CISA Exam Dumps - Certified Information Systems Auditor

The IS audit standard for proficiency states that the IS auditor must have the knowledge, skills and experience needed to perform the audit work. This implies that the IS auditor must be competent in both the technical and business aspects of the audit subject matter. Therefore, team member assignments must be based on individual competencies, so that each auditor can perform the tasks that match their qualifications and expertise. This will also ensure that the audit objectives are met and the audit quality is maintained.

Option B is incorrect because technical co-sourcing is not a requirement to meet the IS audit standard for proficiency. Co-sourcing is an option that may be used when the internal audit function lacks the necessary resources or skills to perform the audit work. However, co-sourcing does not guarantee that the new staff will acquire the proficiency needed for the audit. Moreover, co-sourcing may introduce additional risks and challenges, such as confidentiality, independence, communication and coordination issues.

Option C is incorrect because having a globally recognized audit certification does not necessarily mean that the standard for proficiency is met. A certification is an indication of the auditor’s knowledge and competence in a specific domain, but it does not cover all aspects of IS auditing. The auditor must also have relevant experience and continuous learning to maintain and enhance their proficiency. Furthermore, having one certified member does not ensure that the other members are also proficient.

Option D is incorrect because having a supervisor review the new auditors’ work is not sufficient to meet the IS audit standard for proficiency. A supervisor review is a quality assurance measure that helps to ensure that the audit work is performed in accordance with the standards and policies. However, a supervisor review does not substitute for the proficiency of the auditors who perform the work. The auditors must still have the necessary knowledge, skills and experience to conduct the audit tasks effectively and efficiently.

Enterprise Architecture (EA) governance requires proper oversight and separation of duties to ensure strategic alignment and risk management.

Option A (Correct):If IT application owners have sole authority over architecture approval, there is a high risk of inadequate governance, lack of strategic alignment, and potential conflicts of interest. Architecture decisions should involve multiple stakeholders, including business and security teams, to ensure compliance, security, and business alignment.

Option B (Incorrect):While having the CIO chair the architecture review board might not be ideal, it is not thegreatestconcern. The CIO is a senior leader who can provide oversight and direction, even if additional governance mechanisms should be in place.

Option C (Incorrect):Reviewing security requirements within the EA program is abest practice, as it ensures that security is embedded into enterprise architecture rather than treated as an afterthought.

Option D (Incorrect):Enterprise architecture should ideally encompass both IT and business processes. Governing non-IT-related projects is not inherently problematic, as EA is designed to align business strategy with IT infrastructure.

 The answer B is correct because data minimization is the most important design consideration to mitigate the risk of exposing data through application programming interface (API) queries. An API is a set of rules and protocols that allows different software components or systems to communicate and exchange data. API queries are requests sent by users or applications to an API to retrieve or manipulate data. For example, a user may query an API to get information about a product, a service, or a location.

Data minimization is the principle of collecting, processing, and storing only the minimum amount of data that are necessary for a specific purpose. Data minimization can help to reduce the risk of exposing data through API queries by limiting the amount and type of data that are available or accessible through the API. Data minimization can also help to protect the privacy and security of the data subjects and the data providers, as well as to comply with the relevant laws and regulations.

Some of the benefits of data minimization for API design are:

Privacy: Data minimization can enhance the privacy of the data subjects by ensuring that only the data that are relevant and essential for the API purpose are collected and processed. This can prevent unnecessary or excessive collection or disclosure of personal or sensitive data, such as names, addresses, phone numbers, email addresses, etc. Data minimization can also help to comply with the privacy laws and regulations that require data protection by design and by default, such as GDPR (General Data Protection Regulation) or CCPA (California Consumer Privacy Act).

Security: Data minimization can improve the security of the data providers by reducing the attack surface and the potential damage of a data breach. If less data are stored or transmitted through the API, there are fewer opportunities for attackers to access or compromise the data. Data minimization can also help to implement security controls such as encryption, access control, or logging more efficiently and effectively.

Performance: Data minimization can increase the performance of the API by optimizing the use of resources and bandwidth. If less data are stored or transmitted through the API, there are less storage space and network traffic required. Data minimization can also help to improve the speed and reliability of the API responses.

Some of the techniques for data minimization in API design are:

Define clear and specific purposes for the API and document them in the API specification or documentation.

Identify and classify the data that are needed for each purpose and assign them appropriate labels or levels, such as public, internal, confidential, or restricted.

Implement filters or parameters in the API queries that allow users or applications to specify or limit the data fields or attributes they want to retrieve or manipulate.

Use pagination or throttling in the API responses that limit the number or size of data items returned per request.

Use anonymization or pseudonymization techniques that remove or replace any identifying information from the data before sending them through the API.

Some examples of web resources that discuss data minimization in API design are:

Data Minimization in Web APIs - World Wide Web Consortium (W3C)

Adding Privacy by Design in Secure Application Development

Chung-ju/Data-Minimization: A repository of related papers. - GitHub

 Implementing an email containerization solution on personal devices is the best recommendation for an IS auditor, because it allows the organization to separate and secure the email data from the rest of the device data. Email containerization creates a virtual environment that encrypts andisolates the email data, preventing unauthorized access, leakage, or loss of sensitive information12. Requiring passwords or antivirus protection on personal devices may not be sufficient or enforceable, while prohibiting employees from storing companyemail onpersonal devices may not be feasible or practical. References: 1: CISA Review Manual (DigitalVersion), Chapter 5, Section 5.4.3 2: CISA Online Review Course, Module 5, Lesson 4

Comprehensive and Detailed Explanation:

The most concerning issue in DLP implementations is when tuning has never been completed.

DLP solutions require fine-tuning to properly recognize sensitive data patterns and avoid false positives/false negatives.

If tuning is incomplete, the solution will either block legitimate business processes (too restrictive) or fail to detect actual leaks (too permissive).

Now let’s break down the options:

Option A: Server support limitations may be an issue, but DLP is primarily endpoint-focused here.

Option B: Implementing blocking mode without tuning can cause disruptions, but it is not as bad as never completing tuning.

Option D: Running in monitoring mode is acceptable in early stages of deployment (testing phase).

Therefore, never completing tuning (C) represents a fundamental control weakness and is the greatest concern.

📖 ISACA Reference: CISA Review Manual 27th Edition, Domain 5, section on data leakage prevention and monitoring tools.