What is SAST?

Static application security testing (SAST) is a method for analyzing source code, bytecode, or binaries to identify security vulnerabilities before software runs. Unlike dynamic testing, which examines applications during execution, SAST works early in the software development lifecycle (SDLC), typically during the coding or build stages. Integrating SAST into these early phases helps catch issues before they become costly or complex.

SAST scans code without executing it, making it ideal for detecting flaws such as injection risks, insecure dependencies, and logic errors. Industry standards such as the Open Worldwide Application Security Project (OWASP) recommend incorporating SAST as part of a secure development strategy. In GitHub, SAST capabilities integrate directly into developer workflows, enabling teams to review findings alongside code changes.

Why SAST matters

SAST plays a role in ensuring software is built securely. It’s valuable because it proactively detects vulnerabilities, helping development teams build more secure and robust code from the start. Taking this proactive approach has cost benefits, too—it’s far less expensive to fix flaws during coding than it is to fix them after deployment, which would involve emergency patches, downtime, and additional testing. Early detection prevents data breaches, reputational damage, and costly remediation.

SAST tools align with proactive risk management strategies such as:

• “Shift-left” practices, which move security closer to the beginning of the SDLC.

• DevSecOps, where security is integrated into continuous delivery.

How SAST works

SAST tools perform scans automatically, bringing issues to light without interrupting developer workflows. They’re designed to scan the entire codebase, providing detailed feedback on coding errors and insecure practices to fix before deployment. Here are some more details about how SAST tools operate:

Source code analysis

SAST tools evaluate and find vulnerabilities in source code, bytecode, or compiled binaries. Because they work statically, they interoperate well with integrated development environments (IDEs) and CI/CD pipelines.

Data flow and control flow

SAST tools analyze data flow to track how information moves through the application and control flow to examine the order in which instructions execute. When combined with semantic analysis, which interprets the meaning of code rather than just its structure, these processes help developers spend less time chasing false positives.

Vulnerability detection

Common vulnerabilities that SAST can detect include SQL injection (SQLi), cross-site scripting (XSS), and buffer overflows. SAST tools are designed to minimize both false positive and false negative findings. Whereas false positives occur when a tool incorrectly flags a non-issue, false negatives occur when a real vulnerability goes undetected.

GitHub Code Scanning uses semantic analysis and customizable rules to reduce false positives, helping teams focus on real risks.

SAST vs. DAST

SAST and dynamic application security testing (DAST) are two distinct methods used in application security testing, each with its own strengths and weaknesses.

Key differences

The core difference between SAST and DAST lies in their approach. SAST analyzes an application’s source code, bytecode, or binaries for vulnerabilities, while DAST tests the application in its running state to identify potential exploits.

Following is a summary of some of the key differences between the two kinds of testing:

When to use each

SAST is typically used early in the SDLC, allowing developers to catch issues before code is executed. DAST, on the other hand, is often used after an application has been deployed to identify runtime vulnerabilities.

While SAST provides a deep understanding of the application and can identify issues early, it may not catch runtime vulnerabilities or configuration errors. DAST can identify these issues but may not provide as much insight into their root cause.

Both approaches serve different purposes and work best together. Using both creates a layered defense, helping development teams catch issues before deployment and confirming that the application will be resilient in real-world conditions.

The importance of SAST for security

SAST tools are critical in ensuring application security (AppSec). They serve as a proactive measure to identify and rectify vulnerabilities such as the OWASP Top Ten.

The impact of SAST on mitigating cyberthreats and preventing organizational breaches is significant. By identifying potential security flaws before the application is deployed, SAST reduces the risk of exploitation and the potential damage that could result from a security breach.

SAST aligns with “shift-left” methodology, considered a software development best practice. This involves integrating security measures as early as possible in the SDLC, an approach that allows developers to address security issues as they arise before deployment.

By minimizing security risks early on, SAST not only helps enhance AppSec but can also help save time and resources that would otherwise be spent on addressing security issues post-deployment.

Key features of SAST tools

Here’s a breakdown of the functionality of SAST tools.

Limitations of SAST tools

SAST tools struggle with certain vulnerabilities, such as authentication problems and access control issues. They may miss configuration-related security risks as well as vulnerabilities in code that can’t be compiled. Dynamically generated code, for example, poses challenges for SAST analysis.

SAST tools are just one piece of the security puzzle. Combining them with other testing methods, such as DAST, better secures software applications.

Benefits of SAST

SAST offers development teams many advantages, including:

• Early scanning: SAST works solely on source code, checking it against best practices. This means SAST can be applied while writing your code.

• No test cases or app execution required: An SAST tool will simply apply all its rules to your codebase. These rules can be manually implemented by the SAST tool creator or a community. Because the SAST scan works before the application runs, it’s typically quicker than other application testing suites.

• Improved security and code quality: SAST helps improve the security posture of software applications and enhances code quality.

• Scalability and integration: SAST can be easily integrated into the development process and can scale with the project as it grows. This makes it a cost-effective solution for both small and large projects.

Challenges of SAST

Despite the many benefits of SAST tools, there are gaps in their capabilities, and they can sometimes create obstacles. These include:

• False positives: SAST tools often generate a high volume of false positives, which can lead to unnecessary work and confusion.

• Limited runtime visibility: SAST tools have a limited scope and can’t detect runtime vulnerabilities.

• Language/tool fragmentation

  If you use multiple programming languages and frameworks, more than one tool is probably needed.

• Need for security expertise: Interpreting the results of an SAST tool requires a certain level of security expertise.

• Time-consuming for large applications: Checking the code of large applications can sometimes be slower.

Best practices for SAST

SAST is a crucial part of the SDLC, and the challenges of using it can often be overcome using best practices, including:

• Code reviews: Regular code reviews can help identify and fix vulnerabilities early in the development process. They also help reduce false positives by understanding the context of the code.

• Automated remediation: Once vulnerabilities are identified, immediate remediation is essential. Some SAST tools support automated remediation processes so developers can spend less time fixing code and retesting.

• Team collaboration: Security is a team effort. Encourage collaboration between developers, security teams, and operations to ensure everyone understands and follows security best practices.

• Continuous integration and monitoring: Regularly monitor the codebase for new vulnerabilities as changes are continuously integrated. This helps to fortify the security posture of the application.

• An established SAST process: This includes when to perform an SAST test, how to handle the results, and who is responsible for remediation.

• Reducing vulnerabilities over time: Aim to reduce the number of vulnerabilities through applied learning. This can be achieved through continuous improvement of coding practices and regular training sessions.

By following these best practices, the challenges of SAST can be effectively managed, leading to the development of more secure applications.

Emerging trends in SAST

As we look towards the future, several trends are set to shape the evolution of SAST. Here are some key points:

AI and machine learning in SAST

The latest SAST security tools use AI and machine learning algorithms to improve the accuracy and speed of vulnerability detection. These technologies help identify complex patterns in code and reduce false positives by learning from historical data. AI assists developers by providing context for vulnerabilities within the workspace, suggesting fixes, and helping to prioritize issues.

Real-time feedback in IDEs and CI/CD

Instant alerts directly within IDE and CI/CD pipelines have become the standard expectation for SAST tools. This immediate visibility allows developers to address issues without leaving their workflow, reinforcing “shift-left” security practices.

Automated capabilities

Modern SAST tools offer autofix and auto-remediation capabilities, further easing the burden on developers. Autofix generates secure code suggestions for common vulnerabilities, whereas auto-remediation applies fixes in certain cases. While these features accelerate resolution, they still require developer review to ensure changes align with project requirements and coding standards.

New tools and technologies

The SAST landscape continues to evolve with platforms that combine static analysis, dependency scanning, and policy enforcement. Continuous advancements in technology will lead to the development of new tools that can better detect and manage security vulnerabilities in code.

The future of SAST is promising, with advancements in AI and other technologies paving the way for more secure and efficient software development. For more insights, explore related content in the GitHub Advanced Security demo, including information about code scanning capabilities to enhance your coding experience and security practices. Also, you can learn more about securing code without disrupting innovation by reading this code security e-book.