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Microsoft GH-500 Exam Overview:

Certification Vendor:Microsoft
Exam Name:GH-500: GitHub Advanced Security
Exam Number:GH-500
Exam Format:Interactive tasks, Multiple-choice, Scenario-based
Passing Score:700 / 1000
Exam Price:$99 USD
Available Languages:German, English, Arabic (Saudi Arabia), Korean, French, Spanish, Chinese (Simplified), Portuguese (Brazil), Japanese
Certificate Validity Period:1 year
Exam Duration:100 minutes
Real Exam Qty:40โ€“60
Recommended Training:Course GH-500T00: GitHub Advanced Security
GitHub Advanced Security Learning Path
Exam Registration:Microsoft Learn Exam Registration
Pearson VUE Scheduling
Sample Questions:Microsoft GH-500 Sample Questions
Exam Way:Online proctored or onsite testing via Pearson VUE
Pre Condition:Familiarity with GitHub fundamentals, CI/CD pipelines, and secure development practices; no mandatory prerequisite exams
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/gh-500

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Microsoft GH-500 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 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
  • 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 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 (Q76-Q81):

NEW QUESTION # 76
When using code scanning and GitHub Actions on Windows, what is the relative difference between the minute consumption of code scanning jobs and jobs on Linux runners?

Answer: B

Explanation:
Under the GitHub Actions minute-multiplier model tested by this question, jobs executed on GitHub-hosted Windows runners consume included minutes at twice the rate of equivalent Linux-runner jobs. Linux has a multiplier of 1, while Windows has a multiplier of 2; historically macOS used a substantially higher multiplier. Because CodeQL advanced setup can execute as a GitHub Actions workflow, the operating system selected with runs-on affects Actions consumption in the same way as other GitHub-hosted workflows.
GitHub's newer billing documentation increasingly expresses runner usage through operating-system-specific per-minute pricing rather than only multiplier terminology, but the exam question specifically tests the established Windows-versus-Linux minute multiplier. Therefore, the expected answer is 2x higher.


NEW QUESTION # 77
Where can you find a deleted line of code that contained a secret value?

Answer: C

Explanation:
Secrets committed and then deleted are still accessible in the repository's Git history. To locate them, navigate to the Commits tab. GitHub's secret scanning can detect secrets in both current and historical commits, which is why remediation should also include revoking the secret, not just removing it from the latest code.


NEW QUESTION # 78
You are viewing a code scanning alert. What detail is included in the alert?

Answer: A

Explanation:
A code scanning alert provides information that helps a developer identify and understand the security problem detected by the analysis tool. GitHub specifically displays the line of code that triggered the alert, together with properties such as severity, security severity, the nature of the problem, and when the issue was introduced. CodeQL-generated alerts may additionally contain remediation guidance and data-flow information. Secret values are handled through secret scanning rather than being shown as the defining detail of a code scanning alert. GitHub also does not list all users with repository Read access within an individual alert, and a CWE submission date is not the primary alert-location information. The source-code location is therefore the correct answer.


NEW QUESTION # 79
A dependency has a known vulnerability. What does the warning message include?

Answer: B

Explanation:
When a vulnerability is detected, GitHub shows a warning that includes a brief description of the vulnerability. This typically covers the name of the CVE (if available), a short summary of the issue, severity level, and potential impact. The message also links to additional advisory data from the GitHub Advisory Database.
This helps developers understand the context and urgency of the vulnerability before applying the fix.


NEW QUESTION # 80
Which of the following dependencies could trigger a Dependabot alert? (Each answer presents a complete solution. Choose two.)

Answer: A,B

Explanation:
Dependabot alerts can identify vulnerable direct dependencies declared in a manifest and vulnerable indirect or transitive dependencies when GitHub can determine their versions from a lockfile. GitHub's dependency graph extracts dependency information from supported manifest and lock files and compares identified package versions against security advisories in the GitHub Advisory Database. Direct dependencies explicitly declared in manifests therefore qualify for vulnerability detection. Transitive dependencies recorded with resolvable versions in lockfiles can also generate alerts. A "loose" dependency declaration may not provide GitHub with a sufficiently specific installed version to establish that the project actually uses a vulnerable release, while a particular time such as 08:00 UTC has nothing to do with whether a dependency qualifies for an alert. Thus, A and C are correct.


NEW QUESTION # 81
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