The GitHub Advanced Security Exam (GH-500) is designed for developers, security engineers, and DevOps professionals who implement and manage security controls within GitHub repositories. This exam validates your ability to configure GitHub Advanced Security features, respond to vulnerabilities, and enforce security best practices across your organization. This landing page provides a clear study roadmap, topic breakdown, and practical preparation guidance to help you earn your Microsoft GitHub Certifications credential with confidence.
Use this topic map to guide your study for Microsoft GH-500 (GitHub Advanced Security Exam) within the Microsoft GitHub Certifications path.
The GH-500 exam uses a mix of question types to assess both conceptual knowledge and practical decision-making in real-world security scenarios.
Questions progress in difficulty and emphasize practical application, ensuring you can implement security controls in actual projects, not just recall definitions.
An effective study plan breaks the exam into weekly milestones and combines reading, hands-on practice, and review. Allocate 3-4 weeks to cover all topics thoroughly, with extra time for weak areas and timed practice.
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CodeQL and code scanning typically account for a larger portion of the exam, as they require both conceptual understanding and practical configuration skills. Secret scanning and Dependabot are equally important but often tested with slightly fewer questions. Best practices and organizational policies appear throughout, reinforcing how all features work together.
Secret scanning runs on every push to catch exposed credentials immediately. Dependabot monitors your dependencies and alerts you to vulnerabilities, while Dependency Review lets you assess risk before merging. CodeQL scans your code for logic flaws and security patterns. Together, they create a layered defense: secrets are blocked early, dependencies are kept current, and code quality is verified before release.
Hands-on experience is valuable but not mandatory if you study the configuration flows carefully. Prioritize labs that let you enable secret scanning and push protection, configure Dependabot alerts and auto-updates, and set up a CodeQL scanning workflow in a GitHub Actions pipeline. These three areas directly map to exam questions and build practical confidence.
Many candidates confuse Dependabot alerts with Dependency Review or don't understand the difference between secret scanning and push protection. Others misinterpret CodeQL results or don't know how to prioritize findings by severity. Weak understanding of organizational policies and how to enforce them across teams also costs points. Review the distinctions between features and practice scenario questions that ask you to choose the best response to a security finding.
In the final week, focus on timed practice tests and review only the topics where you scored below 80%. Re-read explanations for any missed questions to lock in the reasoning. Do a full-length mock exam 2-3 days before the real test to identify any remaining gaps, then spend your last day reviewing those specific areas rather than re-studying everything. Get good sleep the night before the exam to ensure sharp focus.
-- [Configure and Use Dependency Management]
What should you do after receiving an alert about a dependency added in a pull request?
If an alert is raised on a pull request dependency, best practice is to update the dependency to a secure version before merging the PR. This prevents the vulnerable version from entering the main codebase.
Merging or deploying the PR without fixing the issue exposes your production environment to known risks.
-- [Configure and Use Dependency Management]
Which Dependabot configuration fields are required? (Each answer presents part of the solution. Choose three.)
Comprehensive and Detailed Explanation:
When configuring Dependabot via the dependabot.yml file, the following fields are mandatory for each update configuration:
directory: Specifies the location of the package manifest within the repository. This tells Dependabot where to look for dependency files.
package-ecosystem: Indicates the type of package manager (e.g., npm, pip, maven) used in the specified directory.
schedule.interval: Defines how frequently Dependabot checks for updates (e.g., daily, weekly). This ensures regular scanning for outdated or vulnerable dependencies.
The milestone field is optional and used for associating pull requests with milestones. The allow field is also optional and used to specify which dependencies to update.
GitLab
-- [Describe GHAS Security Features and Functionality]
Which alerts do you see in the repository's Security tab? (Each answer presents part of the solution. Choose three.)
In a repository's Security tab, you can view:
Secret scanning alerts: Exposed credentials or tokens
Dependabot alerts: Vulnerable dependencies from the advisory database
Code scanning alerts: Vulnerabilities in code detected via static analysis (e.g., CodeQL)
You won't see general 'security status alerts' (not a formal category) or permission-related alerts here.
-- [Use Code Scanning with CodeQL]
What does a CodeQL database of your repository contain?
Comprehensive and Detailed Explanation:
A CodeQL database contains a representation of your codebase, including the build of the code and extracted data. This database is used to run CodeQL queries to analyze your code for potential vulnerabilities and errors.
GitHub Docs
-- [Configure and Use Dependency Management]
In a private repository, what minimum requirements does GitHub need to generate a dependency graph? (Each answer presents part of the solution. Choose two.)
Comprehensive and Detailed Explanation:
To generate a dependency graph for a private repository, GitHub requires:
Dependency graph enabled: The repository must have the dependency graph feature enabled. This can be configured at the organization level to apply to all new private repositories.
Access to manifest and lock files: GitHub needs read-only access to the repository's dependency manifest and lock files (e.g., package.json, requirements.txt) to identify and map dependencies.
