WGU Cybersecurity-Architecture-and-Engineering Exam Prep
WGU Cybersecurity Architecture and Engineering (KFO1/D488) (Page 2 )

• Existing Eventhouse data: remains available only in the KQL database.
• Data ingested after enabling the feature: is copied to OneLake and can be accessed through OneLake file explorer.
• New databases: are irrelevant; the setting applies to the selected KQL database.

• Complete MFA, or
• Securely change their password

• Identity Protection: evaluates user and sign-in risk and can trigger remediation.
• Privileged Identity Management (PIM): manages temporary, just-in-time access to privileged roles; it does not automatically require password changes for risky sign-ins.

• Scale out during the hours when customer traffic is high.
• Scale in during low-demand periods, reducing instance-hours and cost.
• Use scaling policies based on metrics such as CPU utilization or request count.

• Multiple Availability Zones: Improves availability and fault tolerance, but does not automatically reduce cost.
• Placement group: Helps with specialized performance or low-latency requirements, not cost optimization.
• Private subnets: Improve network security, but do not automatically adjust capacity or reduce EC2 usage costs.

• AWS Network Firewall can inspect and block traffic across a VPC when traffic is routed through the firewall. A Drop action rule can deny traffic from the suspicious source IP.
• GuardDuty findings are sent to Security Hub.
• A Lambda function can be invoked when Security Hub receives a new GuardDuty finding, extract the source IP, and update the Network Firewall policy with a blocking rule.

• GuardDuty threat lists: Used to identify or increase the severity of findings; they do not directly block VPC traffic.
• AWS WAF: Protects supported web applications, such as CloudFront or Application Load Balancers. It does not provide general VPC-wide traffic blocking.
• GuardDuty suppression rules: Suppress or hide findings. They do not block the suspicious traffic.

• Controlar o fluxo de dados entre S3 e SageMaker;
• Aplicar regras de segurança por meio da VPC;
• Reduzir a exposição dos dados;
• Permitir acesso privado ao bucket do S3.

• Amazon Inspector: avalia vulnerabilidades, mas não gerencia o fluxo de dados.
• Amazon Macie: ajuda a descobrir e proteger dados sensíveis no S3, mas não cria a conexão com o SageMaker.
• S3 Glacier Deep Archive: é uma classe de armazenamento para arquivamento, não uma solução de conectividade.

• Matching hashes: The software is likely unchanged.
• Different hashes: The software or its contents have been modified.

• Encryption: Protects confidentiality, not primarily integrity.
• Baselines: Document expected configurations and support comparison, but hashing is more directly suited to verifying file integrity.
• Tokenization: Replaces sensitive data with tokens and is unrelated to software tampering.

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

1. Discovery tries the SSH probe first.
2. SSH fails.
3. Discovery tries SNMP, which succeeds.
4. Discovery records SNMP as the preferred service for that IP.
5. Future discoveries try SNMP first.

• Classification identifies the type of device, such as a server, router, or printer.
• Credential affinity remembers which credentials work for a device.
• MID Server affinity associates a device or network with a particular MID Server.
• IP service affinity specifically controls the preferred discovery protocol or service.

• Allow only approved MAC addresses
• Limit the number of learned addresses
• Shut down or restrict a port when a violation occurs

• Load balancer: Distributes application traffic; it does not protect switch MAC tables.
• IPS: May detect some attack traffic, but it is not the direct control for limiting MAC addresses on switch ports.
• NGFW: Filters routed network traffic, while this attack targets Layer 2 switch behavior.

• Menerjemahkan soal ke bahasa Indonesia.
• Menyebutkan jawaban yang benar.
• Menjelaskan alasan jawaban tersebut.
• Memberi tahu jika kunci jawaban yang tersedia tampaknya keliru.
• Menjelaskan istilah teknis penting dalam soal.

• MTTC: Time required to contain or limit the incident’s impact — best match.
• MTTR: Time required to remediate or recover from the incident; this may include eradication, restoration, and cleanup, which goes beyond merely stopping spread.
• MTTD: How long it takes to discover the incident.
• MTBF: Average time between failures, generally a reliability metric.

• Base table — the table containing common inherited fields
• Parent table — the table directly extended by the child
• Other tables in the hierarchy

• 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.

• Information sources: Collect security-related data, such as network packets, system logs, audit records, or application events.
• Analysis: Examines the collected data to identify suspicious activity, attacks, or policy violations.
• Response: Takes or recommends action, such as generating alerts, logging the event, or supporting a protective response.

• Each team’s Bedrock workflow uses a separate IAM service role.
• The role’s Amazon S3 permissions can be limited to only that team’s customer folder or objects.
• This enforces least privilege and prevents one team’s Bedrock application from accessing another team’s data.
• Access is enforced by AWS permissions, not by asking users to provide a customer name in each request.

• A single role with broad S3 access does not provide team-level isolation.
• Asking teams to specify a customer name is not an access-control mechanism.
• Redacting data does not prevent unauthorized access.
• A bucket policy alone is insufficient unless it explicitly enforces the required team-role restrictions.

• 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.

• Identity: User-assigned managed identity

• Authorization: Azure RBAC

• Accept: Acknowledge the risk and take no additional action.
• Transfer: Shift the risk or financial impact to another party, such as through insurance or a contract.
• Mitigate: Reduce the likelihood or impact using controls, such as firewalls, training, or backups.
• Avoid: Eliminate the activity that creates the risk.

• Employees can work from any location, including remote sites and offices worldwide.
• Login can be relatively seamless after the device is registered.
• It does not require distributing additional physical authentication equipment.

• Geotagging: Identifies location, but location alone is not a strong authentication method and may prevent legitimate remote access.
• Smart cards: Provide strong authentication but require card readers and physical cards, increasing equipment and management requirements.
• Time-based logins: Typically involve one-time codes that users must enter, making the experience less seamless and potentially requiring a token or authenticator app.

• Operating profit is affected because transfer price determines internal sales revenue.
• Return on investment (ROI) is affected because ROI depends partly on operating profit.
• Sales revenue is affected because the division records revenue from transferring its output.
• Cost of components purchased is not affected by the transfer price. These are input costs paid to external suppliers and are based on the supplier’s price.

• Determine risk tolerance: Tolerance defines how much variation or exposure the organization is willing to accept. Scenarios may help apply tolerance, but they do not primarily determine it.
• Determine risk appetite: Risk appetite is established at an enterprise or governance level. Scenarios help compare risks with the appetite; they do not normally establish it.
• Develop risk responses: Once risks are identified and assessed, scenarios support response planning. However, response development comes later.

• API tool matcher: runs a deterministic normalization command after the API tool returns.
• Write/Edit matcher: checks whether the target path begins with src/api/ and runs the linter.

json 
{ 
  "hooks": { 
    "PostToolUse": [ 
      { 
        "matcher": "api_tool", 
        "hooks": [ 
          { "type": "command", "command": "normalize-to-snake-case" } 
        ] 
      }, 
      { 
        "matcher": "Write|Edit", 
        "hooks": [ 
          { "type": "command", "command": "lint-if-under-src-api" } 
        ] 
      } 
    ] 
  } 
}

• Run the backup with WITH CHECKSUM
• Store the backup on an SMB network share

sql 
BACKUP DATABASE DB1 
TO DISK = '\\FileServer\SqlBackups\DB1_full.bak' 
WITH CHECKSUM;

• DMS does not create the SQL Server backups for you.
• You must provide a valid full database backup.
• You must continue taking transaction log backups while the source database remains online.
• The full backup and subsequent log backups must be available in the SMB share that DMS can access.
• WITH CHECKSUM enables backup checksum validation, helping detect backup corruption.

• 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

• Dark web: A place where leaked credentials may be sold or shared, not usually the original source.
• Threat feeds: Collections of intelligence about threats, not a typical leakage source.
• State actors: A type of attacker, not an accidental corporate disclosure source.
• Vulnerability databases: Track known vulnerabilities, rather than leaked credentials.

• Create the field in the CRM on the relevant person records—typically Lead and Contact in Salesforce.
• Give the Marketo Sync User read/write access to the field.

• CPU: Number of virtual CPUs and, where applicable, CPU reservations.
• Memory: Amount of memory and memory reservations.

• Network interface: Usually configured through the VM or workload networking configuration.
• PCI devices: Specialized hardware and not a standard VM Class resource in this context.
• Storage: Typically selected through storage policies or the VM’s storage configuration.

• SAML (Security Assertion Markup Language): Commonly used for enterprise SSO between an identity provider and cloud applications. It sends signed authentication assertions to the service provider.
• RADIUS: Primarily used for centralized authentication to network devices, VPNs, and wireless networks.
• EAP: An authentication framework commonly used with network access technologies; it is not typically the SSO protocol for SaaS applications.
• OpenID: Related to identity authentication, but traditional enterprise SSO questions involving cloud applications generally expect SAML. OpenID Connect is a newer authentication layer built on OAuth 2.0.

1. Create Workspace2 with Lakehouse2 — F
2. Migrate the Employee table to Lakehouse2 — E
3. Assign the data engineer the Contributor role for Workspace1 — D

Why

• Sharing Lakehouse1 would not provide the required isolation.
• Viewer access would not allow writing to Customer.
• Giving Contributor access to Workspace2 would expose the sensitive table.

• 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.

• Fine-tuning requires a properly formatted training dataset.
• For classification or instruction-style fine-tuning, examples are supplied in JSONL format.
• Each line represents one training example, typically containing the input prompt and the desired completion or label.
• The file must then be uploaded or made available to the Microsoft Foundry fine-tuning workflow.

• A: Prompt Flow is useful for prompt experimentation, but it is not required to start fine-tuning.
• B: You do not need to deploy the base model to an online endpoint before fine-tuning.
• C: Tracing supports observability and evaluation, but it does not prepare the fine-tuning job or dataset.

• 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.

• Behavioral and anomaly detection
• Threat intelligence integration
• User and entity behavior analytics
• Automated response actions, often through SOAR integration

• Virus signatures: Associated primarily with antivirus or endpoint protection.
• Security agent deployment: Usually an endpoint-management or EDR function.
• Vulnerability scanning: Typically performed by vulnerability-management tools, though a SIEM may integrate their results.

• Microsoft Purview portal: Create and manage sensitivity labels and configure support for sensitivity labels used with Office files in SharePoint and OneDrive.
• SharePoint admin center: Primarily manages SharePoint settings. Older guidance and PowerShell procedures used SharePoint tenant configuration, which can make this question confusing.
• IRM: Concerns Information Rights Management and is a separate protection mechanism; it should not be used to identify the portal for configuring Microsoft Purview sensitivity labels.

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.

• Prevention costs: Avoiding defects, such as staff training and improved product design. The company has invested in these.
• Appraisal costs: Detecting defects before products reach customers, such as inspection and testing. The planned batch sampling has not been implemented.
• Internal failure costs: Correcting defects found before delivery.
• External failure costs: Dealing with defects after delivery, such as refunds, replacements, complaints and lost sales.

• Report on the discount approval time for quotes

• Dashboard of opportunity stage duration

• Lead conversion trends measure lead-generation effectiveness, not opportunity closing time.
• Campaign ROI evaluates marketing performance, not delays in the sales process.

• A single summarized value, such as total annual sales
• Progress toward a defined target or goal
• Whether performance is below, near, or above the target

• Table: Displays detailed records or summarized rows, but not goal progress visually.
• Stacked Bar: Compares multiple categories and their parts.
• Donut: Shows how a total is divided among categories, not progress toward a target.

• Sets a high initial price for a new product.
• Targets customers willing to pay more, often called early adopters.
• Gradually reduces the price to attract more price-sensitive customers as the product becomes less novel and competition increases.

• Penetration pricing: starts with a low price to gain market share quickly.
• Premium pricing: maintains a high price to communicate superior quality or status; it does not necessarily involve later price reductions.
• Loss leader pricing: sells one product at a very low price, sometimes below cost, to attract customers who may buy other products.

1. Open Notepad as Administrator.
2. Open:

1. Remove or correct the line mapping the website to the wrong IP address.
2. Save the file.
3. Optionally run:

cmd 
   ipconfig /flushdns

• Ramen is a Linux worm associated with Red Hat Linux 6.2 and 7.0 systems.
• It spreads by scanning randomly generated IP addresses using tools such as synscan.
• It exploits vulnerable network services, including web-related services, and may leave malicious files or altered web content.
• The tar.gz file is also a clue because it is a common Linux archive/package format.

• Code Red: Primarily targeted Microsoft IIS servers running Windows.
• LoveLetter: Spread mainly through email attachments.
• Nimda: A Windows-based worm that spread through email, web servers, and network shares.

• 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

• A — Consumption-based pricing: AWS generally uses a pay-as-you-go model. You pay for the resources you consume rather than purchasing hardware upfront or paying for unused capacity.
• C — Economies of scale: AWS purchases and operates infrastructure at a very large scale, allowing it to reduce costs and pass some savings to customers through lower service prices.

• Perpetual licenses: These involve paying once for permanent software ownership and are not a primary AWS Cloud economic benefit.
• AWS Enterprise Support at no additional cost: Enterprise Support has an additional charge.
• Bring-your-own-hardware model: AWS provides and manages the underlying cloud infrastructure; customers do not normally bring their own physical servers.

• Confirming the data has the required columns and data types
• Handling missing or duplicate records
• Converting data into a suitable format
• Selecting or engineering useful features
• Splitting it into training, validation, and test sets

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

1. Append Table1 and Table2 as a new query

1. Select the product column in the appended query.

1. Choose Remove Rows > Remove Duplicates

• D — Managers focus on keeping costs low in the short term to maximise profits.

• E — Managers are given incentives to meet or undercut budgets.

• F — Managers delegate responsibility simply to reduce their workload.

• A. Continue using the current system: It will eventually fail and offers no recovery strategy.
• B. Virtualize the entire system: Correct. A VM can preserve the old OS, application, settings, and dependencies while running on newer physical hardware.
• C. Containerize the application: Containers generally share the host OS kernel and are not suitable for preserving an entire incompatible legacy OS.
• D. Clone the disks to USB: A disk clone may provide backup or temporary recovery, but it does not solve hardware compatibility or provide a reliable long-term platform.

• Default route: 0.0.0.0/0; used only when no more specific route exists.
• Network route: A route covering the destination, such as 10.10.13.0/24.
• Host route: An exact 10.10.13.10/32 entry in the routing table.
• Floating static route: A backup static route with a higher administrative distance.

Statement 1 — Correct

Statement 2 — Correct

• 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.