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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
  • 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 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 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
  • 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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Microsoft GitHub Advanced Security Sample Questions (Q25-Q30):

NEW QUESTION # 25
Which syntax in a query suite tells CodeQL to look for one or more specified .ql files?

Answer: B

Explanation:
Locating queries to add to a query suite
When creating a query suite, you first need to specify the locations of the queries that you want to select. You can define the location of one or more queries using:
A query instruction: Tells CodeQL to look for one or more specified .ql files:
- query: <path-to-query>
The argument must be one or more file paths, relative to the CodeQL pack containing the suite definition.


NEW QUESTION # 26
Where can you use CodeQL analysis for code scanning? (Each answer presents part of the solution. Choose two.)

Answer: B,C

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 # 27
Where can you find the vulnerable dependencies that GitHub detected in your repository?

Answer: D

Explanation:
Known vulnerable dependencies detected in a repository are presented as Dependabot alerts. GitHub uses the dependency graph to determine which packages and versions the repository depends on and compares that information with vulnerability data from the GitHub Advisory Database. When a match is found, an alert appears in the repository's Security and quality area under Dependabot vulnerabilities. Each alert can provide the affected dependency, vulnerability details, severity, the affected manifest or lockfile, and a secure version when one is available. Secret scanning alerts relate to exposed credentials, while code scanning alerts represent vulnerabilities or coding errors in source code. Security advisories are vulnerability records and disclosure mechanisms rather than the repository-specific list of vulnerable dependencies.


NEW QUESTION # 28
When using CodeQL, what extension stores query suite definitions?

Answer: B

Explanation:
Query suite definitions in CodeQL are stored using the .qls file extension. A query suite defines a collection of queries to be run during an analysis and allows for grouping them based on categories like language, security relevance, or custom filters.
In contrast:
.ql files are individual queries.
.qll files are libraries used by .ql queries.
.yml is used for workflows, not query suites.


NEW QUESTION # 29
What step is required to run a SARIF-compatible (Static Analysis Results Interchange Format) tool on GitHub Actions?

Answer: D

Explanation:
About SARIF file uploads for code scanning
GitHub creates code scanning alerts in a repository using information from Static Analysis Results Interchange Format (SARIF) files. SARIF files can be uploaded to a repository using the API or GitHub Actions.
You can upload the results using GitHub Actions, the code scanning API, or the CodeQL CLI.
The best upload method will depend on how you generate the SARIF file, for example, if you use:
* GitHub Actions to run the CodeQL action, there is no further action required. The CodeQL action uploads the SARIF file automatically when it completes analysis.
* GitHub Actions to run a SARIF-compatible analysis tool, you could update the workflow to include a final step that uploads the results.
Uploading a code scanning analysis with GitHub Actions
To use GitHub Actions to upload a third-party SARIF file to a repository, you'll need a workflow.
Your workflow will need to use the upload-sarif action, which is part of the github/codeql-action repository. It has input parameters that you can use to configure the upload.
* The CodeQL CLI to run code scanning in your CI system, you can use the CLI to upload results to GitHub


NEW QUESTION # 30
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