CIPT Exam Dumps : Certified Information Privacy Technologist

A code audit typically involves reviewing the source code to identify security vulnerabilities, compliance with coding standards, and the presence of appropriate logic and controls. However, determining whether consent is durably recorded in the event of a server crash is outside the scope of what can be assessed in a code audit. This requires operational checks and validation of data resilience and durability mechanisms, such as database configurations and backup procedures. The IAPP Information Privacy Technologist documentation highlights that auditing focuses more on code correctness and security rather than operational durability.

The main reason the Do Not Track (DNT) header is not acknowledged by more companies is:

Lack of consensus about what the DNT header should mean (Option C): There has been significant debate and no clear agreement on how companies should interpret and respond to the DNT header. This lack of standardization and enforceable regulations has led to its limited adoption.

Option A is incorrect because most web browsers do support the DNT feature.Option B is incorrect; there are no high financial penalties for violating DNT guidelines.Option D is also incorrect as the technological challenges are not the primary reason for non-acknowledgment.

References:

IAPP Information Privacy Technologist (CIPT) training materials

W3C Tracking Protection Working Group reports

FAIR (Factor Analysis of Information Risk) analysis is a structured approach to understanding, analyzing, and quantifying information risks. The core factors in FAIR analysis include the severity of the harm (option A), the capability of a threat actor (option B), and the probability of a threat actor's success (option D). The stage of the data life cycle, while important in understanding data management practices, is not a direct factor in the FAIR analysis framework. According to IAPP documentation, FAIR analysis focuses on quantifying risk factors to evaluate and manage privacy risks effectively, emphasizing measurable and actionable components rather than the data life cycle stage.