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| Topic | Details |
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| Topic 1 | - 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 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.
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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 | - 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 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 (Q94-Q99):
NEW QUESTION # 94
Assuming that no custom patterns are configured, what type of secret is detected by secret scanning?
- A. Sealed boxes
- B. Usernames
- C. Private keys
- D. Personally Identifiable Information (PII)
Answer: C
Explanation:
GitHub secret scanning is designed to identify credentials and other sensitive values that match supported secret patterns. Among the options listed, private keys are the supported secret type. GitHub classifies private keys such as RSA, OpenSSH, EC, and PGP private keys as generic secret patterns. These are distinct from organization-specific custom patterns, which administrators create by defining their own regular expressions.
Usernames and general PII are not treated as standard secret-scanning credential patterns, while "sealed boxes" are not a supported secret category. In current GitHub terminology, generic-pattern detection is separately configurable, so it may need to be enabled for the repository. Nevertheless, of the choices presented, private keys are the valid secret-scanning type.
NEW QUESTION # 95
In the pull request, how can developers avoid adding new dependencies with known vulnerabilities?
- A. Enable Dependabot security updates.
- B. Enable Dependabot alerts.
- C. Add Dependabot rules.
- D. Add a workflow with the dependency review action.
Answer: D
Explanation:
To detect and block vulnerable dependencies before merge , developers should use the Dependency Review GitHub Action in their pull request workflows. It scans all proposed dependency changes and flags any packages with known vulnerabilities.
This is a preventative measure during development, unlike Dependabot, which reacts after the fact .
: GitHub Docs - Dependency Review Action
NEW QUESTION # 96
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. CodeQL excludes alerts for those dependencies specified in the language matrix.
- C. CodeQL will only analyze the languages in the matrix.
- D. You can use the languages parameter under the init action.
Answer: C
Explanation:
If your workflow uses the language matrix, then CodeQL will only analyze the languages in the matrix.
Note:
The default CodeQL analysis workflow file created after configuring advanced setup for code scanning with CodeQL defines a matrix containing a property named language which lists the languages in your repository that will be analyzed. This matrix has been automatically pre- populated with supported languages detected in your repository. Using the language matrix allows CodeQL to run each language analysis in parallel and to customize analysis for each language. In an individual analysis, the name of the language from the matrix is provided to the init action as the argument for the languages input. We recommend that all workflows adopt this configuration.
Incorrect:
[Not A]
Using the language matrix allows CodeQL to run each language analysis in parallel.
NEW QUESTION # 97
What is a prerequisite to define a custom pattern for a repository?
- A. Close other secret scanning alerts
- B. Change the repository visibility to Internal
- C. Specify additional match criteria
- D. Enable secret scanning
Answer: D
Explanation:
You must enable secret scanning before defining custom patterns. Secret scanning provides the foundational capability for detecting exposed credentials, and custom patterns build upon that by allowing organizations to specify their own regex-based patterns for secrets unique to their environment.
Without enabling secret scanning, GitHub will not process or apply custom patterns.
NEW QUESTION # 98
What is the purpose of the SECURITY.md file in a GitHub repository?
- A. contributing.md
- B. security.md
- C. support.md
- D. readme.md
Answer: B
Explanation:
The correct place to look is the SECURITY.md file. This file provides contributors and security researchers with instructions on how to responsibly report vulnerabilities. It may include contact methods, preferred communication channels (e.g., security team email), and disclosure guidelines.
This file is considered a GitHub best practice and, when present, activates a "Report a vulnerability" button in the repository's Security tab.
NEW QUESTION # 99
......
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