Test Prep NREMT Exam Prep
National Registry Emergency Medical Technician (Page 29 )

• 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.

• The CSV contains the external users’ email addresses.
• The bulk invitation feature supports inviting many guest users in one operation.
• Each invited user becomes a guest account in contoso.com.

Question 3: AWS Storage Gateway File Gateway

• A: S3 bucket per user — S3 is object storage, not a traditional shared file system; mounting it requires extra tools and is less efficient.
• B: File Gateway — Provides a local file share using standard file protocols while storing files in Amazon S3. This preserves convenient local access and extends storage capacity.
• C: WorkSpaces and WorkDocs — Designed for virtual desktops and document collaboration, not large shared file storage.
• D: EC2 with EBS — EBS is attached to one EC2 instance and is not designed for direct multi-user file sharing.

• SOW
• SLA
• MOA
• MOU

• SAML: Enables federated authentication and single sign-on between the IdP and SaaS providers.
• OAuth tokens: Allow delegated application access; OAuth is not primarily the first step for employee SSO.
• Password vaulting: Stores or autofills multiple passwords but does not eliminate the separate credentials or provide true federation.

• Import: Copies data into the Power BI model. It requires scheduled or manual refresh, so it may not meet the two-minute requirement.
• Live connection: Connects to an existing Power BI semantic model or Analysis Services model; it is not the appropriate choice for connecting directly to the Azure SQL database in this scenario.

1. Install a Cassandra-compatible ODBC driver.
2. Configure a data source name (DSN), if required.
3. In Power BI Desktop, select Get Data > ODBC.
4. Choose the configured DSN and connect.

• Microsoft SQL Server database: Connects to SQL Server, not Cassandra.
• OLE DB: Requires a compatible OLE DB provider; this is not the standard choice for Cassandra in Power BI.
• OData: Requires Cassandra data to be exposed through an OData service, which is not the normal direct connection method.

• Threat perspective: Focuses on possible attacks, but may seem technical or hypothetical.
• Compliance perspective: Can motivate action, but compliance alone does not demonstrate the broader business value of governance.
• Policy perspective: Policies are important, but they are a means of implementing governance, not its primary business justification.

• Compute: Not used; no virtual warehouse is required.
• Data Storage: Not scanned again.
• Metadata: May help Snowflake manage and validate cached results, but it is not the Snowflake architectural layer identified as serving the request.
• Cloud Services: Handles query coordination, metadata services, authentication, and result-cache access.

• Internal hostnames and subdomains
• Network structure and naming conventions
• Servers and services
• Relationships between systems

• Determining ISP-assigned address space: Usually involves external registration and DNS information, not internal host discovery.
• Bypassing DNS sinkholing: Would require evidence that malicious DNS requests avoided redirection.
• Initial access: DNS queries alone do not show that the attacker gained access.
• Exfiltrating data: DNS tunneling can do this, but the snippet would typically show encoded or unusually long DNS queries.

• Advanced Persistent Threat (APT): A sustained, targeted attack campaign or attacker group—not a vulnerability.
• Trojan: Malware disguised as legitimate software.
• Stealthware: A general term for malware designed to avoid detection; it does not specifically mean an unknown vulnerability.

1. Select Exchange email as a location.
2. Use the built-in Azure Storage Account key sensitive information type as the condition.
3. Configure the DLP action to encrypt the email—for example, using Microsoft Purview Message Encryption.

1. Create a temporary Onboarding OU.
2. Move the new account into it.
3. Move the restrictive SCPs from the organization root to the Production OU.
4. Allow the account to update AWS Config.
5. Move the account into Production after onboarding.

• An SCP attached at the organization root applies to every account and OU beneath it.
• An SCP attached to the Production OU applies only to accounts in that OU.
• Therefore, moving the restrictive SCP from the root to Production temporarily exempts the onboarding account without weakening the policies for existing production accounts.
• Once onboarding is complete, moving the account into Production subjects it to the normal restrictions.

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

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

• B: Developer Edition has limited user, storage, and data-volume capacity, making realistic community testing difficult.
• C: A Developer Edition org cannot contain sandboxes, so it cannot provide separate environments for development, integration, and UAT.
• E: A standalone Developer Edition org is not part of the production org’s deployment path, so change sets cannot be used to deploy from it directly to that production org. The team would need Metadata API, Salesforce CLI, or another deployment method.

• The S3 bucket as an origin for static content
• The Application Load Balancer (ALB) as an origin for dynamic content
• An Amazon Route 53 alias record pointing the application domain to CloudFront

Why this works

• Static data: CloudFront caches objects from S3 at edge locations, reducing latency for users worldwide.
• Dynamic data: CloudFront forwards requests that require application processing to the ALB. It can also maintain persistent connections and use the AWS global edge network to improve delivery performance.
• One domain: CloudFront behaviors can route different path patterns to different origins—for example, /static/* to S3 and other paths to the ALB.

Why the other options are incorrect

• Global Accelerator is designed primarily for accelerating traffic to applications with endpoints such as ALBs, not for caching S3 content.
• Using separate domains or splitting static and dynamic traffic adds unnecessary complexity.
• CloudFront already provides the required global edge distribution and caching, so combining it with Global Accelerator is unnecessary here.

• Input feature distributions differ from training data ? Analyze dataset drift metrics

• Model accuracy drops without code changes ? Analyze dataset drift metrics

• Endpoint latency increases under load ? Investigate scaling and infrastructure metrics

• 800 devices ? a scalable, centralized solution is needed.
• Four hardware/vendor classes ? the tool must handle different drivers and images.
• Two user groups ? it should allow different configurations for each group.
• “Distribute custom images” ? an imaging/deployment tool is required, not just a file-copy utility.

• A — Increasing the minimum password length to 14 characters: Longer passwords have more possible combinations, making them harder to guess or crack through brute force.
• F — Requiring at least one special character: This increases password complexity and expands the possible character combinations.

• MD5 to SHA-512: Improves password-hash resistance, but does not stop users from choosing easy-to-guess passwords. Also, modern systems should use a password-specific hashing algorithm such as bcrypt, scrypt, or Argon2.
• Increasing maximum age to 120 days: Leaves weak passwords in use longer.
• Reducing minimum length to 10: Makes guessing easier.
• Reducing minimum age to zero: Allows immediate password changes but does not make the password itself harder to guess.

• Maintain head office control: Transfer pricing generally supports decentralisation rather than direct head-office control.
• Establish centralised decision making: This conflicts with divisional autonomy.
• Develop a top-down culture: Transfer pricing is intended to support empowered divisions and goal congruence, not impose purely top-down management.

• Wireshark captures packets and allows you to examine their contents, potentially revealing usernames and passwords sent without encryption.
• Netcat creates network connections and can send or receive data, but it is not primarily a packet-analysis tool.
• Nessus scans for known vulnerabilities and configuration issues; it generally would not prove that credentials are visible in transit.
• Nmap performs network discovery and port/service scanning, not detailed packet-content inspection.

• Active-active routers: Provide redundant Internet connections/devices. Both can operate, so traffic can fail over or be load-balanced.
• Active-active firewalls: Avoid a single firewall becoming a failure point while maintaining security inspection.
• Load balancers: Distribute requests across multiple web servers. If one server fails, traffic can go to the other.
• Redundant power supplies: A server with separate power supplies should connect to independent power sources or circuits.
• UPS A and UPS B: Provide backup power and redundancy. Ideally, each power supply is connected to a different UPS.
• SONET ring: A ring topology provides alternate paths if a fiber link or segment fails.

• SharePoint search: Finds documents based on search terms, but it does not reliably identify every 32-character account number for DLP enforcement.
• A hunting query in Microsoft 365 Defender: Used for security investigations, not for defining sensitive content in a DLP policy.
• Azure Information Protection: Uses classification and labeling; it does not automatically identify this specific account-number pattern unless configured with a matching sensitive information type.
• RegEx pattern matching: Best suited for structured identifiers with a known format, such as account numbers, employee IDs, or policy numbers.

• Valor maior: mais aderência às instruções e aos detalhes descritos.
• Valor menor: mais liberdade criativa e resultados potencialmente mais variados.
• Valor excessivamente alto: pode causar artefatos ou imagens menos naturais.

• Aumentar o número de passos de geração: pode melhorar qualidade e refinamento, mas não é o principal controle de especificidade do prompt.
• MASK_IMAGE_BLACK: relaciona-se ao uso de máscara em geração ou edição de imagens, não à especificidade textual.
• Prompt strength: é mais associado à força do prompt em processos como image-to-image; nesta questão, o parâmetro diretamente ligado à aderência textual é o CFG scale.

• CSIRT: A team that responds to and manages security incidents.
• CVSS: A scoring system for rating the severity of vulnerabilities.
• SOAR: A technology platform for automating and coordinating security operations and incident response.

• Remote and global work: Access is based on the approved device, not a specific office or geographic location.
• Seamless login: Users may not need to repeatedly enter credentials on a recognized device.
• Limited equipment: It uses devices employees already have rather than requiring separate hardware.

• Geotagging: Restricts access based on location and may prevent legitimate remote work.
• Smart cards: Require issuing and managing additional physical equipment.
• Time-based logins: Limit access by time and do not provide a seamless authentication experience.

• desktopwidth:i:1280
• desktopheight:i:1024

• Connection information: Controls connection-related settings, not the desktop resolution.
• Scaling plan: Controls when session hosts start, stop, or scale based on demand.
• Session behaviour: Controls behavior such as disconnect or logoff handling.
• Display settings: Specifically controls RDP display properties, making it the appropriate choice.

• User preferences change, so the model must learn from recent data.
• Keeping the existing data helps preserve knowledge of older patterns and provides a broader training distribution.
• Training only on new data can cause catastrophic forgetting and may overfit if the new dataset is small.
• The new data should not automatically be used as the test set, because it is needed for training and the model must still be evaluated on separate, representative data.

• C — Custom buttons display at the top and bottom of a page: Correct. In Salesforce Classic, buttons can appear in the page’s button areas, including the top and bottom of record pages.
• D — Custom buttons are available for Person Accounts: Correct. Person Accounts use the Account object, so Account custom buttons can be available on Person Account layouts.
• E — Custom buttons can reference an external app: Correct. A URL custom button can launch or navigate to an external application or website.

• A: JavaScript custom buttons are a Salesforce Classic feature and are not supported in Lightning Experience. They do not enhance Lightning Experience.
• B: The User object does not generally support custom buttons in the same way standard business objects do.

1. Define – establish the project’s objectives, scope, feasibility and requirements.
2. Design – plan how the project will be carried out, including resources, schedules and controls.
3. Deliver – execute the project and produce the required outputs.
4. Develop – close the project formally and capture learning for future projects.

• Filing documentation and records
• Closing project and accounting systems
• Settling costs
• Handing over the completed work and obtaining sign-off
• Reviewing performance and giving feedback

• 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.

• Deterministic approve/reject results
• Strict adherence to predefined rules
• Consistent, reproducible outcomes
• Auditability and regulatory compliance

• tag=Priv searches the tag field for values beginning with Priv. The wildcard can match the remaining characters, so it matches Privileged.
• tag=Priv would search for the exact tag Priv, not Privileged.
• tag=priv* uses lowercase priv; tag matching is treated as case-sensitive here, so it may not match the tag Privileged.
• tag=privileged uses the wrong capitalization for the exact tag.

Statement 1 — Correct

Statement 2 — Correct

• Domínios personalizados.
• Armazenamento suficiente.
• Instâncias dedicadas.
• Balanceamento de carga.
• Menor custo entre os planos que atendem a tudo.

• The listener uses a virtual IP address shared by the availability-group replicas.
• Floating IP, also called Direct Server Return (DSR), allows the SQL Server nodes to respond using the listener’s IP address rather than their individual VM IP addresses.
• This is required for the availability-group listener to function correctly with an Azure internal load balancer.

• Regression predicts continuous numeric outcomes, such as house price, temperature, or sales amount.
• Linear regression assumes the target can be estimated from a linear relationship between the input features and the target.
• In Azure Machine Learning, you use a labeled dataset containing:

• Classification predicts a category or class, such as “spam” or “not spam.”
• Clustering groups similar records without a known label; it is an unsupervised learning technique.

• Understating expenses and liabilities
• Overstating profit
• Misleading users of the financial information
• Potentially breaching integrity, objectivity, and professional competence and due care

• Guiding principles
• Governance
• Service value chain
• Practices
• Continual improvement

• Guiding principles: Recommendations that guide decisions and actions; they do not describe the entire system.
• Four dimensions: Perspectives used to ensure a balanced approach to service management.
• Service relationship: Describes cooperation between a service provider and service consumer, rather than the whole value-creation system.

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.

• A. IDS attack signatures: An IDS primarily detects suspicious network activity; it is not the best tool for scanning uploaded files.
• C. Load balancer: Improves availability and distributes traffic but does not inspect files for malware.
• D. WAF: Protects web applications against attacks such as SQL injection and command injection. It may inspect HTTP requests, but malware scanning of uploaded PDFs is the key requirement here.

• Transfer — przeniesienie skutków lub kosztów ryzyka na inna organizacje, np. przez ubezpieczenie lub umowe.
• Akceptacja — firma swiadomie przyjmuje ryzyko bez dodatkowych dzialan.
• Mitigacja — zmniejszenie prawdopodobienstwa wystapienia ryzyka lub jego wplywu, np. przez wdrozenie kontroli bezpieczenstwa.
• Unikanie — calkowite wyeliminowanie ryzykownej dzialalnosci.

• Sensitive document shared during a Teams chat: Teams chat
• Sensitive document stored/shared in a Teams channel: Teams channel messages

• Files shared in a chat are generally stored in the sender’s OneDrive, but the relevant DLP context is the Teams chat message and its attachment.
• Files shared in a channel are stored in the team’s SharePoint site, but the relevant context is the Teams channel message.
• The DLP rule can then use an action such as restrict access to the content to prevent guest users from opening the sensitive document.

• Escape to host: A virtualization attack where code escapes a guest VM and accesses the host system. Nothing in the scenario mentions virtualization.
• Browser extension: Can redirect or manipulate web-browser traffic, but not normally database-server traffic.
• Valid accounts: Describes using stolen or compromised credentials, not redirecting network traffic.
• Process injection: Injecting malicious code into a legitimate database or networking process could allow an attacker to alter how that process handles outgoing traffic.

1. Open the Microsoft Entra Connect wizard.
2. Select Configure.
3. Choose Customize synchronization options.
4. Authenticate when prompted.
5. On the Domain and OU filtering page, select:

1. Complete the wizard.

• Start-ADSyncSyncCycle only starts synchronization; it does not change which OUs are included.
• Manage federation configures federation settings, which are unrelated to OU filtering.
• Add-ADSyncConnectorAttributeInclusion concerns connector attributes, not selecting additional OUs for synchronization.

• 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

• 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.

• Create and manage approved IT services as products
• Control which users can deploy those products
• Apply governance, permissions, and constraints
• Use and manage infrastructure-as-code templates, such as AWS CloudFormation templates

• AWS Resource Explorer: Helps find and browse AWS resources; it does not govern IaC deployments.
• AWS Organizations: Manages accounts, consolidated billing, and organization-wide policies.
• AWS Systems Manager: Provides operational management, such as patching, automation, and parameter storage, but it is not primarily used to catalog and govern IaC-based service deployments.

• 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.