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| Topic | Details |
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| 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.
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| Topic 2 | - 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.
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| 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.
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| Topic 4 | - 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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| 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 (Q23-Q28):
NEW QUESTION # 23
What filter or sort settings can be used to prioritize the secret scanning alerts that present the most risk?
- A. Sort to display the oldest first
- B. Filter to display active secrets
- C. Select only the custom patterns
- D. Sort to display the newest first
Answer: B
Explanation:
The best way to prioritize secret scanning alerts is to filter by active secrets - these are secrets GitHub has confirmed are still valid and could be exploited. This allows security teams to focus on high-risk exposures that require immediate attention.
Sorting by time or filtering by custom patterns won't help with risk prioritization directly.
: GitHub Docs - Filtering Secret Scanning Alerts
NEW QUESTION # 24
To be compatible with code scanning, what data format must third-party code scanning tools use for output?
- A. Static Analysis Results Interchange Format (SARIF)
- B. ESLint
- C. YAML
- D. ECMAScript
Answer: A
Explanation:
GitHub code scanning integrates with third-party static analysis tools through SARIF, the Static Analysis Results Interchange Format. A compatible analysis tool generates its findings as a SARIF file, which GitHub can process and display as code scanning alerts within the repository. GitHub supports SARIF output generated outside GitHub, including results from external CI/CD systems or security-analysis products. The results can then be uploaded to GitHub using an appropriate workflow action, API, or supported integration.
YAML is commonly used for GitHub Actions workflow configuration but is not the interchange format for code scanning findings. ESLint is an analysis tool rather than a results-exchange specification, and ECMAScript defines JavaScript language standards. Therefore, SARIF is the required output format.
NEW QUESTION # 25
What is required to trigger code scanning on a specified branch?
- A. The repository must be private.
- B. The workflow file must exist in that branch.
- C. Secret scanning must be enabled on the repository.
- D. Developers must actively maintain the repository.
Answer: B
Explanation:
Scanning on push
By default, the CodeQL analysis workflow uses the on:push event to trigger a code scan on every push to the default branch of the repository and any protected branches. For code scanning to be triggered on a specified branch, the workflow must exist in that branch. For more information, see Workflow syntax for GitHub Actions.
NEW QUESTION # 26
You are configuring code scanning with CodeQL. What is one impact of using a language matrix in your workflow?
- A. CodeQL is configured to run analysis sequentially.
- B. You can use the languages parameter under the init action.
- C. CodeQL excludes alerts for those dependencies specified in the language matrix.
- D. CodeQL will only analyze the languages in the matrix.
Answer: D
Explanation:
When a CodeQL workflow uses a language matrix, the matrix explicitly defines which programming languages the workflow analyzes. GitHub states that CodeQL will analyze only the languages included in that matrix; adding or removing matrix entries therefore directly changes the languages scanned. The matrix also allows separate language-analysis jobs to run in parallel, so it does not inherently make analysis sequential.
The languages input of the CodeQL init action commonly receives the current matrix.language value, but that describes how the matrix value is passed into CodeQL rather than the principal impact asked for here. The matrix also does not represent dependency exclusions. Consequently, the operational effect being tested is that CodeQL analysis is restricted to the languages explicitly included in the workflow's matrix.
NEW QUESTION # 27
Which of the following options would close a Dependabot alert?
- A. Leaving the repository in its current state
- B. Viewing the dependency graph
- C. Creating a pull request to resolve the vulnerability that will be approved and merged
- D. Viewing the Dependabot alert on the Dependabot alerts tab of your repository
Answer: C
Explanation:
A Dependabot alert is only marked as resolved when the related vulnerability is no longer present in your code - specifically after you merge a pull request that updates the vulnerable dependency.
Simply viewing alerts or graphs does not affect their status. Ignoring the alert by leaving the repo unchanged keeps the vulnerability active and unresolved.
NEW QUESTION # 28
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