Explanation
Integrity of data means accuracy and completeness of the data. Integrity is one of the three main objectives of information security, along with confidentiality and availability. Integrity ensures that information and systems are not corrupted, modified, or deleted by unauthorized actions or events. Data should be viewable at all times is not related to integrity, but to availability. Data should be accessed by only the right people is not related to integrity, but to confidentiality. References: : CQI & IRCA ISO 27001:2022 Lead Auditor Course Handbook, page 24. : [ISO/IEC 27001 Brochures | PECB], page 4.

Explanation
Audit evidence should be evaluated against the audit criteria in order to determine audit findings.
* Audit evidence is the information obtained by the auditors during the audit process that is used as a basis for forming an audit opinion or conclusion12. Audit evidence could include records, documents, statements, observations, interviews, or test results12.
* Audit criteria are the set of policies, procedures, standards, regulations, or requirements that are used as a reference against which audit evidence is compared12. Audit criteria could be derived from internal or external sources, such as ISO standards, industry best practices, or legal obligations12.
* Audit findings are the results of a process that evaluates audit evidence and compares it against audit criteria13. Audit findings can show that audit criteria are being met (conformity) or that they are not being met (nonconformity). They can also identify best practices or improvement opportunities13.
References :=
* ISO 19011:2022 Guidelines for auditing management systems
* ISO/IEC 27001:2022 Information technology - Security techniques - Information security management systems - Requirements
* Components of Audit Findings - The Institute of Internal Auditors

The four options for the actions you could take are A, C, F, and G. These options are consistent with the guidance and requirements of ISO 19011:2018, Clause 6.712. You could agree with the auditee/audit client how the remaining nonconformity will be cleared, by when, and how its clearance will be verified (A), and document the agreement in the audit report1. You could close the follow-up audit as the organisation has demonstrated it is committed to clearing the nonconformities raised , and report the outcome to the audit client and other relevant parties1. You could note the progress made but hold the audit open until all corrective action has been cleared (F), and determine the need for another follow-up audit or other actions1. You could also advise the individual managing the audit programme of any decision taken regarding the outstanding nonconformity (G), as they are responsible for the overall management and coordination of the audit programme3. The other options are either not appropriate or not necessary for the situation. You should not recommend that the outstanding minor nonconformity is dealt with at the next surveillance audit (B), as this may compromise the audit objectives and the audit programme1. You should not recommend suspension of the organisation's certification as they have failed to implement the agreed corrections and corrective actions within the agreed timescale (D), as this is not within your role or authority as an ISMS auditor4. You should not advise the auditee that you will arrange for the next audit to be an online audit to deal with the outstanding nonconformity (E), as this may not be feasible or effective depending on the nature and complexity of the nonconformity1. You should not conduct an unannounced follow-up audit on-site to review the one outstanding minor nonconformity once it has been cleared (H), as this may not be in accordance with the audit agreement or the audit programme1. References: 1: ISO 19011:2018, Guidelines for auditing management systems, Clause 6.7 \n2: PECB Certified ISO/IEC 27001 Lead Auditor Exam Preparation Guide, Domain 6:
Closing an ISO/IEC 27001 audit \n3: ISO 19011:2018, Guidelines for auditing management systems, Clause
5.3 \n4: ISO/IEC 27006:2022, Information technology - Security techniques - Requirements for bodies providing audit and certification of information security management systems, Clause 9.6

Social engineering is a technique that involves creating a situation wherein a third party gains confidential information from you by manipulating your trust or exploiting your weaknesses. Social engineering can take various forms, such as phishing emails, phone calls, impersonation, or baiting. Social engineering is a common threat to information security, as it targets the human factor rather than the technical defenses. Reference: : CQI & IRCA ISO 27001:2022 Lead Auditor Course Handbook, page 26. : ISO/IEC 27001 LEAD AUDITOR - PECB, page 13.

Explanation
Two types of data classification are restricted data and unrestricted data. Restricted data is data that has a high level of sensitivity or confidentiality, and requires strict protection from unauthorized access, disclosure, modification or destruction. Examples of restricted data include personal data, financial data, trade secrets, intellectual property, etc. Unrestricted data is data that has a low level of sensitivity or confidentiality, and can be freely accessed, disclosed, modified or destroyed without significant consequences. Examples of unrestricted data include public information, marketing materials, general news, etc. Data classification is a process of assigning categories or labels to data based on its value, sensitivity, criticality and legal requirements. Data classification helps to determine the appropriate level of security controls and handling procedures for different types of data. ISO/IEC 27001:2022 requires the organization to classify information in terms of legal requirements, value, criticality and sensitivity to unauthorized disclosure or modification (see clause A.8.2.1). References: [CQI & IRCA Certified ISO/IEC 27001:2022 Lead Auditor Training Course], ISO/IEC 27001:2022 Information technology - Security techniques - Information security management systems - Requirements, What is Data Classification?