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Microsoft GH-500 Exam Syllabus Topics:

Topic	Details
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	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	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 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 5	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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Microsoft GitHub Advanced Security Sample Questions (Q97-Q102):

NEW QUESTION # 97
You have a GitHub repository named Repo1that runs CodeQL code scanning. Repo1contains both Java and Kotlin source code. Repo1generates additional source files during compilation.
Recent alerts indicate that Kotlin files cannot be processed without a build.
You need to ensure that CodeQL analyzes both the Java files and the Kotlin files and includes the generated source files in the CodeQL database.
What should you do?

A. Set the CodeQL build mode to manual.
B. Set the CodeQL build mode to autobuild.
C. Set the CodeQL build mode to none.
D. Add Kotlin to the CodeQL languages list.

Answer: D

Explanation:
To fix this issue, you must switch your CodeQL workflow execution configuration from using the default "none" build mode to a manual build step configuration. For repositories that mix Java and Kotlin alongside dynamic code generation during compilation, explicit build commands ensure CodeQL intercepts the compilation process to catalog the generated source files and analyze the Kotlin files completely.
Update the CodeQL Initialization Language Matrix
Ensure CodeQL treats both languages as unified by specifying java-kotlin inside your initialization step.
Update the languages parameter in the github/codeql-action/init step.Use java-kotlin instead of java to instruct the extractor to capture both source formats.
- name: Initialize CodeQL
uses: github/codeql-action/init@v3
with:
languages: 'java-kotlin'
# Optional: explicitly tell CodeQL not to run default build-mode none
build-mode: 'manual'
Reference:
https://docs.github.com/en/code-security/reference/code-scanning/troubleshoot-analysis-errors/kotlin-detected-in-no-build

NEW QUESTION # 98
As a developer with write access, you navigate to a code scanning alert in your repository. When will GitHub close this alert?

A. After you fix the code by committing within the pull request
B. When you use data-flow analysis to find potential security issues in code
C. After you triage the pull request containing the alert
D. After you find the code and click the alert within the pull request

Answer: A

Explanation:
GitHub automatically closes a code scanning alert when the vulnerable code is fixed in the same branch where the alert was generated , usually via a commit inside a pull request . Simply clicking or triaging an alert does not resolve it. The alert is re-evaluated after each push to the branch, and if the issue no longer exists, it is marked as resolved.
: GitHub Docs - Code Scanning Alerts Lifecycle

NEW QUESTION # 99
Where can you use CodeQL analysis for code scanning? (Each answer presents part of the solution. Choose two.)

A. In a workflow
B. In an external continuous integration (CI) system
C. In a third-party Git repository
D. In the Files changed tab of the pull request

Answer: A,B

Explanation:
* In a workflow : GitHub Actions workflows are the most common place for CodeQL code scanning.
The codeql-analysis.yml defines how the analysis runs and when it triggers.
* In an external CI system : GitHub allows you to run CodeQL analysis outside of GitHub Actions.
Once complete, the results can be uploaded using the upload-sarif action to make alerts visible in the repository.
You cannot run or trigger analysis from third-party repositories directly, and the Files changed tab in pull requests only shows diff - not analysis results.
: GitHub Docs - Using CodeQL with CI and workflows

NEW QUESTION # 100
By default, where will secret scanning look in a repository in order to execute its job? Each correct answer presents part of the solution. (Choose three.)

A. all branches
B. selected files in the repository
C. dependencies
D. all files in the repository
E. full commit history

Answer: A,B,E

Explanation:
Secret scanning scans your entire Git history[D] on all branches [E] present in your GitHub repository for secrets, even if the repository is archived. GitHub will also periodically run a full Git history scan for new secret types in existing content in public repositories where secret scanning is enabled [C, not A] when new supported secret types are added.
Additionally, secret scanning scans:
Descriptions and comments in issues
Titles, descriptions, and comments, in open and closed historical issues. A notification is sent to the relevant partner when a historical partner pattern is detected.
Titles, descriptions, and comments in pull requests
Titles, descriptions, and comments in GitHub Discussions Wikis

NEW QUESTION # 101
How does GitHub Advanced Security (GHAS) help integrate security into each step of the software development life cycle?

A. By providing a comprehensive dashboard summarizing the security status of the repository.
B. By providing access to curated security intelligence from millions of developers and security researchers around the world.
C. By generating alerts for outdated dependencies in a project.
D. By automating security checks with every pull request, surfacing issues in the context of the development workflow.

Answer: D

NEW QUESTION # 102
......

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