GH-500 Aktuelle Prüfung - GH-500 Prüfungsguide & GH-500 Praxisprüfung

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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 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.
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 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.

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GH-500 Vorbereitungsfragen, GH-500 Prüfungsfragen

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Microsoft GitHub Advanced Security GH-500 Prüfungsfragen mit Lösungen (Q100-Q105):

100. Frage
Which of the following is the most complete method for Dependabot to find vulnerabilities in third- party dependencies?

Antwort: B

Begründung:
Security Alerts
Dependabot security alerts is a native GitHub service designed for the efficient management of vulnerable dependencies. It continuously scans the project's dependency graph, comparing it to the GitHub security advisory database. Upon detecting a vulnerable dependency version, it prompts developers with a security alert. Dependabot leverages the dependency graph to execute vulnerability scans. To generate this graph, it parses both manifest and lock files residing in the repository's default branch and constructs a comprehensive representation of the complete dependency tree.
Note: GitHub Advisory Database is one of the data sources that GitHub uses to identify vulnerable dependencies and malware. It's a free, curated database of security advisories for common package ecosystems on GitHub. It includes both data reported directly to GitHub from GitHub Security Advisories, as well as official feeds and community sources. This data is reviewed and curated by GitHub to ensure that false or unactionable information is not shared with the development community.


101. Frage
You have a GitHub Enterprise Cloud Organization that uses GitHub Advanced Security code scanning with CodeQL advanced setup.
The security engineering team at your company maintains a private repository named Repo1 that stores custom CodeQL queries and query suites for multiple languages.
You discover that changes to the custom queries can introduce noisy results and break existing tests. The regressions are detected only after the queries are deployed to production repositories.
You add a workflow step that runs CodeQL query tests on every pull request (PR). The step runs the following CodeQL CLI command.
codeql test run ./tests
You need to ensure that the workflow fails when query tests detect regressions.
What should you configure in the workflow?

Antwort: B

Begründung:
To ensure that the GitHub Actions workflow fails when query tests detect regressions, you must configure the command or step to return a non-zero exit code on test failures.
By default, the codeql test run command executes unit tests by comparing the query output against expected .expected files.
Default Behavior: If any tests fail (meaning actual results deviate from the expected results), the CodeQL CLI natively emits a non-zero exit code (typically 1).
CI Integration: In GitHub Actions, any step that executes a command returning a non-zero exit code will automatically fail the step and halt the workflow.
The Risk: If the workflow is configured to suppress errors (e.g., using || true in a shell script, wrapping it in an accidental error-ignoring configuration, or setting continue-on-error: true at the step level), it will mask the failure by returning an exit code of 0.
Reference:
https://github.com/advanced-security/codeql-development-template/blob/main/resources/cli/qlt/qlt_test_run_execute-unit-tests.prompt.md


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

Antwort: C

Begründung:
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.


103. Frage
What YAML syntax do you use to exclude certain files from secret scanning?

Antwort: C

Begründung:
Excluding folders and files from secret scanning
You can customize secret scanning to automatically close alerts for secrets found in specific directories or files by configuring a secret_scanning.yml file in your repository.
Under Edit new file, type paths-ignore: followed by the paths you want to exclude from secret scanning. This tells secret scanning to automatically close alerts for everything in the docs directory.


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

Antwort: A

Begründung:
You can use the dependency review action to help enforce dependency reviews on pull requests in your repository. The dependency review action scans your pull requests for dependency changes and raises an error if any new dependencies have known vulnerabilities.
Note: About dependency review
Dependency review helps you understand dependency changes and the security impact of these changes at every pull request. It provides an easily understandable visualization of dependency changes with a rich diff on the "Files Changed" tab of a pull request. Dependency review informs you of:
Which dependencies were added, removed, or updated, along with the release dates How many projects use these components Vulnerability data for these dependencies Dependency review allows you to "shift left". You can use the provided predictive information to catch vulnerable dependencies before they hit production.


105. Frage
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Heutzutage, wo IT-Branche schnell entwickelt ist, müssen wir die IT-Fachleuten mit anderen Augen sehen. Sie haben uns viele unglaubliche Bequemlichkeiten nach ihrer spitzen Technik geboten und dem Staat sowie Unternehmen eine Menge Menschenkräfte sowie Ressourcen erspart. Sie beziehen sicher ein hohes Gehalt. Wollen Sie gleich wie sie werden? Dann müssen Sie zuerst die Microsoft GH-500 Zertifizierungsprüfung bestehen.

GH-500 Vorbereitungsfragen: https://www.it-pruefung.com/GH-500.html

Laden Sie die neuesten It-Pruefung GH-500 PDF-Versionen von Prüfungsfragen kostenlos von Google Drive herunter: https://drive.google.com/open?id=1VtYNBCUzrBzlXPug84P78GOUTyJImih6