This AZ-400 practice question tests your understanding of design and implement a source control strategy. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Your team uses GitHub for source control. You need to ensure that sensitive data, such as connection strings, is never committed to the repository. Which tool should you use?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "never"
Why it matters: Absolute qualifier. True only if the statement has zero exceptions — be cautious of options that seem obvious but break down in edge cases.
GitHub Actions
Why wrong: GitHub Actions is for automation, not built-in secret detection.
Dependabot
Why wrong: Dependabot manages dependency updates, not secret detection.
Git Large File Storage (LFS)
Why wrong: Git LFS handles large files, not secrets.
GitHub secret scanning
Secret scanning detects secrets like connection strings in code.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
GitHub secret scanning
GitHub secret scanning automatically detects sensitive data like connection strings, API keys, and tokens as they are pushed to a repository, preventing them from being committed. It scans for known patterns and can block the push or alert the repository administrator, making it the correct tool for this requirement.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
GitHub Actions
Why it's wrong here
GitHub Actions is for automation, not built-in secret detection.
Dependabot
Why it's wrong here
Dependabot manages dependency updates, not secret detection.
Git Large File Storage (LFS)
Why it's wrong here
Git LFS handles large files, not secrets.
GitHub secret scanning
Why this is correct
Secret scanning detects secrets like connection strings in code.
Clue confirmation
The clue word "never" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
The trap here is that candidates often confuse secret scanning with Dependabot (which handles dependency vulnerabilities, not secrets) or assume GitHub Actions can be scripted to scan for secrets, but secret scanning is a dedicated, built-in feature that operates at the push level without requiring workflow configuration.
Detailed technical explanation
GitHub secret scanning uses custom or partner-defined patterns (e.g., regex for AWS keys, Azure connection strings) and can be configured with push protection, which blocks the push entirely if a secret is detected. Under the hood, it integrates with GitHub's pre-receive hooks and the push event pipeline, scanning each commit's diff before the push is accepted. In a real-world scenario, a developer accidentally including a production database connection string in a config file would be caught immediately, preventing exposure in the repository history.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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FAQ
Design and implement a source control strategy — This question tests Design and implement a source control strategy — Read the scenario before looking for a memorised answer..
The correct answer is: GitHub secret scanning — GitHub secret scanning automatically detects sensitive data like connection strings, API keys, and tokens as they are pushed to a repository, preventing them from being committed. It scans for known patterns and can block the push or alert the repository administrator, making it the correct tool for this requirement.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Yes — watch for: "never". Absolute qualifier. True only if the statement has zero exceptions — be cautious of options that seem obvious but break down in edge cases.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 25, 2026
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