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Microsoft GH-500 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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.
Topic 2
  • 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.
Topic 3
  • 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.
Topic 4
  • 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 5
  • 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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Microsoft GitHub Advanced Security Sample Questions (Q32-Q37):

NEW QUESTION # 32
What does a CodeQL database of your repository contain?

Answer: D

Explanation:
GitHub
Agentic AI for AppSec Teams
Explanation:
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


NEW QUESTION # 33
How would you build your code within the CodeQL analysis workflow? Each answer presents a complete solution. (Choose two.)

Answer: B,C

Explanation:
[B] Build Modes
The CodeQL Action supports different build modes for analyzing the source code. The available build modes are:
none: The database will be created without building the source code. Available for all interpreted languages and some compiled languages.
*-> autobuild: The database will be created by attempting to automatically build the source code.
Available for all compiled languages.
manual: The database will be created by building the source code using a manually specified build command. To use this build mode, specify manual build steps in your workflow between the init and analyze steps. Available for all compiled languages.
[D] Actions
This repository contains several actions that enable you to analyze code in your repository using CodeQL and upload the analysis to GitHub Code Scanning. Actions in this repository also allow you to upload to GitHub analyses generated by any SARIF-producing SAST tool.
Actions for CodeQL analyses:
*-> init: Sets up CodeQL for analysis.
analyze: Finalizes the CodeQL database, runs the analysis, and uploads the results to Code Scanning.


NEW QUESTION # 34
Which of the following is the best way to prevent developers from adding secrets to the repository?

Answer: A

Explanation:
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.


NEW QUESTION # 35
In the pull request, how can developers avoid adding new dependencies with known vulnerabilities?

Answer: C

Explanation:
To detect and block vulnerable dependencies before merge , developers should use the Dependency Review GitHub Action in their pull request workflows. It scans all proposed dependency changes and flags any packages with known vulnerabilities.
This is a preventative measure during development, unlike Dependabot, which reacts after the fact .
: GitHub Docs - Dependency Review Action


NEW QUESTION # 36
As a repository owner, you do not want to run a GitHub Actions workflow when changes are made to any .txt or markdown files. How would you adjust the event trigger for a pull request that targets the main branch?
(Each answer presents part of the solution. Choose three.)
* on:
* pull_request:
* branches: [main]

Answer: B,C,E

Explanation:
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.
: GitHub Docs - Workflow Syntax for GitHub Actions


NEW QUESTION # 37
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