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Microsoft GH-500 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 3	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 4	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 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 (Q37-Q42):

NEW QUESTION # 37
Which of the following statements best describes secret scanning push protection?

• A. Secret scanning alerts must be closed before a branch can be merged into the repository.
• B. Buttons for sensitive actions in the GitHub UI are disabled.
• C. Commits that contain secrets are blocked before code is added to the repository.
• D. Users need to reply to a 2FA challenge before any push events.

Answer: C

Explanation:
Comprehensive and Detailed Explanation:
Secret scanning push protection is a proactive feature that scans for secrets in your code during the push process. If a secret is detected, the push is blocked, preventing the secret from being added to the repository. This helps prevent accidental exposure of sensitive information.
GitHub Docs

 

NEW QUESTION # 38
You are a maintainer of a repository and Dependabot notifies you of a vulnerability. Where could the vulnerability have been disclosed? (Each answer presents part of the solution. Choose two.)

• A. In the dependency graph
• B. In the National Vulnerability Database
• C. In security advisories reported on GitHub
• D. In manifest and lock files

Answer: B,C

Explanation:
Comprehensive and Detailed Explanation:
Dependabot alerts are generated based on data from various sources:
National Vulnerability Database (NVD): A comprehensive repository of known vulnerabilities, which GitHub integrates into its advisory database.
GitHub Docs
Security Advisories Reported on GitHub: GitHub allows maintainers and security researchers to report and discuss vulnerabilities, which are then included in the advisory database.
The dependency graph and manifest/lock files are tools used by GitHub to determine which dependencies are present in a repository but are not sources of vulnerability disclosures themselves.

 

NEW QUESTION # 39
Which of the following is the most complete method for Dependabot to find vulnerabilities in third-party dependencies?

• A. The build tool finds the vulnerable dependencies and calls the Dependabot API
• B. A dependency graph is created, and Dependabot compares the graph to the GitHub Advisory database
• C. CodeQL analyzes the code and raises vulnerabilities in third-party dependencies
• D. Dependabot reviews manifest files in the repository

Answer: B

Explanation:
Dependabot builds a dependency graph by analyzing package manifests and lockfiles in your repository. This graph includes both direct and transitive dependencies. It then compares this graph against the GitHub Advisory Database, which includes curated, security-reviewed advisories.
This method provides a comprehensive and automated way to discover all known vulnerabilities across your dependency tree.

 

NEW QUESTION # 40
You have enabled security updates for a repository. When does GitHub mark a Dependabot alert as resolved for that repository?

• A. When you dismiss the Dependabot alert
• B. When Dependabot creates a pull request to update dependencies
• C. When the pull request checks are successful
• D. When you merge a pull request that contains a security update

Answer: D

Explanation:
A Dependabot alert is marked as resolved only after the related pull request is merged into the repository. This indicates that the vulnerable dependency has been officially replaced with a secure version in the active codebase.
Simply generating a PR or passing checks does not change the alert status; merging is the key step.

 

NEW QUESTION # 41
As a developer with write access, you navigate to a code scanning alert in your repository. When will GitHub close this alert?

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

Answer: D

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.

 

NEW QUESTION # 42
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