IAPP CIPT Exam Prep
Certified Information Privacy Technologist (CIPT) (Page 24 )

• C series: CPU-optimized instances; not designed primarily for LLM training.
• G series: GPU instances generally optimized for graphics and some machine learning workloads, but not specifically large-scale model training efficiency.
• P series: Powerful GPU instances for ML training, but typically consume more energy than Trainium-based instances for suitable training workloads.

• Periodic vulnerability assessments: Identify technical weaknesses but do not establish governance or ensure risks are managed.
• Established information security metrics: Help measure performance and report status, but measurement alone does not make governance effective.
• Advanced security technologies: Support security operations, but governance is primarily about direction, accountability, decision-making, and alignment with business objectives.

• The requirement is an assessment of the Azure environment’s design, which requires a support plan offering proactive architectural guidance.
• Premier support would provide this capability, but it is a high-cost option.
• Since the requirement says to minimize expenses, Premier is not the best recommendation.
• A lower-cost plan with the required advisory/design-review capability—historically Professional Direct in Azure’s support-plan model—would be more appropriate.

• A script of cloud CLI commands: IaC because the commands can be saved, reviewed, versioned, and rerun consistently.
• Manually run curl commands: Not necessarily IaC; they are manual actions unless organized into an automated script.
• A sequence of REST requests passed to an API: Could represent automation, but the wording does not explicitly say they are stored and executed as reusable code.
• Commands entered into a cloud console: Manual operation, not IaC.

• Business
• People
• Governance
• Platform
• Security
• Operations

• Cloud financial management
• Portfolio management
• Data governance
• Risk management
• Compliance

• Monitoring: Detects activity but does not remove the underlying risk.
• Patching: Useful for systems that must remain operational, but these desktops are unused.
• Isolating: Can be a temporary containment measure, but permanently removing unnecessary systems is more appropriate.

• A vulnerability scanner automates discovery of known vulnerabilities and misconfigurations across systems. It can contribute to a supply-chain assessment.
• A penetration test actively attempts exploitation and is usually limited to an agreed scope.
• SCAP standardizes vulnerability and configuration assessment data; it is not the analysis itself.
• Illumination tool is not a commonly defined CompTIA Security+ term.

• Azure Resource Manager (ARM) templates
• Or, in newer Azure terminology, Bicep files

• Suspended an operator who refused to use unsafe equipment.
• Paid another operator a bonus for using it.
• Prioritised short-term productivity over employee safety.

• A — Management is not particularly concerned with managing risks.

• B — Employees will perceive that management does not care about health and safety risks.

• C — The factory’s safety record is likely to be poor.

• An Adj-SID does not necessarily need manual configuration.
• It can often be dynamically allocated by the router, although manual configuration may also be possible.
• The adjacency information is advertised through the IGP, such as IS-IS or OSPF.

• It is identified by an Adj-SID.
• It represents a particular adjacency of a node.
• Its meaning is generally local to the advertising node; unlike a Node-SID, it is not a globally reusable instruction across the network.

• Reviewing and validating generated code
• Checking security, licensing, and quality concerns
• Testing the implementation
• Making the final design and coding decisions

• A: Copilot is not a complete replacement for developers.
• C: Human input, review, and oversight are still required.
• D: Copilot Chat supports many tasks beyond debugging, including explanation, generation, refactoring, and testing assistance.

• SQL injection
• Cross-site scripting (XSS)
• Malicious or malformed web requests
• Some application-layer attacks

• Layer 4 firewall: Filters based mainly on IP addresses, ports, and transport protocols; it cannot deeply inspect web application content.
• NGFW: Provides advanced network filtering and may include application awareness, but a WAF is more specifically designed to protect web applications.
• UTM: Combines several security functions in one appliance, but it is not the most targeted solution for a web portal.

• Confirm the required columns and data types
• Identify the target/label column
• Handle missing or duplicate records if present
• Transform data into a suitable format
• Split it into training and validation/test datasets

1. Prepare the training data
2. Select an algorithm or configure AutoML
3. Train the model
4. Evaluate its performance
5. Tune hyperparameters if needed
6. Deploy the model

• Crash cart: Provides local physical access, not remote access.
• Jump box: A secured intermediary used to reach devices over the normal network; it may be inaccessible if the appliance has not booted.
• Secure Shell (SSH): Requires the device’s operating system and network services to be running properly.

• Whether a user has a console password
• Password age and last password change
• Whether MFA is enabled
• Access key status
• Access key creation date and last-use information
• Access key age, which helps audit rotation

• IAM Access Analyzer identifies unintended access to resources; it does not report credential age or rotation.
• AWS Artifact provides AWS compliance documents and agreements, not details about your IAM users.
• AWS Audit Manager helps collect evidence for audits, but it is not the direct tool for viewing IAM credential rotation details.

• AWS Budgets lets you create a cost or usage budget and configure alerts when actual or forecasted spending reaches a threshold. Notifications can be sent through email or Amazon SNS.
• Amazon CloudWatch can monitor AWS billing metrics and trigger an alarm when estimated charges exceed a specified amount.

• Amazon SQS is a message queue, not a cost-monitoring service.
• Cost Explorer analyzes spending but does not directly provide threshold notifications.
• AWS Cost and Usage Report delivers detailed billing data for analysis; it does not itself send threshold alerts.

• Data loss prevention (DLP): Helps detect or prevent unauthorized data transfers, but does not directly protect data on a stolen, powered-off laptop.
• Operating system hardening: Reduces vulnerabilities and attack surface, but does not adequately protect stored data if the device is stolen.
• Boot security: Helps prevent unauthorized operating systems or boot media from loading. It supports device security but is not the primary solution for protecting the data itself.

• Managerial: policies, standards, risk management, governance
• Operational: procedures carried out by people, such as training, incident response, and backups
• Technical: firewalls, encryption, access-control systems
• Physical: locks, guards, cameras

sql 
SELECT COUNT(*) FROM table;

• A: It does not normally need to scan all data files for this operation.
• B: Results are not simply reused from a query cache every time. Caching is separate from Delta’s metadata optimization.
• D: The relevant metadata is maintained through the Delta transaction log, not directly treated as a Parquet-file metadata operation in this context.

1. Create a custom Sensitive Information Type (SIT) in the Microsoft Purview portal.
2. Use a regular expression to match the 32-character alphanumeric account number.
3. Reference that SIT in the DLP policy protecting SharePoint Online.

• Format-based data ? custom SIT with RegEx
• Built-in sensitive data ? Microsoft-provided SIT
• Document classification/protection ? sensitivity labels
• Security investigation queries ? Advanced Hunting, not DLP detection

• Un AG puede tener réplicas en Windows y Linux desde SQL Server 2017; por tanto, una réplica Windows y otra Linux es posible.
• Sin embargo, las réplicas de un AG deben utilizar normalmente la misma versión principal de SQL Server. Una instancia SQL Server 2017 no puede tener directamente una réplica secundaria SQL Server 2019 como configuración normal y permanente.
• En tu escenario, SQL Server 2017 en Windows y SQL Server 2019 en Linux no se pueden añadir directamente como réplicas equivalentes de AG1. Primero habría que realizar un proceso de actualización/migración compatible, por ejemplo mediante una actualización gradual o una tecnología de migración como log shipping o distributed availability groups, según el diseño.

• Tipo de clúster y mecanismo de quorum.
• Failover normalmente manual en configuraciones multiplataforma.
• Edición y características compatibles.
• Configuración de endpoints y permisos.
• Limitaciones específicas de SQL Server en Linux.

1. Write a structured log entry to CloudWatch Logs containing:

1. Create a CloudWatch Logs metric filter that:

text 
ApiRequests 
Operation=GetOrders 
ResponseCode=500 
Version=2.4.0

• B is incorrect: CloudWatch Logs Insights queries analyze logs but do not directly publish metrics in this manner.
• C is incorrect: ALB access logs do not contain arbitrary Lambda response metadata as custom fields.
• D is incorrect: X-Ray traces and insights are not the appropriate mechanism for creating these custom, dimensioned application metrics.

• 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.

• Issuer: Identifies the party issuing a SAML message—usually the identity provider in the assertion. It is not the Salesforce-specific identifier the architect should provide for differentiating Salesforce.
• Identity Provider Login URL: The endpoint where users are sent to authenticate.
• SAML identity location: Determines where the user identity is found in the SAML assertion, such as the subject or an attribute.

• AWS AppSync is designed for serverless applications that need to retrieve and combine data from multiple sources.
• A pipeline resolver can invoke multiple functions or data-source resolvers, including resolvers connected to different DynamoDB tables.
• The application can receive the combined result through one GraphQL request, without requiring custom aggregation logic in the application.
• This is operationally efficient because AppSync manages the API layer and resolver execution.

• Athena Federated Query is intended primarily for analytics and ad hoc querying, not low-latency application data retrieval.
• Querying DynamoDB through Athena can consume DynamoDB read capacity and may affect table performance.
• It also introduces analytical-query overhead and is not the normal choice for a microservice web application.

• BCP (Business Continuity Plan): Ensures the organization can continue its broader business operations during and after a disruption. It is broader than the IT-focused recovery required here.
• Communication plan: Defines how information is shared with employees, the public, and other stakeholders; it does not restore systems.
• IRP (Incident Response Plan): Handles and contains security incidents, such as malware or unauthorized access. A tornado is a disaster, not primarily a cybersecurity incident.

1. Convert text and images into numerical embeddings.
2. Store or compare those embeddings.
3. Retrieve the most semantically similar items.

• Embedding model: Best for similarity search and retrieval.
• Generation model: Best for producing new text or other content from multimodal input.

• Third-party enterprise application with embedded AI: The provider manages most security controls. The customer mainly manages users, data, and configuration.
• Application using an existing third-party FM: The customer controls the application and its inputs/outputs, but the provider controls the underlying model and infrastructure.
• Fine-tuning a third-party FM: The customer has additional responsibility for training data, data protection, and model behavior, but still depends on the provider’s base model and platform.
• Building and training a model from scratch: The customer controls the model, training data, application, deployment, and many security safeguards. This creates the greatest security ownership.

• B. Deploy to a SageMaker endpoint: This is needed for SageMaker-hosted models, not for a model intended to be used directly in Amazon Bedrock.
• C. Register with SageMaker Model Registry: SageMaker Model Registry is unrelated to invoking custom models in Bedrock.
• D. Grant access in Bedrock: Access permissions may be necessary, but they do not replace the required provisioned capacity.

• Accept: Acknowledge the risk and choose not to take additional action.
• Transfer: Shift the risk or its financial impact to another party, such as through insurance or outsourcing.
• Mitigate: Reduce the likelihood or impact of the risk, such as by implementing security controls.
• Avoid: Eliminate the activity or condition that creates the risk.

• Discovers sensitive data in Amazon S3 buckets
• Uses machine learning and pattern matching to identify data such as personally identifiable information (PII)
• Helps assess S3 security and privacy risks
• Generates findings for potentially sensitive or exposed data

• Amazon Detective: Investigates security findings and performs root-cause analysis.
• Amazon GuardDuty: Detects threats and suspicious activity across AWS accounts and workloads.
• AWS IAM Access Analyzer: Identifies resources that are accessible from outside their intended trust zone, such as publicly accessible S3 buckets.

• Crowd-sourced evaluation: Requires recruiting and managing many evaluators.
• Human-worker evaluation: Provides human judgment but requires coordination, labeling instructions, and quality control.
• RLHF: Is a training and alignment process, not simply a low-overhead model comparison method.
• Automatic model evaluation: Quickly evaluates outputs using predefined toxicity or quality metrics with minimal manual effort.

• Prevent connections to malware command-and-control servers
• Identify infected systems making those DNS requests
• Collect information for incident response

• A: Attackers do not normally use sinkholes to map a company’s domain structure.
• B: Redirecting employees from legitimate sites to attacker-owned sites describes malicious DNS manipulation, not a defensive sinkhole.
• D: Attracting attackers away from real resources is more closely associated with a honeypot or deception system.

• The audience and stakeholders
• The complexity and type of requirements
• The communication method and level of detail needed
• Whether to use diagrams, models, documents, demonstrations, or slides

• B: Authority to host the presentation is not the key preparation activity.
• C: Stakeholder sign-off may occur later; presenting requirements does not always require formal approval beforehand.
• D: A scribe may be useful in a meeting, but hiring one is not a core preparation requirement for presenting.

• File1.png — Yes: User1 can apply Label1 with the Microsoft Purview Information Protection client. The client supports labeling image files such as .png in this scenario.

• Folder2 — No: Folder2 is the root folder. The client does not allow labeling the root folder itself. Although the client can label ordinary folders, selecting one applies the label to existing files and subfolders—not automatically to future files.

• File1.docx — Yes: .docx is a supported Microsoft Word file type, so User1 can apply Label1 to it.

• B — Sales staff will tender for riskier contracts:

• C — Sales staff will encroach on other territories:

• D — Sales staff will look for new jobs:

• A: Using an external OAuth 2.0 identity provider could provide unified identity, but it does not specifically address Salesforce capacity or high-volume login limits.
• B: Making the Experience Cloud community a SAML identity provider and using JIT provisioning is a possible federation pattern, but it may not be appropriate for this scale without Salesforce validation.
• C: A default account is unrelated to solving identity unification and high login throughput. Person Accounts can be supported in appropriate B2C Commerce integrations.

• Customer contains one row per customer and the customer’s Address ID.
• Address contains one row per address and the corresponding location details.

1. Select the Customer query.
2. Choose Merge Queries.
3. Match Customer[Address ID] with Address[Address ID].
4. Use a Left outer join so every customer is retained.
5. Expand the merged Address column and select City, State/Region, and Country.

• Append adds rows vertically and is used for tables with the same structure.
• Group By summarizes rows rather than adding related columns.
• Transpose switches rows and columns and does not establish a relationship.

1. Product + ProductSubCategory: Inner join

1. Result + ProductCategory: Left outer join

• A: Allow SAN certificates — SANs are used to identify valid hostnames in a certificate. They do not bypass trust validation.
• C: Open the secure LDAP port — A blocked port would normally cause a timeout or connection-refused error, not certificate errors.
• D: Increase the TLS version on the RA — The issue concerns certificate trust, not the organization’s registration authority.

• B. The community must be built with the Customer Account Portal template.

• C. An experience ID (expid) or placeholder parameter must be used in the URL.

• A: The Visualforce + Salesforce Tabs template does not provide this dynamic branding capability.
• D: An external CMS is not required. The branding configuration is handled within Salesforce Experience Cloud.

• VLAN 10 for data
• VLAN 20 for voice

• A: Describes physical trunking or logical switch ports, not an SVI.
• B: An SVI can provide management access, but that is only one use—not the best description here.
• D: SVI use is not related to running out of physical ports.

• Outer packet: 10.5.1.1 > 52.165.16.154
• IPv4 protocol field: 41, which indicates IPv6 encapsulation
• Inner packet: IPv6 traffic between 2001:... addresses

• MAC address spoofing: Changes Layer 2 addressing; it does not explain the IPv6-in-IPv4 structure.
• Steganography: Hides data inside files or media, not visibly in a tunneled protocol.
• Broken encryption: No evidence of encryption being cracked.
• On-path sniffing: Involves intercepting traffic, not sending data to an external host.

• Customer: Dual
• Date: Dual
• Sales: DirectQuery
• SalesAggregate: Import

• Sales – DirectQuery: Near-real-time data should not rely on an imported cache. DirectQuery sends queries to the source when visuals are loaded, allowing recent sales data to appear.
• SalesAggregate – Import: A weekly refresh is sufficient, and imported data generally gives faster visual performance because it is stored in Power BI’s in-memory cache.
• Customer and Date – Dual: These are dimension tables used with both the DirectQuery Sales table and the imported SalesAggregate table. Dual allows Power BI to use cached data when possible, while still behaving appropriately in queries involving DirectQuery data. This can improve performance and reduce unnecessary limited relationships.

• Users logging in more frequently than average
• Logins occurring during non-business hours
• Patterns that may indicate compromised credentials or suspicious access

• Login History: Shows individual login attempts and basic details, but does not provide behavioral analysis or averages.
• Login Inspector: Used to troubleshoot or inspect a specific login attempt, rather than analyze organization-wide patterns.
• Login Report: May provide reportable login information, but it is not the specialized tool for forensic behavioral analysis.

Statement 1 — Correct

Statement 2 — Correct

• Domain controllers, because the requirement specifically excludes them. However, note that both member servers and domain controllers run Windows Server, so OS targeting alone cannot distinguish them unless the targeting option allows selecting the relevant server role/version. In the usual exam interpretation, target the applicable server OS category.
• Client computers, because they run a client Windows operating system.

• Domain: Targets membership in a domain, not the computer’s operating-system type.
• Security Group: Would require creating and maintaining a group containing all member servers, increasing administrative effort.
• Environment Variable: Not designed to reliably identify member servers.

1. You try to access a cloud application, such as accounting software.
2. The application redirects you to the company’s IdP.
3. You authenticate with the IdP.
4. The IdP sends a digitally signed SAML assertion to the application.
5. The application validates the assertion and grants access.

• The user’s identity
• Whether authentication succeeded
• Roles or group membership
• Access-related attributes

• Which host first communicated with the suspected malicious source
• Whether that host initiated suspicious traffic or merely received it
• Which other hosts show evidence of infection, such as connections from the originating host
• Which hosts have no related suspicious activity and are therefore clean

• An outbound connection to a suspicious external address
• A downloaded or executed malicious file
• Later lateral connections from that host to other internal systems
• Firewall logs showing the direction and timing of the traffic

• ARP poisoning: Redirects or intercepts local network traffic; monitoring would typically show suspicious ARP changes or man-in-the-middle behavior.
• Jamming: Interferes with wireless or radio signals. It would affect connectivity, not usually show a server-specific overload.
• Kerberoasting: Attempts to obtain and crack Kerberos service-account hashes; it does not normally cause a system outage.