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Microsoft GH-500 Exam Syllabus Topics:

Topic
Details

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 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.

Topic 5

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.

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Microsoft GitHub Advanced Security Sample Questions (Q63-Q68):

NEW QUESTION # 63
Which alerts do you see in the repository's Security tab? (Each answer presents part of the solution. Choose three.)

A. Repository permissions
B. Secret scanning alerts
C. Dependabot alerts
D. Code scanning alerts
E. Security status alerts

Answer: B,C,D

Explanation:
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.

NEW QUESTION # 64
Which of the following secret scanning features can verify whether a secret is still active?

A. Validity checks
B. Push protection
C. Branch protection
D. Custom patterns

Answer: A

Explanation:
Validity checks, also called secret validation, allow GitHub to check if a detected secret is still active. If verified as live, the alert is marked as "valid", allowing security teams to prioritize the most critical leaks.
Push protection blocks secrets but does not check their validity. Custom patterns are user-defined and do not include live checks.

NEW QUESTION # 65
What filter or sort settings can be used to prioritize the secret scanning alerts that present the most risk?

A. Sort to display the oldest first
B. Select only the custom patterns
C. Sort to display the newest first
D. Filter to display active secrets

Answer: D

Explanation:
The best way to prioritize secret scanning alerts is to filter by active secrets - these are secrets GitHub has confirmed are still valid and could be exploited. This allows security teams to focus on high-risk exposures that require immediate attention.
Sorting by time or filtering by custom patterns won't help with risk prioritization directly.

NEW QUESTION # 66
Assuming that no custom Dependabot behavior is configured, who has the ability to merge a pull request created via Dependabot security updates?

A. A repository member of an enterprise organization
B. A user who has write access to the repository
C. A user who has read access to the repository
D. An enterprise administrator

Answer: B

Explanation:
Comprehensive and Detailed Explanation:
By default, users with write access to a repository have the ability to merge pull requests, including those created by Dependabot for security updates. This access level allows contributors to manage and integrate changes, ensuring that vulnerabilities are addressed promptly.
Users with only read access cannot merge pull requests, and enterprise administrators do not automatically have merge rights unless they have write or higher permissions on the specific repository.

NEW QUESTION # 67
When using CodeQL, how does extraction for compiled languages work?

A. By resolving dependencies to give an accurate representation of the codebase
B. By generating one language at a time
C. By running directly on the source code
D. By monitoring the normal build process

Answer: D

Explanation:
For compiled languages, CodeQL performs extraction by monitoring the normal build process. This means it watches your usual build commands (like make, javac, or dotnet build) and extracts the relevant data from the actual build steps being executed. CodeQL uses this information to construct a semantic database of the application.
This approach ensures that CodeQL captures a precise, real-world representation of the code and its behavior as it is compiled, including platform-specific configurations or conditional logic used during build.

NEW QUESTION # 68
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