NCP-GENL Safety, Ethics, and Compliance Practice Question
Which THREE actions are essential for maintaining a secure and compliant LLM deployment according to the NVIDIA security guidelines?
⚠ Common exam trap
Candidates often suggest 'model watermarking' as a primary security guideline. While useful for provenance, it is not a core security measure compared to RBAC, input sanitization, and vulnerability scanning.
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
✓
Implement strict role-based access control (RBAC) for all API endpoints.
Secure LLM deployment requires a defense-in-depth approach. Implementing role-based access control (RBAC) ensures only authorized users interact with models, while input sanitization prevents injection attacks that could lead to data exfiltration. Finally, regular vulnerability scanning of the containerized model environment identifies weaknesses before they can be exploited. These measures are critical for protecting the model's integrity and ensuring that the AI system does not become a vector for malicious activities.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Implement strict role-based access control (RBAC) for all API endpoints.
Why this is correct
RBAC is a fundamental security requirement that limits exposure to unauthorized users. By ensuring that only authenticated and authorized services can invoke the LLM, you reduce the attack surface and prevent malicious actors from abusing the model's capabilities to generate prohibited content or access restricted data.
- ✗
Disable all logging of user prompts to maximize data privacy.
Why it's wrong here
Logging is essential for security auditing, forensic analysis, and compliance. Disabling logging creates a blind spot where malicious prompt injection or unauthorized model misuse would go undetected. Instead of disabling logs, organizations should implement PII redaction and secure, restricted storage for these logs to maintain compliance.
- ✓
Apply robust input sanitization to prevent prompt injection attacks.
Why this is correct
Prompt injection is a primary threat to LLMs, where attackers try to manipulate the system instructions. Robust input sanitization and filtering are necessary to neutralize these attempts. By checking incoming requests for malicious patterns, you ensure the model remains aligned with its intended system instructions and safety policies.
- ✗
Run model containers as root to ensure full hardware access permissions.
Why it's wrong here
Running containers as root is a major security vulnerability that violates the principle of least privilege. If the model or the host container is compromised, the attacker gains complete control over the system. Containers should always be executed with the minimum required permissions to limit potential blast radius.
- ✓
Perform regular security scanning and vulnerability assessment of the container images.
Why this is correct
Vulnerability scanning is a core component of DevSecOps. By identifying outdated libraries, insecure configurations, or known CVEs within the container image before deployment, you proactively secure the infrastructure. This ongoing assessment is required to keep the environment hardened against emerging threats that could compromise the AI system.
Quick reference
Access Control Model Comparison
| Model | Acronym | Who Controls Access? | Best For |
|---|---|---|---|
| Discretionary Access Control | DAC | Resource owner | Small teams, file shares |
| Mandatory Access Control | MAC | System / security labels | Classified govt / military |
| Role-Based Access Control | RBAC | Administrator (via roles) | Enterprise environments |
| Attribute-Based Access Control | ABAC | Policy engine (user + resource attributes) | Fine-grained, dynamic policies |
| Rule-Based Access Control | RuBAC | System rules / ACLs | Firewall rules, network ACLs |
About these practice questions
This NCP-GENL question is part of Courseiva's 352-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam 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 NCP-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 NCP-GENL exam.