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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchSecurity as code means managing infrastructure, security policies, delivery checks, and monitoring configurations as versioned code—and validating changes before they reach production. It gives teams repeatable controls and a reviewable record of changes, but it does not guarantee a secure workload or compliance. The approach works when automated checks are paired with accountable review, disciplined access, and monitoring after deployment.
What security as code includes
Security as code is broader than scanning application source code or checking infrastructure templates for mistakes. For cloud-native systems, NIST Special Publication 800-204C (March 2022) describes five related kinds of code:
| Code type | What it manages |
|---|---|
| Application code | The software’s functionality and behavior. |
| Application-services code | Services and components the application uses, such as managed platform capabilities. |
| Infrastructure as code | Provisioning and configuration of compute, networking, and storage. |
| Policy as code | Declarative rules for how systems should behave at runtime, including policies aligned with zero-trust principles. |
| Observability as code | Configurations used to monitor runtime state and surface operational or security signals. |
These categories connect software delivery with the controls around it: identity and access, build and deployment workflows, software artifacts, policy enforcement, and operational feedback. A secure infrastructure-as-code practice is therefore one part of a broader security-as-code operating model.
How security as code fits a cloud delivery workflow
The practical goal is to express intended system state and security rules in managed code, validate changes before deployment, and check the deployed system continuously. The National Security Agency’s March 2024 information sheet, Enforce Secure Automated Deployment Practices through Infrastructure as Code, describes IaC templates as a way to automate compute, network, storage, and security-policy deployment. Templates may be human-readable and vendor-specific or vendor-agnostic, and can be used in cloud or on-premises environments.
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- Define desired state. Describe infrastructure and security requirements in reviewed templates and policy definitions. Keep these changes in version control so reviewers can see who changed what and when.
- Review and validate before deployment. Add security and policy checks to the CI/CD workflow. For example, validate that proposed resources meet required configuration rules, and block a deployment when a required condition fails. The NSA describes combining IaC with policy as code to vet resources before deployment.
- Secure the delivery path. Apply controls throughout build, test, package, deploy, and operations—not only to infrastructure files. NIST SP 800-204C describes these CI/CD stages; NIST SP 800-204D (February 2024) focuses on integrating software supply-chain security measures into CI/CD.
- Keep decision evidence. Record validation results and the approval or release decision in a form that can be reviewed later. An AWS Security Blog example published May 19, 2026 uses Open Policy Agent (OPA) to validate AWS infrastructure changes before deployment and retains validation artifacts for release decisions and audit review.
- Monitor what runs. After deployment, compare runtime conditions with intended policy, monitor for vulnerabilities and unexpected changes, and feed findings back into development and operations. NIST’s NCCoE DevSecOps project describes continuous monitoring, vulnerability management, and feedback as parts of the lifecycle.
Microsoft Azure architecture guidance recommends deploying infrastructure changes through code and CI/CD pipelines, and favors declarative approaches in which files state the desired final condition. This is Microsoft’s guidance for its architecture context, not proof that one implementation style or tool is right for every environment.
Which controls matter when implementing it
Choose controls by the risk they address and the point in the delivery lifecycle where they operate. A tool that flags an issue before deployment is not equivalent to one that detects a problem in a running service.
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- Preventive checks: Decide which policy violations should block a release and which should create an advisory finding for review. Document who can approve exceptions and how those exceptions expire or are revisited.
- Identity and access: Limit who can change templates, policies, pipeline configuration, and production resources. NIST’s DevSecOps practices discuss least privilege and zero-trust verification; automation should not become a route around those controls.
- Artifact and supply-chain controls: Include checks for build and release artifacts as well as infrastructure configuration. NIST SP 800-204D addresses supply-chain measures in CI/CD, making this part of the same security story rather than a separate concern.
- Runtime coverage: Define what deployed systems must report and how teams respond to policy drift, vulnerabilities, and other findings. Pre-deployment validation cannot establish that a workload remains safe after release.
- Audit evidence: Preserve change history, validation output, approvals, and exception records according to the organization’s governance needs. A useful record should help explain both what was deployed and why it was allowed.
When organizations need machine-readable control definitions, NIST’s Open Security Controls Assessment Language (OSCAL) offers XML, JSON, and YAML formats for control-related information, including baselines, assessment, and monitoring. NIST also describes translating policy requirements into standardized OSCAL to operationalize policy as code. OSCAL can help standardize control information; adopting it alone does not implement a complete compliance program.
How to choose an implementation approach
There is no single platform comparison established by the guidance cited here. Before selecting tools or designing a platform, assess the actual coverage and operating model against these questions:
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- Does it check proposed changes before deployment, monitor runtime state, or do both?
- Which infrastructure languages, cloud environments, and on-premises systems does it support?
- Can it enforce a rule by blocking a release, or does it only report findings?
- How are identities, permissions, and secrets handled across source control, CI/CD, and deployed workloads?
- Who reviews exceptions, what evidence is retained, and how can later reviewers reconstruct a release decision?
- Do checks cover software supply-chain artifacts in addition to infrastructure configuration?
These questions help expose gaps that a feature checklist can hide. For example, a strong template scanner may have limited value if its findings are advisory when the risk requires enforcement, or if there is no monitoring after deployment.
Risks and limitations to plan for
A reusable mistake can spread
IaC makes repeated deployments more consistent, but consistency also means a flawed template or policy can reproduce the same weakness across environments. The NSA’s guidance supports pre-deployment vetting and notes the risk of human error in manual deployment; the practical implication is that templates and rules themselves need review, testing, and maintenance.
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Passing checks does not prove security
Automated checks only evaluate the rules and scope they have been given. They may miss vulnerabilities, unsafe interactions, or conditions that emerge at runtime. AWS’s 2026 OPA example is explicitly focused on pre-deployment validation; it does not replace runtime monitoring or post-deployment controls.
Dynamic systems still need people and governance
NIST’s NCCoE DevSecOps project describes vulnerability identification as challenging in dynamic environments involving many tools, automations, ecosystems, and services. Teams still need people to assess risk, investigate findings, maintain policy, control access, and decide how exceptions are handled. A passing automated test is evidence that specified checks passed—not a blanket assurance that the workload is secure or compliant.
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- Choose a bounded service or deployment path. Map how its source, infrastructure, pipeline, identities, artifacts, and runtime monitoring connect.
- Write down the intended controls. Convert a small set of clear security requirements into versioned policy and configuration checks, with an owner for each rule.
- Set enforcement and exception rules. Decide which failures stop deployment, who may authorize an exception, and what record that decision requires.
- Close the runtime loop. Identify the monitoring signals and vulnerability-management process that will detect issues the pre-deployment checks cannot.
- Review evidence and gaps. Use release records and runtime findings to refine controls, then expand to more services when the workflow is understood.
Official guidance describes repeatability, versioned change history, earlier detection, and policy enforcement as benefits of these practices. It does not establish a quantified reduction in breaches or show that automation guarantees compliance. Measure outcomes in the context of your own systems rather than treating adoption itself as proof of improved security.
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