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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 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.
Topic 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.
Topic 4
  • 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 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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Microsoft GitHub Advanced Security Sample Questions (Q38-Q43):

NEW QUESTION # 38
Which of the following features helps to prioritize secret scanning alerts that present an immediate risk?

Answer: B

Explanation:
Secret validation checks whether a secret found in your repository is still valid and active with the issuing provider (e.g., AWS, GitHub, Stripe). If a secret is confirmed to be active, the alert is marked as verified , which means it's considered a high-priority issue because it presents an immediate security risk.
This helps teams respond faster to valid, exploitable secrets rather than wasting time on expired or fake tokens.
: GitHub Docs - Secret validation in secret scanning


NEW QUESTION # 39
What filter or sort settings can be used to prioritize the secret scanning alerts that present the most risk?

Answer: B

Explanation:
The best way to prioritize secret scanning alerts is to filter by active secrets - these are secrets GitHub has confirmed are still valid and could be exploited. This allows security teams to focus on high-risk exposures that require immediate attention.
Sorting by time or filtering by custom patterns won't help with risk prioritization directly.


NEW QUESTION # 40
Which of the following is the most complete method for Dependabot to find vulnerabilities in third-party dependencies?

Answer: A

Explanation:
Dependabot builds a dependency graph by analyzing package manifests and lockfiles in your repository. This graph includes both direct and transitive dependencies. It then compares this graph against the GitHub Advisory Database, which includes curated, security-reviewed advisories.
This method provides a comprehensive and automated way to discover all known vulnerabilities across your dependency tree.
: GitHub Docs - About the dependency graph; About Dependabot alerts


NEW QUESTION # 41
Which of the following would raise secret scanning alerts?

Answer: B

Explanation:
A secret scanning alert is raised when sensitive data, such as API keys, passwords, or access tokens, is detected in a code repository, often due to accidental inclusion by developers. The detection uses pattern-matching and entropy analysis to identify high-entropy strings that look like secrets, but can sometimes generate false positives from non-sensitive data like UUIDs. Alerts can also occur when a developer attempts to bypass the push protection feature that prevents secrets from being committed.


NEW QUESTION # 42
When using the advanced CodeQL code scanning setup, what is the name of the workflow file?

Answer: D

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.
References: GitHub Docs - Customizing your advanced setup for code scanning


NEW QUESTION # 43
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