GH-500 Valid Examcollection - GH-500 Training Tools

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Microsoft GH-500 Exam Syllabus Topics:

TopicDetails
Topic 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.
Topic 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.
Topic 3
  • 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 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.
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 (Q11-Q16):

NEW QUESTION # 11
Where can you find a deleted line of code that contained a secret value?

Answer: A

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 # 12
A secret scanning alert should be closed as "used in tests" when a secret is:

Answer: B

Explanation:
If a secret is intentionally used in a test environment and poses no real-world security risk, you may close the alert with the reason "used in tests". This helps reduce noise and clarify that the alert was reviewed and accepted as non-critical.
Just being in a test file isn't enough unless its purpose is purely for testing.


NEW QUESTION # 13
Where can you find the vulnerable dependencies that GitHub detected in your repository?

Answer: C

Explanation:
Identifying vulnerabilities in your project's dependencies with Dependabot alerts Dependabot generates Dependabot alerts when known vulnerabilities are detected in dependencies that your project uses.
Dependabot alerts tab
If GitHub discovers insecure dependencies in your project, you can view details on the Dependabot alerts tab of your repository. Then, you can update your project to resolve or dismiss the alert.


NEW QUESTION # 14
How would you build your code within the CodeQL analysis workflow? (Each answer presents a complete solution. Choose two.)

Answer: A,D

Explanation:
Comprehensive and Detailed Explanation:
When setting up CodeQL analysis for compiled languages, there are two primary methods to build your code:
GitHub Docs
Autobuild: CodeQL attempts to automatically build your codebase using the most likely build method. This is suitable for standard build processes.
GitHub Docs
Custom Build Steps: For complex or non-standard build processes, you can implement custom build steps by specifying explicit build commands in your workflow. This provides greater control over the build process.
GitHub Docs
The init action initializes the CodeQL analysis but does not build the code. The jobs.analyze.runs-on specifies the operating system for the runner but is not directly related to building the code. Uploading compiled binaries is not a method supported by CodeQL for analysis.


NEW QUESTION # 15
When using the advanced CodeQL code scanning setup, what is the name of the workflow file?

Answer: C

Explanation:
Comprehensive and Detailed Explanation:
In the advanced setup for CodeQL code scanning, GitHub generates a workflow file named codeql-analysis.yml. This file is located in the .github/workflows directory of your repository. It defines the configuration for the CodeQL analysis, including the languages to analyze, the events that trigger the analysis, and the steps to perform during the workflow.


NEW QUESTION # 16
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