{"id":18353,"date":"2026-09-22T06:52:21","date_gmt":"2026-09-22T06:52:21","guid":{"rendered":"https:\/\/www.examlabs.com\/certification\/?p=18353"},"modified":"2026-09-22T06:52:21","modified_gmt":"2026-09-22T06:52:21","slug":"isaca-aair-practice-test-questions-and-exam-dumps-part15-q281-300","status":"publish","type":"post","link":"https:\/\/www.examlabs.com\/certification\/isaca-aair-practice-test-questions-and-exam-dumps-part15-q281-300\/","title":{"rendered":"Isaca AAIR Practice Test Questions and Exam Dumps Part15 Q281-300"},"content":{"rendered":"

View Full <\/b>Isaca AAIR Exam Dumps<\/b><\/a> and Practice Test Dumps.<\/b><\/p>\n


\n<\/b>Q281. An AI governance committee member is also the executive sponsor of a high-risk AI project being reviewed for approval. What is the BEST governance response?<\/b><\/p>\n

    \n
  1. <\/b> Allow the member to make the final decision because of project knowledge<\/span>
    \n<\/span>2.<\/b> Apply the organization’s conflict-of-interest process and preserve independent challenge<\/span>
    \n<\/span>3.<\/b> Cancel the project automatically<\/span>
    \n<\/span>4.<\/b> Remove all business executives from AI governance<\/span><\/li>\n<\/ol>\n

    Correct Answer: 2. Apply the organization’s conflict-of-interest process and preserve independent challenge<\/b><\/p>\n

    Explanation:<\/b> Effective governance requires objective challenge, particularly for high-risk AI decisions. An executive sponsor may provide important business context but also has an interest in project approval. The organization should follow its conflict-of-interest rules, which may require disclosure, recusal from certain decisions, or independent approval by other authorized members. Automatically excluding all executives would remove valuable business expertise, while allowing the sponsor sole authority weakens independence. The goal is to balance informed participation with sufficient separation so risk acceptance, control exceptions, and deployment decisions are made objectively and remain credible to stakeholders.<\/span><\/p>\n

    Q282. A company acquires another organization that operates dozens of AI systems under different governance standards. What should the acquiring company’s AI risk function do FIRST?<\/b><\/p>\n

      \n
    1. <\/b> Immediately retire every acquired AI system<\/span>
      \n<\/span>2.<\/b> Assume the acquired company’s approvals remain sufficient indefinitely<\/span>
      \n<\/span>3.<\/b> Remove the acquired AI systems from reporting until integration is complete<\/span>
      \n<\/span>4.<\/b> Inventory and assess the acquired AI systems against the organization’s governance and risk requirements**<\/span><\/li>\n<\/ol>\n

      Correct Answer: 4. Inventory and assess the acquired AI systems against the organization’s governance and risk requirements<\/b><\/p>\n

      Explanation:<\/b> Mergers and acquisitions can introduce AI systems, datasets, vendors, and risk practices that differ significantly from the acquiring organization’s standards. The first step should be to establish visibility into what has been acquired and assess material systems against existing risk classifications, policies, legal obligations, and control expectations. High-risk gaps can then be prioritized for remediation or temporary restrictions. Automatically retiring systems may unnecessarily disrupt business operations, while assuming prior approvals remain sufficient can leave significant risks unrecognized. Integration should be risk based and supported by clear ownership and transition planning.<\/span><\/p>\n

      Q283. An organization plans to automate work previously performed by a large group of employees. Which AI governance consideration is MOST important in addition to technical risk?<\/b><\/p>\n

        \n
      1. <\/b> Workforce impact, reskilling needs, change management, and affected stakeholder considerations<\/span>
        \n<\/span>2.<\/b> Whether the AI uses the largest available model<\/span>
        \n<\/span>3.<\/b> Whether all employees use identical computers<\/span>
        \n<\/span>4.<\/b> Whether the AI vendor has offices nearby<\/span><\/li>\n<\/ol>\n

        Correct Answer: 1. Workforce impact, reskilling needs, change management, and affected stakeholder considerations<\/b><\/p>\n

        Explanation:<\/b> AI adoption can materially change roles, responsibilities, skills, and employment conditions. Responsible governance should consider how affected employees will transition, what new competencies are required, whether duties or controls are being lost, and how changes will be communicated. Workforce consequences may also create operational, ethical, reputational, and cultural risks. Technical performance alone does not determine whether an AI transformation is successful. Organizations should align implementation with broader change-management practices and consider whether employees need retraining, new oversight responsibilities, or alternative roles as automation changes existing processes.<\/span><\/p>\n

        Q284. A consumer-facing AI service interacts directly with customers who may not realize they are communicating with an automated system. What control is MOST appropriate?<\/b><\/p>\n

          \n
        1. <\/b> Conceal the use of AI to increase adoption<\/span>
          \n<\/span>2.<\/b> Remove all customer feedback mechanisms<\/span>
          \n<\/span>3.<\/b> Provide appropriate transparency that AI is being used and explain relevant limitations or escalation options<\/span>
          \n<\/span>4.<\/b> Require customers to understand the model architecture<\/span><\/li>\n<\/ol>\n

          Correct Answer: 3. Provide appropriate transparency that AI is being used and explain relevant limitations or escalation options<\/b><\/p>\n

          Explanation:<\/b> Transparency helps customers understand when they are interacting with AI and what role the system plays in the service. Depending on the use case and applicable requirements, the organization may also explain important limitations, how significant decisions are reviewed, and how a person can be contacted when necessary. Transparency should be useful and proportionate rather than overwhelming users with technical details. Concealing AI use can undermine trust and may conflict with legal or ethical expectations. Governance should consider the needs of affected stakeholders rather than assuming that technical disclosure is unnecessary.<\/span><\/p>\n

          Q285. A training dataset is transferred among several teams before model development. What control BEST supports confidence that the dataset has not been altered unexpectedly?<\/b><\/p>\n

            \n
          1. <\/b> Integrity verification using controlled repositories, hashes, or equivalent tamper-detection mechanisms<\/span>
            \n<\/span>2.<\/b> Naming the file according to the current date<\/span>
            \n<\/span>3.<\/b> Emailing multiple copies to developers<\/span>
            \n<\/span>4.<\/b> Removing dataset version information<\/span><\/li>\n<\/ol>\n

            Correct Answer: 1. Integrity verification using controlled repositories, hashes, or equivalent tamper-detection mechanisms<\/b><\/p>\n

            Explanation:<\/b> Training-data integrity is important because unauthorized or accidental modification can alter model behavior. Controlled repositories, cryptographic hashes, access controls, versioning, and logging can help demonstrate that the dataset used for training matches the approved version. This also supports investigation when unexpected model behavior occurs. File names alone provide weak evidence because they can be changed easily. Multiple uncontrolled copies increase the risk of version confusion. Data-integrity controls should complement lineage, provenance, quality, authorization, and change-management practices throughout the AI lifecycle.<\/span><\/p>\n

            Q286. An organization stores production AI models in a repository where developers can directly overwrite approved versions. What is the GREATEST risk?<\/b><\/p>\n

              \n
            1. <\/b> Model training will take longer<\/span>
              \n<\/span>2.<\/b> The repository will necessarily become unavailable<\/span>
              \n<\/span>3.<\/b> Model accuracy will always increase<\/span>
              \n<\/span>4.<\/b> Unauthorized or unvalidated models could replace approved production artifacts**<\/span><\/li>\n<\/ol>\n

              Correct Answer: 4. Unauthorized or unvalidated models could replace approved production artifacts<\/b><\/p>\n

              Explanation:<\/b> Production model repositories should protect the integrity of approved artifacts. If developers can overwrite production versions directly, change-management, validation, segregation-of-duties, and audit controls can be bypassed. The organization should restrict write access, preserve immutable versions where appropriate, require controlled promotion, and maintain evidence linking each production artifact to its validation and approval. Model repositories are critical lifecycle assets because even a small unauthorized change can affect many downstream decisions. Strong governance distinguishes experimentation and development repositories from controlled production model stores.<\/span><\/p>\n

              Q287. A forecasting model is evaluated using random train-test splitting, but the real-world task predicts future events from past data. Which testing approach would provide stronger evidence?<\/b><\/p>\n

                \n
              1. <\/b> Use the entire dataset for training and testing<\/span>
                \n<\/span>2.<\/b> Use a time-based split that tests the model on later periods not used for training<\/span>
                \n<\/span>3.<\/b> Remove timestamps before evaluation<\/span>
                \n<\/span>4.<\/b> Evaluate only the model’s training accuracy<\/span><\/li>\n<\/ol>\n

                Correct Answer: 2. Use a time-based split that tests the model on later periods not used for training<\/b><\/p>\n

                Explanation:<\/b> For forecasting problems, random splitting can leak future patterns into training and create unrealistically strong results. A time-based split better represents the actual use case by training on earlier periods and evaluating on later unseen data. This provides stronger evidence that the model generalizes forward in time. The exact design depends on the business context, seasonality, and data availability. Evaluation methodology should mimic production conditions as closely as practical because misleading test design can lead management to approve a model whose real-world performance is substantially weaker.<\/span><\/p>\n

                Q288. An organization wants to introduce a newly validated AI model gradually rather than expose all users at once. Which deployment method BEST reduces rollout risk?<\/b><\/p>\n

                  \n
                1. <\/b> Immediate enterprise-wide deployment<\/span>
                  \n<\/span>2.<\/b> Disable production monitoring during the release<\/span>
                  \n<\/span>3.<\/b> Canary or phased deployment with predefined monitoring and rollback criteria<\/span>
                  \n<\/span>4.<\/b> Delete the previous model before deployment<\/span><\/li>\n<\/ol>\n

                  Correct Answer: 3. Canary or phased deployment with predefined monitoring and rollback criteria<\/b><\/p>\n

                  Explanation:<\/b> A canary or phased deployment limits initial exposure to a subset of users, transactions, or business units. The organization can observe model performance, fairness, latency, incidents, and other risk indicators under real operating conditions before expanding the rollout. Predefined rollback thresholds allow rapid response when behavior differs from approved expectations. This approach does not replace predeployment validation, but it reduces blast radius when production reveals issues that testing did not identify. Retaining the previous known-good model can also support controlled recovery if the new version performs poorly.<\/span><\/p>\n

                  Q289. A malicious third party publishes a modified version of a legitimate pretrained model containing a hidden behavior that activates when a particular input pattern appears. What threat does this BEST describe?<\/b><\/p>\n

                    \n
                  1. <\/b> Normal model drift<\/span>
                    \n<\/span>2.<\/b> Data minimization failure<\/span>
                    \n<\/span>3.<\/b> Model calibration error<\/span>
                    \n<\/span>4.<\/b> A model backdoor or trojan introduced through the supply chain**<\/span><\/li>\n<\/ol>\n

                    Correct Answer: 4. A model backdoor or trojan introduced through the supply chain<\/b><\/p>\n

                    Explanation:<\/b> A backdoored model can behave normally during ordinary testing while producing attacker-chosen behavior when a hidden trigger appears. This makes model provenance, integrity verification, trusted repositories, independent testing, and supply-chain controls important when acquiring pretrained models. Standard accuracy testing may not detect the problem if trigger conditions are absent from evaluation data. Organizations should treat external model artifacts similarly to other critical software supply-chain components and validate authenticity, provenance, licensing, maintenance status, and relevant security characteristics before production deployment.<\/span><\/p>\n

                    Q290. Two AI risks have the same likelihood and impact ratings, but one is very difficult to detect before harm occurs. What additional characteristic may justify giving it higher priority?<\/b><\/p>\n

                      \n
                    1. <\/b> Low detectability or limited warning before impact<\/span>
                      \n<\/span>2.<\/b> The model has a shorter name<\/span>
                      \n<\/span>3.<\/b> The affected system uses fewer servers<\/span>
                      \n<\/span>4.<\/b> The risk was documented later<\/span><\/li>\n<\/ol>\n

                      Correct Answer: 1. Low detectability or limited warning before impact<\/b><\/p>\n

                      Explanation:<\/b> Likelihood and impact are important, but additional risk characteristics can help management prioritize scenarios with similar base ratings. A risk that is difficult to detect may progress further before containment begins and could therefore warrant stronger preventive controls or monitoring. Other useful dimensions can include velocity, persistence, concentration, and reversibility. These factors should be incorporated consistently into the organization’s methodology rather than used arbitrarily. Considering detectability can improve treatment decisions where two risks appear identical using only conventional likelihood-impact scoring.<\/span><\/p>\n

                      Q291. Management wants to compare potential annual financial exposure from two AI risk scenarios. Which approach is MOST useful?<\/b><\/p>\n

                        \n
                      1. <\/b> Compare only model accuracy<\/span>
                        \n<\/span>2.<\/b> Rank risks by the number of controls<\/span>
                        \n<\/span>3.<\/b> Estimate frequency and financial impact ranges for each scenario using documented assumptions<\/span>
                        \n<\/span>4.<\/b> Select whichever scenario has the longer description<\/span><\/li>\n<\/ol>\n

                        Correct Answer: 3. Estimate frequency and financial impact ranges for each scenario using documented assumptions<\/b><\/p>\n

                        Explanation:<\/b> Quantitative comparison can help management understand the relative financial significance of risk scenarios. The organization can estimate event frequency and potential loss ranges while documenting assumptions and uncertainty. Relevant losses might include service interruption, regulatory penalties, customer remediation, investigation costs, lost revenue, or contractual liability. Estimates should not imply more precision than the evidence supports. Sensitivity analysis can show which assumptions most affect the result. Quantification complements rather than replaces qualitative considerations such as ethics, safety, legal rights, or reputational effects that may be difficult to express financially.<\/span><\/p>\n

                        Q292. A proposed AI control is technically incapable of preventing the risk event it is supposed to address, even if it operates exactly as documented. What type of control problem is this?<\/b><\/p>\n

                          \n
                        1. <\/b> Operating-effectiveness failure only<\/span>
                          \n<\/span>2.<\/b> Control design deficiency<\/span>
                          \n<\/span>3.<\/b> Successful compensating control<\/span>
                          \n<\/span>4.<\/b> Risk transfer<\/span><\/li>\n<\/ol>\n

                          Correct Answer: 2. Control design deficiency<\/b><\/p>\n

                          Explanation:<\/b> Control design effectiveness asks whether a control, if implemented and operated correctly, is capable of achieving its intended risk-reduction objective. If the control cannot address the underlying threat or failure mode, the problem exists in the design itself. Operating-effectiveness testing would be relevant only after an adequate design exists. Management should redesign or replace the control and reassess residual risk. Distinguishing design from operating failures helps identify whether remediation should change the control concept or improve how an otherwise sound control is executed.<\/span><\/p>\n

                          Q293. An AI model owner is also listed as the owner of a control that restricts model deployment. Why may the organization still need to distinguish the two responsibilities?<\/b><\/p>\n

                            \n
                          1. <\/b> Model ownership and control ownership involve different accountability for asset performance and control operation<\/span>
                            \n<\/span>2.<\/b> One individual can never hold more than one role<\/span>
                            \n<\/span>3.<\/b> Model owners should not understand controls<\/span>
                            \n<\/span>4.<\/b> Control owners are responsible only for financial reporting<\/span><\/li>\n<\/ol>\n

                            Correct Answer: 1. Model ownership and control ownership involve different accountability for asset performance and control operation<\/b><\/p>\n

                            Explanation:<\/b> Model owners are generally accountable for appropriate use, performance, lifecycle decisions, and business suitability of the AI asset. Control owners are accountable for ensuring a specific safeguard is designed, implemented, monitored, and remediated appropriately. The same person may hold both roles in some organizations, but the responsibilities should still be defined distinctly so governance activities are clear. This distinction improves accountability, testing, escalation, and separation-of-duties analysis. Ambiguous ownership can result in important risk or control tasks being assumed by everyone and performed by no one.<\/span><\/p>\n

                            Q294. An organization transfers some financial AI risk through insurance, but a major incident could still damage customer trust. What should the residual-risk assessment recognize?<\/b><\/p>\n

                              \n
                            1. <\/b> Insurance removes all AI risk<\/span>
                              \n<\/span>2.<\/b> Reputational and operational consequences may remain even when some financial loss is transferred<\/span>
                              \n<\/span>3.<\/b> The risk should be removed from the register<\/span>
                              \n<\/span>4.<\/b> Customer trust is irrelevant to risk assessment<\/span><\/li>\n<\/ol>\n

                              Correct Answer: 4. Reputational and operational consequences may remain even when some financial loss is transferred<\/b><\/p>\n

                              Explanation:<\/b> Risk transfer generally shifts only specified consequences to another party. Insurance may reimburse certain direct costs, but it cannot fully transfer customer harm, business interruption, management distraction, regulatory scrutiny, or reputational damage. Residual-risk assessment should identify which consequences remain with the organization after the transfer mechanism is considered. This is why risk transfer often complements rather than replaces prevention, detection, response, and continuity controls. Management should avoid assuming that a financial contract eliminates the underlying scenario or organizational accountability.<\/span><\/p>\n

                              Q295. An organization is establishing a threshold for an AI model-error KRI. What should MOST influence the threshold?<\/b><\/p>\n

                                \n
                              1. <\/b> The number of people attending governance meetings<\/span>
                                \n<\/span>2.<\/b> Competitors’ model sizes<\/span>
                                \n<\/span>3.<\/b> The risk tolerance and business consequence associated with model errors<\/span>
                                \n<\/span>4.<\/b> The preferred threshold of the development team<\/span><\/li>\n<\/ol>\n

                                Correct Answer: 3. The risk tolerance and business consequence associated with model errors<\/b><\/p>\n

                                Explanation:<\/b> KRI thresholds should connect measurable conditions to the level of exposure the organization is willing to tolerate. A 5% error rate might be acceptable for a low-impact content recommendation but completely unacceptable for a safety-critical decision. Thresholds should therefore reflect business consequence, stakeholder impact, regulatory obligations, model criticality, and enterprise risk tolerance. They should also have defined escalation and response procedures. Arbitrary thresholds provide little governance value even when the underlying metric itself is measured accurately.<\/span><\/p>\n

                                Q296. A board wants AI risk information grouped into themes such as privacy, legal, operational, and third-party risk rather than individual model-level issues. What is the PRIMARY benefit?<\/b><\/p>\n

                                  \n
                                1. <\/b> It removes the need for underlying risk records<\/span>
                                  \n<\/span>2.<\/b> It supports aggregation and identification of enterprise-level concentrations and trends<\/span>
                                  \n<\/span>3.<\/b> It guarantees each individual risk will be low<\/span>
                                  \n<\/span>4.<\/b> It prevents risk owners from receiving reports<\/span><\/li>\n<\/ol>\n

                                  Correct Answer: 2. It supports aggregation and identification of enterprise-level concentrations and trends<\/b><\/p>\n

                                  Explanation:<\/b> Thematic reporting can help boards understand where AI exposure is accumulating across the enterprise. Individual model risks may appear manageable in isolation while collectively creating significant privacy, third-party, legal, or operational concentration. Aggregation should preserve traceability to underlying risk records so management can investigate drivers and treatment status. Executive reporting should summarize without losing accountability. This approach supports portfolio-level decisions, resource allocation, and assessment of whether enterprise risk appetite remains appropriate as AI adoption expands.<\/span><\/p>\n

                                  Q297. A third-party AI vendor hosts customer data through several subprocessors in different countries. Which information is MOST important for ongoing supply-chain oversight?<\/b><\/p>\n

                                    \n
                                  1. <\/b> The vendor’s advertising budget<\/span>
                                    \n<\/span>2.<\/b> Number of employees in each country<\/span>
                                    \n<\/span>3.<\/b> Office-opening hours<\/span>
                                    \n<\/span>4.<\/b> Material subprocessors, processing locations, roles, and notification of significant changes**<\/span><\/li>\n<\/ol>\n

                                    Correct Answer: 4. Material subprocessors, processing locations, roles, and notification of significant changes<\/b><\/p>\n

                                    Explanation:<\/b> Customers need visibility into material subprocessors because those entities may handle sensitive data or provide critical components of the AI service. Relevant information includes what each subprocessor does, where processing occurs, how data is protected, and how changes will be communicated. This supports privacy, residency, concentration, resilience, and contractual risk assessment. The required depth of oversight should be proportionate to service criticality and data sensitivity. Supply-chain governance is ineffective if it considers only the direct provider while ignoring important upstream dependencies.<\/span><\/p>\n

                                    Q298. An AI incident response team contains technical specialists but no representative authorized to decide whether customer transactions should be suspended. What is the PRIMARY gap?<\/b><\/p>\n

                                      \n
                                    1. <\/b> The team lacks sufficient business decision authority for containment actions<\/span>
                                      \n<\/span>2.<\/b> The team needs a larger AI model<\/span>
                                      \n<\/span>3.<\/b> The incident must be reclassified automatically as low severity<\/span>
                                      \n<\/span>4.<\/b> Technical teams should make every business decision<\/span><\/li>\n<\/ol>\n

                                      Correct Answer: 2. The team lacks sufficient business decision authority for containment actions<\/b><\/p>\n

                                      Explanation:<\/b> Incident response requires both technical expertise and appropriate decision authority. Technical responders may identify the problem, but suspending customer transactions can have significant financial, contractual, and customer consequences requiring an authorized business decision-maker. Response plans should identify who can disable systems, stop business processes, invoke fallbacks, communicate externally, and accept temporary impacts. Without clear authority, containment may be delayed while harmful activity continues. Cross-functional incident structures improve the organization’s ability to respond quickly while maintaining accountability.<\/span><\/p>\n

                                      Q299. A business continuity strategy depends on switching to an alternate AI provider during a major outage. What provides the STRONGEST evidence that this strategy will work?<\/b><\/p>\n

                                        \n
                                      1. <\/b> A successful test demonstrating compatible data, interfaces, performance, and operating procedures<\/span>
                                        \n<\/span>2.<\/b> The alternate provider’s marketing claim<\/span>
                                        \n<\/span>3.<\/b> A contract signed several years ago<\/span>
                                        \n<\/span>4.<\/b> The assumption that all AI providers are interchangeable<\/span><\/li>\n<\/ol>\n

                                        Correct Answer: 1. A successful test demonstrating compatible data, interfaces, performance, and operating procedures<\/b><\/p>\n

                                        Explanation:<\/b> Alternate-provider strategies often fail because of incompatible APIs, model behavior, data formats, credentials, capacity, contractual restrictions, or operational procedures. Testing provides practical evidence that failover can be achieved within required business objectives. The exercise should validate data availability, integrations, required skills, performance, and recovery procedures. It may not be necessary to conduct a full production switch frequently, but material assumptions should be tested periodically. Vendor claims or contract language alone cannot demonstrate end-to-end operational readiness.<\/span><\/p>\n

                                        Q300. An organization uses AI to automate testing of AI risk controls. What is the MOST important governance consideration?<\/b><\/p>\n

                                          \n
                                        1. <\/b> AI-generated test results should automatically close all findings<\/span>
                                          \n<\/span>2.<\/b> Human reviewers should never inspect automated results<\/span>
                                          \n<\/span>3.<\/b> The AI testing tool itself should be validated, monitored, and subject to appropriate human oversight<\/span>
                                          \n<\/span>4.<\/b> AI-based testing eliminates the need for independent assurance<\/span><\/li>\n<\/ol>\n

                                          Correct Answer: 3. The AI testing tool itself should be validated, monitored, and subject to appropriate human oversight<\/b><\/p>\n

                                          Explanation:<\/b> Using AI to test controls can increase coverage and efficiency, but the testing tool becomes part of the assurance process and introduces its own risk. The organization should understand its limitations, validate its outputs, monitor performance, control access, and retain qualified human oversight for material conclusions. False positives can waste resources, while false negatives can create misplaced confidence in ineffective controls. AI-assisted assurance should augment rather than automatically replace professional judgment, especially for high-risk systems and controls requiring independent challenge.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

                                          View Full Isaca AAIR Exam Dumps and Practice Test Dumps. Q281. An AI governance committee member is also the executive sponsor of a high-risk AI project being reviewed for approval. What is the BEST governance response? Allow the member to make the final decision because of project knowledge 2. Apply the organization’s conflict-of-interest process and […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[1648,1647],"tags":[],"_links":{"self":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/18353"}],"collection":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/comments?post=18353"}],"version-history":[{"count":1,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/18353\/revisions"}],"predecessor-version":[{"id":18354,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/18353\/revisions\/18354"}],"wp:attachment":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/media?parent=18353"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/categories?post=18353"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/tags?post=18353"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}