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GH-500 - Fantastic GitHub Advanced Security Valid Test Voucher

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Microsoft GH-500 Exam Syllabus Topics:

Topic
Details

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 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 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 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 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 (Q53-Q58):

NEW QUESTION # 53
When configuring code scanning with CodeQL, what are your options for specifying additional queries? (Each answer presents part of the solution. Choose two.)

• A. github/codeql
• B. Packs
• C. Queries
• D. Scope

Answer: B,C

Explanation:
You can customize CodeQL scanning by including additional query packs or by specifying individual queries:
Packs: These are reusable collections of CodeQL queries bundled into a single package.
Queries: You can point to specific files or directories containing .ql queries to include in the analysis.
github/codeql refers to a pack by name but is not a method or field. Scope is not a valid field used for configuration in this context.

 

NEW QUESTION # 54
How many alerts are created when two instances of the same secret value are in the same repository?

• A. 0
• B. 1
• C. 2
• D. 3

Answer: A

Explanation:
When multiple instances of the same secret value appear in a repository, only one alert is generated. Secret scanning works by identifying exposed credentials and token patterns, and it groups identical matches into a single alert to reduce noise and avoid duplication.
This makes triaging easier and helps teams focus on remediating the actual exposed credential rather than reviewing multiple redundant alerts.

 

NEW QUESTION # 55
What combination of security measures helps to mitigate risks throughout the SDLC (Software Development Life Cycle)?

• A. Search for potential security vulnerabilities, detect secrets, and show the full impact of changes to dependencies
• B. View alerts about dependencies that are known to contain security vulnerabilities
• C. Confidentially report security vulnerabilities and privately discuss and fix security vulnerabilities in your repository's code
• D. Automatically raise pull requests, which reduces your exposure to older versions of dependencies

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 # 56
Where can you view code scanning results from CodeQL analysis?

• A. The repository's code scanning alerts
• B. A CodeQL query pack
• C. At Security advisories
• D. A CodeQL database

Answer: A

Explanation:
All results from CodeQL analysis appear under the repository's code scanning alerts tab. This section is part of the Security tab and provides a list of all current, fixed, and dismissed alerts found by CodeQL.
A CodeQL database is used internally during scanning but does not display results. Query packs contain rules, not results. Security advisories are for published vulnerabilities, not per-repo findings.

 

NEW QUESTION # 57
What does a CodeQL database of your repository contain?

• A. A build for Go projects to set up the project
• B. A representation of all of the source code
• C. Build commands for C/C++, C#, and Java
• D. A build of the code and extracted data

Answer: D

Explanation:
GitHub
Agentic AI for AppSec Teams
Explanation:
Comprehensive and Detailed Explanation:
A CodeQL database contains a representation of your codebase, including the build of the code and extracted data. This database is used to run CodeQL queries to analyze your code for potential vulnerabilities and errors.
GitHub Docs

 

NEW QUESTION # 58
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