IIA IIA-CIA-PART3-3P Exam Prep
Certified Internal Auditor - Part 3, Business Analysis and Information Technology (Page 129 )

• A. Modify CommunitiesSelfRegController

• C. Configure Communities registration to use a custom Visualforce page

• B. Modify the self-registration trigger — There is no standard “self-registration trigger” intended for this configuration. The registration logic is handled by the Visualforce controller.
• D. Configure a custom Apex controller — The standard approach is to modify the provided CommunitiesSelfRegController, rather than simply selecting a separate controller configuration.

• Date: 2018-12-31
• Time: 08:59

• B: The original value contains the text at, so it cannot be converted directly to a date.
• A: The last characters contain the time, not the date.
• D: Extracting the first 11 characters can leave an unwanted space and does not properly separate the time component.

1. The sender hashes the original message and sends the message plus its hash.
2. The receiver applies the same hashing algorithm to the received message.
3. The receiver compares the newly calculated hash with the sender’s hash.
4. Matching values indicate that the message was not altered in transit.

• A binary image is not the normal description of a hash result.
• Using a different algorithm produces a different type of digest, so the values cannot be directly compared.
• Hashing verifies integrity, but by itself does not prove who sent the message. Digital signatures or MACs address authentication and integrity together.

• The first step in risk management is to understand objectives, constraints, and drivers from those who care about the project. This stakeholder engagement helps identify what could go wrong and what risks are most critical.
• Only after you’ve gathered input from stakeholders should you identify risks and document them in the risk register. Updating the risk register (option C) is important, but it comes after identifying and analyzing risks.
• Options B (ensure resources) and D (revise the risk management plan) are actions that may follow once risks are identified and understood; they’re not the initial step.

• Multiple AWS accounts: Create a separate account for each department or workload. This provides clear isolation and makes it easier to track each department’s usage and costs for chargeback.
• Consolidated billing: AWS Organizations can combine billing for multiple accounts into one central payer account. The company can still view costs by account while managing payment centrally.

• Placement groups: Control how EC2 instances are physically placed for networking or performance; they do not provide departmental billing separation.
• Edge locations: Infrastructure used by services such as Amazon CloudFront; unrelated to chargeback.
• AWS Config: Records and evaluates resource configurations and compliance; it is not a billing-separation mechanism.

• OpenID Connect (OIDC) is an authentication layer built on OAuth 2.0.
• It returns an ID token, normally a JWT containing identity claims such as the user’s subject, name, email, or other permitted attributes.
• The wellness application can consume those claims without needing a separate user-information call.

• JWT Bearer Token Flow: intended for server-to-server authorization and does not primarily provide an end-user ID token.
• Web Server Flow: is an OAuth authorization-code flow. It can be used with OIDC in some implementations, but “Web Server Flow” alone does not specifically guarantee an ID token.
• User Agent Flow: describes an OAuth flow, not the identity protocol itself.

Flat organisation

• Few levels of management
• A wide span of control—managers supervise many employees
• Shorter communication channels
• More employee autonomy and quicker decisions
• Fewer formal promotion levels

Tall organisation

• Many levels of management
• A narrow span of control—managers supervise relatively few employees
• A clear hierarchy and reporting structure
• More formal supervision and communication channels
• More obvious promotion and career stages

• Árvores de decisão: usam regras sequenciais, como “se característica X > valor, siga para este ramo”. São fáceis de visualizar e explicar. Atendem bem a problemas de classificação e regressão com alta interpretabilidade.

• Regressão linear: prevê um valor numérico contínuo, como preço, custo ou temperatura. Não é a escolha principal para classificar genes em categorias.

• Regressão logística: calcula a probabilidade de uma categoria. Pode atender à classificação, inclusive multiclasses, mas sua explicação costuma ser menos intuitiva que uma árvore para documentar decisões.

• Redes neurais: atendem a tarefas complexas, como imagens, texto e padrões não lineares. Porém, são menos interpretáveis, funcionando mais como uma “caixa-preta”.

• Assign users or their team an appropriate security role.
• Ensure the role has the required table privileges, such as read, create, write, and append.
• Share the app with that security role in the app designer.

• Dynamics administration center: Used for environment and service administration, not routine app access configuration.
• Manage Roles: Not the specific Dataverse area used to define app and data permissions.
• Security Roles: Define what users can access and which operations they can perform.

1. Determine which host was infected first—the originating host.
2. Decide whether each other host is clean or infected based on communication and event logs.

• Compare timestamps and find the earliest suspicious event.
• Look for the host that initiated the malicious connection, file transfer, exploit, or command—not merely a host that later received traffic.
• Follow the timeline through the firewall:

• A host is likely infected if it both receives suspicious activity and then initiates related malicious traffic.
• A host may be clean if the firewall blocked the connection and there is no evidence of execution or follow-on communication.

• Assign a Teams license to a user — Licenses are assigned through the Microsoft 365 admin center, Microsoft Entra ID, or PowerShell.
• Deploy the Teams client — The Teams admin center manages Teams policies and apps, but it is not the primary tool for deploying the desktop client.
• Prevent users from creating teams — Team creation depends on controlling the creation of Microsoft 365 groups, generally configured through Microsoft Entra ID and PowerShell rather than directly in the Teams admin center.

• VM CPU, memory, disk, and network usage
• Storage transactions and latency
• App Service response time
• Database DTU or CPU utilization

• Azure Traffic Analytics analyzes network traffic flows and security patterns; it is not the general infrastructure metrics tool.
• Azure Activity Log records subscription-level control-plane operations, such as resource creation, deletion, or configuration changes.
• Azure Advisor provides recommendations about cost, security, reliability, performance, and operational excellence, but it is not the primary tool for investigating live metrics.

• The two correct options are:

• The two incorrect options:

• SageMaker endpoint: Not required because the model is being used through Amazon Bedrock.
• SageMaker Model Registry: Used for managing SageMaker models, not for making a Bedrock custom model available.
• Grant access in Amazon Bedrock: IAM permissions may still be needed, but granting access alone does not provide the required inference capacity.

• MFA verifies a user’s identity using additional authentication factors, such as a phone prompt or security token.
• It helps prevent unauthorized access even if a password is compromised.
• It does not provide secure storage or encryption of credentials used during automated deployment.

• Why: Table.Profile returns a per-column profile that includes statistics such as count, null count, distinct count, and standard deviation. It also provides min/max and average where applicable, which matches the requested metrics (Count, Average, Null count, Distinct count, Standard deviation).
• Syntax: Table.Profile(table as table, optional additionalAggregates as nullable list) as table
• How it helps: After running Table.Profile on your table, you can extract the per-column stats you need and display them in your semantic model or report.

• Compensating control: The server is end-of-life, so it may no longer receive security patches or support. Placing it on a restricted VLAN provides an alternative layer of protection by reducing who can access it and limiting its exposure.
• Technical control: VLAN segmentation and access control lists (ACLs) are technology-based mechanisms that enforce network access restrictions automatically.

• Managerial: Policies, procedures, and governance—not network configuration.
• Physical: Locks, guards, or barriers.
• Corrective: Restores systems after an incident.
• Detective: Identifies suspicious activity rather than restricting access.
• Deterrent: Discourages behavior but does not enforce access rules.

1. Start with the 48-bit MAC address.
2. Split it into two 24-bit halves.
3. Insert FF:FE between the halves, creating a 64-bit value.
4. Invert the U/L bit—the seventh bit from the left in the first MAC byte.

text 
MAC:       00:1A:2B:3C:4D:5E 
EUI-64:    02:1A:2B:FF:FE:3C:4D:5E

• FE80 is the prefix commonly used for an IPv6 link-local address, not part of the EUI-64 interface ID.
• The interface ID is not random.
• The MAC address is modified by inserting FF:FE and changing the U/L bit.

• Correct answer: A
• What this is saying: You need to write a Transact-SQL query that uses REGEXP_SUBSTR to extract the ID from MessageText, and you should apply STRING_ESCAPE(MessageText, 'json') before calling REGEXP_SUBSTR.

• MessageText may contain JSON characters (quotes, backslashes, etc.). Escaping the JSON content first ensures the string you pass to the regex is safe and won’t confuse the regex engine.
• The pattern you apply with REGEXP_SUBSTR would then extract the first substring that matches your ID pattern from the (escaped) text.

• Example (conceptual):

• The question implies REGEXP_SUBSTR is available in this environment; some SQL Server and Fabric contexts don’t expose it natively in all versions. If REGEXP_SUBSTR isn’t available, you’d need an alternative approach (e.g., using built-in regex-like capabilities or CLR/UDFs).
• If you need the ID specifically from the first paragraph, you might first isolate the first paragraph and then apply REGEXP_SUBSTR, or compose a single pattern that anchors to the first paragraph.

• The requirement is a fully managed file server that natively supports Microsoft workloads and file systems and uses the SMB protocol. FSx for Windows File Server is built specifically for Windows workloads, provides native SMB file shares, and supports Windows permissions/Active Directory integration.
• Why the others don’t fit:

json 
"Resource": "arn:aws:s3:::bucket-name/*"

• A: Revoking or changing an instance profile does not reliably invalidate temporary credentials that have already been issued and may still be valid.
• B: Changing the EC2 security group does not necessarily stop the attacker from using the stolen credentials from elsewhere.
• C: Amazon Macie helps discover sensitive data; Object Lock prevents modification/deletion, not reads or downloads.

• Hardware and infrastructure
• System software
• Networks and communications
• Technology platforms and services

• Business Architecture: Defines business strategy, organization, functions, and processes.
• Data Architecture: Defines the structure and management of enterprise data.
• Application Architecture: Describes application systems and how they interact to support business and data processing.

• SAMLRequest: the SAML authentication request
• RelayState: the original destination or application state

• RedirectURL: not the standard SAML parameter for preserving the original request.
• DisplayState: not a standard SAML SSO parameter.
• StartURL: Salesforce-related terminology, but not the standard parameter used in this SAML exchange.

• A — Reports: Reports are informational and don’t enforce access during an SSO transaction.
• B — Apex trigger and Permission Sets: A trigger could update permissions when a Case changes, but this creates synchronization and timing issues. It also changes Salesforce permissions rather than making a direct, real-time decision for the external system.
• C — Custom SAML JIT Provisioning: JIT provisioning is primarily for creating or updating users at login. It isn’t the appropriate mechanism for dynamically querying business records and deciding whether access should be granted.
• D — Connected App Handler: Designed for custom, programmatic control during connected-app authentication and authorization. Apex can check the user’s current open classified cases and permit or reject the SSO request.

• A — Add a Path for Stage: A Path lets users update the Opportunity’s Stage directly from the record page, without opening the full edit form. It can also display guidance and key fields.
• B — Use a Kanban list view: Users can move Opportunities between stages by dragging records between columns, which is ideal when Stage is the only field they normally change.

• Correct answer: Day 3 (Option B)

• Why: In Engagement Studio, when the program is paused, the prospects’ wait times are also paused and do not count down. They resume from the same point when the program restarts. Here, the prospect was at day 3 of a 5-day wait when paused, so they resume on day 3 after the 1-day pause.

• A — IDS attack signatures: An IDS generally detects suspicious network activity but does not necessarily scan uploaded PDF files or prevent them from being accepted.
• C — Load balancer: Distributes traffic among servers; it does not inspect files for malware.
• D — WAF command-injection blocking: A WAF can help block web attacks such as command injection, SQL injection, and cross-site scripting, but this option does not specifically address malicious PDF uploads.

• Developed and maintained independently
• Deployed without changing the entire application
• Scaled separately based on demand
• More resilient when another service has problems

• A: Functional testing is useful, but it is not the main practice described.
• B: Automation helps deployment, but the scenario focuses on architectural decomposition.
• C: Multiple locations improve availability, not application modularity.

• The 99.99% availability SLA for VMs is achieved when you run VMs across two or more Availability Zones.
• Two VMs in a single Availability Zone do not meet the 99.99% target (their SLA is lower, e.g., around 99.95% or less depending on configuration).

• Deploy at least two VMs across two different Availability Zones (one VM in each zone, or both in two zones with a load balancer).
• This provides the required zone redundancy and the 99.99% SLA.

• A. Implement retries with exponential backoff

• C. Reduce the frequency and/or size of requests

• B. Use PutRecord instead of PutRecords — PutRecord sends one record per call and does not remove the underlying throughput limitation. It may increase request overhead.
• D. Use Amazon SNS instead — SNS is not a direct fix for Kinesis shard throttling and changes the required streaming architecture.
• E. Reduce KCL consumers — KCL consumers read from Kinesis; they do not solve producer-side PutRecords throttling.

• Server — provides services or resources
• Endpoint — a user device connected to the network
• Ethernet — a networking technology, not a filtering device
• Firewall — filters and controls traffic

• The Balanced Scorecard translates an organization’s vision and strategy into a set of concrete objectives and metrics across four perspectives (financial, customer, internal processes, learning & growth). This framework explicitly links IT goals to business goals and provides a way to measure and monitor alignment over time.

• Enterprise architecture (EA): Great for governance, standards, and roadmaps to ensure IT assets support business needs, but it’s more about structure and alignment at design time rather than directly measuring ongoing alignment of goals.
• KPIs: Useful metrics, but they don’t by themselves provide a full framework to ensure IT goals are aligned with organizational strategy.
• Enterprise dashboard: A visualization tool for metrics; it helps report status but doesn’t inherently establish or assess alignment.

• Create and manage catalogs of approved IT services
• Govern and publish infrastructure-as-code (IaC) templates, commonly AWS CloudFormation templates
• Control which users can deploy specific products and configurations
• Apply versioning, permissions, and deployment constraints

• AWS Resource Explorer: Searches and discovers AWS resources; it does not govern IaC templates.
• AWS Organizations: Manages multiple AWS accounts, policies, and consolidated billing.
• AWS Systems Manager: Helps operate and manage deployed resources, such as patching and automation, but is not primarily a catalog for governed IaC products.

• A: Daily involvement is unnecessary and may not solve the availability problem.
• C: Clarifying all requirements at the start conflicts with agile’s iterative refinement.
• D: Simply reviewing based on availability leaves the problem unresolved and allows rework to continue.

• State is stored remotely in Terraform Cloud/Enterprise, not as a local file.
• Terraform runs (plan/apply) can be executed on remote infrastructure, with results visible in the remote workspace UI.
• Supports workspace-based organization, state locking, and concurrency control.
• Useful for team collaboration, centralized governance, and auditable logs.

• In your configuration, you use a backend block like backend "remote" { ... }.
• You still run terraform init to configure/migrate to the remote backend.
• After setup, terraform plan/terraform apply may be executed remotely, and the outputs/logs appear in the Terraform Cloud/Enterprise UI rather than (only) in your local terminal.

• Other backends store state remotely but typically do not provide remote execution; with the remote backend you get remote runs and a collaborative UI, not just remote state storage.

• Normalize casing in the data source—for example, convert all values to uppercase or lowercase.
• Add an index key to provide a unique, stable identifier for each row or value.

• Equipment and hardware
• Facilities
• Inventory
• Backup media
• Supplies stored at an alternate or remote location

• Personal belongings of staff: Usually not organizational assets.
• DR line-item revenues: Revenue is a financial impact, not a physical asset.
• Cloud-based applications: These are primarily logical or information-processing assets, even though they depend on physical infrastructure.

• Microsoft Teams: Connects to Teams-related data, but it isn’t the primary connector for the Power Apps data tables.
• Personal Analytics: Provides personal productivity insights, not application data.
• SQL Server database: Only applies if the app explicitly uses SQL Server as its data source.
• Dataflows: Used for preparing and centralizing data, not as the normal direct connection to a Power Apps app.

• B — Prompts and suggestions retained for 28 days
• C — User engagement data kept for two years

• The key distinction is between content data—your prompts, code context, and generated suggestions—and engagement data, such as usage activity.
• Do not confuse retention with training: enterprise Copilot data is generally not used to train GitHub’s models without appropriate authorization.
• For a current exam, verify the policy version cited by the exam provider. The key’s C is likely correct, but B should be treated cautiously and may no longer reflect the current policy.

• Batch processing, such as scheduled data transformations
• Streaming processing, such as continuously ingesting events

• Manipulating data with multiple languages: Mainly a benefit of Databricks and Spark.
• Real-time notebook collaboration: A workspace/notebook feature.
• Alerts for query failures: A Databricks SQL or job-monitoring feature.
• Distributing complex operations: Primarily a Spark compute capability.

• Pay-as-you-go in Azure is an operating expense (OPEX) model, not an “elastic” expenditure model.
• Elastic or scalable terms describe capacity planning, not the cost category. The cost should be treated as OPEX since you pay for usage each month.
• The parallel question (Question 12) shows the correct approach is using an operational expenditure model.

• AWS IoT Greengrass supports local ML inference using models trained in Amazon SageMaker.
• The model and inference code run on the factory’s local server, so processing continues even when internet connectivity is unavailable.
• A Greengrass component can:

• This provides low latency and avoids sending images to AWS for every inference.

• A: Uses AWS-hosted services and therefore depends on internet connectivity. It would fail during an outage.
• C: Snowball Edge is unnecessary for this use case and adds deployment complexity. A local Greengrass server is the intended edge-inference solution.
• D: Amazon Monitron is designed for monitoring industrial equipment health, not analyzing camera images with a custom SageMaker model.

• A assigned without var becomes a global variable (in non-strict mode). So after myFunction(), a = 5 is accessible.
• b is declared with var inside the function, so it’s local to that function (function-scoped). It’s not defined in the outer (global) scope.

• console.log(a) prints 5.
• console.log(b) throws a ReferenceError: b is not defined.

• Looking up accounts, contacts, and opportunities
• Logging calls and updating Salesforce records
• Accessing previously available customer information when temporarily offline

• Salesforce Touch App: Primarily an older tablet-focused experience, not the best general solution for the sales team.
• Custom hybrid app: Unnecessary development when Salesforce provides the required capabilities natively.
• SalesforceA: Intended mainly for Salesforce administrators, not sales representatives.

• Primary and core nodes: Use On-Demand Instances because the workload is business-critical. These nodes manage the cluster and store/process HDFS data.
• Task nodes: Use Spot Instances in an instance fleet. Task nodes are suitable for interruption because they do not hold essential cluster data and can be replaced or diversified across instance types.
• Terminate the entire cluster after processing: The job runs only about six hours each morning, and EMRFS stores data in Amazon S3. Keeping the cluster running for the rest of the day would waste money.

• A: Using Spot for primary and core nodes risks interruption of the critical cluster.
• C: All On-Demand is reliable but unnecessarily expensive; terminating the cluster helps, but Spot task nodes provide greater savings.
• D: Leaving primary and core nodes running after the task finishes continues to incur costs. Savings Plans also are less appropriate for this intermittent workload.

• Low usage during the first three weeks
• Very high usage during the last week

• High availability: Keeps services running despite failures.
• High latency: Means slow response times; it is not a benefit.
• Load balancing: Distributes traffic across resources but does not specifically address scaling resources up and down.

• A. IDS attack signatures: An IDS primarily detects suspicious network activity and usually alerts rather than directly scanning and blocking uploaded files.
• C. Load balancer: Distributes traffic among servers but does not inspect files for malware.
• D. WAF: Protects web applications from attacks such as SQL injection, cross-site scripting, and some malicious requests. It is not primarily a PDF-malware scanning solution.