GH-500 GitHub Advanced Security Exam Questions and Answers

Dependabot alert and advisory details can include a CVE identifier, a GHSA identifier, and associated CWE classifications. CVE provides the standardized identifier for a publicly known vulnerability. GitHub assigns a unique GHSA ID to advisories in the GitHub Advisory Database, while CWE identifies the underlying category or class of software weakness associated with the vulnerability. GitHub's Dependabot alert interface exposes these values when they are available. EPSS is also now surfaced by GitHub and can be used to prioritize alerts, but EPSS is a probability-based exploit-risk score, not one of the three vulnerability identifiers/classifications being tested by this question. SAST describes a security-analysis methodology rather than an advisory classification. Therefore, the intended selections are CVE, GHSA, and CWE: C, D, and E.

By default, users with Write, Maintain, or Admin permissions will receive notifications for new Dependabot alerts . However, Write permission is the minimum level needed to be automatically notified. Users with only Read access do not receive alerts unless added explicitly.

Comprehensive and Detailed Explanation:

In private repositories, users with write access can fix code scanning alerts. They can do this by committing changes that address the issues identified by the code scanning tools. This level of access ensures that only trusted contributors can modify the code to resolve potential security vulnerabilities.​

GitHub Docs

Users with read or triage roles do not have the necessary permissions to make code changes, and the security manager role is primarily focused on managing security settings rather than directly modifying code.​

In a repository's Security tab, you can view:

Secret scanning alerts : Exposed credentials or tokens

Dependabot alerts : Vulnerable dependencies from the advisory database

Code scanning alerts : Vulnerabilities in code detected via static analysis (e.g., CodeQL)

You won’t see general "security status alerts" (not a formal category) or permission-related alerts here.

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.

The first step when you receive a secret scanning alert is to revoke the secret if it is still valid. This ensures the secret can no longer be used maliciously. Only after revoking it should you proceed to remove it from the code history and apply other mitigation steps.

Simply deleting the secret from the code does not remove the risk if it hasn’t been revoked — especially since it may already be exposed in commit history.

GitHub secret scanning examines the repository comprehensively rather than limiting analysis to selected files or dependency metadata. GitHub states that secret scanning scans the entire Git history across all branches for supported secrets. Consequently, both current files and historical versions of files can be inspected, which is why simply deleting a leaked credential in a later commit does not eliminate the security risk. The feature searches repository content for supported provider, generic, and other enabled secret patterns. Dependencies themselves are handled primarily through dependency graph and Dependabot functionality and are not a secret-scanning scope category. Therefore, the correct selections are all branches, the full commit history, and all files in the repository.

Known vulnerable dependencies detected in a repository are presented as Dependabot alerts. GitHub uses the dependency graph to determine which packages and versions the repository depends on and compares that information with vulnerability data from the GitHub Advisory Database. When a match is found, an alert appears in the repository's Security and quality area under Dependabot vulnerabilities. Each alert can provide the affected dependency, vulnerability details, severity, the affected manifest or lockfile, and a secure version when one is available. Secret scanning alerts relate to exposed credentials, while code scanning alerts represent vulnerabilities or coding errors in source code. Security advisories are vulnerability records and disclosure mechanisms rather than the repository-specific list of vulnerable dependencies.

To create or modify a code scanning workflow file (typically under .github/workflows/codeql-analysis.yml), you must have Write access to the repository.

Write permission allows you to commit the workflow file, which is required to run or configure code scanning using GitHub Actions.

Dependabot alerts can identify vulnerable direct dependencies declared in a manifest and vulnerable indirect or transitive dependencies when GitHub can determine their versions from a lockfile. GitHub's dependency graph extracts dependency information from supported manifest and lock files and compares identified package versions against security advisories in the GitHub Advisory Database. Direct dependencies explicitly declared in manifests therefore qualify for vulnerability detection. Transitive dependencies recorded with resolvable versions in lockfiles can also generate alerts. A “loose” dependency declaration may not provide GitHub with a sufficiently specific installed version to establish that the project actually uses a vulnerable release, while a particular time such as 08:00 UTC has nothing to do with whether a dependency qualifies for an alert. Thus, A and C are correct.

GitHub Actions supports path filters for events such as push and pull_request. The paths: key allows a workflow to run only when changed files match one or more specified path patterns. For example, a workflow could use paths: - 'src/**' so that a code scanning job runs when files under the src directory are changed. The related paths-ignore: key performs the opposite function by excluding matching paths. Characters such as ** are glob-pattern components placed beneath paths:; they are not replacements for the paths keyword itself. Therefore, because the workflow must conditionally run when files in a particular directory change, line 3 should contain paths: followed by the applicable directory pattern.

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.

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.​

You can customize CodeQL scanning by including additional query packs or by specifying individual queries :

Packs : These are reusable collections of CodeQL queries bundled into a single package.

Queries : You can point to specific files or directories containing .ql queries to include in the analysis.

github/codeql refers to a pack by name but is not a method or field. Scope is not a valid field used for configuration in this context.

GitHub documents a size limit for the .github/secret_scanning.yml configuration file. If the file is larger than 1 MB, secret scanning ignores the entire configuration file. This file is used primarily to define paths-ignore entries for directories or files where matching secrets should automatically be excluded or alerts closed as ignored by configuration. There is also a separate limit on path exclusions: if paths-ignore contains more than 1,000 entries, GitHub processes only the first 1,000 directories rather than ignoring the complete configuration file. Therefore, the 1,000-entry condition has different behavior from exceeding the file-size limit. A 100 KB file remains below GitHub's documented threshold. Consequently, option B accurately identifies the condition that causes the entire secret_scanning.yml file to be ignored.

When secret scanning is enabled on a private repository, GitHub performs a read-only analysis of the repository's contents. This includes the entire Git history and files to identify strings that match known secret patterns or custom-defined patterns.

GitHub does not alter the repository, and enabling secret scanning does not automatically enable code scanning or dependency review — each must be configured separately.

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.

Secret validation checks whether a secret found in your repository is still valid and active with the issuing provider (e.g., AWS, GitHub, Stripe). If a secret is confirmed to be active, the alert is marked as verified , which means it's considered a high-priority issue because it presents an immediate security risk.

This helps teams respond faster to valid, exploitable secrets rather than wasting time on expired or fake tokens.

Dependency review runs as part of a pull request and shows which dependencies are being added, removed, or changed — and highlights vulnerabilities associated with any added packages.

It works in real-time and is specifically designed for use during pull request workflows.

The dependency graph is an overview, Dependabot alerts notify post-merge, and the Security tab shows the aggregated alert list.

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.

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.

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 a CodeQL workflow uses a language matrix, the matrix explicitly defines which programming languages the workflow analyzes. GitHub states that CodeQL will analyze only the languages included in that matrix; adding or removing matrix entries therefore directly changes the languages scanned. The matrix also allows separate language-analysis jobs to run in parallel, so it does not inherently make analysis sequential. The languages input of the CodeQL init action commonly receives the current matrix.language value, but that describes how the matrix value is passed into CodeQL rather than the principal impact asked for here. The matrix also does not represent dependency exclusions. Consequently, the operational effect being tested is that CodeQL analysis is restricted to the languages explicitly included in the workflow's matrix.

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.​

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

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.

Dependabot security updates are automated pull requests triggered when GitHub detects a vulnerability in a dependency listed in your manifest or lockfile. These PRs upgrade the dependency to the minimum safe version that fixes the vulnerability.

This is separate from regular updates (which keep versions current even if not vulnerable).

Dependabot builds a dependency graph by analyzing package manifests and lockfiles in your repository. This graph includes both direct and transitive dependencies. It then compares this graph against the GitHub Advisory Database, which includes curated, security-reviewed advisories.

This method provides a comprehensive and automated way to discover all known vulnerabilities across your dependency tree.

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.​

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.

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.

Comprehensive and Detailed Explanation:

Push protection for secret scanning custom patterns is an opt-in feature. This means that for each custom pattern defined in a repository, maintainers can choose to enable or disable push protection individually. This provides flexibility, allowing teams to enforce push protection on sensitive patterns while leaving it disabled for others.​

The GitHub Code Scanning API includes endpoints that allow you to:

List alerts for a repository (filtered by branch, state, or tool) — useful for monitoring security over time.

Get a single alert by its ID to inspect its metadata, status, and locations in the code.

However, GitHub does not support modifying the severity of alerts via API — severity is defined by the scanning tool (e.g., CodeQL). Likewise, alerts cannot be deleted via the API; they are resolved by fixing the code or dismissing them manually.