CAS-005 Exam Dumps : CompTIA SecurityX Certification Exam

Creating a separate network for users who need access tothe application is the best action to secure an internal application that is critical to the production area and cannot be updated.

Why Separate Network?

Network Segmentation: Isolates the critical application from the rest of the network, reducing the risk of compromise and limiting the potential impact of any security incidents.

Controlled Access: Ensures that only authorized users have access to the application, enhancing security and reducing the attack surface.

Minimized Risk: Segmentation helps in protecting the application from vulnerabilities that could be exploited from other parts of the network.

Other options, while beneficial, do not provide the same level of security for a critical application:

A. Disallow wireless access: Useful but does not provide comprehensive protection.

B. Deploy intrusion detection capabilities using a network tap: Enhances monitoring but does not provide the same level of isolation and control.

C. Create an acceptable use policy: Important for governance but does not provide technical security controls.

Input sanitation is a critical process in cybersecurity that involvesvalidating and cleaning data provided by users to prevent malicious inputs from causing harm. In the context of AI concerns:

A. Model inversion involves an attacker inferring sensitive data from model outputs, typically requiring sophisticated methods beyond just manipulating input data.

B. Prompt Injection is a form of attack where an adversary provides malicious input to manipulate the behavior of AI models, particularly those dealing with natural language processing (NLP). Input sanitation directly addresses this by ensuring that inputs are cleaned andvalidated to remove potentially harmful commands or instructions that could alter the AI's behavior.

C. Data poisoning involves injecting malicious data into the training set to compromise the model. While input sanitation can help by filtering out bad data, data poisoning is typically addressed through robust data validation and monitoring during the model training phase, rather than real-time input sanitation.

D. Non-explainable model refers to the lack of transparency in how AI models make decisions. This concern is not addressed by input sanitation, as it relates more to model design and interpretability techniques.

Input sanitation is most relevant and effective for preventing Prompt Injection attacks, where the integrity of user inputs directly impacts the performance and security of AI models.

Regression testing is a software testingpractice that ensures that recent code changes have not adversely affected existing functionalities. In this scenario, the reintroduction of a previously fixed bug indicates that changes or integrations brought back the old issue. Implementing comprehensive regression testing would help detect such reintroductions by systematically retesting the existing functionalities whenever changes are made to the codebase. This practice is crucial in maintaining the integrity of the application, especially in complexsystems where multiple components interact.​