GH-500 Schulungsangebot, GH-500 Testing Engine, GitHub Advanced Security Trainingsunterlagen

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Microsoft GH-500 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft GitHub Advanced Security (GH-500)
Exam Number:GH-500
Exam Format:Multiple choice, Case studies, Scenario-based questions, Multiple response
Certificate Validity Period:1 year (renewable via Microsoft certification renewal)
Available Languages:English
Passing Score:700 (on a scale of 1000)
Related Certifications:Microsoft DevOps Engineer Expert
GitHub Administration
GitHub Actions
Exam Duration:120 minutes
Real Exam Qty:40-60 (approx.)
Exam Price:$165 USD (may vary by region)
Recommended Training:GitHub Advanced Security Documentation
Microsoft Learn - GitHub Advanced Security
Exam Registration:Pearson VUE Microsoft Exams
Microsoft Certification Exam Page
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/

>> GH-500 Originale Fragen <<

Die seit kurzem aktuellsten Microsoft GH-500 Prüfungsunterlagen, 100% Garantie für Ihen Erfolg in der GitHub Advanced Security Prüfungen!

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Microsoft GH-500 Prüfungsplan:

ThemaEinzelheiten
Thema 1
  • 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.
Thema 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.
Thema 3
  • 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.
Thema 4
  • 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.
Thema 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 GH-500 Prüfungsfragen mit Lösungen (Q113-Q118):

113. Frage
Where is secret scanning enabled on a private repository?

Antwort: A

Begründung:
About enabling secure access to private registries
If your organization uses private registries, providing code scanning and Dependabot secure access to these registries will improve code analysis and allow Dependabot to update a wider range of dependencies.
About the importance of providing access to private registries
When a repository uses code stored in a private registry, some security features need access to the registry to enable them to work effectively. Without access to all the dependencies of a repository, code scanning default setup and Dependabot are limited.
Code scanning default setup access to private registries
If you do not define access to the private registries your organization uses, then code scanning will only gather necessary data from dependencies available in public registries.
Defining registry access for code scanning default setup
You need to be an organization owner to set up access to private registries in the user interface.
You can also use the REST API with organization owner or {read,write}_org_private_registries permission.
Note:
1. On the Settings tab for the organization, scroll down to the "Security" section and select Secrets and variables.
2. In the expanded list of secrets and variables, select Private registries to display the "Private Registries" page.
3. Select New private registry to add access details for a private registry.
4. Use the URL and Type fields to define the location and type of the registry:


114. Frage
When using CodeQL, how does extraction for compiled languages work?

Antwort: B

Begründung:
For compiled languages, CodeQL performs extraction bymonitoring 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.


115. Frage
In the pull request, how can developers avoid adding new dependencies with known vulnerabilities?

Antwort: D

Begründung:
To detect and block vulnerable dependencies before merge, developers should use the Dependency Review GitHub Action in their pull request workflows. It scans all proposed dependency changes and flags any packages with known vulnerabilities.
This is a preventative measure during development, unlike Dependabot, which reacts after the fact.


116. Frage
Assuming that no custom patterns are configured, what type of secret is detected by secret scanning?

Antwort: D

Begründung:
GitHub secret scanning detects and alerts on sensitive data exposure, such as API keys and credentials, in your code repositories.


117. Frage
Which of the following is the best way to prevent developers from adding secrets to the repository?

Antwort: A

Begründung:
The best proactive control is push protection. It scans for secrets during a git push and blocks the commit before it enters the repository.
Other options (like CODEOWNERS or security managers) help with oversight but do not prevent secret leaks.
Making a repo public would increase the risk, not reduce it.


118. Frage
......

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