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| Topic | Details |
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| Topic 1 | - 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 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.
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| 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.
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| 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.
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| Topic 5 | - 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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Microsoft GitHub Advanced Security Sample Questions (Q58-Q63):
NEW QUESTION # 58
Which security feature shows a vulnerable dependency in a pull request?
- A. Dependabot alert
- B. Dependency review
- C. Dependency graph
- D. The repository's Security tab
Answer: B
Explanation:
Dependency review runs as part of a pull request and shows which dependencies are being added, removed, or changed - and highlights vulnerabilities associated with any added packages.
It works in real-time and is specifically designed for use during pull request workflows.
The dependency graph is an overview, Dependabot alerts notify post-merge, and the Security tab shows the aggregated alert list.
: GitHub Docs - About Dependency Review
NEW QUESTION # 59
When using CodeQL, how does extraction for compiled languages work?
- A. By resolving dependencies to give an accurate representation of the codebase
- B. By running directly on the source code
- C. By generating one language at a time
- D. By monitoring the normal build process
Answer: D
Explanation:
For compiled languages, CodeQL performs extraction by monitoring the normal build process. This means it watches your usual build commands (like make, javac, or dotnet build) and extracts the relevant data from the actual build steps being executed. CodeQL uses this information to construct a semantic database of the application.
This approach ensures that CodeQL captures a precise, real-world representation of the code and its behavior as it is compiled, including platform-specific configurations or conditional logic used during build.
NEW QUESTION # 60
After looking into an injection code scanning alert, you notice that the input is properly sanitized with custom logic. Which of the following is the next step?
- A. Ignore the alert.
- B. Open an issue in the CodeQL repository.
- C. Draft a pull request to update the open source query.
- D. Dismiss the alert with the reason "false positive."
Answer: D
Explanation:
Dismissing alerts
There are two ways of closing an alert. You can fix the problem in the code, or you can dismiss the alert.
Dismissing an alert is a way of closing an alert that you don't think needs to be fixed. For example, an error in code that's used only for testing, or when the effort of fixing the error is greater than the potential benefit of improving the code. You can dismiss alerts from code scanning annotations in code, or from the summary list within the Security tab.
If you dismiss a CodeQL alert as a false positive result, for example because the code uses a sanitization library that isn't supported, consider contributing to the CodeQL repository and improving the analysis.
NEW QUESTION # 61
Which of the following options are code scanning application programming interface (API) endpoints? (Each answer presents part of the solution. Choose two.)
- A. Delete all open code scanning alerts
- B. List all open code scanning alerts for the default branch
- C. Get a single code scanning alert
- D. Modify the severity of an open code scanning alert
Answer: B,C
Explanation:
The GitHub Code Scanning API includes endpoints that allow you to:
* List alerts for a repository (filtered by branch, state, or tool) - useful for monitoring security over time.
* Get a single alert by its ID to inspect its metadata, status, and locations in the code.
However, GitHub does not support modifying the severity of alerts via API - severity is defined by the scanning tool (e.g., CodeQL). Likewise, alerts cannot be deleted via the API; they are resolved by fixing the code or dismissing them manually.
: GitHub Docs - Code Scanning REST API
NEW QUESTION # 62
What is required to trigger code scanning on a specified branch?
- A. The workflow file must exist in that branch.
- B. Developers must actively maintain the repository.
- C. Secret scanning must be enabled on the repository.
- D. The repository must be private.
Answer: A
Explanation:
Comprehensive and Detailed Explanation:
For code scanning to be triggered on a specific branch, the branch must contain the appropriate workflow file, typically located in the .github/workflows directory. This YAML file defines the code scanning configuration and specifies the events that trigger the scan (e.g., push, pull_request).
Without the workflow file in the branch, GitHub Actions will not execute the code scanning process for that branch. The repository's visibility (private or public), the status of secret scanning, or the activity level of developers do not directly influence the triggering of code scanning.
NEW QUESTION # 63
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