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| Section | Objectives |
|---|---|
| Topic 1: Security operations and governance | - Security alert management
|
| Topic 2: Dependency management and supply chain security | - Dependabot configuration
|
| Topic 3: Configure GitHub Advanced Security | - Enable and configure GitHub Advanced Security features
|
| Topic 4: Implement code scanning and analysis | - Configure CodeQL
|
| Topic 5: Manage secret scanning | - Detect and remediate secrets
|
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NEW QUESTION # 59
What is the scope of the Enable all setting for Dependabot alerts at the organization level?
Answer: B
Explanation:
At organization scope, enabling Dependabot alerts broadly applies the feature to the organization's eligible repositories, rather than limiting it solely to private repositories or repositories licensed for the broader GitHub Advanced Security product. Dependabot alerts support public, private, and internal repositories, subject to repository eligibility and applicable organization or enterprise configuration. GitHub's current documentation describes organization-level management as enabling Dependabot alerts across all eligible repositories through security configurations. The feature is distinct from licensed GitHub Code Security or Secret Protection capabilities, so the setting is not restricted merely to repositories where those products are enabled. Consequently, All repositories is the intended answer in the supplied choices, with the practical qualification that GitHub applies the configuration to repositories that are eligible for the feature.
NEW QUESTION # 60
You have a GitHub Enterprise Cloud Organization that contains public repositories and uses GitHub Advanced Security.
You need to detect vulnerability and secrets for the repositories. The solution must minimize costs.
What should you use?
Answer: B
Explanation:
The correct answer option is code scanning, dependency review, and secret scanning.
Code Scanning: This feature uses CodeQL static analysis to evaluate your custom code for specific security flaws (e.g., SQL injections, cross-site scripting). This fulfills the requirement to detect code vulnerabilities.
Dependency Review: This caught-at-pull-request tool allows you to track changes in third-party packages, flagging introduced components that contain known open-source vulnerabilities. This handles vulnerability detection for dependencies.
Secret Scanning: This searches your entire Git history and branches to identify hardcoded credentials like API keys or tokens. This covers the mandatory requirement to detect secrets.
Low-Cost Efficiency: For public repositories, all three core GitHub Advanced Security (GHAS) features (code scanning, dependency review, and secret scanning) are provided free of charge by GitHub. Enabling them aligns perfectly with the goal of keeping financial costs minimized.
Incorrect:
[Not A, not D] (Push Protection): While push protection is a highly effective feature that proactive intercepts secrets before they enter the repository, it does not satisfy the core requirement to scan the existing code base for vulnerabilities.
[Not B, not D] (Copilot Secret Scanning): Copilot secret scanning relies on generative AI models to flag unstructured passwords. Because it requires a paid GitHub Copilot subscription, it violates the "low cost" constraint.
[Not C, not D] (Secret Risk Assessment): The secret risk assessment tool merely functions as a high-level administrative reporting dashboard to evaluate overall posture. It does not provide automated active scanning mechanisms or remediation alerts on repository pull requests.
Reference:
https://docs.github.com/en/get-started/learning-about-github/about-github-advanced-security
NEW QUESTION # 61
When using CodeQL, what extension stores query suite definitions?
Answer: A
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 # 62
You are tasked with filtering queries in a CodeQL query suite. Which metadata tag matches on the last path component?
Answer: D
Explanation:
In a CodeQL query suite, the query filename constraint matches the final path component-that is, the filename of the query file itself. GitHub distinguishes this from query path, which matches the path to the query relative to the enclosing CodeQL pack. The tags contain and tags contain all constraints operate on values from the query's @tags metadata rather than its filesystem path. tags contain requires one of the specified strings to match a tag component, while tags contain all requires all specified strings to be represented. Therefore, when the objective is specifically to filter queries according to the last component of their file path, query filename is the appropriate CodeQL query-suite constraint.
NEW QUESTION # 63
Where can you view code scanning results from CodeQL analysis?
Answer: D
Explanation:
You can use CodeQL to identify vulnerabilities and errors in your code. The results are shown as code scanning alerts in GitHub.
Note:
Viewing the alerts for a repository
You need write permission to view a summary of all the alerts for a repository on the Security tab.
By default, the code scanning alerts page is filtered to show alerts for the default branch of the repository only.
1. On GitHub, navigate to the main page of the repository.
2. Under the repository name, click Security. If you cannot see the "Security" tab, select the dropdown menu, and then click Security.
3. In the left sidebar, click Code scanning.
4. Optionally, use the free text search box or the dropdown menus to filter alerts. For example, you can filter by the tool that was used to identify alerts.
5. Etc.
NEW QUESTION # 64
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