Free Practice Questions for the Microsoft GitHub Administrator GH-500 Exam (2026 Updated)

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.

When defining a custom pattern for secret scanning, two key fields are required:

Name of the pattern : A unique label to identify the pattern

Secret format : A regular expression that defines what the secret looks like (e.g., token format)

You can optionally specify additional match requirements (like required context keywords), but they’re not mandatory. Listing repositories is also not part of the required fields during pattern creation.

To grant specific users access to view and manage secret scanning alerts , you do this via the Settings tab of the repository. From there, under the "Code security and analysis" section, you can add individuals or teams with roles such as security manager .

The Security tab only displays alerts; access control is handled in Settings.

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.​

When a person's access to a private repository is removed, GitHub deletes that person's private forks belonging to the repository's network. This prevents the GitHub-hosted fork from remaining available after the user loses authorization to the upstream private repository. GitHub cannot, however, automatically erase local clones that the person previously downloaded to their own computers; the documentation explicitly states that local clones are retained. Removing one individual's access also does not necessarily revoke an entire team's access, because team permissions are managed separately. Nor does GitHub automatically delete confidential information that may have been copied outside the repository. GitHub therefore advises organizations to ensure that former collaborators appropriately dispose of confidential or proprietary information. The direct platform behavior described in the question is deletion of the user's private forks.

Dependabot alerts utilize standardized identifiers to describe vulnerabilities:​

CVE (Common Vulnerabilities and Exposures): A widely recognized identifier for publicly known cybersecurity vulnerabilities.​

CWE (Common Weakness Enumeration): A category system for software weaknesses and vulnerabilities.​

These identifiers help developers understand the nature of the vulnerabilities and facilitate the search for more information or remediation strategies.​

The best proactive control is push protection . It scans for secrets during a git push and blocks the commit before it enters the repository.

Other options (like CODEOWNERS or security managers) help with oversight but do not prevent secret leaks.

Making a repo public would increase the risk, not reduce it.

The command @dependabot ignore this dependency closes the current Dependabot pull request and creates an ignore condition that prevents Dependabot from opening additional pull requests for that dependency. The restriction remains until the pull request is reopened or the dependency is manually upgraded to the suggested version. @dependabot recreate performs the opposite action: it recreates the pull request and overwrites edits made to it. @dependabot rebase rebases the Dependabot pull request against the current target branch. GitHub does not document @dependabot close as the command for permanently suppressing the dependency update. GitHub also provides more granular commands to ignore only a major, minor, or patch version when permanent dependency-level suppression would be too broad.

The Security tab in a GitHub repository provides a central location for viewing security-related information, especially when GitHub Advanced Security is enabled. The following can be accessed:

Number of alerts related to:

Code scanning

Secret scanning

Dependency (Dependabot) alerts

Summary and visibility into open, closed, and dismissed security issues.

It does not show 2FA options, access control settings, or configuration panels for GHAS itself. Those belong to account or organization-level settings.

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.​

Comprehensive and Detailed Explanation:

A CodeQL database contains a representation of your codebase, including the build of the code and extracted data. This database is used to run CodeQL queries to analyze your code for potential vulnerabilities and errors.​

GitHub Docs

Before CodeQL can execute security queries, the source code must first be represented in a CodeQL database. Database creation extracts structured, relational information from the source code and, where applicable, observes or performs the build process required for the language being analyzed. Once the database exists, CodeQL can execute queries against it. The resulting query output is then interpreted using query metadata and can ultimately be converted to a format such as SARIF for presentation as code scanning alerts. Therefore, running queries, interpreting results, and converting results are later phases of analysis. GitHub's CodeQL documentation explicitly identifies creation of the CodeQL database as a prerequisite for analyzing source code with CodeQL queries, making preparation/database creation the correct first step.

Comprehensive and Detailed Explanation:

When GitHub identifies a vulnerable dependency in a repository with Dependabot alerts enabled, it performs the following actions:​

Generates a Dependabot alert: The alert is displayed on the repository's Security tab, providing details about the vulnerability and affected dependency.​

Notifies repository maintainers: By default, GitHub notifies users with write, maintain, or admin permissions about new Dependabot alerts.​

GitHub Docs

These actions ensure that responsible parties are informed promptly to address the vulnerability.​

Validity checks — where GitHub verifies if a secret is still active — are available for partner patterns only. These are secrets issued by GitHub's trusted partners (like AWS, Slack, etc.) and have APIs for GitHub to validate token activity status.

Custom patterns and high entropy patterns do not support automated validity checks.

GitHub explicitly notifies the commit author when that person accidentally commits a detected secret, regardless of the author's notification preferences. Repository administrators are also among the users eligible to receive secret-scanning security notifications, subject to their repository watch and email notification configuration. GitHub's current notification model can additionally notify security managers and users with explicitly granted security-alert access, but those choices are not represented accurately by the generic “security analyst” option. Write and Maintain roles alone do not make a user the default repository-wide recipient represented by this question. For incremental scans, users who have security-alert access receive notifications according to their configured notification preferences, while commit authors receive notification regardless. Therefore, among the supplied choices, the expected combination remains the committer and repository administrators: B and C.

To exclude .txt and .md files from triggering workflows on pull requests to the main branch:

on: defines the event (e.g., pull_request)

pull_request: is the trigger

paths-ignore: is the key used to ignore file patterns

Example YAML:

yaml

CopyEdit

on:

pull_request:

branches:

- main

paths-ignore:

- '*.md'

- '*.txt'

Using paths: would include only specific files instead — not exclude. paths-ignore: is correct here.

Under the GitHub Actions minute-multiplier model tested by this question, jobs executed on GitHub-hosted Windows runners consume included minutes at twice the rate of equivalent Linux-runner jobs. Linux has a multiplier of 1, while Windows has a multiplier of 2; historically macOS used a substantially higher multiplier. Because CodeQL advanced setup can execute as a GitHub Actions workflow, the operating system selected with runs-on affects Actions consumption in the same way as other GitHub-hosted workflows. GitHub's newer billing documentation increasingly expresses runner usage through operating-system-specific per-minute pricing rather than only multiplier terminology, but the exam question specifically tests the established Windows-versus-Linux minute multiplier. Therefore, the expected answer is 2x higher.

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.​

The dependency graph in a repository is built by parsing manifest and lock files (like package.json, pom.xml, requirements.txt). It helps GitHub detect dependencies and cross-reference them with known vulnerability databases for alerting.

It is specific to each repository and does not show org-wide or cross-repo summaries.

The config-file input is used with the github/codeql-action/init action to specify the path to a custom CodeQL configuration file. This configuration can define additional query packs, custom queries, directories to include or exclude, and other CodeQL analysis settings. GitHub's official workflow documentation shows config-file under the with: section of the CodeQL initialization step. The queries input is used to specify additional query suites or query packs directly, rather than referencing a configuration file. source-root and db-location are not the appropriate init inputs for supplying the configuration-file path. Therefore, when the CodeQL workflow must load settings from a separate YAML configuration file, config-file is the correct parameter.

If autobuild fails (which attempts to automatically detect how to build your project), you should disable it in your workflow and replace it with explicit build commands , using steps like run: make or run: ./gradlew build.

This ensures CodeQL can still extract and analyze the code correctly.

GitHub Advanced Security features can be managed at both the organization and repository levels. Organization owners can control security configurations and Advanced Security access across repositories from the organization's Settings area. At the repository level, administrators can manage eligible security and analysis features through the repository's Settings, subject to any policies or security configurations enforced by the organization or enterprise. Current GitHub terminology separates Advanced Security into products such as GitHub Secret Protection and GitHub Code Security, but the same management hierarchy applies. The organization's Repository permissions area manages general repository access permissions rather than feature licensing or enablement, while enterprise settings primarily establish higher-level policies rather than directly serving as the normal per-repository control described here.

After generating an alert for a vulnerable dependency, Dependabot automatically attempts to create a pull request to upgrade that dependency to the minimum required secure version —if a fix is available and compatible with your project.

This automated PR helps teams fix vulnerabilities quickly with minimal manual intervention. You can also configure update behaviors using dependabot.yml, but in the default state, PR creation is automatic.

Comprehensive and Detailed Explanation:

Before defining a custom pattern for secret scanning in a repository, you must enable secret scanning for that repository. Secret scanning must be active to utilize custom patterns, which allow you to define specific formats (using regular expressions) for secrets unique to your organization.​

Once secret scanning is enabled, you can add custom patterns to detect and prevent the exposure of sensitive information tailored to your needs.​

Comprehensive and Detailed Explanation:

Dependency review is triggered by specific events in GitHub workflows:​

pull_request: When a pull request is opened, synchronized, or reopened, GitHub can analyze the changes in dependencies and provide a dependency review.​

workflow_dispatch: This manual trigger allows users to initiate workflows, including those that perform dependency reviews.​

The trigger and commit options are not recognized GitHub Actions events and would not initiate a dependency review.​

Secret scanning is a feature provided by GitHub that scans the contents of your GitHub repositories for known types of secrets, such as API keys and tokens. It operates within the GitHub environment and does not scan external systems, services, or repositories outside of GitHub. Its primary function is to prevent the accidental exposure of sensitive information within your GitHub-hosted code.​

GitHub states that its repository security advisory form is a standardized form that matches the Common Vulnerabilities and Exposures (CVE) description format. GitHub Security Advisories build on the CVE ecosystem, and GitHub itself is a CVE Numbering Authority capable of assigning CVE identification numbers for eligible vulnerabilities. The advisory form captures structured information such as the vulnerability description, affected products, vulnerable and patched versions, severity, CWEs, references, and CVE information. A CNA is an organization authorized to assign CVEs rather than a separate advisory-description format. Dependabot alerts are generated for vulnerable dependencies and are unrelated to the structure of the security advisory form. Therefore, the CVE description format is the correct choice.

Secret scanning for a private repository is enabled through the repository's security configuration/settings, currently located under Settings → Security and quality → Advanced Security. In current GitHub terminology, enabling Secret Protection enables secret scanning alerts for an eligible private or internal repository. Repository rulesets control policies such as branch protection, required checks, and merge conditions; they are not the primary mechanism for enabling secret scanning. GitHub also does not use a secret.yml file to activate the feature. Code scanning default setup configures CodeQL analysis and is separate from secret detection. Organization owners can additionally enable Secret Protection and secret-scanning capabilities at scale by applying security configurations to repositories. Consequently, the code security or Advanced Security settings area is the correct location, making A the correct answer.

A code scanning alert provides information that helps a developer identify and understand the security problem detected by the analysis tool. GitHub specifically displays the line of code that triggered the alert, together with properties such as severity, security severity, the nature of the problem, and when the issue was introduced. CodeQL-generated alerts may additionally contain remediation guidance and data-flow information. Secret values are handled through secret scanning rather than being shown as the defining detail of a code scanning alert. GitHub also does not list all users with repository Read access within an individual alert, and a CWE submission date is not the primary alert-location information. The source-code location is therefore the correct answer.

By default , no repositories receive Dependabot alerts unless configuration is explicitly enabled. GitHub does not enable Dependabot alerts automatically for any repositories unless:

The feature is turned on manually

It's configured at the organization or enterprise level via security policies

This includes public, private, and enterprise-owned repositories — manual activation is required .

In a query suite (a .qls file), the **query** key is used to specify the paths to one or more .ql files that should be included in the suite.

Example:

- query: path/to/query.ql

qls is the file format.

qlpack is used for packaging queries, not in suite syntax.

A valid Dependabot configuration requires the top-level version and updates keys. The configuration currently uses version: 2, which identifies the Dependabot configuration syntax. The updates section contains one or more configuration entries describing package ecosystems that Dependabot should monitor. Within each update entry, additional required settings include package-ecosystem, directory or directories, and schedule.interval. The top-level registries key is optional and is used when Dependabot needs authentication information for private registries. assignees is also optional and controls which users are automatically assigned to Dependabot-created pull requests. Therefore, although several other properties may appear in a practical configuration file, only version and updates are mandatory top-level keys among the choices provided.

When you identify that a code scanning alert is a false positive—such as when your code uses a custom sanitization method not recognized by the analysis—you should dismiss the alert with the reason "false positive." This action helps improve the accuracy of future analyses and maintains the relevance of your security alerts.​

As per GitHub's documentation:​

"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."​

By dismissing the alert appropriately, you ensure that your codebase's security alerts remain actionable and relevant.

In a dependabot.yml configuration file, package-ecosystem is a required key . It defines the package manager being used in that update configuration (e.g., npm, pip, maven, etc.).

Without this key, Dependabot cannot determine how to analyze or update dependencies. Other keys like rebase-strategy or commit-message are optional and used for customizing behavior.