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Microsoft GH-500 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft GitHub Advanced Security (GH-500)
Exam Number:GH-500
Related Certifications:GitHub Actions
GitHub Administration
Microsoft DevOps Engineer Expert
Exam Format:Case studies, Multiple response, Multiple choice, Scenario-based questions
Exam Price:$165 USD (may vary by region)
Certificate Validity Period:1 year (renewable via Microsoft certification renewal)
Exam Duration:120 minutes
Available Languages:English
Real Exam Qty:40-60 (approx.)
Passing Score:700 (on a scale of 1000)
Recommended Training:GitHub Advanced Security Documentation
Microsoft Learn - GitHub Advanced Security
Exam Registration:Microsoft Certification Exam Page
Pearson VUE Microsoft Exams
Sample Questions:Microsoft GH-500 Sample Questions
Exam Way:Online proctored exam or authorized testing center (Pearson VUE)
Pre Condition:Recommended: familiarity with GitHub, DevSecOps practices, and CI/CD pipelines. No formal prerequisites required.
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/exams/gh-500/

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Microsoft GH-500 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Configure and use Dependabot and Dependency Review: Focused on Software Engineers and Vulnerability Management Specialists, this section describes tools for managing vulnerabilities in dependencies. Candidates learn about the dependency graph and how it is generated, the concept and format of the Software Bill of Materials (SBOM), definitions of dependency vulnerabilities, Dependabot alerts and security updates, and Dependency Review functionality. It covers how alerts are generated based on the dependency graph and GitHub Advisory Database, differences between Dependabot and Dependency Review, enabling and configuring these tools in private repositories and organizations, default alert settings, required permissions, creating Dependabot configuration files and rules to auto-dismiss alerts, setting up Dependency Review workflows including license checks and severity thresholds, configuring notifications, identifying vulnerabilities from alerts and pull requests, enabling security updates, and taking remediation actions including testing and merging pull requests.
Topic 2
  • Describe the GHAS security features and functionality: This section of the exam measures skills of Security Engineers and Software Developers and covers understanding the role of GitHub Advanced Security (GHAS) features within the overall security ecosystem. Candidates learn to differentiate security features available automatically for open source projects versus those unlocked when GHAS is paired with GitHub Enterprise Cloud (GHEC) or GitHub Enterprise Server (GHES). The domain includes knowledge of Security Overview dashboards, the distinctions between secret scanning and code scanning, and how secret scanning, code scanning, and Dependabot work together to secure the software development lifecycle. It also covers scenarios contrasting isolated security reviews with integrated security throughout the development lifecycle, how vulnerable dependencies are detected using manifests and vulnerability databases, appropriate responses to alerts, the risks of ignoring alerts, developer responsibilities for alerts, access management for viewing alerts, and the placement of Dependabot alerts in the development process.
Topic 3
  • Describe GitHub Advanced Security best practices, results, and how to take corrective measures: This section evaluates skills of Security Managers and Development Team Leads in effectively handling GHAS results and applying best practices. It includes using Common Vulnerabilities and Exposures (CVE) and Common Weakness Enumeration (CWE) identifiers to describe alerts and suggest remediation, decision-making processes for closing or dismissing alerts including documentation and data-based decisions, understanding default CodeQL query suites, how CodeQL analyzes compiled versus interpreted languages, the roles and responsibilities of development and security teams in workflows, adjusting severity thresholds for code scanning pull request status checks, prioritizing secret scanning remediation with filters, enforcing CodeQL and Dependency Review workflows via repository rulesets, and configuring code scanning, secret scanning, and dependency analysis to detect and remediate vulnerabilities earlier in the development lifecycle, such as during pull requests or by enabling push protection.
Topic 4
  • Configure and use Code Scanning with CodeQL: This domain measures skills of Application Security Analysts and DevSecOps Engineers in code scanning using both CodeQL and third-party tools. It covers enabling code scanning, the role of code scanning in the development lifecycle, differences between enabling CodeQL versus third-party analysis, implementing CodeQL in GitHub Actions workflows versus other CI tools, uploading SARIF results, configuring workflow frequency and triggering events, editing workflow templates for active repositories, viewing CodeQL scan results, troubleshooting workflow failures and customizing configurations, analyzing data flows through code, interpreting code scanning alerts with linked documentation, deciding when to dismiss alerts, understanding CodeQL limitations related to compilation and language support, and defining SARIF categories.
Topic 5
  • Configure and use secret scanning: This domain targets DevOps Engineers and Security Analysts with the skills to configure and manage secret scanning. It includes understanding what secret scanning is and its push protection capability to prevent secret leaks. Candidates differentiate secret scanning availability in public versus private repositories, enable scanning in private repos, and learn how to respond appropriately to alerts. The domain covers alert generation criteria for secrets, user role-based alert visibility and notification, customizing default scanning behavior, assigning alert recipients beyond admins, excluding files from scans, and enabling custom secret scanning within repositories.

Microsoft GitHub Advanced Security Sample Questions (Q36-Q41):

NEW QUESTION # 36
Which key is required in the update settings of the Dependabot configuration file?

Answer: B

Explanation:
In a dependabot.yml configuration file, package-ecosystem is a required key . It defines the package manager being used in that update configuration (e.g., npm, pip, maven, etc.).
Without this key, Dependabot cannot determine how to analyze or update dependencies. Other keys like rebase-strategy or commit-message are optional and used for customizing behavior.
: GitHub Docs - Dependabot Configuration Options


NEW QUESTION # 37
What is the best method to ensure all new code is scanned for vulnerabilities?

Answer: B

Explanation:
To systematically analyze newly introduced source code for security weaknesses, you should configure code scanning. GitHub code scanning can use CodeQL or supported third-party analysis tools and can run automatically when developers push changes or create pull requests. This places vulnerability detection directly into the development workflow rather than depending on manual review. The extended CodeQL query suite broadens the set of queries executed, but it only has an effect after code scanning itself is configured. CODEOWNERS determines who reviews specific paths and does not perform vulnerability analysis. A security policy explains how vulnerabilities should be reported but does not scan source code.
Therefore, enabling and properly configuring code scanning is the foundational mechanism for ensuring new code is automatically analyzed.


NEW QUESTION # 38
Which of the following features helps to prioritize secret scanning alerts that present an immediate risk?

Answer: A

Explanation:
Secret validation checks whether a secret found in your repository is still valid and active with the issuing provider (e.g., AWS, GitHub, Stripe). If a secret is confirmed to be active, the alert is marked as verified , which means it's considered a high-priority issue because it presents an immediate security risk.
This helps teams respond faster to valid, exploitable secrets rather than wasting time on expired or fake tokens.
: GitHub Docs - Secret validation in secret scanning


NEW QUESTION # 39
What is the first step in CodeQL analysis?

Answer: C

Explanation:
Before CodeQL can execute security queries, the source code must first be represented in a CodeQL database.
Database creation extracts structured, relational information from the source code and, where applicable, observes or performs the build process required for the language being analyzed. Once the database exists, CodeQL can execute queries against it. The resulting query output is then interpreted using query metadata and can ultimately be converted to a format such as SARIF for presentation as code scanning alerts.
Therefore, running queries, interpreting results, and converting results are later phases of analysis. GitHub's CodeQL documentation explicitly identifies creation of the CodeQL database as a prerequisite for analyzing source code with CodeQL queries, making preparation/database creation the correct first step.


NEW QUESTION # 40
If default code security settings have not been changed at the repository, organization, or enterprise level, which repositories receive Dependabot alerts?

Answer: B

Explanation:
By default, no repositories receive Dependabot alerts unless configuration is explicitly enabled. GitHub does not enable Dependabot alerts automatically for any repositories unless:
The feature is turned on manually
It's configured at the organization or enterprise level via security policies This includes public, private, and enterprise-owned repositories - manual activation is required.


NEW QUESTION # 41
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