runtime—so developers stay in flow, security teams fix real risks faster, and your business ships secure software with confidence.