What is shift-left testing?
Shift-left security testing completely changes how organizations approach security by moving testing and validation processes to the beginning of the software development lifecycle (SDLC) rather than waiting until deployment day. In other words, it brings security to the left of the development timeline to catch any problems when they’re easiest and cheapest to fix.
The approach contrasts traditional “waterfall” testing, which frequently pushes security to the end of the SDLC—a last hurdle to clear before deployment. The big problem there? Waiting for release day to integrate security often results in delays and vulnerabilities.
Alongside security testing, shift-left performance testing ensures that performance issues are found and addressed early, preventing costly fixes later and improving user experience from the start. Similarly, shift-left observability embeds monitoring and telemetry early in development, providing continuous insights and faster detection of anomalies.
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The Secure Coding Cheat Sheet is designed to be your comprehensive, go-to resource for embedding security into every stage of your code development. It doesn’t just list recommendations; it provides clear, actionable advice and code examples to help you implement the secure practices.
Shift-left vs. shift-right security
Shift-right security emphasizes testing and validation in production environments to uncover runtime issues that only manifest under real-world conditions, such as zero-day exploits or business logic flaws. In cloud-native settings, both shift-left and shift-right security are valuable because the infrastructure is ephemeral, numerous services/identities are in the mix, and sensitive data moves around. An optimal security strategy leverages shift-left testing to avoid known vulnerabilities and shift-right testing to catch those novel threats you haven't seen before.
Shift Left vs Shift Right: Key Differences and Benefits
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Why does shift-left testing matter for cloud security?
Early detection eliminates expenses associated with emergency patches, production downtime, incident response, and potential breach costs. For example, remediating a critical vulnerability in production might require coordinating across multiple teams, rolling back deployments, and conducting forensic analysis—activities that consume 10–100× more engineering hours than fixing the same issue during code review.
Cloud environments bring some unique considerations that make shift-left approaches particularly important:
Infrastructure-as-code (IaC) security: Misconfiguration of cloud resources can be disastrous. Scanning IaC templates before you deploy can stop these issues in their tracks.
Container security: Containers bundle your code and dependencies together, which creates a complex security surface—one that needs to be checked before you deploy.
Serverless function security: Serverless architectures open the door to new attack vectors because they aren’t covered by traditional perimeter security. Shift-left testing closes the gap.
API security: Cloud-native apps depend on APIs, making it essential to test API security early on in development.
The four types of shift-left testing approaches
1. Static application security testing (SAST)
SAST tools analyze application source code, bytecode, or compiled binaries without executing them. They detect insecure coding patterns such as SQL injection vulnerabilities, cross-site scripting (XSS) flaws, and hardcoded credentials. Common SAST tools include SonarQube, Checkmarx, and Semgrep.
2. Dynamic application security testing (DAST)
DAST tests applications externally, simulating attacks to find vulnerabilities that only show up during runtime. Since it doesn’t require access to source code, DAST is good for testing third-party or closed-source components. In the cloud, it’s critical for testing microservice interactions and API security to make sure applications behave securely in real-world conditions.
3. Interactive application security testing (IAST)
IAST works by blending static and dynamic analysis techniques. The upsides? It gives deeper insights and fewer false positives than standalone methods. IAST is particularly useful in cloud-native and microservice-based environments, where static analysis alone might miss complex runtime issues.
4. Software composition analysis (SCA)
SCA tools identify security vulnerabilities, license risks, and outdated components in open-source libraries and third-party dependencies. Because modern applications are often built on large dependency graphs, SCA helps teams catch known CVEs, supply chain risks, and unsafe transitive packages early in development. Common SCA tools include Snyk, Mend, GitHub Dependabot, and Wiz Dependency Analysis.
Shift-left testing in practice
To truly shift left, testing needs to be embedded throughout the development workflow:
Code repository scanning: As the first line of defense, it’s best practice to scan all commits and pull requests in GitHub, GitLab, and Azure DevOps. Immediate feedback prevents vulnerable code from being merged.
CI/CD pipeline integration: Security checks at each build and deployment stage—like dependency scans and container image verification—ensure consistency. As maturity grows, organizations can strengthen these gates by implementing policies-as-code and admission controllers to block deployments that violate security baselines.
Container image scanning: Container image scanning has two key components: Scanners probe base and added components for vulnerabilities and misconfigurations, and they also maintain a registry to block outdated or insecure images.
Kubernetes and Helm Chart scanning: These scans check orchestration configurations for best practices by finding excessive permissions, weak network policies, and misconfigured RBAC settings.
Infrastructure-as-code (IaC) scanning: IaC scanning looks for misconfigurations like exposed storage or weak encryption in Terraform, CloudFormation, or ARM templates before deployment.
Different scanner categories address distinct security concerns in shift-left testing:
| Scanner type | What it analyzes | Example findings | Common tools |
|---|---|---|---|
| Static application security testing (SAST) | Application source code, bytecode | SQL injection, XSS, hardcoded secrets, insecure crypto | SonarQube, Checkmarx, Semgrep |
| IaC scanner | Infrastructure templates (Terraform, CloudFormation, ARM) | Overly permissive security groups, unencrypted storage, missing logging | Checkov, tfsec, Snyk IaC |
| Container scanner | Container images, layers, dependencies | Vulnerable base images, outdated packages, malware | Trivy, Grype, Clair |
| Kubernetes scanner | Cluster manifests, Helm Charts, pod specs | Excessive RBAC, missing pod security standards, weak network policies | Kubesec, Polaris, Datree |
| Dependency scanner | Third-party libraries, packages | Known CVEs in dependencies, license compliance issues | Snyk, Dependabot, OWASP Dependency-Check |
| Secrets scanner | Code repositories, configuration files | Exposed API keys, passwords, certificates | GitGuardian, TruffleHog, detect-secrets |
Want to learn more about protecting your Kubernetes clusters, workloads, and infrastructure? Download our ultimate Kubernetes security guide today.
Implementing shift-left testing in cloud-native environments
Making shift-left testing work in cloud environments requires a thoughtful approach:
Start with pilot repositories: Pick 2–3 apps that have engaged dev teams who will help you refine the process before you go wider.
Establish security baselines: Define security requirements that match the risk level of your apps. Start by addressing the most critical vulnerabilities and gradually get stricter as teams get up to speed.
Integrate with your CI pipelines: When you integrate shift-left testing with your CI workflows, you’ll get immediate feedback on every build. Go for the quick tests first and then add the deeper dives as your pipelines can handle it.
Set up admission controls: Put Kubernetes admission controllers or similar safeguards in place to prevent the deployment of anything that doesn't meet your security standards.
Keep track and improve: Log your security metrics before and after implementation so you can prove the value of shift-left testing to stakeholders. And keep listening to your dev teams about ways you can improve the process.
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Measuring shift-left testing success and ROI
Measuring the success of shift-left testing is all about tracking key numbers like MTTD and MTTR. Here’s what to keep an eye on:
Vulnerability density: How many vulnerabilities are you dealing with per thousand lines of code (before and after shift-left testing implementation)?
Mean time to detect (MTTD): How long does it take you to spot security issues?
Mean time to remediate (MTTR): How long does it take to resolve security issues after you spot them?
Security debt: How many known, unfixed security issues are you dealing with?
Deployment frequency: How often does your code actually get deployed? (This metric makes sure security measures aren’t slowing developers down.)
Common challenges and how to overcome them
Technical challenges and solutions
Tool sprawl
Problem: Multiple security tools create alert fatigue and integration chaos.
Solution: Consolidate and standardize until you have a small set of integrated tools that provide consistent reporting and work seamlessly with CI/CD pipelines.
Long scan times
Problem: Deep scans can slow development pipelines to a crawl.
Solution: Adopt incremental scanning strategies, such as scanning only changed code or using lightweight, fast pre-commit checks, while reserving deep scans for scheduled builds or releases.
False alarms
Problem: Excessive false positives waste time and erode trust.
Solution: Tune scanners to reduce noise, focus on high-confidence issues, and implement a feedback loop where developers can flag false positives to continuously improve detection.
Legacy apps
Problem: Older systems weren’t built for modern testing.
Solution: Use proxy testing, containerization, or gradual modernization strategies to safely incorporate legacy applications into security pipelines without massive rewrites.
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Cultural challenges and solutions
Friction between development and security teams
Problem: Silos mean there can be friction when security becomes part of the development process.
Solution: Foster cross-team collaboration so that security and development teams share responsibility for code quality and risk management.
Skill gaps between teams
Problem: Developers lack security knowledge; security lacks dev context.
Solution: Invest in training, workshops, and pair programming. This way, security engineers can mentor devs on secure coding practices, and devs can explain the application context to security teams.
Resistance to change
Problem: Teams might see new security steps as slowing them down.
Solution: Introduce changes incrementally, celebrate small wins, and demonstrate the tangible benefits of shift-left security.
Speed over security
Problem: When success is only measured by delivery speed, security suffers.
Solution: Update teams' KPIs to include security quality as well as delivery speed.
Shift Left Explained: What It Means to Shift Security Left
Improve development workflows with shift left security by embedding testing early to catch vulnerabilities and speed delivery.
Read moreHow Wiz Code enables comprehensive shift-left testing
Wiz Code embeds security directly into the dev workflow, enabling teams to catch vulnerabilities early and deliver secure applications faster.
From the first line of code to live applications, Wiz provides end-to-end code-to-cloud traceability. This means you can trace a vulnerability from its introduction in source code, through build artifacts and container images, and all the way to running workloads in production. For example, when a critical vulnerability is discovered in a third-party library, Wiz immediately identifies:
Which repositories contain the vulnerable dependency
Which container images were built with it
Which Kubernetes clusters are running those images
Whether affected workloads are internet-exposed
What IAM permissions and data access those workloads have
This traceability enables targeted remediation—you fix the source code, rebuild affected images, and redeploy only the workloads that are actually exploitable, rather than conducting organization-wide emergency patching.
By combining these capabilities, Wiz Code transforms shift-left security from an aspirational goal into a practical, developer-friendly reality—catching risks early, reducing remediation time, and enabling faster and safer software delivery. Ready to see for yourself? Book a Wiz demo today.
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