GitHub Code Scanning Reviews

Name: GitHub Code Scanning
Brand: GitHub
Rating: 4.3 (6 reviews)

4.3 out of 5

6 reviews
100% willing to recommend

What is GitHub Code Scanning?

Code scanning is a feature that you use to analyze the code in a GitHub repository to find security vulnerabilities and coding errors. Any problems identified by the analysis are shown in GitHub.

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GitHub Code Scanning is the #17 ranked solution in AST tools. PeerSpot users give GitHub Code Scanning an average rating of 8.6 out of 10. GitHub Code Scanning is most commonly compared to SonarQube Server (formerly SonarQube): GitHub Code Scanning vs SonarQube Server (formerly SonarQube). GitHub Code Scanning is popular among the large enterprise segment, accounting for 65% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a computer software company, accounting for 12% of all views.

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Static Application Security Testing (SAST)

June 2025

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Helped 861,390 peers since 2012

Featured GitHub Code Scanning reviews

VishalSingh

Consulting & Solutions, BA/BD in Enterprise IT on Open Source, Red Hat & EDB at KEEN AND ABLE COMPUTERS PVT LTD

You can use the tool locally on your system or in the cloud. I rate it a nine out of ten. It's a very good tool for people who want to start using GitHubCode Scanning, especially for software development or team collaboration. GitHubCode Scanning allows teams to collaborate by uploading files to repositories. For example, if someone is developing an application, they can host the code on GitHub Code Scanning. Other developers can then download the code for testing purposes. If bugs are found, fixes can be applied using the GitHub Code Scanningrepository, and everyone on the team can see the changes. Software developers often use GitHub Code Scanning for version control, and it's essential for CI/CD pipelines to work.

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AbhishekKumar20

Software Development Manager at Amazon

I have been using Git for approximately 13-14 years. I have used GitHub Code Scanning for about three to four years. The primary purpose is to identify any vulnerability in the code itself. The system logs vulnerabilities that we can immediately examine to see all the error-prone areas. The AI functionalities include predefined agents that scan through and immediately provide responses regarding the best nomenclature or code coverage percentage. It's actually a one-time setup, and the team benefits as long as they push code and changes in the repository itself. Every time we push something, we immediately check the total deviation, whether our code coverage has improved, or if any vulnerability has been identified. There is always a metrics dashboard that we can see and identify. Primarily, GitHub is used for doing the versioning itself in the repository. With vulnerability functionality being provided and AI agents available, it makes a complete package. As soon as we publish our code, we immediately get to know the test code coverage. This immediately informs us about all the vulnerable areas which are not being fully tested. If we address those areas, most vulnerabilities are resolved. Even after tests are added, if by any chance the test is not treated cleanly or corner cases are missed, GitHub Code Scanning immediately flags those corners. It's always beneficial to have because it's not humanly possible to check all corner case scenarios, but as a system where they diagnose each line item, that's very helpful.

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SekarSadasivam

Senior Engineering Manager at a logistics company with 10,001+ employees

When running code scans, GitHub Code Scanning provides recommendations for probable fixes. However, integrating a feature where developers receive real-time highlights of vulnerabilities when checking in or merging a PR would be beneficial. This would allow developers to address issues before the code gets merged. Adding this capability could ensure developers are alerted to potential vulnerabilities upfront.

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GitHub Code Scanning mindshare

As of July 2025, the mindshare of GitHub Code Scanning in the Static Application Security Testing (SAST) category stands at 1.2%, up from 0.3% compared to the previous year, according to calculations based on PeerSpot user engagement data.

Static Application Security Testing (SAST)

Key learnings from peers

Last updated Jul 9, 2025

Valuable Features

GitHub Code Scanning offers valuable features such as identifying vulnerabilities, tracking code coverage, and providing an intuitive metrics dashboard. Its static code analysis capability aids in ensuring code quality. AI functionalities like predefined agents enhance code nomenclature and coverage. The automation feature accelerates code quality processes, improving developer efficiency. GitHub Actions facilitates repository management with extensive options for code reviews, Git branching, and integrations, making setup and maintenance more efficient with integrated capabilities.

"GitHub Code Scanning has positively impacted my organization as it helps us recognize errors and avoid many later issues which may arise."
"It's very scalable, very easy to handle, and very intuitive."
"The static code analysis capability in GitHub Code Scanning is a very powerful feature, providing the ability to identify vulnerabilities and ensure code quality."

Room for Improvement

GitHub Code Scanning could improve by adding more templates, using AI to summarize extensive reports, and highlighting outdated libraries. It would be helpful to integrate real-time vulnerability alerts during code check-ins or merges. Enhancing documentation support with AI assistance is suggested. Users find it annoying at times as it highlights intuitive aspects, prompting extra code coverage. Performance for its designed purpose is excellent, with a seven or eight out of ten rating for developer experience.

"At times it becomes very annoying as it highlights certain things which are intuitive. They require code coverage for those aspects as an extra overhead."
"When running code scans, GitHub Code Scanning provides recommendations for probable fixes. However, integrating a feature where developers receive real-time highlights of vulnerabilities when checking in or merging a PR would be beneficial."
"One area for improvement could be the ability to have an AI system digest the reports generated from code scanning and provide a summary. Currently, the reports can be extensive, and users may overlook details, such as outdated libraries, which could be highlighted for attention."

Pricing

"The minimum pricing for the tool is five dollars a month."
"GitHub Code Scanning is a moderately priced solution."

Popular Use Cases

Organizations utilize GitHub Code Scanning primarily for static code analysis and identifying vulnerabilities, such as OWASP vulnerabilities. They integrate it into their code quality efforts, ensuring compliance by checking for logical errors and code coverage. The tool effectively scans networks to determine open ports as per compliance policies. Users also employ CodeQL and AI agents for dashboards, validating code at various development and production stages to prevent vulnerabilities and code leaks before production deployment.

Deployment

GitHub Code Scanning's initial setup is described as straightforward by users. They find it simple due to detailed manuals and note it as easier compared to building custom pipelines with tools like Jenkins. Ports are pre-defined within the operating system, but users can change them if needed. This simplicity and clarity in configuration make it an accessible option for those looking for a hassle-free implementation.

Scalability

GitHub Code Scanning is widely acknowledged for its strong scalability. Many organizations report seamless integration for thousands of users without limitations. Its cloud-based infrastructure efficiently manages large-scale needs, ensuring it operates effectively across diverse corporate environments. Users appreciate its intuitive interface and minimal maintenance requirements, making it an accessible tool for extensive networks. The adaptability to handle varying network sizes contributes to its favorable perception in terms of scalability.

These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.

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