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Whatever your professional, working towards a GitHub Advanced Security GH-500 certification or designation takes a significant amount of effort and time. Once you have put all your effort, and investment and prepared well then you will be in a position to pass the GitHub Advanced Security GH-500 Certification Exam. But once you get success in the GitHub Advanced Security GH-500 test you’ll be eligible to avail all the personal and professional benefits associated with GitHub Advanced Security GH-500 certification.

Microsoft GH-500 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft GitHub Advanced Security (GH-500)
Exam Number:GH-500
Certificate Validity Period:1 year (renewable via Microsoft certification renewal)
Exam Format:Scenario-based questions, Multiple response, Case studies, Multiple choice
Real Exam Qty:40-60 (approx.)
Related Certifications:GitHub Administration
GitHub Actions
Microsoft DevOps Engineer Expert
Exam Duration:120 minutes
Passing Score:700 (on a scale of 1000)
Exam Price:$165 USD (may vary by region)
Available Languages:English
Recommended Training:GitHub Advanced Security Documentation
Microsoft Learn - GitHub Advanced Security
Exam Registration:Pearson VUE Microsoft Exams
Microsoft Certification Exam Page
Sample Questions:Microsoft GH-500 Sample Questions
Exam Way:Online proctored exam or authorized testing center (Pearson VUE)
Pre Condition:Recommended: familiarity with GitHub, DevSecOps practices, and CI/CD pipelines. No formal prerequisites required.
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/exams/gh-500/

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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 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 3
  • 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 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 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.

Microsoft GitHub Advanced Security Sample Questions (Q49-Q54):

NEW QUESTION # 49
Which patterns are secret scanning validity checks available to?

Answer: A

Explanation:
Validity checks - where GitHub verifies if a secret is still active - are available for partner patterns only. These are secrets issued by GitHub's trusted partners (like AWS, Slack, etc.) and have APIs for GitHub to validate token activity status.
Custom patterns and high entropy patterns do not support automated validity checks.


NEW QUESTION # 50
Assuming that no custom Dependabot behavior is configured, who has the ability to merge a pull request created via Dependabot security updates?

Answer: C

Explanation:
Managing pull requests for dependency updates
You manage pull requests raised by Dependabot in much the same way as other pull requests, but there are some extra options.
Who can use this feature?
Users with write access


NEW QUESTION # 51
Which of the following features helps to prioritize secret scanning alerts that present an immediate risk?

Answer: C

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.


NEW QUESTION # 52
Which syntax in a query suite tells CodeQL to look for one or more specified .ql files?

Answer: C


NEW QUESTION # 53
The autobuild step in the CodeQL workflow has failed. What should you do?

Answer: D

Explanation:
If auto build fails (which attempts to automatically detect how to build your project), you shoulddisable itin your workflow andreplace it with explicit build commands, using steps like run:
make or run: ./gradlew build.
This ensures CodeQL can still extract and analyze the code correctly.


NEW QUESTION # 54
......

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