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Microsoft GH-500 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • 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 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.
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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Free PDF Quiz 2026 GH-500: GitHub Advanced Security – Trustable Online Tests

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Microsoft GitHub Advanced Security Sample Questions (Q52-Q57):

NEW QUESTION # 52
You have enabled security updates for a repository. When does GitHub mark a Dependabot alert as resolved for that repository?

Answer: A

Explanation:
A Dependabot alert is marked as resolved only after the related pull request is merged into the repository. This indicates that the vulnerable dependency has been officially replaced with a secure version in the active codebase.
Simply generating a PR or passing checks does not change the alert status; merging is the key step.


NEW QUESTION # 53
What should you do after receiving an alert about a dependency added in a pull request?

Answer: C

Explanation:
If an alert is raised on a pull request dependency , best practice is to update the dependency to a secure version before merging the PR. This prevents the vulnerable version from entering the main codebase.
Merging or deploying the PR without fixing the issue exposes your production environment to known risks.
: GitHub Docs - Reviewing Dependabot Alerts in Pull Requests


NEW QUESTION # 54
Which of the following steps should you follow to integrate CodeQL into a third-party continuous integration system? (Each answer presents part of the solution. Choose three.)

Answer: A,C,E

Explanation:
When integrating CodeQL outside of GitHub Actions (e.g., in Jenkins, CircleCI):
Install the CLI: Needed to run CodeQL commands.
Analyze code: Perform the CodeQL analysis on your project with the CLI.
Upload scan results: Export the results in SARIF format and use GitHub's API to upload them to your repo's security tab.
You don't need to write custom queries unless extending functionality. "Processing alerts" happens after GitHub receives the results.


NEW QUESTION # 55
You are managing code scanning alerts for your repository. You receive an alert highlighting a problem with data flow. What do you click for additional context on the alert?

Answer: A

Explanation:
When dealing with a data flow issue in a code scanning alert, clicking on "Show paths" provides a detailed view of the data's journey through the code. This includes the source of the data, the path it takes, and where it ends up (the sink). This information is crucial for understanding how untrusted data might reach sensitive parts of your application and helps in identifying where to implement proper validation or sanitization.


NEW QUESTION # 56
What YAML syntax do you use to exclude certain files from secret scanning?

Answer: D

Explanation:
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.


NEW QUESTION # 57
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