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Microsoft GH-500 Exam Overview:
| Certification Vendor: | Microsoft |
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| Exam Name: | GH-500: GitHub Advanced Security |
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| Exam Number: | GH-500 |
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| Exam Price: | $99 USD |
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| Certificate Validity Period: | 1 year |
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| Exam Duration: | 100 minutes |
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| Real Exam Qty: | 40–60 |
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| Passing Score: | 700 / 1000 |
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| Available Languages: | Portuguese (Brazil), Chinese (Simplified), Japanese, German, English, Korean, French, Arabic (Saudi Arabia), Spanish |
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| Exam Format: | Multiple-choice, Scenario-based, Interactive tasks |
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| Recommended Training: | Course GH-500T00: GitHub Advanced Security GitHub Advanced Security Learning Path |
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| Exam Registration: | Pearson VUE Scheduling Microsoft Learn Exam Registration |
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| Sample Questions: | Microsoft GH-500 Sample Questions |
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| Exam Way: | Online proctored or onsite testing via Pearson VUE |
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| Pre Condition: | Familiarity with GitHub fundamentals, CI/CD pipelines, and secure development practices; no mandatory prerequisite exams |
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| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/gh-500 |
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Achieving the Microsoft GH-500 certificate is an excellent way of paying your way in the tech field. However, to become Microsoft GH-500 certified, you will have to crack the Microsoft GH-500 exam. This is a challenging task since preparation for the Microsoft GH-500 Exam demands an inside-out understanding of GH-500 domains and many Microsoft GH-500 test applicants do not have enough time due to their busy routines.
| Topic | Details |
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| 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.
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| 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.
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| 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.
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| 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.
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| 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 (Q14-Q19):
NEW QUESTION # 14
You are configuring a CodeQL workflow for compiled languages. What happens if your workflow uses a language matrix?
- A. Autobuild attempts to build the supported language that has the most source files in the repository.
- B. You may need to install additional software to use the autobuild process.
- C. Autobuild attempts to build each of the languages listed in the matrix.
- D. Analysis of other languages in your repository will fail unless you supply explicit build commands.
Answer: C
Explanation:
When a CodeQL workflow uses a language matrix, the autobuild step attempts to build each compiled language listed in that matrix. This differs from a workflow without a language matrix, where autobuild attempts to build the supported compiled language with the greatest number of source files in the repository.
A matrix is therefore useful when a repository contains multiple languages that require separate CodeQL analysis jobs. GitHub's current CodeQL build documentation explicitly describes this matrix behavior. The analysis may use newer build modes such as none for some compiled languages, depending on language and configuration, but when the workflow specifically uses autobuild with a language matrix, each compiled language represented by that matrix is processed independently. Therefore, option D correctly describes the behavior.
NEW QUESTION # 15
When using the advanced CodeQL code scanning setup, what is the name of the workflow file?
- A. codeql-workflow.yml
- B. codeql-config.yml
- C. codeql-analysis.yml
- D. codeql-scan.yml
Answer: C
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 # 16
What is required to trigger code scanning on a specified branch?
- A. The workflow file must exist in that branch.
- B. The repository must be private.
- C. Developers must actively maintain the repository.
- D. Secret scanning must be enabled on the repository.
Answer: A
NEW QUESTION # 17
How does GitHub Advanced Security (GHAS) help integrate security into each step of the software development life cycle?
- A. By automating security checks with every pull request, surfacing issues in the context of the development workflow.
- B. By generating alerts for outdated dependencies in a project.
- C. By providing access to curated security intelligence from millions of developers and security researchers around the world.
- D. By providing a comprehensive dashboard summarizing the security status of the repository.
Answer: A
NEW QUESTION # 18
When using the advanced CodeQL code scanning setup, what is the name of the workflow file?
- A. codeql.yml
- B. codeql-workflow.yml
- C. codeql-config.yml
- D. codeql-scan.yml
Answer: A
Explanation:
If you already enabled CodeQL with the default settings, select the menu labeled "...", then select Switch to advanced. Select Disable CodeQL when prompted. Don't worry, we will re-enable it after we've completed the advanced setup process.
After selecting or switching to advanced, you'll be taken to a GitHub Actions workflow file named codeql.yml. You can find it in your Web Goat repository's /.github/workflows directory. This is the file we use to run and configure CodeQL.
NEW QUESTION # 19
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