A system architect is evaluating a newly introduced generative technology for code creation. The security team has observed scripts referencing unsupported libraries. Management wants to maintain the speed advantage of this new method while improving reliability. Which approach meets this goal?
Place generated scripts in a private repository without planned review from team members
Depend on the built-in scanning function to detect most potential issues
Incorporate human validation along with rule-based checks before putting generated scripts into service
Let the generator update configurations across machines when required
Adding a peer evaluation step with rule-based checks provides oversight for any unexpected outputs. Human reviewers and automated rules help ensure that the generated material is fit for production. Simply storing it without review removes an important safeguard. Giving the tool complete redeployment authority may replicate incorrect data. Relying on a built-in scanning feature may miss environment-specific vulnerabilities.
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Why is human validation necessary for generative code tools?
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What are rule-based checks in the context of code validation?
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Why is relying solely on built-in scanning insufficient for code validation?