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Microsoft GH-500 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 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
  • 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.

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Microsoft GitHub Advanced Security Sample Questions (Q96-Q101):

NEW QUESTION # 96
What combination of security measures helps to mitigate risks throughout the SDLC (Software Development Life Cycle)?

Answer: A

Explanation:
These three features provide a complete layer of defense:
Code scanning identifies security flaws in your source code
Secret scanning detects exposed credentials
Dependency review shows the impact of package changes during a pull request Together, they give developers actionable insight into risk and coverage throughout the SDLC.


NEW QUESTION # 97
After defining a secret scanning custom pattern, what is the final step before publishing the pattern?

Answer: C

Explanation:
GitHub requires you to perform a dry run before publishing a new secret scanning custom pattern. After defining the pattern and providing a sample test string, you select Save and dry run. GitHub searches the relevant repository data without creating secret scanning alerts and returns a sample of matching results. You should review these results for false positives, adjust the regular expression or additional match requirements if necessary, and repeat the dry run until the pattern behaves as intended. Only after a successful dry run and review should you publish the custom pattern. Push protection is optional and is enabled after the pattern has been published; GitHub explicitly notes that the option is not available until the dry run succeeds and the pattern is published.


NEW QUESTION # 98
Which CodeQL query suite provides queries of lower severity than the default query suite?

Answer: C

Explanation:
The security-extended query suite includes additional CodeQL queries that detect lower severity issues than those in the default security-and-quality suite.
It's often used when projects want broader visibility into code hygiene and potential weak spots beyond critical vulnerabilities.
The other options listed are paths to language packs , not query suites themselves.
: GitHub Docs - CodeQL Query Suite Types


NEW QUESTION # 99
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 # 100
When using the advanced CodeQL code scanning setup, what is the name of the workflow file?

Answer: A

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 # 101
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