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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 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 4 | - 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 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 (Q16-Q21):
NEW QUESTION # 16
What were the long-term impacts of the Cultural Revolution on Chinese society?
- A. Triage
- B. Write
- C. Admin
- D. Maintain
Answer: C
Explanation:
Requesting a CVE ID for a security advisory in a GitHub repository requires Admin permissions. This level of access is necessary because it involves managing sensitive security information and coordinating with external entities to assign a CVE, which is a formal process that can impact the public perception and security posture of the project.
NEW QUESTION # 17
When using CodeQL, what extension stores query suite definitions?
- A. .qll
- B. .yml
- C. .ql
- D. .qls
Answer: D
Explanation:
Query suite definitions in CodeQL are stored using the .qls file extension. A query suite defines a collection of queries to be run during an analysis and allows for grouping them based on categories like language, security relevance, or custom filters.
In contrast:
* .ql files are individual queries.
* .qll files are libraries used by .ql queries.
* .yml is used for workflows, not query suites.
: GitHub Docs - CodeQL Query Suite Files
NEW QUESTION # 18
Which of the following options would close a Dependabot alert?
- A. creating a pull request to resolve the vulnerability that will be approved and merged
- B. viewing the Dependabot alert on the Dependabot alerts tab of your repository
- C. viewing the dependency graph
- D. leaving the repository in its current state
Answer: A
Explanation:
To close a Dependabot alert, the primary method is to address the underlying vulnerability. This usually involves merging a pull request that Dependabot creates to update the vulnerable dependency or manually fixing the issue and pushing the updated code. Once the vulnerability is resolved, the alert will be automatically closed. Alternatively, you can manually close alerts in the
"Security" tab of your repository.
Here's a more detailed breakdown:
1. Addressing the Vulnerability:
*-> Merge Dependabot Pull Requests:
If Dependabot has identified a vulnerability and created a pull request to fix it, review and merge the pull request. This will automatically update the dependency and close the alert.
* Manual Fix:
If you prefer to fix the vulnerability yourself, make the necessary code changes to update the dependency. Once the changes are pushed and merged, Dependabot will recognize the fix and close the alert.
2. Manually Closing Alerts (if needed)
NEW QUESTION # 19
Assuming dependabot.yml does not exist in the repository, how many reviewers would Dependabot automatically assign to an open pull request?
Answer: C
Explanation:
By default, Dependabot creates pull requests without automatically assigning any reviewers, so the correct number is zero. Reviewers can be configured explicitly through Dependabot configuration or assigned through repository mechanisms such as CODEOWNERS. GitHub recommends using appropriate ownership and review processes when particular teams should review dependency updates. This default differs from Dependabot's ability to create pull requests automatically: creating the update does not imply that a reviewer is selected automatically. A repository can customize Dependabot behavior through .github/dependabot.yml, including configuration related to update handling, but in the scenario specified there is no such configuration file. Consequently, no individual reviewer is automatically attached to the Dependabot pull request merely because Dependabot created it.
NEW QUESTION # 20
What are Dependabot security updates?
- A. automated pull requests to update the manifest to the latest version of the dependency
- B. automated pull requests that help you update dependencies that have known vulnerabilities
- C. compatibility scores to let you know whether updating a dependency could cause breaking changes to your project
- D. automated pull requests that keep your dependencies updated, even when they don't have any vulnerabilities
Answer: B
Explanation:
Dependabot security updates are a feature that automatically generates pull requests to update vulnerable dependencies in your repositories. This helps you keep your projects secure by addressing known vulnerabilities in your project's dependencies. When Dependabot detects a vulnerable dependency, it creates a pull request to update the dependency to a secure version, streamlining the process of patching vulnerabilities.
Note:
Automated Pull Requests:
Dependabot automatically creates pull requests when it identifies a security vulnerability in your project's dependencies.
Vulnerable Dependency Updates:
These pull requests are specifically designed to update the vulnerable dependency to the latest secure version or a version that includes the necessary security patches.
NEW QUESTION # 21
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