Question 787 of 945
AI-102 Implement generative AI solutions Practice Question
A developer uses the Azure OpenAI SDK to generate code snippets. The generated code sometimes contains security vulnerabilities. What is the most effective way to mitigate this risk?
⚠ Common exam trap
Microsoft often tests the misconception that fine-tuning is the only way to customize model behavior, but the trap here is that a system message is a simpler, more flexible, and equally effective method for guiding output without the overhead of retraining.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Include a system message that instructs the model to avoid insecure coding patterns.
A system message sets the behavioral context for the model at inference time, instructing it to avoid insecure coding patterns without requiring retraining. This is the most direct and effective mitigation as it leverages the model's instruction-following capability to reduce vulnerabilities in generated code, aligning with Azure OpenAI's content filtering and safety system guidance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set the temperature parameter to 0 to make the output deterministic.
Why it's wrong here
Deterministic output does not ensure security.
- ✗
Post-process the generated code using a static code analysis tool.
Why it's wrong here
Post-processing is valuable but not the most effective upfront mitigation.
- ✗
Fine-tune the model on a dataset of secure code examples.
Why it's wrong here
Fine-tuning is resource-intensive and may not cover all vulnerability types.
- ✓
Include a system message that instructs the model to avoid insecure coding patterns.
Why this is correct
System messages can guide the model to produce safer code.
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Last reviewed: Jun 30, 2026
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