GH-500 Trainingsmaterialien: GitHub Advanced Security & GH-500 Lernmittel & Microsoft GH-500 Quiz

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Microsoft GH-500 Exam Overview:

Certification Vendor:Microsoft
Exam Name:GH-500: GitHub Advanced Security
Exam Number:GH-500
Certificate Validity Period:1 year
Passing Score:700 / 1000
Exam Format:Multiple-choice, Scenario-based, Interactive tasks
Real Exam Qty:40–60
Available Languages:Spanish, Chinese (Simplified), French, Japanese, English, Portuguese (Brazil), German, Korean, Arabic (Saudi Arabia)
Exam Duration:100 minutes
Exam Price:$99 USD
Recommended Training:Course GH-500T00: GitHub Advanced Security
GitHub Advanced Security Learning Path
Exam Registration:Pearson VUE Scheduling
Microsoft Learn Exam Registration
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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GH-500 Musterprüfungsfragen - GH-500Zertifizierung & GH-500Testfagen

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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 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 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.
Thema 4
  • 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 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 (Q91-Q96):

91. Frage
Which syntax in a query suite tells CodeQL to look for one or more specified .ql files?

Antwort: B

Begründung:
Locating queries to add to a query suite
When creating a query suite, you first need to specify the locations of the queries that you want to select. You can define the location of one or more queries using:
A query instruction: Tells CodeQL to look for one or more specified .ql files:
- query: <path-to-query>
The argument must be one or more file paths, relative to the CodeQL pack containing the suite definition.


92. Frage
What kind of repository permissions do you need to request a Common Vulnerabilities and Exposures (CVE) identification number for a security advisory?

Antwort: A

Begründung:
Requesting a CVE ID for a security advisory in a GitHub repository requires Admin permissions. This level of access is necessary because it involves managing sensitive security information and coordinating with external entities to assign a CVE, which is a formal process that can impact the public perception and security posture of the project.
: GitHub Docs - About repository security advisories


93. Frage
Which details do you have to provide to create a custom pattern for secret scanning? Each answer presents part of the solution. (Choose two.)

Antwort: B,C

Begründung:
Defining a custom pattern for an organization
Before defining a custom pattern, you must ensure that you enable secret scanning for the repositories that you want to scan in your organization. You can use security configurations to enable secret scanning on all repositories in your organization.
1. In the upper-right corner of GitHub, click your profile picture, then click Your organizations.
2. Next to the organization, click Settings.
3. In the "Security" section of the sidebar, select the Advanced Security dropdown menu, then click Global settings.
4. Under "Custom patterns", click New pattern.
*-> 5. Enter the details for your new custom pattern. You must at least provide the name for your pattern, and a regular expression for the format of your secret pattern.
Example:


94. Frage
The autobuild step in the CodeQL workflow has failed. What should you do?

Antwort: B

Begründung:
If autobuild fails (which attempts to automatically detect how to build your project), you should disable it in your workflow and replace it with explicit build commands , using steps like run: make or run: ./gradlew build.
This ensures CodeQL can still extract and analyze the code correctly.
: GitHub Docs - CodeQL Build Configurations for Compiled Languages


95. Frage
What does a CodeQL database of your repository contain?

Antwort: C

Begründung:
CodeQL databases contain queryable data extracted from a codebase, for a single language at a particular point in time. The database contains a full, hierarchical representation of the code, including a representation of the abstract syntax tree, the data flow graph, and the control flow graph.
Each language has its own unique database schema that defines the relations used to create a database. The schema provides an interface between the initial lexical analysis during the extraction process, and the actual complex analysis using CodeQL. The schema specifies, for instance, that there is a table for every language construct.
For each language, the CodeQL libraries define classes to provide a layer of abstraction over the database tables. This provides an object-oriented view of the data which makes it easier to write queries.


96. Frage
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