NCA-GENL Trustworthy AI Practice Question
Exhibit
{
"guardrail_type": "input",
"block_list": ["sensitive_pii", "illegal_acts"],
"enforcement_mode": "strict"
}Refer to the exhibit. What is the effect of the 'enforcement_mode: strict' configuration on the AI application?
⚠ Common exam trap
Candidates often confuse strict enforcement modes with warning systems or user overrides, missing that a strict configuration results in immediate and absolute rejection of any prohibited requests.
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
✓
The request is rejected if it triggers any items in the block list.
Setting the enforcement mode to 'strict' indicates that the system will block any input that matches the defined block list, with zero tolerance for ambiguity. In the context of Trustworthy AI, this is a high-security posture that prioritizes safety over user experience. It ensures that any attempt to elicit prohibited information results in an immediate and non-negotiable rejection, effectively preventing the model from acting upon harmful or sensitive user requests.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The model will warn the user about PII but continue processing the request.
Why it's wrong here
A 'strict' mode does not allow for warnings or partial processing. It is a binary, all-or-nothing control mechanism. If an input matches a block list item, the system must reject the request entirely. Warnings are typical of 'permissive' or 'log-only' modes, not a strict security enforcement policy.
- ✗
The model will automatically redact the PII and then answer the request.
Why it's wrong here
Redaction is a data-handling process, not an enforcement-mode behavior. 'Strict' enforcement means the entire request is blocked, not cleaned. If the intent was to allow the request while scrubbing data, the configuration would need a separate 'sanitization' or 'redaction' policy, not just a strict enforcement block list.
- ✓
The request is rejected if it triggers any items in the block list.
Why this is correct
In 'strict' enforcement mode, the system treats any match in the block list as a violation that warrants immediate rejection. This ensures that the model never attempts to reason about sensitive topics or illegal acts, directly supporting the core security and safety requirements of a trustworthy generative AI application.
- ✗
The system logs the violation but permits the model to generate a response.
Why it's wrong here
Logging without blocking is the definition of a 'passive' or 'audit-only' mode. Strict enforcement requires active, immediate intervention. If the system were to permit the response, it would fail to provide the protection that 'strict' enforcement implies, making it an ineffective security control against harmful or forbidden interactions.
About these practice questions
Courseiva writes every NCA-GENL question from scratch — 367 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official NVIDIA exam blueprint
This NCA-GENL practice question is part of Courseiva's free NVIDIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the NCA-GENL exam.