IIA CIA Exam Prep
Certified Internal Auditor Exam (Page 115 )

• state preserves the client’s original context, such as the specific idea URL the user requested.
• The portal sends that value in the OAuth authorization request.
• Salesforce returns it after authorization, allowing the portal to redirect the user to the original idea rather than the Ideas home page.

• A class/teacher fact should contain one row per Class ID. It can support the count of classes and contain attributes such as Teacher First Name and Period Number.
• An attendance fact should contain one row per attendance event, such as Class ID + student + date. It supports attendance counts by day and monthly averages.

• Teacher First Name ? Teacher fact
• Period Number ? Attendance fact

• One network address
• Two usable host addresses—one for each router
• One broadcast address

• Router A: 10.2.1.1
• Router B: 10.2.1.2

• Data source: Folder
• Transformation: Remove the Content column (or keep only the file-metadata columns)

Why

• File name
• Extension
• Date modified
• Folder path
• Content — the binary contents of the file

• Install unauthorized or unapproved applications
• Access system areas normally restricted
• Add features unavailable in the default software
• Modify the device’s operating system

• SQL injection (SQLi): Attacks databases by inserting malicious SQL commands.
• Cross-site scripting (XSS): Injects malicious scripts into web pages viewed by users.
• Sideloading: Installs an application from outside the official app store, but it does not necessarily remove the phone’s operating-system restrictions.

• Orders contains order-level information, such as the order date.
• Order Line Items contains the products, quantities, and line amounts associated with each order.
• Merging them on the order key, such as OrderID, places the order date alongside each line item. This allows you to calculate total order value and analyze it over time.
• Product attributes can remain in the Products table and be related to the resulting line-item table through ProductID.

• Merging line items with products addresses product attributes but does not first provide the order-level date and value needed for time analysis.
• DAX calculated columns or lists add unnecessary model complexity.
• Calculating order counts is not the first requirement and does not combine the required order and line-item data.

• Repetitive and time-consuming
• Based on measurable conditions, such as last check-in time
• Easy to automate with alerts, dashboards, or scheduled reports
• Important for ensuring scan coverage

• Assigning custom recommendations usually requires analyst judgment and context.
• Analyzing false positives can sometimes be assisted by automation, but validation often requires human review.
• Rendering an additional executive report increases reporting activity rather than reducing a core operational workload.

• Atomicity: a write fully succeeds or does not appear.
• Consistency: table state remains valid.
• Isolation: concurrent operations do not corrupt one another.
• Durability: committed changes persist.

• Flexible schemas: common data lakes often support flexible or schema-on-read data.
• Open-source formats: common data lakes commonly use open formats such as Parquet.
• Scalable storage: cloud data lakes already provide scalable storage.

• An active relationship is used automatically when filters are evaluated. An inactive relationship does not propagate filters unless explicitly activated in DAX, so it would not reliably enforce the required security behavior.
• Apply security filter in both directions allows RLS filters to propagate across the relationship in both directions. This ensures that bidirectional filtering respects the RLS rules applied to both tables.
• Assume referential integrity is unrelated to RLS. It is mainly a DirectQuery optimization that allows Power BI to use an inner join when matching keys are guaranteed to exist.
• The relationship must therefore be active, with security filtering enabled in both directions.

• Deficiency found before patient use: usually does not require an adverse-event report because no patient exposure occurred.
• Event caused solely by the patient’s condition: may not be reportable if the device did not contribute.
• Malfunction protection operated correctly: generally exempt when the device’s safety mechanism worked as intended and prevented harm.

• Warehouse size: Larger warehouses use more credits per unit of time than smaller ones.
• Number of clusters: A multi-cluster warehouse can run multiple clusters, and each active cluster consumes credits. Therefore, increasing the maximum or active cluster count can increase consumption.

• Number of users: More users may cause more workload, but users themselves do not consume credits.
• Amount of data processed: Snowflake warehouses are not charged directly by the amount of data scanned. However, processing more data may cause the warehouse to run longer, indirectly increasing credits.

1. Yes — Microsoft Foundry provides a secure, governed environment for building and managing generative AI applications and agents. It brings together models, data, tools, evaluation, deployment, and monitoring.

1. Yes — Foundry is designed for enterprise workloads and supports scaling AI applications as usage grows. Scalability comes from the underlying Azure services and managed infrastructure.

1. Yes — Foundry can be used in solutions involving image recognition and computer vision. Applications can use vision-capable models and Azure AI vision capabilities for tasks such as image analysis, object detection, and OCR.

• Business risks
• Potential financial, operational, legal, or reputational impact
• How governance reduces risk to organizational objectives
• How much risk the organization is willing to accept

• IRR assumes that interim cash flows can be reinvested at the project’s own IRR. This may be unrealistic, especially when the IRR is very high.
• MIRR assumes reinvestment at a specified rate, usually the company’s cost of capital or another realistic reinvestment rate.

• B: MIRR does not specifically favour projects with long payback periods.
• C: MIRR and IRR can rank competing projects differently.
• D: MIRR is not always higher than IRR; it may be higher or lower depending on the cash flows and reinvestment rate.

• Red team: Simulates attackers and tests exploitability.
• Blue team: Defends, monitors, detects, and responds to attacks.
• Purple team: Combines red- and blue-team activities to improve cooperation and defenses.
• White team: Manages and oversees the rules, scope, and authorization of the exercise.

• Row counts
• Minimum and maximum values for columns
• Distinct-value information
• Other characteristics used for optimization

• Sales revenue is affected because internal sales are recorded at the transfer price.
• Operating profit is affected because revenue changes while costs may remain unchanged.
• Return on investment (ROI) is affected because ROI depends on operating profit and the division’s investment.
• Cost of components purchased is not affected by the transfer price. These are costs incurred when buying components from external suppliers, not the internal price charged for the division’s output.

• Restrict a port to a defined number of MAC addresses
• Use statically assigned or “sticky” MAC addresses
• Shut down or restrict the port when violations occur

• Load balancer: Distributes application traffic; it does not protect switch MAC tables.
• IPS: May detect suspicious network activity, but is not the primary control for limiting switch MAC entries.
• NGFW: Filters traffic at the network boundary; it does not directly prevent MAC table flooding on access switches.

• B — Notify affected business units: Notification should follow an initial determination of scope and impact; otherwise, the organization may communicate incomplete or inaccurate requirements.
• C — Assess noncompliance risk: Risk assessment requires understanding the regulation’s requirements first.
• D — Inform senior management: Management should be informed, but with a clear summary of the regulation’s impact, risks, and recommended actions.

• transform() — modifies every element in an array
• filter() — keeps elements matching a condition
• exists() — checks whether any element matches
• aggregate() — reduces array elements to one result

sql 
SELECT transform(scores, x -> x * 2) 
FROM student_scores;

• A is incorrect because higher-order functions are mainly useful for nested or complex data.
• B is incorrect because they do not convert logic into Python.
• D is incorrect because their purpose is not to fix slow built-in functions, but to process arrays or maps with custom logic.

• S3 Glacier Deep Archive is designed for long-term archival data with very infrequent access and has a lower storage cost than S3 One Zone-IA.
• The documents are copies stored elsewhere, so reduced availability and delayed retrieval are acceptable.
• An S3 interface VPC endpoint allows private access from the VPC without exposing the bucket through the public internet.
• A bucket policy can restrict access to requests coming through that endpoint.

• VPC: A logically isolated virtual network within a cloud provider; it describes network design, not the user-access model.
• NFV: Runs network services as software instead of on dedicated hardware.
• SaaS: Delivers software over the internet. Although the application may be delivered as SaaS, the question emphasizes its availability to multiple user groups, which points to multitenancy.

• Instant messaging/chat: Can be abused to send malicious links or attachments, but P2P file sharing is the more direct high-risk source.
• E-mail: A common malware delivery method, but this question specifically emphasizes an application type associated with direct file exchange.
• End-to-end applications: This describes communication protection or architecture, not a specific application category known for malware distribution.

Statement 1 — Correct

Statement 2 — Correct

• Asynchronous inference is designed for applications that submit individual inference requests, place them in a queue, and retrieve results later. It is useful when requests may take a long time or when traffic is intermittent.
• Batch transform is designed specifically to run inference over an entire large dataset stored in Amazon S3 and produce an output dataset.

• Large dataset/offline processing ? Batch transform
• Large or slow individual requests processed later ? Asynchronous inference

• Bronze: Raw ingested data
• Silver: Cleaned, validated, and transformed data
• Gold: Business-level data for analytics, dashboards, and reporting

• Custom domain: miami.weyland.com requires a paid App Service tier; Free and Shared are unsuitable.
• Two instances: Standard supports scaling to multiple instances.
• SSL: Standard includes SSL support.
• 12 GB storage: Basic provides only about 10 GB, so it does not meet the requirement. Standard provides substantially more storage.
• Cost minimization: Standard is the lowest tier among the choices that satisfies all requirements.

• B — AWS DataSync: Transfers data between storage systems. It is not a marketplace or integration service for third-party datasets.
• C — Kinesis Data Streams and CodeCommit: CodeCommit stores source code, not third-party analytical datasets. Kinesis is for streaming data, not retrieving datasets from repositories.
• D — Kinesis Data Streams and ECR: Amazon ECR stores container images, not third-party datasets.

• Identifies which user or department owns the device
• Supports inventory and compliance requirements
• Enables tracking of lost, stolen, retired, or unauthorized devices
• Helps enforce security controls such as mobile-device management and secure configuration

• Feedback form: Captures opinions, not necessarily actual behavior; users may not respond.
• Questionnaire: Relies on memory and subjective judgments about usefulness.
• Interviews: Can provide valuable qualitative insights, but a sample of users may not represent overall usage accurately.

• GPS coordinates
• Date and time the image was taken
• Camera or device model
• Exposure settings

• Log data: Records events or activities, such as system or application activity.
• Encrypted data: Information intentionally encoded to prevent unauthorized access.
• Sensitive data: A broad classification for information requiring protection; geolocation may be sensitive, but the technical type stored in the image is metadata.

• Keep earlier prompt versions.
• Identify the last version that produced acceptable output.
• Restore it as a baseline.
• Make small, controlled changes—ideally one significant change at a time.
• Test the output after each change.

• A: Discards useful information about what worked.
• B: Large simultaneous changes make it difficult to identify the cause of problems.
• D: Accepts output that does not meet the requirements.

• 10.2.1.0 — network address
• 10.2.1.1 — usable host
• 10.2.1.2 — usable host
• 10.2.1.3 — broadcast address

• Plenum: Describes a fire-resistant cable jacket rating, not a transmission medium or speed.
• Ethernet: Describes a networking technology; Ethernet can use copper or fiber, so the term alone does not identify the fastest cable type.
• DAC (Direct Attach Copper): Uses copper and is typically intended for short-distance, high-speed connections in data centers.

Correct reasoning

• Create storage5 as a General-purpose v2 (StorageV2) account.
• Configure Blob object replication from storage5 to an existing compatible storage account.
• The destination must support object replication—typically another StorageV2 or premium block blob account.
• Blob versioning must be enabled on both accounts.
• Blob change feed must be enabled on the source account.
• The accounts must meet Azure’s object-replication requirements, including being in supported regions and having compatible configuration.

1. Open the Offenses tab

1. Open the offense details

1. Review contributing events

1. Analyze the attack chain

1. Investigate the assets

1. Validate and respond