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Microsoft GH-500 Exam Overview:

Certification Vendor:Microsoft
Exam Name:GitHub Advanced Security
Exam Number:GH-500
Real Exam Qty:40-60
Passing Score:700 out of 1000
Certificate Validity Period:1 year
Exam Format:Multiple choice, Drag and drop, Case study
Exam Price:$165 USD
Exam Duration:120 minutes
Available Languages:Korean, Spanish, Chinese (Simplified), English, Japanese, French, German
Related Certifications:GitHub Advanced Security Certification
Sample Questions:Microsoft GH-500 Sample Questions
Exam Way:Online (Proctored) or In-person at a testing center
Pre Condition:No mandatory prerequisites. Recommended to have experience with GitHub and basic understanding of security concepts.
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/github-advanced-security/

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Microsoft GH-500 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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 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 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 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.

Microsoft GitHub Advanced Security Sample Questions (Q116-Q121):

NEW QUESTION # 116
What kind of repository permissions do you need to request a Common Vulnerabilities and Exposures (CVE) identification number for a security advisory?

Answer: D

Explanation:
Anyone with admin permissions to a security advisory can request a CVE identification number.


NEW QUESTION # 117
When does Dependabot alert you of a vulnerability in your software development process?

Answer: B

Explanation:
Dependabot alerts are generated as soon as GitHub detects a known vulnerability in one of your dependencies. GitHub does this by analyzing your repository's dependency graph and matching it against vulnerabilities listed in the GitHub Advisory Database. Once a match is found, the system raises an alert automatically without waiting for a PR or manual action.
This allows organizations to proactively mitigate vulnerabilities as early as possible, based on real-time detection.


NEW QUESTION # 118
What happens when you enable secret scanning on a private repository?

Answer: B

Explanation:
When secret scanning is enabled on a private repository, GitHub performs a read-only analysis of the repository's contents. This includes the entire Git history and files to identify strings that match known secret patterns or custom-defined patterns.
GitHub does not alter the repository, and enabling secret scanning does not automatically enable code scanning or dependency review - each must be configured separately.


NEW QUESTION # 119
If notification and alert recipients are not customized, which users receive notifications about new Dependabot alerts in an affected repository?

Answer: D

Explanation:
Access to Dependabot alerts
You can see all of the alerts that affect a particular project on the repository's Security tab or in the repository's dependency graph.
By default, we notify people with write, maintain, or admin permissions in the affected repositories about new Dependabot alerts.
Write permissionis the minimum levelneeded to be automatically notified.


NEW QUESTION # 120
You are configuring code scanning with CodeQL. What is one impact of using a language matrix in your workflow?

Answer: C

Explanation:
If your workflow uses the language matrix, then CodeQL will only analyze the languages in the matrix.
Note:
The default CodeQL analysis workflow file created after configuring advanced setup for code scanning with CodeQL defines a matrix containing a property named language which lists the languages in your repository that will be analyzed. This matrix has been automatically pre- populated with supported languages detected in your repository. Using the language matrix allows CodeQL to run each language analysis in parallel and to customize analysis for each language. In an individual analysis, the name of the language from the matrix is provided to the init action as the argument for the languages input. We recommend that all workflows adopt this configuration.
Incorrect:
[Not A]
Using the language matrix allows CodeQL to run each language analysis in parallel.


NEW QUESTION # 121
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