What is static code analysis?
Static code analysis is an automated tool that scans your application's source code, bytecode, or binary code to identify security vulnerabilities, quality issues, and style errors. In fact, following a 2021 Executive Order on cybersecurity, NIST listed static code scanning as one of its recommended minimum standards for software verification to find top bugs.
Unlike dynamic analysis, which requires the code to be running, static analysis examines the code at rest. This allows it to be performed early and often during development, a practice commonly known as shifting left. The goal is to provide developers with immediate feedback, helping them learn secure coding practices and prevent common mistakes from ever being deployed.
Secure Coding Best Practices [Cheat Sheet]
In this 11 page cheat sheet we'll cover 10+ essential security topics, offering practical steps for areas like API security, input validation, and containerized application protection—ideal for both beginner and advanced users.
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How static code analysis works
Static code analysis tools follow a systematic process to inspect code. While the specifics vary between tools, the general workflow includes these steps:
Code Parsing: The tool first parses the source code to build an intermediate representation, often an Abstract Syntax Tree (AST). This tree models the code's structure, making it easier to analyze.
Analysis Engine: The tool then applies a series of rules and checks to the AST. These rules can detect a wide range of issues, from simple syntax errors to complex security vulnerabilities like SQL injection or cross-site scripting (XSS).
Reporting: Finally, the static code analysis tool generates a report of its findings, highlighting the issue, its location in the code, and often providing recommendations for remediation. Modern tools integrate these reports directly into the developer's IDE or CI/CD pipeline for immediate review.
Catch code risks before you deploy
Learn how Wiz Code scans IaC, containers, and pipelines to stop misconfigurations and vulnerabilities before they hit your cloud.
Benefits of static code analysis
Integrating static code analysis into your development process offers several key advantages:
Early detection of flaws: Find and fix vulnerabilities and bugs during development, when they are cheapest and easiest to resolve.
Improved code quality: Enforce consistent coding standards and best practices across all teams, leading to more readable and maintainable code.
Enhanced security posture: Proactively identify and mitigate common security risks before they can be exploited in production, which is critical in a landscape where malicious actors have exploited more zero-day vulnerabilities in recent years.
Accelerated development: Automate code reviews for common issues, freeing up developers to focus on building features and reducing time spent on manual debugging.
Types of static code analysis
Static analysis tools can be categorized based on the types of issues they are designed to find. Common types include:
Security (SAST): Focuses on identifying security vulnerabilities in the source code, such as those listed in the OWASP Top 10. This includes issues like injection flaws, hardcoded secrets, insecure configurations, and broken access control, which OWASP reported as one of the most common categories of weaknesses in its 2021 analysis.
Linting: Checks for stylistic errors, formatting inconsistencies, and potential programming mistakes that may not break functionality but violate coding standards or best practices. This improves readability, consistency, and collaboration across teams.
Quality and Complexity: Measures code complexity through metrics such as cyclomatic complexity or nesting depth, identifies duplicate or dead code, and flags overly complex functions that may be difficult to maintain, test, or scale over time.
Static vs dynamic code analysis
Static and dynamic code analysis (DAST) are two complementary approaches to application security testing. The primary difference lies in how they inspect the code.
Static Analysis (SAST) examines the code from the inside out, without executing it. It's like proofreading a document for errors. It excels at finding flaws in the source code itself, such as insecure coding patterns or vulnerable dependencies.
Dynamic Analysis (DAST) tests the application from the outside in, while it is running. It simulates attacks against a live application to find vulnerabilities that only appear at runtime, such as server configuration issues or authentication problems.
A comprehensive security strategy uses both SAST and DAST to cover risks across the entire application lifecycle. Government cybersecurity agencies like CISA recommend using both static and dynamic application security testing (SAST/DAST) to analyze source code and application behavior to detect error-prone practices.
| Feature | Static Code Analysis | Dynamic Code Analysis |
|---|---|---|
| Execution required? | No | Yes |
| Detects security vulnerabilities? | Yes | Yes |
| Identifies runtime issues? | No | Yes |
| Integrates with CI/CD? | Yes | Sometimes |
| Performance overhead | Minimal | High |
Common coding issues detected by static analysis tools
Static analysis tools can pinpoint a wide range of issues, including:
SQL injection risks: Static analysis solutions look for insecure database query problems that attackers may exploit to modify data. The system identifies unsafe user input concatenation, helping you prevent vulnerabilities from becoming exploitable before deployment.
Hardcoded secrets: By flagging API keys, credentials, and passwords stored directly in source code, static analysis tools protect sensitive information from accidental exposure. Remember: Hardcoded secrets can lead to unauthorized access if exposed in public repositories or logs.
Undefined behavior: Logical inconsistencies and syntax errors can lead to unpredictable application behavior. Static analysis tools ensure that software remains reliable under diverse conditions by detecting undefined states.
Memory leaks (in languages like C/C++): Static analysis tools identify improper memory allocation and deallocation practices, reducing resource exhaustion risks. Detecting leaks early helps prevent application crashes and degraded performance over time.
Compliance violations: Static analysis tools help enforce secure coding practices aligned with industry standards like OWASP Top 10 (which outlines common application security risks) and regulatory requirements such as PCI DSS and ISO 27001, which mandate secure software development practices.
AI/ML model analysis: Static analysis tools are evolving to support AI/ML applications by detecting security flaws in AI model implementations, such as hardcoded credentials in model pipelines, improper input sanitization, and insecure API exposure. However, AI security also requires other testing methods to detect adversarial attacks, data poisoning, and model inference threats, which static analysis alone cannot identify.
Infrastructure as code (IaC) security helps identify misconfigurations in the cloud in Terraform, Kubernetes, and AWS CloudFormation templates, such as overly permissive IAM roles, insecure network policies, and unencrypted storage. Unlike traditional static analysis, IaC security scanning prioritizes misconfiguration detection to prevent cloud security breaches.
State of Code Security
SAST helps detect vulnerabilities in code, but secrets detection and repository security remain major blind spots. The State of Code Security Report 2025 found that 80% of GitHub workflows have insecure default permissions.
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Tools and techniques used in static code analysis
There are tons of tools out there for various programming languages, like Java, Python, and JavaScript. They work across different environments, such as IDEs and CI/CD pipelines, to help catch bugs and improve code quality before they become issues.
Top static code analysis solutions
SonarQube supports many programming languages and conducts rule-based code evaluation.
ESLint is a popular tool that performs JavaScript and TypeScript linting operations.
Pylint enforces Python code standards and detects errors.
Checkmarx is a specialized tool used in security-focused static analysis.
When choosing a static analysis tool, organizations should weigh the trade-offs between open-source and commercial solutions:
Open-source tools are cost-effective, highly customizable, and community-supported but may lack enterprise-grade features like compliance reporting and advanced rules.
Commercial solutions offer more comprehensive security scanning, vulnerability management, and enterprise integrations, at the cost of licensing fees and potential vendor lock-in.
For security-focused development, a hybrid approach—using open-source tools for code linting and a commercial SAST tool for security assessments—often provides the best balance.
Techniques used in static code analysis
Types of analysis
Rule-based analysis: Detects violations of predefined coding standards
Data flow analysis: Tracks data movement within an application to detect security vulnerabilities
Pattern matching: Identifies known bad practices using regex or predefined rules
Lexical analysis: Analyzes the code structure to enforce proper programming standards and best practices
CI/CD integration
Static analysis presents unique challenges in cloud-native environments, where fast-changing, ephemeral workloads and microservices architectures complicate traditional security assessments. Frequent code updates, distributed components, and dynamically loaded dependencies make it difficult to maintain a strong code security posture.
The solution? Embedding static analysis directly into CI/CD pipelines—but with a critical caveat: scans must be fast and minimally disruptive. Developers expect rapid iteration cycles, and if security scans slow down builds or overwhelm them with false positives, they’ll simply disable or bypass them. To be effective, static analysis in CI/CD should:
Run in seconds, not minutes – Ensuring developers aren’t waiting for security results before merging code.
Fully embedded – Appearing in CI job logs, providing all the necessary details on findings, without requiring context switching.
Support cross-file taint analysis – As modern software development increasingly relies on modular code, microservices, and external dependencies, security scanners must track data flows across multiple files, services, and repositories to detect vulnerabilities that span beyond a single function or file.
Ongoing monitoring is also key. By continuously analyzing code with every commit and merge, static analysis tools can catch vulnerabilities early while maintaining compliance and software quality—without frustrating developers. The best solutions strike a balance: strong security guardrails that don’t slow teams down.
Key features to look for in a static code analysis tool
When selecting a static code analysis tool, consider the following key features:
CI/CD integration: The tool should connect directly with your existing CI/CD pipelines, IDEs, and development workflows without disrupting productivity.
Real-time feedback: Look for tools that provide instant analysis and reporting. Immediate feedback helps developers catch and fix issues as they write code, preventing security flaws from reaching production.
Custom rules and scalability: Ensure you can create custom security rules and extend functionality as your projects grow. This flexibility supports both immediate needs and long-term organizational scaling.
Wiz Code
Static analysis is crucial for catching security flaws early, but traditional SAST tools often flood teams with unactionable findings. Wiz Code changes that. Instead of just detecting issues, it ingests findings from third-party SAST tools and enriches them with real-world risk context—exposure, reachability, and exploitability—so teams can prioritize what truly matters.
How Wiz Code makes SAST smarter:
Risk-Based Prioritization – Maps vulnerabilities to cloud resources, runtime configurations, and permissions.
Seamless Integration – Ingests findings from leading SAST tools and delivers enriched insights into IDEs, CI/CD, and security dashboards.
Cloud-Aware Security – Correlates code risks with real-world attack paths for meaningful remediation.
By linking static analysis to cloud posture and runtime context, Wiz Code ensures vulnerabilities aren’t just detected—they’re understood in context and addressed efficiently.
Simply put, Wiz Code makes static code analysis easy. Want to see for yourself? Schedule a demo today.
