CISA Exam Dumps - Certified Information Systems Auditor

The completeness of the vulnerability scanning process depends on the accuracy and currency of the organization’s systems inventory, which is a list of all the hardware and software assets that are owned or used by the organization. A complete and up-to-date systems inventory can help ensure that all the systems are identified and scanned for vulnerabilities, and that no system is missed or overlooked. Vulnerability scanning results are reported to the CISO is a good practice for ensuring accountability and visibility of the vulnerability management process, but it is not the most important thing to verify when determining the completeness of the vulnerability scanning process, as reporting does not guarantee that all the systems are scanned. The organization is using a cloud-hosted scanning tool for identification of vulnerabilities is a possible option for conducting vulnerability scanning, but it is not the most important thing to verify when determining the completeness of the vulnerability scanning process, as the type of scanning tool does not affect the scope or coverage of the scanning. Access to the vulnerability scanning tool is periodically reviewed is a critical control for ensuring the security and integrity of the vulnerability scanning tool, but it is not the most important thing to verify when determining the completeness of the vulnerability scanning process, as access review does not ensure that all the systems are scanned. 

 IT value analysis has not been completed is a finding from an IT governance review that should be of greatest concern. IT value analysis is a process of measuring and demonstrating the contribution of IT to the organization’s goals and objectives. An IS auditor should be concerned about the lack of IT value analysis, as it may indicate that the IT investments and resources are not aligned with the business needs and expectations, or that the IT performance and outcomes are not monitored and evaluated. The other options are less critical findings that may not have a significant impact on the IT governance. References:

CISA Review Manual (Digital Version), Chapter 5, Section 5.11

CISA Review Questions, Answers & Explanations Database, Question ID 218

The answer D is correct because the best way for the auditor to confirm the change log is complete is to take the last change from the system and trace it back to the log. A change log is a record of all the changes that have been made to a system, such as software updates, bug fixes, configuration modifications, etc. A change log should contain information such as the date and time of the change, the description and purpose of the change, the person or service who made the change, and the approval status of the change. A complete change log helps to ensure that the system is secure, reliable, and compliant with the relevant standards and regulations.

An IS auditor evaluating the change management process must select a sample from the change log to verify that the changes are properly authorized, documented, tested, and implemented. However, before selecting a sample, the auditor must ensure that the change log is complete and accurate, meaning that it contains all the changes that have been made to the system and that there are no missing, duplicated, or falsified entries. To do this, the auditor can use a technique called backward tracing, which involves taking the last change from the system and tracing it back to the log. This way, the auditor can check if the change is recorded in the log with all the relevant details and if there are any gaps or inconsistencies in the log. If the last change from the system is not found in the log or does not match with the log entry, it indicates that the change log is incomplete or inaccurate.

The other options are not as good as option D. Interviewing change management personnel about completeness (option A) is not a reliable way to confirm the change log is complete because it relies on subjective opinions and self-reported information, which may not be truthful or accurate. Taking an item from the log and tracing it back to the system (option B) is a technique called forward tracing, which can be used to verify that a specific change in the log has been implemented in the system. However, this technique does not confirm that all changes in the system are recorded in the log. Obtaining management attestation of completeness (option C) is not a sufficient way to confirm the change log is complete because it does not provide any evidence or verification of completeness. Management attestation may also be biased or influenced by conflicts of interest.

The most effective way to identify exfiltration of sensitive data by a malicious insider is to establish behavioral analytics monitoring. Behavioral analytics is the process of analyzing the patterns and anomalies in user behavior to detect and prevent insider threats. Behavioral analytics can help identify unusual or suspicious activities, such as accessing sensitive data at odd hours, transferring large amounts of data to external devices or locations, or using unauthorized applications or protocols. Behavioral analytics can also help correlate data from multiple sources, such as network logs, user profiles, and access rights, to provide a holistic view of user activity and risk.

Data loss prevention (DLP) software is a tool that can help prevent exfiltration of sensitive data by a malicious insider, but it is not the most effective way to identify it. DLP software can block or alert on unauthorized data transfers based on predefined rules and policies, but it may not be able to detect sophisticated or stealthy exfiltration techniques, such as encryption, steganography, or data obfuscation.

Reviewing perimeter firewall logs is a way to identify exfiltration of sensitive data by a malicious insider, but it is not the most effective way. Perimeter firewall logs can show the traffic volume and destination of data transfers, but they may not be able to show the content or context of the data. Perimeter firewall logs may also be overwhelmed by the amount of normal traffic and miss the signals of malicious exfiltration.

Providing ongoing information security awareness training is a way to reduce the risk of exfiltration of sensitive data by a malicious insider, but it is not a way to identify it. Information security awareness training can help educate users on the importance of protecting sensitive data and the consequences of violating policies and regulations, but it may not deter or detect those who are intentionally or maliciously exfiltrating data.

The best recommendation to prevent unauthorized access to a highly sensitive data center by piggybacking or tailgating is to use an airlock entrance. An airlock entrance is a type of access control system that consists of two doors that are interlocked, so that only one door can be opened at a time. This prevents an unauthorized person from following an authorized person into the data center without being detected. An airlock entrance can also be integrated with other security measures, such as biometrics, card readers, or PIN pads, to verify the identity and authorization of each person entering the data center.

Biometrics (option A) is a method of verifying the identity of a person based on their physical or behavioral characteristics, such as fingerprints, iris scans, or voice recognition. Biometrics can provide a high level of security, but they are not sufficient to prevent piggybacking or tailgating, as an unauthorized person can still follow an authorized person who has been authenticated by the biometric system.

Procedures for escorting visitors (option B) is a policy that requires all visitors to the data center to be accompanied by an authorized employee at all times. This can help prevent unauthorized access by visitors, but it does not address the risk of piggybacking or tailgating by other employees or contractors who may have legitimate access to the building but not to the data center.

Intruder alarms (option D) are devices that detect and alert when an unauthorized person enters a restricted area. Intruder alarms can provide a deterrent and a response mechanism for unauthorized access, but they are not effective in preventing piggybacking or tailgating, as they rely on the detection of the intruder after they have already entered the data center.

Full disk encryption (FDE) is a means of protecting information by encrypting all of thedata on a disk, including temporary files, programs, and system files1. FDE is best suited for addressing the risk scenario of physical theft of media on which information is stored, as it prevents unauthorized access to the data even if the device is lost or stolen2. FDE does not prevent data leakage as a result of employees leaving to work for competitors, as they may still have access to the data while using the device or copy the data to another device before leaving. FDE does not prevent noncompliance fines related to storage of regulated information, as it does not ensure that the data is stored in accordance with the applicable laws and regulations. FDE does not prevent unauthorized logical access to information through an application interface, as it does not control the access rights and permissions of users and applications. *References: According to the ISACA IT Audit and Assurance Standards, Guidelines and Tools and Techniques for IS Audit and Assurance Professionals, section 2402 Planning, “The IS audit and assurance professional should identify and assess risk relevant to the area under review.” 3 Oneof the risk factors to consider is “the sensitivity of information processed, stored or transmitted by the system” 3. FDE is one of the possible controls to mitigate the risk of unauthorized disclosure of sensitive information due to physical theft of media.

 The most useful analytical method when trying to identify groups with similar behavior or characteristics in a large population is classification. Classification is a technique that assigns data points to predefined categories or classes based on their features or attributes. Classification can help to discover patterns, trends, and relationships among the data and reveal the similarities or differences among the groups. Classification can also help to support decision making, prediction, or recommendation based on the data analysis. References:

CISA ReviewManual (Digital Version), Chapter 3, Section 3.4.21

CISA Online Review Course, Domain 2, Module 3, Lesson 12