Pass the Microsoft GitHub Administrator GH-500 Questions and answers with ValidTests

Comprehensive and Detailed Explanation:

To generate a dependency graph for a private repository, GitHub requires:​

Dependency graph enabled: The repository must have the dependency graph feature enabled. This can be configured at the organization level to apply to all new private repositories.​

Access to manifest and lock files: GitHub needs read-only access to the repository's dependency manifest and lock files (e.g., package.json, requirements.txt) to identify and map dependencies.​

When dealing with a data flow issue in a code scanning alert, clicking on "Show paths" provides a detailed view of the data's journey through the code. This includes the source of the data, the path it takes, and where it ends up (the sink). This information is crucial for understanding how untrusted data might reach sensitive parts of your application and helps in identifying where to implement proper validation or sanitization.​

A security policy is defined by a SECURITY.md file in the root of your repository or .github/ directory. This file informs contributors and security researchers about how to responsibly report vulnerabilities. It improves your project’s transparency and ensures timely communication and mitigation of any reported issues.

Adding this file also enables a “Report a vulnerability” button in the repository’s Security tab.

Using the Custom setting allows you to subscribe to specific event types, such as Dependabot alerts or vulnerability notifications, without being overwhelmed by all repository activity. This is essential for repository maintainers who need fine-grained control over what kinds of events trigger notifications.

This setting is configurable per repository and allows users to stay aware of critical issues while minimizing notification noise.

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.

Comprehensive and Detailed Explanation:

By default, users with write access to a repository have the ability to merge pull requests, including those created by Dependabot for security updates. This access level allows contributors to manage and integrate changes, ensuring that vulnerabilities are addressed promptly.​

Users with only read access cannot merge pull requests, and enterprise administrators do not automatically have merge rights unless they have write or higher permissions on the specific repository.​

Comprehensive and Detailed Explanation:

In the advanced setup for CodeQL code scanning, GitHub generates a workflow file named codeql-analysis.yml. This file is located in the .github/workflows directory of your repository. It defines the configuration for the CodeQL analysis, including the languages to analyze, the events that trigger the analysis, and the steps to perform during the workflow.​

If a secret is intentionally used in a test environment and poses no real-world security risk, you may close the alert with the reason "used in tests". This helps reduce noise and clarify that the alert was reviewed and accepted as non-critical.

Just being in a test file isn't enough unless its purpose is purely for testing.

All results from CodeQL analysis appear under the repository’s code scanning alerts tab. This section is part of the Security tab and provides a list of all current, fixed, and dismissed alerts found by CodeQL.

A CodeQL database is used internally during scanning but does not display results. Query packs contain rules, not results. Security advisories are for published vulnerabilities, not per-repo findings.

Comprehensive and Detailed Explanation:

When setting up CodeQL analysis for compiled languages, there are two primary methods to build your code:​

GitHub Docs

Autobuild: CodeQL attempts to automatically build your codebase using the most likely build method. This is suitable for standard build processes.​

GitHub Docs

Custom Build Steps: For complex or non-standard build processes, you can implement custom build steps by specifying explicit build commands in your workflow. This provides greater control over the build process.​

GitHub Docs

The init action initializes the CodeQL analysis but does not build the code. The jobs.analyze.runs-on specifies the operating system for the runner but is not directly related to building the code. Uploading compiled binaries is not a method supported by CodeQL for analysis.​