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| Section | Objectives |
|---|---|
| Topic 1: Implement code scanning and analysis | - Configure CodeQL
|
| Topic 2: Security operations and governance | - Security alert management
|
| Topic 3: Dependency management and supply chain security | - Dependabot configuration
|
| Topic 4: Manage secret scanning | - Detect and remediate secrets
|
| Topic 5: Configure GitHub Advanced Security | - Enable and configure GitHub Advanced Security features
|
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NEW QUESTION # 20
Which alerts do you see in the repository's Security tab? (Each answer presents part of the solution. Choose three.)
Answer: B,D,E
Explanation:
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.
: GitHub Docs - Understanding the Security Tab
NEW QUESTION # 21
The autobuild step in the CodeQL workflow has failed. What should you do?
Answer: C
Explanation:
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 Docs - CodeQL Build Configurations for Compiled Languages
NEW QUESTION # 22
Which of the following is the most complete method for Dependabot to find vulnerabilities in third- party dependencies?
Answer: A
Explanation:
Security Alerts
Dependabot security alerts is a native GitHub service designed for the efficient management of vulnerable dependencies. It continuously scans the project's dependency graph, comparing it to the GitHub security advisory database. Upon detecting a vulnerable dependency version, it prompts developers with a security alert. Dependabot leverages the dependency graph to execute vulnerability scans. To generate this graph, it parses both manifest and lock files residing in the repository's default branch and constructs a comprehensive representation of the complete dependency tree.
Note: GitHub Advisory Database is one of the data sources that GitHub uses to identify vulnerable dependencies and malware. It's a free, curated database of security advisories for common package ecosystems on GitHub. It includes both data reported directly to GitHub from GitHub Security Advisories, as well as official feeds and community sources. This data is reviewed and curated by GitHub to ensure that false or unactionable information is not shared with the development community.
NEW QUESTION # 23
When using CodeQL, how does extraction for compiled languages work?
Answer: B
Explanation:
For compiled languages, CodeQL performs extraction by monitoring the normal build process . This means it watches your usual build commands (like make, javac, or dotnet build) and extracts the relevant data from the actual build steps being executed. CodeQL uses this information to construct a semantic database of the application.
This approach ensures that CodeQL captures a precise, real-world representation of the code and its behavior as it is compiled, including platform-specific configurations or conditional logic used during build.
: GitHub Docs - CodeQL for compiled languages
NEW QUESTION # 24
After defining a secret scanning custom pattern, what is the final step before publishing the pattern?
Answer: B
Explanation:
GitHub requires you to perform a dry run before publishing a new secret scanning custom pattern. After defining the pattern and providing a sample test string, you select Save and dry run. GitHub searches the relevant repository data without creating secret scanning alerts and returns a sample of matching results. You should review these results for false positives, adjust the regular expression or additional match requirements if necessary, and repeat the dry run until the pattern behaves as intended. Only after a successful dry run and review should you publish the custom pattern. Push protection is optional and is enabled after the pattern has been published; GitHub explicitly notes that the option is not available until the dry run succeeds and the pattern is published.
NEW QUESTION # 25
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