Static code analysis has revolutionized the way computer programming is done. Gone are the days of manual programming using punch cards, where programmers had to check for correctness and hope for successful execution meticulously. Nowadays, developers receive instant feedback on the correctness of their code as they type it into their code editor, thanks to advancements in static code analysis.

Static code analysis helps detect and prevent issues early in software development. However, it’s essential to be mindful of the resources it consumes. While static code analysis is already valuable for enhancing software testing and quality assurance, its value can be further increased by incorporating test impact analysis and predictive test selection techniques.

Unlike dynamic code testing, which involves executing the program to verify its behavior, static code analysis focuses on analyzing the source code for potential issues. Static analyzers utilize algorithms and rule sets to identify issues, classify them based on severity and impact, and provide developers with a list of issues to address.

What is static code analysis?

Static Code Analysis, also known as Source Code Analysis, plays a crucial role in Code Review and is conducted during the Implementation phase of a Security Development Lifecycle (SDL). It aims to identify potential vulnerabilities in the ‘static’ (non-running) source code by utilizing advanced techniques like Taint Analysis and Data Flow Analysis.

In an ideal scenario, these tools would autonomously detect security flaws with high certainty. However, achieving such a level of accuracy remains challenging for many application security flaws. Consequently, these tools often serve as aids for analysts, enabling them to focus on security-relevant code sections and efficiently discover flaws rather than being a magic bullet that uncovers flaws automatically.

There is a rising trend of integrating these tools into Integrated Development Environments (IDEs). This integration proves to be highly beneficial during the software development phase itself, as it provides immediate feedback to developers regarding any potential issues they may introduce into the code during its development. This timely feedback significantly surpasses the process of identifying vulnerabilities at a later stage in the Software Development Life Cycle.

Static analysis excels at uncovering various coding issues, including:

• Programming errors
• Violations of coding standards
• Undefined values
• Syntax violations
• Security vulnerabilities

Static Code Analysis: How is it Performed?

The process of static code analysis becomes straightforward when automated. Typically, static analysis occurs early in the development phase, before software testing. In the DevOps development approach, it takes place during the creation phases.

After the code is written, running a static code analyzer is essential to examine it. The analyzer checks the code against predefined coding rules, either from standards or custom rules. Running the code through the static code analyzer identifies whether the code adheres to the specified rules. Occasionally, the software may flag false positives, requiring someone to review and dismiss them. Once false positives are addressed, developers can start rectifying apparent errors, usually focusing on the most critical ones. After resolving code issues, the code can proceed to testing by execution.

Performing static analysis without code testing tools can be laborious since humans need to review the code and anticipate its behavior in runtime environments. Therefore, utilizing an automated tool that streamlines the process completely is advisable. Eliminating time-consuming procedures promotes a more efficient work environment overall.

What are the techniques of static code analysis?

Static code analysis incorporates four techniques derived from compiler technology:

• Abstract Interpretation: Abstract interpretation creates a mathematical representation of the software, considering each statement’s and declaration’s inherent characteristics.
• Taint Analysis: Taint analysis constructs mathematical equations to represent the value of modified or ‘tainted’ variables at specific code locations. By tracing these variables, potential vulnerabilities can be identified.
• Lexical Analysis: Lexical analysis breaks down the syntax of the source code into informative tokens. This abstraction of the source code simplifies modification and manipulation.
• Data Flow Analysis: This technique is employed to collect runtime information about the data within the software while it is in a static state.

Benefits of Static Code Analysis in the Software Development Process

Static code analysis offers numerous benefits, including but not limited to:

• Early problem identification: detecting potential issues early in the development cycle, preventing costly and time-consuming debugging efforts later.
• Ensuring code quality: enforcing specific standards and practices and improving the overall quality and reliability of the software.
• Enhancing security: By identifying vulnerabilities and security issues, static code analysis contributes to preventing security breaches and safeguarding sensitive data.
• Increased efficiency: Automating the code review process saves developers time, allowing them to focus on other essential tasks.

Improved Quality and Reliability of Software:

Static code analysis tools can detect bugs and vulnerabilities, such as null pointer dereferences, buffer overflows, race conditions, code injection vulnerabilities, security misconfigurations, and resource leaks. Identifying these issues early reduces the risk of defects and errors, consequently improving software quality and reliability.

Enhanced Security of Software:

Effective in identifying potential vulnerabilities and security issues, including weak passwords, unencrypted data, and SQL injection attacks. Static code analysis helps prevent security breaches and properly protects personal data by addressing these issues before deployment.

Increased Efficiency of the Software Development Process:

They contribute to the efficiency of the software development process by identifying potential issues early on, reducing the risk of errors and defects. This automation of the code review process saves time and improves code quality, allowing organizations to deliver software products more efficiently and effectively.

Challenges of static code analysis

Time-consuming nature

Static code analysis can be time-consuming, especially when reviewing and analyzing the entire codebase. The results generated by the tool can contain a substantial amount of data and information. Although the analysis is automated, it requires someone to interpret the results, distinguish real issues from false positives, and make the necessary code changes.

Possibility of false negatives/positives

Static code analysis tools, unfortunately, may generate false positives, leading to additional time and effort being spent. False positives occur when code is flagged as problematic or non-compliant despite no issue. False negatives occur when the tool fails to identify genuine problems in the code.

Examples include:

• Flagging unused code or variables as potential bugs.
• Identifying incomplete code or code intentionally missing sections.
• Recognizing code that is technically correct but doesn’t adhere to specific stylistic or formatting standards.
• Missing security vulnerabilities that the tool doesn’t detect.
• Overlooking memory leaks or buffer overflows.
• Failing to detect dead or redundant code.

Scope limitations

Static code analysis tools can only identify issues without executing the code. Therefore, they may not detect performance or usability issues that can only be observed during code execution.

Other limitations are worth mentioning:

• Inability to identify runtime errors since static analysis doesn’t execute the code.
• Limited support for complex programming languages. While popular languages like Java, C++, and Python are well-supported, less popular or complex languages may have limited or no analysis capabilities.

Conclusion

Although static code analysis provides numerous benefits, its limitations prevent it from guaranteeing complete application security. It is important to recognize that static code analysis alone is insufficient; a broader approach is needed to assist the testing process better. There is no single solution or magic remedy that can assure the absolute security of an application. Instead, keep in mind aiming to build a comprehensive security solution by combining various security tools and testing methods is preferable.

By incorporating an intelligent and comprehensive vulnerability scanner, manual penetration testing, security audits, and seeking the expertise of security professionals like SHIFT ASIA, you are set to achieve successful and comprehensive security coverage. All these are to effectively strengthen web application security from the development stage.