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Microsoft GH-500 Exam Syllabus Topics:

TopicDetails
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 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 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 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 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 (Q119-Q124):

NEW QUESTION # 119
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.)

Answer: B,C,E

Explanation:
GitHub secret scanning examines the repository comprehensively rather than limiting analysis to selected files or dependency metadata. GitHub states that secret scanning scans the entire Git history across all branches for supported secrets. Consequently, both current files and historical versions of files can be inspected, which is why simply deleting a leaked credential in a later commit does not eliminate the security risk. The feature searches repository content for supported provider, generic, and other enabled secret patterns. Dependencies themselves are handled primarily through dependency graph and Dependabot functionality and are not a secret-scanning scope category. Therefore, the correct selections are all branches, the full commit history, and all files in the repository.


NEW QUESTION # 120
Which security feature shows a vulnerable dependency in a pull request?

Answer: B

Explanation:
Configuring the dependency review action
You can use the dependency review action to catch vulnerabilities before they are added to your project.
About the dependency review action
The "dependency review action" refers to the specific action that can report on differences in a pull request within the GitHub Actions context, and add enforcement mechanisms to the GitHub Actions workflow.
The dependency review action scans your pull requests for dependency changes and raises an error if any new dependencies have known vulnerabilities. The action is supported by an API endpoint that compares the dependencies between two revisions and reports any differences.


NEW QUESTION # 121
A secret scanning alert should be closed as "used in tests" when a secret is:

Answer: D

Explanation:
If a secret is intentionally used in a test environment and poses no real-world security risk , you may close the alert with the reason "used in tests" . This helps reduce noise and clarify that the alert was reviewed and accepted as non-critical.
Just being in a test file isn't enough unless its purpose is purely for testing .
: GitHub Docs - Managing Secret Scanning Alerts


NEW QUESTION # 122
After defining a secret scanning custom pattern, what is the final step before publishing the pattern?

Answer: C

Explanation:
GitHub requires you to perform a dry run before publishing a new secret scanning custom pattern. After defining the pattern and providing a sample test string, you select Save and dry run. GitHub searches the relevant repository data without creating secret scanning alerts and returns a sample of matching results. You should review these results for false positives, adjust the regular expression or additional match requirements if necessary, and repeat the dry run until the pattern behaves as intended. Only after a successful dry run and review should you publish the custom pattern. Push protection is optional and is enabled after the pattern has been published; GitHub explicitly notes that the option is not available until the dry run succeeds and the pattern is published.


NEW QUESTION # 123
As a repository owner, you do not want to run a GitHub Actions workflow when changes are made to any .txt or markdown files. How would you adjust the event trigger for a pull request that targets the main branch? (Each answer presents part of the solution. Choose three.) on:
pull_request:
branches: [main]

Answer: B,C,E

Explanation:
To exclude .txt and .md files from triggering workflows on pull requests to the main branch:
on: defines the event (e.g., pull_request)
pull_request: is the trigger
paths-ignore: is the key used to ignore file patterns
Example YAML:
yaml
CopyEdit
on:
pull_request:
branches:
- main
paths-ignore:
- '*.md'
- '*.txt'
Using paths: would include only specific files instead - not exclude. paths-ignore: is correct here.


NEW QUESTION # 124
......

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