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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
  • 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
  • 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 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 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.

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Microsoft GitHub Advanced Security Sample Questions (Q92-Q97):

NEW QUESTION # 92
Which GitHub security feature should you use to see details of any vulnerable dependency versions within a pull request?

Answer: A

Explanation:
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


NEW QUESTION # 93
Assuming that no custom patterns are configured, what type of secret is detected by secret scanning?

Answer: D

Explanation:
GitHub secret scanning detects and alerts on sensitive data exposure, such as API keys and credentials, in your code repositories.


NEW QUESTION # 94
Which of the following would raise secret scanning alerts?

Answer: C

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 # 95
Which of the following is the best way to prevent developers from adding secrets to the repository?

Answer: A

Explanation:
The best proactive control is push protection. It scans for secrets during a git push and blocks the commit before it enters the repository.
Other options (like CODEOWNERS or security managers) help with oversight but do not prevent secret leaks.
Making a repo public would increase the risk, not reduce it.


NEW QUESTION # 96
What is the best method to ensure all new code is scanned for vulnerabilities?

Answer: B

Explanation:
To systematically analyze newly introduced source code for security weaknesses, you should configure code scanning. GitHub code scanning can use CodeQL or supported third-party analysis tools and can run automatically when developers push changes or create pull requests. This places vulnerability detection directly into the development workflow rather than depending on manual review. The extended CodeQL query suite broadens the set of queries executed, but it only has an effect after code scanning itself is configured. CODEOWNERS determines who reviews specific paths and does not perform vulnerability analysis. A security policy explains how vulnerabilities should be reported but does not scan source code.
Therefore, enabling and properly configuring code scanning is the foundational mechanism for ensuring new code is automatically analyzed.


NEW QUESTION # 97
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