Test Prep TEAS Test Exam Prep
Test of Essential Academic Skills: Reading Comprehension, Sentence Correction, Math Problem Solving, Sentence Completion (Page 50 )

• True positive: The scan reports a vulnerability that really exists.
• False positive: The scan reports a vulnerability that does not exist.
• True negative: The scan correctly reports no vulnerability.
• False negative: The scan fails to detect a vulnerability that is actually present.

• IaaS: você gerencia a VM e o sistema operacional.
• PaaS: o Azure gerencia a infraestrutura; você se concentra no aplicativo.

xml 
<apex:page> 
    <apex:stylesheet value="{!URLFOR($Resource.MyStyles, 'styles/main.css')}" /> 
</apex:page>

• <apex:includeScript> is for JavaScript.
• <apex:includeStyle> is not a valid Visualforce component.
• <apex:require> is not the Visualforce tag used to load CSS.

• Customers may boycott V’s products.
• Supermarket customers may stop buying from V.
• Investors may view V as having higher legal, ethical and reputational risk.
• V could face fines, lawsuits, contract losses and higher costs.
• Expected future profits may fall.

• Amazon EC2 instances — ???????? ?? ?? ??????? CPU, memory ??? instance size ???????? ???????
• AWS Lambda functions — memory configuration ?????????? ???????
• Amazon EBS volumes — volume type ?? size optimize ???? ???????
• ??????? ECS workloads — resource configuration ? cost optimization-?? ???????

• Memory ? compute usage ?????????? ???? custom code ????? ???? development ? maintenance ??????
• Cost allocation tags ???? ????? ??? ?????? ???? ??????? ???; inefficient resource ??????? ?? recommendation ???? ???
• CloudTrail resource ???? ?? API activity ??????, resource utilization ????

• Matching hashes: The software likely has not changed.
• Different hashes: The software was modified or corrupted.

• Encryption: Protects confidentiality by making data unreadable; it does not primarily detect changes.
• Baselines: Define an approved system or configuration state, but they are not the specific integrity mechanism here.
• Tokenization: Replaces sensitive data with substitute values.

• Code suggestions: Inline completions as you write code, such as lines, functions, or blocks.
• Chat: An interactive interface for asking questions, explaining code, generating code, and helping with debugging.

• Knowledge Base: Not listed as a standard Copilot Individual IDE feature in this context.
• Pull Request Diff Analysis: More closely associated with GitHub-based code review or pull-request features, not the core Individual IDE extension capabilities.

• Espionage: Stealing information for intelligence or competitive purposes.
• Data exfiltration: Unauthorized removal or transfer of data.
• Nation-state attack: An attack sponsored or conducted by a government.
• Shadow IT: Technology or access methods used outside approved IT processes.

1. The original app version exists.
2. You create and publish a new version, so there are now two versions.
3. When you restore the previous version, Power Apps does not delete or overwrite the newer version. Instead, it creates another version based on the restored one.

• Original version
• Newly created and published version
• New version created by the restore operation

• Install unauthorized or unsupported software
• Access features blocked by the manufacturer or operating system
• Customize system behavior beyond normal settings

1. Find the subnet-mask increment in the octet where the prefix ends.
2. Identify the network address by finding the subnet boundary at or below the given IP.
3. The first usable address is network address + 1.
4. The broadcast address is one address before the next subnet.
5. The last usable address is broadcast - 1.

• 172.28.228.144/18

• 172.28.228.144/23

• CHAP: Uses a challenge-response exchange, so the password is not directly transmitted.
• IPsec: Provides authentication, integrity, and encryption for IP communications.
• EAP: An authentication framework that supports stronger methods, such as certificates or token-based authentication.

• C — Some risks cannot be eliminated.

• D — Accepting residual risk does not imply recklessness.

• E — Most companies in this industry will say something similar.

• What information each stakeholder needs
• When and how often it should be communicated
• Which format or channel should be used
• Who is responsible for communicating it

• A: The team should not decide stakeholder communications without first checking the established plan and CEO’s needs.
• B: An executive summary may be appropriate, but choosing a solution before reviewing the plan is premature.
• D: The stakeholder engagement plan addresses how to engage stakeholders, but this is primarily a communication planning issue.

• 16GB RAM: A 64-bit OS is needed to use more than roughly 4GB effectively, but RAM capacity does not prove the CPU supports 64-bit operation.
• 500GB HDD: Storage capacity has no bearing on OS architecture.
• 1Gbps Ethernet: Network speed is unrelated to CPU architecture.

• The message came from the claimed sender (authentication)
• The message was not altered in transit (integrity)
• The sender cannot easily deny having signed and sent it (non-repudiation)

• Compliance standards: May be a reason in some organizations, but it is not the primary security benefit.
• Increase delivery rates: Digital signatures do not generally improve email delivery.
• Block phishing attacks: Signatures can help recipients verify legitimate messages, but they do not block phishing by themselves.

• Two-part tariff pricing: $10 per unit
• Dual pricing: $20 per unit

Two-part tariff pricing

Dual pricing

• Division X, the seller, is credited with the market price: \(\$20\)
• Division Y, the buyer, is charged the marginal cost: \(\$10\)

• Accept: Acknowledging the risk without taking additional action.
• Transfer: Shifting responsibility or financial impact to another party, such as through insurance or outsourcing.
• Mitigate: Reducing the likelihood or impact of the risk through controls.
• Avoid: Eliminating the activity or condition that creates the risk.

• Streams — track change data for tables or views.
• External tables — reference data stored in an external cloud storage location.

• Role — account-level security object.
• Warehouse — account-level compute resource.
• User — account-level security object.
• Share — account-level object used to share data.

• Fileless malware: Nothing in the command indicates malware executing only in memory.
• Living-off-the-land binaries: Mimikatz is a credential-access tool, not a normal system utility used for LOLBin abuse.
• Social engineering: The command shows technical credential abuse, not manipulation of an accountant.

• 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.

• 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.

• 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.

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.

• File is shared externally ? Access level

• File is labeled “Internal only” ? Sensitivity label

• 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

• 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.

• Driver node: Coordinates Spark jobs and runs in the compute environment.
• Worker node: Executes tasks and processes data.
• Databricks Filesystem (DBFS): Provides storage access for data used by compute resources.

• Honeypots: Decoy systems or services made to attract attackers. Legitimate users should not interact with them, so activity there is a strong indicator of malicious behavior.
• DNS sinkholes: Redirect requests for known malicious domains to a controlled internal system. This can reveal infected hosts attempting to contact command-and-control infrastructure.

• Tokenization: Replaces sensitive data with non-sensitive tokens.
• CI/CD: Automates software development, testing, and deployment.
• Threat modeling: Identifies and analyzes potential threats before or during system design.
• Data obfuscation: Makes data harder to understand or interpret.

• Filtering harmful or inappropriate content
• Blocking specified topics
• Detecting and masking sensitive information
• Enforcing content policies suitable for children

• Amazon Rekognition analyzes images and videos; it does not control text generated by a language model.
• Amazon Bedrock playgrounds are for testing models and prompts, not enforcing production safety policies.
• Agents for Amazon Bedrock help models complete tasks and use tools; they do not primarily provide content-safety controls.

• Storage usage of files stored in Microsoft Teams: SharePoint site usage report

• Number of active users per team: Microsoft Teams usage report

1. SharePoint site usage report
2. Microsoft Teams usage report

• Admin access to the deployment pipeline
• Contributor access to the Development and Test workspaces
• Viewer access to the Production workspace

• Firewall
• Intrusion prevention and detection
• Antivirus or antimalware
• Web and email filtering
• Virtual private networking (VPN)
• Sometimes content filtering and centralized reporting

• Laws and regulations
• Litigation holds
• Industry or contractual obligations
• Tax, financial, health, or privacy requirements

• Business strategy and direction: May influence retention, but cannot override legal requirements.
• Storage capacity and longevity: Practical considerations, not the primary driver.
• Business ease and value analysis: May support decisions after compliance obligations are identified.

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.

• A — Correct: Identify the data required by Salesforce, its dependencies, and how it should be validated. Verification scripts help confirm record counts, relationships, field mappings, and data integrity after migration.
• D — Correct: Use a full sandbox and perform trial migrations using realistic—or appropriately masked—legacy data. This exposes transformation, volume, dependency, and integration issues before production cutover.
• B — Less appropriate: Phased user migration and parallel operation primarily address user adoption and rollout risk, not the technical risks of data migration.
• C — Less appropriate: Although sandbox testing and integration testing are valuable, the option emphasizes test-data generation rather than validating the migration with representative legacy data. “A full sandbox for all systems” may also be impractical.

• 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.

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.

• Link-local — FE80::/10; valid only on the local link/subnet and not routed by routers.
• Multicast — FF00::/8; identifies a group of interfaces rather than a private address range.
• Global unicast — 2000::/3; publicly routable IPv6 addressing.

• C. Case after-insert trigger that publishes a Platform Event

• D. Custom Apex controller that publishes a Platform Event

• A. Trigger with a callout: Salesforce triggers should not make direct synchronous callouts, and this tightly couples transaction processing to the external system.
• B. Workflow Rule with Outbound Message: This can react to record changes, but it cannot reliably capture a user clicking a menu item. It also does not provide the same flexible event-driven model as Platform Events.

• \Pipeline1
• \Folder1\Lakehouse1

• Pipeline1 remains at the workspace root in Workspace1, so it is deployed to the root of Workspace2.
• Lakehouse1 was moved into Folder1, so its full path is preserved as \Folder1\Lakehouse1.
• Fabric deployment pipelines preserve folder paths because an item’s full path is treated as part of its name.

• Documented and evaluated
• Assessed for security, cost, and operational impact
• Reviewed and approved by the appropriate personnel
• Tested before implementation
• Tracked with version history and rollback procedures

• Risk management process: May help assess the issues, but it does not authorize and manage design changes.
• Product design process: Applies primarily while creating a new design.
• Design review process: Normally evaluates a design before release; this design is already released.

• 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.

• 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

• The identified risk
• Its likelihood and potential impact
• The person or team responsible for handling it
• The response or treatment plan
• Risk thresholds, such as when escalation or action is required
• Current status and review dates

• Risk tolerance: The amount of risk an organization is willing to accept; it is a concept or limit, not usually the primary documentation.
• Risk transfer: Moving the responsibility or financial impact of a risk to another party, such as through insurance.
• Risk analysis: The process of evaluating risk likelihood and impact.

• 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.

• A: It allows for branching and merging...

• C: It allows multiple engineers to work against the same code and configuration files and manage differences and conflicts.

• B: Build automation and infrastructure provisioning are handled by CI/CD and automation tools, not by version control alone.
• D: User Stories and backlogs are managed by project-management tools.
• E: Version control stores and tracks code, but it does not itself ensure that developers write effective unit tests.

• NIDS: Monitors network traffic for suspicious activity and network-based attacks targeting the application or its supporting services.
• HIPS: Protects an individual host by monitoring processes, files, and system activity. It can help secure the web server, but it is not focused specifically on the application’s network attack surface.
• SIEM: Aggregates and correlates logs; it does not directly prevent attacks.
• Honeypot: A decoy system, not the primary protection for a production web application.
• Certificate revocation list: Deals with certificate trust, not application exploitation.

• 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

• Resources that do not need internet access should remain on private network segments.
• Internet-facing access should be restricted to systems that require it.
• Access should be explicitly allowed rather than broadly exposed.

• A: A single administrator with access to core functions may violate least privilege if that access is broader than necessary.
• B: Inspecting traffic supports monitoring and defense, but does not itself limit privileges.
• C: Updating routing configurations supports availability and connectivity, not least privilege.