Static code analysis is a crucial security process in the realm of information security under the category of CI/CD(delivering code to production) and software development. It involves examining code without executing it, identifying potential vulnerabilities, and ensuring code quality. as part of Information security management system, we emphasize the importance of static code analysis in building secure and robust software applications. Static analysis can cache security vulnerabilities which are hidden by the eye of even the most experience software engineer.
Why is Static Code Analysis Important?
Static code analysis plays a vital role in detecting security flaws and vulnerabilities early in the development lifecycle. By analyzing the code statically, developers can identify issues such as SQL injection, cross-site scripting (XSS), known security vulnerabilities in software languages and other common security vulnerabilities before the code is deployed. Static analysis of code simply relay on database and AI knowledge of security issues rather than on the experience of software engineer.
How Does Static Code Analysis Work?
Static code analysis tools scan the source code of an application to identify patterns, issues, and potential vulnerabilities. These tools analyze the code against a set of predefined rules and best practices to highlight areas that require attention. By using static code analysis, developers can ensure that their code meets security standards and is free from potential vulnerabilities.
Benefits of Static Code Analysis
- Early Detection of Vulnerabilities: Static code analysis helps identify vulnerabilities early in the development process, reducing the risk of security breaches.
- Improved Code Quality: By identifying and fixing issues early, static code analysis leads to improved code quality and reliability.
- Cost-Effective: Addressing vulnerabilities early in the development process is more cost-effective than fixing them later.
- Compliance: Static code analysis helps ensure that software meets security and compliance standards, such as PCI DSS and GDPR.
Best Practices for Static Code Analysis
- Regular Scans: Conduct regular static code analysis scans to identify and address new vulnerabilities.
- Use of Automated Tools: Utilize automated static code analysis tools to streamline the process and ensure comprehensive coverage.
- Integration with Development Process: Integrate static code analysis into the software development lifecycle to catch issues early.
- Continuous Improvement: Continuously refine and update static code analysis rules to adapt to new security threats and best practices.
Code Examples
Here’s an example in Node.js of a potentially insecure file and folder reading function that could be flagged by static code analysis for security concerns:
const http = require('http');
const fs = require('fs');
const path = require('path');
http.createServer((req, res) => {
let filePath = path.join(__dirname, 'public', req.url);
fs.readFile(filePath, (err, data) => {
if (err) {
console.error('Error reading file:', err);
res.writeHead(500);
res.end('Internal Server Error');
return;
}
res.writeHead(200);
res.end(data);
});
}).listen(8080, () => {
console.log('Server running at http://localhost:8080/');
});In this example, the server serves files from the public directory based on the request URL. However, it does not properly sanitize the req.url parameter, which could allow an attacker to perform a directory traversal attack. For example, an attacker could request a URL like /../../../../../etc/passwd to access sensitive system files outside of the intended public directory.
To prevent path traversal attacks, it’s important to sanitize user input and ensure that file paths are properly validated and restricted to a specific directory. Static code analysis can capture security vulnerabilities like this one and alert the engineers writing that code that they are writing code that is not safe and secure. Read more about path traversal attack.
Static Code Analysis Limitation
Static code analysis for security information and vulnerabilities detection has several limitations:
- False Positives: Static analysis tools can produce false positive results, where they report a possible vulnerability that does not actually exist. This can happen because the tool cannot always accurately trace the flow of data through the application from input to output. For example, interactions with closed-source components or external systems may not be fully understood by the tool, leading to false positives.
- False Negatives: Conversely, static analysis tools can also result in false negative results, where vulnerabilities exist but are not reported by the tool. This can occur if a new vulnerability is discovered in an external component that the tool is not aware of, or if the tool lacks knowledge about the runtime environment and its secure configuration.
- Limited Scope: Static analysis tools have a limited scope and may not be able to detect certain types of vulnerabilities, such as those related to runtime behavior or environmental configurations. They are also less effective at detecting vulnerabilities that require complex data flows or interactions between multiple components.
- Code Complexity: Static analysis tools may struggle with highly complex code or code that uses advanced programming techniques. In such cases, the tools may produce inaccurate results or fail to analyze the code altogether.
- Resource Intensive: Running static analysis on large codebases can be resource-intensive, requiring significant computational power and time. This can make it impractical to perform frequent or comprehensive analyses, especially in large-scale development environments.
- Limited to Code Analysis: Static analysis tools are limited to analyzing the code itself and cannot detect vulnerabilities that arise from other aspects of the software development lifecycle, such as design flaws, configuration errors, or insecure deployment practices.
- known issues: static code analysis limited to known issues! good experience technology leader software engineers will be able to detect future security vulnerabilities that are not documented yet.
Despite these limitations, static code analysis remains a valuable tool for identifying potential security issues in software and can help developers improve the overall security of their applications. However, it should be used in conjunction with other security measures and best practices to provide comprehensive security coverage.
List of Static Analysis Tools
| Tool | Latest Release | Cost | Supported Languages | Notes |
|---|---|---|---|---|
| Ada | – | Free | C, C++, C#, Objective-C, JavaScript, TypeScript, .NET, VB.NET, Python, Other languages | JVM |
| Snyk code | – | Free, With plans for companies | – | Integrated IDE, part of CI/cd |
| Yasca (retired) | 2010-11-01 | Yes; multiple licenses | C, C++, Java, JavaScript, ASP, PHP, HTML, CSS, ColdFusion, COBOL | Yet Another Source Code Analyzer, a plugin-based framework to scan arbitrary file types, with plugins. It integrates with other scanners, including FindBugs, PMD, and Pixy. |
| Visual Studio | 2021-10-12 | No; proprietary | C, C++, C# | IDE support. for C/C++ in the editor environment and from the compiler command line. includes support for .NET Compiler Platform (Roslyn) and provides C# and VB.NET analysis. |
| Visual Expert | 2021-09-10 | No; proprietary | PowerBuilder, Oracle PL/SQL, SQL Server Transact-SQL (T-SQL) | Continuous Code inspection part of workflow, reports on quality and security issues, assist understand complex code (cross-references, source code from documentation, code comparison, as well as code performance analysis). |
| Understand | 2023-01-19 | No; proprietary | Ada, C, C++, C#, Objective-C, Java, JavaScript, Python, FORTRAN, Jovial, Pascal, VHDL, HTML, PHP, XML | impressive multi-platform tool for code analysis, comprehension of large code bases. Recognize multiple dialects of C, C++ and C# like ANSI, K&R and Objective C++. |
| StyleCop | 2016-05-02 | Yes; Ms-PL | C# | Analyzes C# source code |
| Squore | 2020-11-27 | No; proprietary | Python, Swift, Ada, C, C++, C#, Objective-C, Java, JavaScript, TypeScript, VB.NET, Fortran, PL/SQL, T-SQL, XAML, PHP | more than one purpose and many language monitoring tool for software projects. Also integrates with other scanners. |
| Splint | 2007-07-12 | Yes; GPLv2 | C | An open-source tool statically checking C programs! for security vulnerabilities and coding mistakes! |
| Sparse | 2021-09-06 | Yes; MIT | C | completely open-source tool designed to find faults in the Linux kernel software code base. |
| Sourcetrail (retired) | 2021-04 | Yes; GPL | C, C++, Java, Python, Perl | free and open-source source code explorer, Provides interactive dependency graph. supports multiple programming languages. |
| SourceMeter | 2016-12-16 | No; proprietary | C, C++, Java, Python, RPG IV (AS/400) | A platform-independent, run from command-line static source code analyzer. Integrates with SpotBugs and PMD. |
| SonarQube | 2024-02-05 | Partly free; framework is LGPL v3.0, but some features cost money | C, C#, C++, Objective-C, Java, Kotlin, Scala, JavaScript, TypeScript, VB.NET, Python, ABAP, Apex, CSS, COBOL, Flex, Go, HTML, PHP, PLI, PL/SQL, Ruby, Swift, TSQL, Visual Basic 6, XML | A continuous inspection engine that tracks vulnerabilities. Also tracks code complexity, unit test coverage and duplication. Offers branch analysis and C/C++/Objective-C support with commercial licenses. |
| SofCheck Inspector, Codepeer | 2020-08-24 | No, proprietary | Ada | Static detection of logic errors, race conditions, and redundant code. Automatically extracts pre-postconditions from code. |
| SLAM project | 2010-07-14 | No, proprietary | C | Project of Microsoft Research. |
| Sider | 2021-02-02 | No; proprietary | JavaScript, CoffeeScript | Static code analysis based fully automated code review tool working on GitHub and GitLab. Checks quality, style, dependencies, security and bugs. It integrates a number of open-source static analysis tools. |
| Semgrep | 2024-03-28 | Yes; LGPL v2.1 | Java, JavaScript, TypeScript, Python, Go, JSON, Ruby, language-agnostic mode | A static analysis tool that helps identify bugs. It also has experimental support for 11 other languages. |
| SAST Online | 2022-03-07 | No; proprietary | Java, Kotlin, APK | checks Android Source code thoroughly to uncover and address potential issues and security concerns and vulnerabilities. Static application security testing (Static Code Analysis) tool Online. |
Common Questions
| Question | Answer |
|---|---|
| What is static code analysis tool? | Static code analysis tools are software tools that perform static analysis on source code to find potential vulnerabilities, bugs, or code smells without executing the code. |
| Is Snyk a static code analysis tool? | Snyk is primarily known for its security testing and monitoring for open source dependencies (SaaS). While it offers some static analysis features, it’s not a dedicated static code analysis tool. However in recent years Snyk offers robust static tool analysis tool. |
| Is SonarQube a static analysis tool? | Yes, SonarQube is a static analysis tool used for continuous inspection of code quality to perform automatic reviews with static analysis of code to detect bugs, code smells, and security vulnerabilities. |
| Which tool belongs to SAST? | SAST stands for Static Application Security Testing, and tools like SonarQube, Fortify, Checkmarx, and Veracode are examples of SAST tools. |
| What are DAST and SAST tools? | DAST (Dynamic Application Security Testing) tools test running applications by sending malicious payloads and monitoring the response, while SAST tools analyze the application without executing the code. |
| Is Black Duck a SAST tool? | Black Duck, now part of Synopsys, is more of a Software Composition Analysis (SCA) tool, focusing on identifying open-source components and their licenses in your codebase. It’s not a pure SAST tool. |
| Is SAST and static code analysis same? | SAST (Static Application Security Testing) is a subset of static code analysis, which also includes other code analysis techniques like code quality checks and performance optimizations. |
Static Code Analysis / Dynamic Code Analysis
Let’s take a look into few static code analysis aspect versus dynamic code analysis so we could understand the difference within information security analysis of security vulnerabilities that we can pick. It might help us decide which tools we want to use for our software and products.
| Aspect | Static Analysis | Dynamic Analysis |
|---|---|---|
| Definition | Identifies issues before running the program. | Identifies issues after running the program. |
| Stage of Analysis | Occurs before program execution, typically between code creation and unit testing. | Occurs during program execution, typically during unit testing. |
| Execution Environment | Non-run-time environment. | Run-time environment. |
| Detection Focus | Identifies defects without executing the code, looking at code structure and syntax. | Identifies defects while executing the code, focusing on interactions with databases, servers, and services. |
| Coverage | Can cover the entire codebase. | Only covers the specific excerpt of code being executed. |
| Effectiveness | Effective for finding potential issues and vulnerabilities early in development. | Effective for finding subtle defects and vulnerabilities, as it examines the code’s real-world interactions. |
| Limitations | Cannot detect defects or vulnerabilities that arise in runtime environments. | Limited in scope, as it only analyzes the code being executed and may not detect issues in unexecuted code paths. |
| Complementarity | Ensures fewer defects during unit testing. | Catches issues that static analysis tools might have missed, enhancing overall test coverage. |
| Benefits | Enhances developer accountability, reduces project costs, highlights bugs early for faster fixes. | Provides almost immediate return on investment, increases code coverage, reduces development time, and more. |
| Challenges | Can return false positives and false negatives, may take a long time to operate manually. | Cannot locate defects or vulnerabilities in runtime environments, deciding which coding standards to apply can be confusing. |
| Conclusion | Both are essential processes, with static analysis ensuring fewer defects during unit testing and dynamic analysis catching issues that static analysis tools might have missed. | Combining the two methods achieves the highest possible level of test coverage and improves the development process in terms of reliability, bug detection, efficiency, and security. |
Conclusion
In conclusion, static code analysis is a critical component of modern software development and information security. By incorporating static code analysis into your development process, you can enhance the security and reliability of your software applications, protect against cybersecurity threats, and ensure compliance with industry standards and regulations.
I am a software engineer with 20 years of experience of writing code, Software languages, Large scale web application, security and data protection of online digital assets in various software systems and services. I’ve decided to write and share my interests in cyber security online and information security to help and improve white hat security, safety and privacy of our online digital assets, As companies, as individuals or experts providing services. In here you’ll be able to read freely about cyber security threats, detections, common problems, services, news and everything related to information security and cyber security – enjoy and feel free to contact me via the contact page for any question.