Spotting security vulnerabilities in your code as early as possible is crucial, and Static Application Security Testing (SAST) plays a big role in that. Choosing between all the tools out there can be overwhelming, but understanding what makes the best SAST tools stand out will help you protect your applications more efficiently. This guide will walk you through what SAST is, why it matters, and how to pick the right solution for your team.
Understanding Static Analysis
Static analysis is basically the process of looking at your code—whether it’s source code, bytecode, or binary—without running the application. The goal is to find vulnerabilities, bugs, or risky coding patterns that could cause trouble later, just by analyzing the structure and logical flow of the code.
It’s like an automated code review, but fully focused on security and code quality. The tool goes through everything, line by line, trying to predict where the code might break or open up a security hole.
How does this work in practice?
Typically, a SAST tool follows a process that looks something like this:
Reads and interprets the code:
First, it parses the code and transforms it into something it can analyze more easily, like an Abstract Syntax Tree (AST). Think of it as a map showing how each part of the code connects.
Runs a bunch of rules on top:
Then, it checks the code against a set of known rules. This can range from simple stuff like:
“Is this code using a function with a known history of security issues?”
To more specific checks like:
“Is there a hardcoded password here?”
Analyzes how data flows through the code (Data Flow):
More advanced tools track how information enters, moves through, and exits the application. For example:
“Is this user input going straight to a database without any validation?”
“Is there a variable receiving external data and then being used in an HTTP response without sanitization?”
Builds the code’s execution flow:
Some tools also create a graph showing how the code could execute in different scenarios, to catch issues that depend on execution paths.
What kind of issues can Static Analysis catch?
- SQL Injection
- Cross-Site Scripting (XSS)
- Hardcoded secrets (like passwords or tokens)
- Path Traversal
- Buffer Overflow (in languages like C/C++)
- OS command injection
All of this happens without running the code. The focus is to catch problems directly from the source code, before running any tests or builds.
And what can’t SAST catch?
It won’t catch issues that only appear when the system is running, like environment misconfigurations or bugs that depend on external service integrations. That’s why SAST is usually just one piece of your overall security strategy. The ideal approach is to combine it with other practices like DAST or even manual security testing, depending on your team’s maturity level.
Benefits of Using SAST Early in the Process
Now that you know how SAST works under the hood, let’s talk about where it really makes a difference in your team’s day-to-day: catching issues as early as possible in the development cycle.
Integrating SAST in the early stages of development—the well-known shifting left—is one of the most effective ways to prevent vulnerabilities from reaching production. The sooner a problem shows up for a developer, the faster and cheaper it is to fix.
When the tool runs directly in the IDE or during the commit process, feedback comes almost in real time. The code is still fresh in the dev’s head, the context is recent, and fixing it becomes just another natural step in development, like resolving a lint error. This helps avoid that classic situation where a problem only gets discovered during QA—or worse, after an incident in production.
Beyond avoiding rework, early SAST also has another big upside: it teaches the team about secure coding practices on the fly. Every time a dev gets a suggestion or vulnerability alert, they learn, in practice, what to avoid in the next piece of code they write.
Over time, this builds a stronger security culture within the team. The number of new vulnerabilities tends to drop sprint after sprint because people start internalizing good practices.
Another important point is preventing the buildup of security technical debt. If the team only finds vulnerabilities after the code is already consolidated and deployed, the cost of fixing them skyrockets. Often, the fix turns into a big and risky refactor.
By integrating SAST from the start, your team gets:
- Faster fixes
- Less rework
- Less technical debt
- Faster delivery without compromising security
- Developers who are more aware of code security
Best SAST Tools: Overview and Comparison
There are a lot of tools out there, each with its strengths and weaknesses. Here’s a quick overview of some of the most popular ones:
Kodus
Kodus was built with a strong focus on developer experience, combining speed, accuracy, and seamless integration with modern development workflows. It’s not just another generic SAST tool—Kodus acts like a senior reviewer on your team.
Technical approach:
Kodus combines AST-based analysis with artificial intelligence (using models like GPT-4o, Gemini, and Claude) to deliver contextual, straightforward, and low-noise feedback. On top of that, the platform’s agent, Kody, learns from your team’s pull request history, enabling only the rules that make sense for your context and filtering out unnecessary suggestions.
Another highlight is that your team can create custom rules in natural language. Before any new rule starts running, the team gets the chance to review and approve it.
Pros:
- Fast scan times, suitable for CI/CD and even pre-commit hooks
- Low false positive rate thanks to alignment with the team’s coding style
- Direct feedback in PRs, with a human-like tone and clear explanations
- Native integration with GitHub, GitLab, Bitbucket, and Azure DevOps
- Support for multiple modern languages (with a growing focus on cloud-native stacks)
- Deployment options: SaaS, self-hosted, and even an open-source version
Cons:
Still a small community, but strong commercial support
SonarQube
One of the most well-known and widely used tools, with both open-source and commercial versions.
Technical approach:
Analyzes source code using a mix of rules, AST, and symbolic execution (for some languages). Detects bugs, code smells, and vulnerabilities.
Pros:
- Broad language support
- Combines security analysis with overall code quality checks
- Good documentation and active community
- Strong CI/CD and issue tracker integrations
- Has a “Security Hotspots” feature that prompts devs for manual review of sensitive areas
Cons:
- Can be heavy for large projects
- Free version has limited security features
- Needs fine-tuning to reduce false positives
Snyk Code
Fully dev-focused, with super-fast scanning and great UX.
Technical approach:
Combines logic with machine learning to analyze code and apply security rules. Prioritizes speed and fits directly into the developer workflow.
Pros:
- Almost real-time feedback
- Native integrations with IDEs, version control, and CI/CD
- Practical remediation examples in suggestions
- Part of the larger Snyk platform (open source, containers, IaC, etc.)
- Good support for modern languages
Cons:
In very complex scenarios, it may lack the depth of some more traditional tools
Some advanced policy features are still evolving
Checkmarx
Well established in the enterprise market.
Technical approach:
Creates a logical representation of the code and applies predefined queries (CxQuery). Supports incremental scanning and doesn’t require a full build environment.
Pros:
- Wide language support, including older ones
- High customization with user-created queries
- Good detection of complex data flows
- Detailed reports
- Strong compliance support
Cons:
- High cost
- Installation and maintenance can be complex
- Scans can take time, depending on project size
GitHub Advanced Security (CodeQL)
The engine behind GitHub’s code scanning.
Technical approach:
Builds a relational database from the code, allowing semantic queries to find vulnerabilities. Uses its own query language, CodeQL.
Pros:
- Deep semantic analysis
- Highly customizable
- Native GitHub integration
- Strong community around QL
- Free for public repos
Cons:
- Requires GitHub Enterprise for private repos
- Steep learning curve for writing custom queries
- Initial database build can be slow
- Integrating with non-GitHub version control or CI systems isn’t as straightforward
Conclusion
At the end of the day, adding SAST to your development process is more about prevention than just following a checklist. It’s the kind of thing that saves you from big headaches down the road.
Understanding how static analysis works, starting at the right stages of development, and picking a tool that fits your team’s context already solves a big part of the problem.
You don’t need to get everything perfect on day one. The important thing is to start, adjust as you go, and make SAST a natural part of your workflow. The more your team uses it, the easier it gets to catch and fix vulnerabilities before they turn into production issues.
