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Microsoft GH-500 Exam Overview:

Certification Vendor:Microsoft
Exam Name:GitHub Advanced Security
Exam Number:GH-500
Passing Score:700 out of 1000
Real Exam Qty:40-60
Related Certifications:GitHub Advanced Security Certification
Certificate Validity Period:1 year
Exam Duration:120 minutes
Available Languages:French, Chinese (Simplified), German, Korean, English, Japanese, Spanish
Exam Format:Multiple choice, Drag and drop, Case study
Exam Price:$165 USD
Sample Questions:Microsoft GH-500 Sample Questions
Exam Way:Online (Proctored) or In-person at a testing center
Pre Condition:No mandatory prerequisites. Recommended to have experience with GitHub and basic understanding of security concepts.
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/github-advanced-security/

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Microsoft GH-500 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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 4
  • 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 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.

Microsoft GitHub Advanced Security Sample Questions (Q55-Q60):

NEW QUESTION # 55
You are a maintainer of a repository and Dependabot notifies you of a vulnerability. Where could the vulnerability have been disclosed? (Each answer presents part of the solution. Choose two.)

Answer: B,C

Explanation:
Comprehensive and Detailed Explanation:
Dependabot alerts are generated based on data from various sources:
National Vulnerability Database (NVD): A comprehensive repository of known vulnerabilities, which GitHub integrates into its advisory database.
GitHub Docs
Security Advisories Reported on GitHub: GitHub allows maintainers and security researchers to report and discuss vulnerabilities, which are then included in the advisory database.
The dependency graph and manifest/lock files are tools used by GitHub to determine which dependencies are present in a repository but are not sources of vulnerability disclosures themselves.
References: GitHub Docs - About Dependabot alerts


NEW QUESTION # 56
Which syntax in a query suite tells CodeQL to look for one or more specified .ql files?

Answer: C

Explanation:
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.


NEW QUESTION # 57
Which of the following steps should you follow to integrate CodeQL into a third-party continuous integration system? Each answer presents part of the solution. (Choose three.)

Answer: A,B,D

Explanation:
Using code scanning with your existing CI system
You can analyze your code with the CodeQL CLI or another tool in a third-party continuous integration system and upload the results to GitHub. The resulting code scanning alerts are shown alongside any alerts generated within GitHub.
[A] Setting up your analysis tool
You will first need to download your analysis tool of choice and set it up with your CI system.
If you are using the CodeQL CLI, you need to make the full contents of the CodeQL CLI bundle available to every CI server that you want to run CodeQL code scanning analysis on.
[B ] Analyzing code
To analyze code with the CodeQL CLI or another analysis tool, you will want to check out the code you want to analyze and set up the codebase environment, making sure that any dependencies are available. You may also want to find the build command for the codebase, typically available in your CI system's configuration file.
You can then complete the steps to analyze your codebase and produce results, which will differ based on the static analysis tool you are using.
[E] Uploading your results to GitHub
Once you have analyzed your code, produced SARIF results, and ensured you can authenticate with GitHub, you can upload the results to GitHub.


NEW QUESTION # 58
As a developer, you need to configure a code scanning workflow for a repository where GitHub Advanced Security is enabled. What minimum repository permission do you need?

Answer: C

Explanation:
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.


NEW QUESTION # 59
Assuming that no custom patterns are configured, what type of secret is detected by secret scanning?

Answer: C

Explanation:
GitHub secret scanning detects and alerts on sensitive data exposure, such as API keys and credentials, in your code repositories.


NEW QUESTION # 60
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