What Is Static Application Security Testing (SAST)? | Palo Alto Networks

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Static application security testing (SAST) is a highly automated, white-box testing method that analyzes source code, bytecode or binary code of an application during the early stages of the software development lifecycle (SDLC). By preemptively identifying and flagging vulnerabilities for remediation, SAST improves the security posture of software applications, making it a vital component in secure software development.

Video 1: Understanding the OWASP Top 10 and fixing common AppSec errors

Static Application Security Testing (SAST) Explained 

SAST stands for static application security testing, a type of software testing methodology that analyzes source code or compiled versions of applications to identify injection flaws, cross-site scripting (XSS), insecure data handling and other pervasive security weaknesses outlined in the OWASP Top 10 and SANS Top 25. 

Considered a white-box testing technique, SAST operates without executing the application. Instead, it relies on static code analysis techniques, such as data flow analysis, control flow analysis and syntactic pattern matching. 

SAST tools typically integrate with integrated development environments (IDEs), version control systems, and continuous integration/continuous deployment (CI/CD) pipelines to provide early and continuous feedback on potential security issues. This enables developers to remediate vulnerabilities before they become part of the compiled or packaged application. 

By using sophisticated code analysis techniques, SAST tools can effectively and efficiently assess large codebases, identify potential security vulnerabilities and provide developers with actionable insights to improve the security posture of their applications.

How SAST Works

At its core, SAST examines an application's source code, bytecode or binary code in search of security weaknesses. SAST can identify a variety of vulnerabilities, including SQL injections, buffer overflows and XSS. By flagging these potential threats early in the SDLC, static application security testing helps developers remediate issues to enhance the security of the application — before deployment.

SAST works by scanning an application's source code to identify coding patterns that could lead to potential vulnerabilities. It systematically checks the code against a set of predefined rules or conditions that pertain to secure coding practices. On detection of a potential weakness, it flags the area in the code where it found the issue, giving developers the opportunity to remedy it before deployment. 

Steps in the SAST process include:

Step 1: Code Parsing

SAST tools begin by parsing the source code, byte code or binary code to create an Abstract Syntax Tree (AST). The AST represents the code's structure and its various components, such as functions, loops, conditional statements and variables.

Step 2: Control and Data Flow Analysis

The SAST tool performs control flow analysis and data flow analysis to understand the application's behavior. Control flow analysis identifies the execution paths through the code, while data flow analysis tracks how data moves between variables, functions and other code components. This helps in identifying insecure data handling, such as SQL injections or XSS vulnerabilities.

Step 3: Security Rules and Policies

SAST tools contain a set of predefined security rules and policies that are used to analyze the code for potential vulnerabilities. These rules are based on industry standards, known vulnerabilities and security standards like OWASP Top Ten or CWE/SANS Top 25.

Step 4: Pattern Matching and Semantic Analysis

The SAST tool applies pattern matching and semantic analysis techniques to identify code components that match the predefined security rules and policies. This process helps detect insecure coding practices, such as weak encryption algorithms, hard-coded passwords or the use of vulnerable libraries.

The SAST Cycle

Static application security testing can be considered an ongoing cyclical process, particularly when integrated into the SDLC as part of a continuous integration and continuous deployment (CI/CD) pipeline. By incorporating SAST in development, DevOps teams can proactively identify and remediate security vulnerabilities throughout the build process.

  • Code Development: Developers write and commit source code, implementing new features or fixing bugs in the application.
  • Integration with CI/CD: When code is committed to the version control system (e.g., Git), the CI/CD pipeline is triggered, which automates the build, testing and deployment process.
  • SAST Execution: As part of the pipeline, and based on predefined rules and policies, SAST tools analyze the source code, byte code or binary code for potential security vulnerabilities.
  • Vulnerability Reporting: The SAST tool generates a report with detailed information about detected vulnerabilities, their severity and suggested remediation steps.
  • Remediation: Developers review the report and address identified vulnerabilities, making necessary changes to the source code to eliminate the issues.
  • Retesting: The updated code is committed to the version control system, and the CI/CD pipeline is triggered again, repeating the cycle of SAST analysis, reporting and remediation.

This cyclical process helps to identify and resolve security vulnerabilities throughout development. By integrating SAST as part of a continuous testing strategy, organizations maintain a high level of security and minimize the cost and effort associated with fixing vulnerabilities at later stages of development.

Why Is SAST Important?

In an age where data breaches can significantly impact an organization's reputation and bottom line, early detection and remediation of vulnerabilities are essential. By detecting code-level vulnerabilities such as buffer overflows, injection flaws and insecure library calls, SAST plays a critical role in enhancing the security posture of an application. 

Facilitating the early detection of these vulnerabilities, SAST not only enhances the overall security posture of the application but also eliminates the need for costly and time-consuming patches after the software has been deployed. When used alongside other security practices like dynamic analysis application security testing (DAST) and in the context of a DevSecOps culture, SAST contributes significantly to building secure, robust applications.

Role of SAST in DevSecOps

With its focus on detecting vulnerabilities early in the SDLC, static application security testing aligns well with the DevSecOps ethos of shifting left. By identifying potential security issues in the codebase, SAST  encourages the development of secure code and contributes to robust application security. SAST also helps maintain the speed of DevOps practices without compromising security, reinforcing its contribution to an effective DevSecOps program.

SAST and Compliance

SAST not only improves code quality but also aids in meeting various compliance requirements. Regulations such as the Payment Card Industry Data Security Standard (PCI DSS) and the General Data Protection Regulation (GDPR) mandate preemptive measures to ensure data security. These mandate measures include identifying and addressing software vulnerabilities.

Running SAST as part of the SDLC demonstrates due diligence in these respects. It can provide reports needed for compliance audits, illustrating an organization’s commitment to securing software against potential breaches.

Video 2: How your organization can partner security teams with developers to embed security into every stage of the software development lifecycle.

SAST Vs. DAST

In contrast to SAST as a white-box method of application security testing, dynamic application security testing (DAST) is a black-box testing technique that examines an application in a simulated runtime state to find vulnerabilities an attacker could exploit.

To differentiate these testing methods, think of SAST as the insider or developer's approach and DAST as the outsider or hacker’s approach. With SAST, the developer has full knowledge of the application’s internal structure, logic and implementation details. With DAST, the tester has no knowledge of what’s inside the black box.

SAST and DAST At-a-Glance

Testing Approach:

  • SAST: Analyzes source code, byte code or binary code without executing the application, focusing on its internal structure and logic.
  • DAST: Tests the application while it's running, simulating actual attacks to identify security vulnerabilities in a live environment.

Visibility:

  • SAST: White-box testing, from the inside out, with full access to the source code or compiled code, which enables a deeper understanding of the application's internal workings.
  • DAST: Black-box testing, from the outside in, treating the application as a black box with no knowledge of its internal implementation, focusing on its exposed interfaces and behavior.

Vulnerability Detection:

  • SAST: Identifies potential vulnerabilities by analyzing code for insecure coding practices, weak algorithms] or the use of vulnerable libraries.
  • DAST: Discovers vulnerabilities by probing the application's exposed interfaces, such as webpages or APIs, for weaknesses attackers can exploit.

Integration with SDLC:

  • SAST: Can be integrated early in the software development lifecycle, enabling developers to identify and fix vulnerabilities before deploying the application.
  • DAST: Typically performed during late stages of the SDLC, often after deploying the application to a testing or staging environment.

Speed and Scalability:

  • SAST: Can be time-consuming, especially for large codebases, as it needs to thoroughly analyze the entire codebase.
  • DAST: Can be faster, as it tests the running application and focuses on specific exposed interfaces, but may require more resources to simulate valid attack scenarios.

Accuracy:

  • SAST: May produce false positives or false negatives due to the static nature of the analysis, which may not always consider the full context of runtime behavior.
  • DAST: Tends to have fewer false positives, as it tests the application in a running state within close-to-authentic conditions.

Types of Vulnerabilities Detected:

  • SAST: Effective at detecting issues like SQL injections, buffer overflows, cross-site scripting, and insecure use of cryptography.
  • DAST: Better at identifying vulnerabilities like server misconfigurations, security issues in third-party components and runtime vulnerabilities not visible in the source code.

SAST and DAST offer complementary approaches to application security testing, each with strengths and weaknesses. Using them together as part of a comprehensive security testing strategy allows organizations to catch and remediate issues during development — and to identify issues that surface only when the application is running.

Software Composition Analysis and SAST

Software composition analysis (SCA) and SAST are complementary application security testing methods that provide a more comprehensive assessment of an application's security posture when used together.

Software composition analysis focuses on identifying and analyzing third-party components, such as open-source libraries, frameworks and dependencies, used within an application. By scanning and analyzing these components, SCA can identify known security vulnerabilities, outdated versions and licensing issues. SCA also helps organizations maintain an inventory of third-party components and their associated risks, enabling them to make informed decisions about component usage and updates.

Static application security testing, as mentioned earlier, analyzes an application's source code, bytecode or binary code to identify potential security vulnerabilities. By examining the code statically, without executing the application, SAST tools can detect insecure data handling, input validation errors, race conditions and other security weaknesses.

Organizations gain a comprehensive view of the application's security posture when using SCA and SAST — as SCA looks at the third-party components and SAST covers the custom-written code. Equipped with a better understanding of the application's security risk, organizations can make informed decisions about prioritizing and addressing vulnerabilities.

Related Download: Cloud Native Security Across the Software Lifecycle

SAST Tools

Both manual and automated SAST approaches exist. Manual SAST involves code reviews conducted by security specialists to uncover security flaws. Automated SAST involves the use of tools to scan the code and provide a report detailing detected vulnerabilities.

Organizations have several SAST tools to choose from, each with different strengths and weaknesses. Well-known SAST tools include:

SonarQube: A popular open-source platform that provides continuous inspection of code quality and supports multiple programming languages. It offers SAST capabilities, along with code quality metrics, and integrates with various CI/CD tools.

Checkmarx: A comprehensive SAST solution that supports a wide range of programming languages and frameworks. It offers deep code analysis, accurate vulnerability detection and integration with DevOps tools.

Fortify: A part of Micro Focus suite, Fortify offers both on-premises and cloud-based SAST solutions. It supports a wide variety of programming languages and offers robust vulnerability detection, remediation guidance and integration with CI/CD pipelines.

Veracode: A cloud-based SAST solution that supports multiple programming languages and provides accurate vulnerability identification, remediation guidance and seamless integration with development tools and CI/CD pipelines.

Coverity: Developed by Synopsys, Coverity is a static code analysis tool that offers extensive language support, accurate vulnerability detection and integration with popular development tools and platforms.

Klocwork: A SAST tool that supports C, C++, C#, and Java, Klocwork provides in-depth code analysis, vulnerability detection and compliance checks for various coding standards, along with integration capabilities with development tools.

CodeScan: A SAST tool specifically designed for Salesforce development, CodeScan offers extensive code analysis, vulnerability detection and compliance checks for Apex, Visualforce and Lightning code, as well as integration with CI/CD tools.

GitLab Ultimate: GitLab's Ultimate plan includes built-in SAST capabilities, supporting multiple languages and providing vulnerability detection, remediation guidance and seamless integration with GitLab's CI/CD pipelines.

PVS-Studio: A SAST tool focused on C, C++, C#, and Java, PVS-Studio offers extensive code analysis, vulnerability detection and integration with popular development environments and tools.

DeepSource: A code analysis platform that supports multiple programming languages, DeepSource provides SAST capabilities, code quality checks and performance optimizations, along with seamless integration with version control systems and CI/CD pipelines.

Selecting the right SAST tool depends on your organization's needs, especially the programming languages you use. Also be aware that implementing SAST isn't without challenges. A common issue is the potential for false positives and negatives. False positives occur when SAST tools flag nonissues as vulnerabilities, leading to wasted remediation efforts. Conversely, false negatives happen when real vulnerabilities go undetected, presenting a risk to the software.

An Integrated Solution

The cloud-native application protection platform (CNAPP), usually deployed as a service, provides an integrated and comprehensive set of features, including runtime visibility and control, cloud security posture management (CSPM), software composition analysis and container scanning. Additional features sometimes include API testing and monitoring, SAST and DAST, as well as runtime web application and API protection and a web application firewall (WAF).

At present, CNAPP and application security testing solutions are complementary. Their functionalities, however, are expected to increasingly overlap. Soon, a comprehensive and fully integrated CNAPP will alleviate the need for conventional SAST and DAST tooling.

Industry Guidelines

Implementing SAST effectively requires following leading practices to ensure optimal results and improved security posture. SAST standard practices include:

  • Incorporate SAST tools and processes early in the software development lifecycle (SDLC) to detect and fix vulnerabilities when they are easier and less expensive to address.
  • Automate SAST scanning within your development pipeline, including integration with continuous integration/continuous deployment (CI/CD) systems, to ensure consistent and continuous security testing.
  • Train developers on secure coding practices, common vulnerabilities, and how to use SAST tools effectively. This will help them understand the importance of security and foster a security-conscious development culture.
  • Configure and tune SAST tools to align with your organization's security policies, coding standards and risk tolerance. This helps reduce false positives and ensures the tool is accurately identifying relevant security issues.
  • Develop a process for triaging and prioritizing the identified vulnerabilities based on their severity, exploitability and potential impact. This will help focus remediation efforts on the most critical issues.
  • Monitor and measure the effectiveness of your SAST implementation by tracking the number of vulnerabilities identified, time to remediate, the overall reduction in security risk and other KPIs.
  • Complement SAST with other security testing techniques, such as DAST, interactive application security testing (IAST), and SCA, to achieve a comprehensive view of your application's security posture.
  • Regularly update your SAST tools to ensure they can identify the latest security vulnerabilities and coding standards.
  • Encourage collaboration and communication between development, security and operations teams to create a shared understanding of security goals and establish a DevSecOps culture.
  • Regularly review and improve your SAST processes, tools and configurations to adapt to the evolving threat landscape and the changing needs of your organization.

The Future of SAST

SAST is evolving with advancements in technology, particularly artificial intelligence (AI) and machine learning (ML). AI and ML, when incorporated into SAST tools, can improve accuracy, reducing false positives and negatives. They can also help SAST tools adapt faster to new vulnerability patterns, keeping pace with the evolving threat landscape.

Static Application Security Testing FAQs

Agile is a philosophy and methodology of software development that emphasizes flexibility, collaboration, customer feedback and incremental progress. Agile methodologies, such as Scrum or Kanban, break projects into smaller, manageable units called "iterations" or "sprints," typically lasting a few weeks. The purpose is to deliver functional components of the software application early and to continually improve upon them based on stakeholder feedback. Agile fosters a culture of communication, feedback and adaptation, enabling teams to respond to changes quickly and efficiently.
Agile practice refers to the implementation of Agile principles in a work setting, typically within software development teams. It involves using Agile methodologies, like Scrum or Kanban, and tools to manage and track progress. An agile environment fosters a collaborative and interactive workspace, often characterized by cross-functional teams, regular stand-ups or Scrum meetings, and iterative progress. The focus is on delivering customer value, prioritizing work according to business benefits, promoting team self-management and fostering a culture of continuous improvement. This practice facilitates faster problem-solving, quicker response to changes, and the delivery of higher-quality software.
Static analysis, also known as static application security testing (SAST), is a testing method that examines an application's code without executing it. The goal is to uncover vulnerabilities, bugs or code quality issues that could lead to security breaches. Static analysis checks code against a set of predefined coding standards and rules, offering a comprehensive view of potential security risks.
An Abstract Syntax Tree (AST) is a simplified data structure that represents the hierarchical structure and relationships between the elements of a source code. It’s created as an intermediate representation of the code during the process of parsing or compiling and is used as a foundation for code analysis, optimization and transformation tasks. Tools like static application security testing use ASTs to analyze the code for potential errors, security vulnerabilities or coding standard violations.
Parsing refers to the process of analyzing source code to ensure that it adheres to the grammar rules of the programming language. The parser reads the source code and breaks it down into a series of tokens, which represent the smallest meaningful units of the code, such as keywords, identifiers, operators and literals. It then checks these tokens against the language's grammar to ensure their correct usage and arrangement. If the code is syntactically valid, the parser constructs an Abstract Syntax Tree (AST).
Compiling is a multiple-stage process in which parsing is an initial step. To convert source code into an executable format, the compiler performs additional tasks that include:
  • Semantic analysis: Checking the code for semantic errors, such as type mismatches, undeclared variables or incorrect function calls.
  • Optimization: Applying various techniques to optimize the code for better performance or smaller size.
  • Code generation: Transforming the AST or an intermediate representation into the target executable format, such as machine code for a specific processor architecture or byte code for a virtual machine (e.g., Java virtual machine or .NET Framework).
Compiled versions of applications refer to the executable files generated by converting the source code written in programming languages (such as Java, Python, C++) into machine code. Compilers perform this process, translating human-readable code into a machine-readable format.
Penetration testing, also known as pentesting, is a practice where security experts simulate a cyberattack against a computer system, network or web application to identify vulnerabilities that could be exploited by hackers. It's an essential tool for finding real-world security weaknesses before an attacker does.
IAST is a security testing method that combines elements of static (SAST) and dynamic application security testing (DAST) to use while the application is running in its production environment. IAST tools monitor application behavior and data flow to identify security vulnerabilities.
Runtime application self-protection (RASP) is a security technology that embeds into an application or its runtime environment and actively detects and prevents attacks as they occur. RASP solutions can identify malicious behavior or attacks by analyzing both the app's behavior and the context of that behavior. It's designed to halt attacks without human intervention, offering protection from the inside.

Gosec, short for "Go Security,” is a static code analysis tool designed for the Go programming language, which is also known as Golang. Gosec inspects Go source code to identify and report potential security vulnerabilities, such as weak cryptographic algorithms, hardcoded credentials and insecure random number generation. Key features of Gosec include:

  • Support for the Go programming language
  • Detection of various common security vulnerabilities
  • Customizable rule sets, allowing users to enable or disable specific checks
  • Integration with CI/CD pipelines and popular development tools
  • Output in multiple formats, including JSON, CSV and text
Semgrep is a lightweight, open-source, static analysis tool that supports multiple programming languages, including Python, JavaScript, TypeScript, Go and Java. Semgrep allows developers to write custom rules to identify code patterns and security vulnerabilities in their source code. Features of Semgrep include:
  • Support for multiple programming languages
  • Ability to create custom rules using a simple, YAML-based syntax
  • Integration with CI/CD pipelines, code editors and popular development tools
  • Pre-built rule sets for various security and coding standards
  • A large, community-driven collection of rules available on the Semgrep Registry
  • Performance optimizations for fast scanning and real-time feedback
Security as Code is an approach to security that aligns with the philosophy of infrastructure as code (IaC), where security policies, practices and infrastructure are defined, implemented and managed through code. This allows for consistent, repeatable and scalable security measures that can be automatically deployed alongside application code. Security as Code integrates security practices into the development and deployment pipeline, promoting the idea of shifting left in security, where security measures are implemented early in the software development lifecycle. The approach makes it possible to automate security checks and enforce security policies, reducing the risk of human error and enhancing overall application security. In essence, Security as Code supports the idea of DevSecOps, where security becomes an integral part of the entire development process.
Threat modeling involves identifying, understanding and addressing potential threats in the design phase of software.
The principle known as Secure by Design involves incorporating security practices into software design from the outset.