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Microsoft GH-500 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 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.
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 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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Microsoft GitHub Advanced Security Sample Questions (Q65-Q70):

NEW QUESTION # 65
What is a security policy?

Answer: C

Explanation:
Adding a security policy to your repository
You can give instructions for how to report a security vulnerability in your project by adding a security policy to your repository.
About security policies
To give people instructions for reporting security vulnerabilities in your project, you can add a SECURITY.md file to your repository's root, docs, or .github folder. Adding this file to this part(s) of your repository automatically creates a row with a description where people can review it.
When someone creates an issue in your repository, they will see a link to your project's security policy.


NEW QUESTION # 66
You are managing code scanning alerts for your repository. You receive an alert highlighting a problem with data flow. What do you click for additional context on the alert?

Answer: A

Explanation:
When dealing with a data flow issue in a code scanning alert, clicking on "Show paths" provides a detailed view of the data's journey through the code. This includes the source of the data, the path it takes, and where it ends up (the sink). This information is crucial for understanding how untrusted data might reach sensitive parts of your application and helps in identifying where to implement proper validation or sanitization.
: GitHub Docs - Assessing code scanning alerts for your repository GitHub Docs+1GitHub Docs+1


NEW QUESTION # 67
How many alerts are created when two instances of the same secret value are in the same repository?

Answer: B

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.
: GitHub Docs - About secret scanning alerts


NEW QUESTION # 68
You have a GitHub Enterprise Cloud Organization that uses GitHub Advanced Security code scanning with CodeQL advanced setup.
The security engineering team at your company maintains a private repository named Repo1 that stores custom CodeQL queries and query suites for multiple languages.
You discover that changes to the custom queries can introduce noisy results and break existing tests. The regressions are detected only after the queries are deployed to production repositories.
You add a workflow step that runs CodeQL query tests on every pull request (PR). The step runs the following CodeQL CLI command.
codeql test run ./tests
You need to ensure that the workflow fails when query tests detect regressions.
What should you configure in the workflow?

Answer: B

Explanation:
To ensure that the GitHub Actions workflow fails when query tests detect regressions, you must configure the command or step to return a non-zero exit code on test failures.
By default, the codeql test run command executes unit tests by comparing the query output against expected .expected files.
Default Behavior: If any tests fail (meaning actual results deviate from the expected results), the CodeQL CLI natively emits a non-zero exit code (typically 1).
CI Integration: In GitHub Actions, any step that executes a command returning a non-zero exit code will automatically fail the step and halt the workflow.
The Risk: If the workflow is configured to suppress errors (e.g., using || true in a shell script, wrapping it in an accidental error-ignoring configuration, or setting continue-on-error: true at the step level), it will mask the failure by returning an exit code of 0.
Reference:
https://github.com/advanced-security/codeql-development-template/blob/main/resources/cli/qlt/qlt_test_run_execute-unit-tests.prompt.md


NEW QUESTION # 69
Who can fix a code scanning alert on a private repository?

Answer: C

Explanation:
Comprehensive and Detailed Explanation:
In private repositories, users with write access can fix code scanning alerts. They can do this by committing changes that address the issues identified by the code scanning tools. This level of access ensures that only trusted contributors can modify the code to resolve potential security vulnerabilities.
GitHub Docs
Users with read or triage roles do not have the necessary permissions to make code changes, and the security manager role is primarily focused on managing security settings rather than directly modifying code.
Reference:
GitHub Docs


NEW QUESTION # 70
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