Test Prep HSPT Test Exam Prep
High School Placement Test (Page 80 )

• Frequency/likelihood = how often or how likely the risk is to occur.
• Severity/impact = how damaging or costly the consequences would be.

• A minor equipment fault occurring frequently may have high frequency but low severity.
• A major cyberattack occurring rarely may have low frequency but high severity.
• A risk that happens often and causes substantial losses has high frequency and high severity.

• Authentication: Verifies who the user is.
• Authorization: Determines what the authenticated user is allowed to access.
• Accounting: Records activity such as login times and resource usage.

• CIA: Confidentiality, integrity, and availability—the three core security goals.
• ACL: Access Control List, which defines permitted or denied traffic or access.
• PEM: A certificate and key encoding format, not the primary function of RADIUS.

• Virus signatures: Primarily associated with antivirus or antimalware tools.
• Security agent deployment: Usually handled by endpoint-management or endpoint-security platforms.
• Vulnerability scanning: Performed by vulnerability-assessment tools, although a SIEM may ingest their results.

• A — Improved management of storage space: Correct.

• B — Improved supplier relationships: Correct.

• C — Improved pricing decisions: Correct.

• D — Non-product-specific costs must be apportioned: Incorrect.

• E — Profitability of each customer group: Incorrect.

• C: Develop the rule in the Rules Editor, define the events, match, and condition sections, then use the test rule feature. This directly validates the YARA-L rule without enabling it in production.
• A: UDM Search can help investigate data and refine filters, but it does not fully test YARA-L logic—especially complex event joins, match windows, and conditions.

• 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.

• Case Assignment Rules normalmente são avaliadas quando o caso é criado. Elas podem ser executadas novamente em uma edição somente se o usuário marcar “Assign using active assignment rules”; isso não acontece automaticamente apenas porque o caso foi fechado.
• Portanto, criar uma regra de atribuição não corrige os centenas de casos já fechados e não garante, por si só, que um caso será transferido antes de ser fechado.

• B — Usar uma ferramenta de dados: corrige os registros históricos já existentes, atualizando o Owner.
• D — Criar uma regra de validação: impede que um caso seja fechado enquanto ainda pertence a uma fila. Exemplo conceitual: se Status = Closed e o proprietário for uma fila, bloquear o salvamento.

• 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.

• Minimum
• Maximum
• Average
• Count
• Null/empty values
• Distinct values

• Enable column profile
• Enable details pane
• Show column profile in details pane

• 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.

• If the hashes match, the software has likely not changed.
• If they differ, the software was modified or corrupted.

• Encryption: Protects confidentiality by making data unreadable; it does not primarily verify that software was unchanged.
• Baselines: Establish expected configurations or states, but hashing is the specific method for checking file integrity.
• Tokenization: Replaces sensitive data with non-sensitive tokens and is unrelated to software integrity.

• Preparing and managing datasets
• Building and training machine-learning models
• Testing and evaluating models
• Deploying models as endpoints for predictions

• Existing expected ROI: 15%
• New project ROI: 14%
• Cost of capital: 12%

• Project return = 14%
• Cost of capital = 12%
• It earns 2% more than the cost of capital, so it should increase shareholder value.

• 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 — If there is no demand, there should be no production.

• B — Not all sales equal profit.

• C — Stocking up on inventory is bad for business.

• D — All costs, except materials, are considered fixed.

• E — Departments should operate at full capacity regardless of bottlenecks.

• A: Knowledge of IT platforms, networks, and methodologies — Useful technical knowledge, but the CISO does not need to be the deepest technical expert.
• C: Regulatory and project management knowledge — Important, but compliance and projects must still support the organization’s broader needs.
• D: Managing people and resources — Essential for execution, but effective management of the wrong security priorities will not produce good results.

• Firewalls and routers
• Servers and applications
• Endpoint devices
• Authentication systems
• Cloud services

• Centralized log collection
• Event correlation
• Dashboards and reporting
• Alerting
• Compliance support

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.

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

• D — Value analysis: Correct. It examines an existing product to identify ways of reducing its cost while still providing the required functions, quality and reliability.
• E — Kaizen costing: Correct. It involves making continuous, small improvements and cost reductions while the product is already in production.

• Functional analysis: It is not limited to minimizing the cost of the originally defined functions. It examines what functions are required and how they can be provided at the lowest overall cost.
• Value engineering: Usually applies to the design and development of a new product, rather than being a fundamental redesign of existing organisational processes. That description is closer to business process re-engineering.
• Target costing: The target cost is generally established during the product development stage, before production begins. It is not continuously reset while the product is in production.

• A — Technical review by business owner: A business owner may approve the business impact, but a technical review is normally performed by technical personnel.
• C — Cost-benefit analysis after implementation: Cost-benefit analysis should occur before implementation to support the approval decision.
• D — Business continuity testing: This can be appropriate for major changes, but it is primarily part of business continuity and disaster recovery planning—not a universal change-management activity.

• Dataset file: Use Import mode. Excel files are imported into Power BI, and the two Sales tables can be combined with Power Query.
• Report file: Use a live connection to the published dataset. This keeps the report separate from the dataset and avoids importing the data again.

• Report file: DirectQuery/live connection
• Dataset file: Import

• 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.

• Insert is used when you are creating a new record. It saves the record to the table and then leaves the form.
• Update is used when editing an existing record. It saves the modifications and then leaves the form.

• Virtual introductions: Team members share their role, experience, location, and working preferences.
• Online icebreakers: Short, informal activities such as “two truths and a lie.”
• Virtual coffee chats: Pair team members for informal, non-project conversations.
• Collaborative problem-solving: The team works together on an online puzzle or scenario.
• Retrospectives: The team discusses what went well, what did not, and how to improve.
• Working-agreement sessions: The team agrees on response times, meeting etiquette, communication channels, and handoffs.
• Recognition sessions: Members acknowledge one another’s contributions.
• Remote workshops: Teams jointly create plans, diagrams, or schedules using collaboration tools.

• 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

• 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.

Recommended process

1. Access each switch’s terminal.
2. Use help to identify available commands.
3. Use the MAC table command, such as:

text 
   show mac-address-table

1. Use VLAN information, such as:

text 
   show vlan

1. Use interface information, such as:

text 
   show ip interface brief

1. Record each device’s:

• Reduce the training data: Usually makes overfitting worse.
• Add hyperparameters: Hyperparameters already control training; simply adding them does not solve the problem. Proper tuning could help, but that is not what the option states.
• Increase training time: More training can worsen overfitting if the model is already memorizing the training data.

• B — Incorporate contextual output encoding/escaping: Encode untrusted data based on its context—HTML, attribute, JavaScript, or URL—so the browser treats it as data rather than executable code.
• D — Run untrusted HTML input through an HTML sanitization engine: Sanitization removes or neutralizes dangerous elements and attributes, such as script-related content, while preserving safe HTML where needed.

• A: Enabling client-side scripts does not prevent XSS. Script restrictions may reduce risk in some environments, but “enable” is not a general XSS control.
• C: Cookie inspection is unrelated to preventing injected scripts.
• E: The SameSite cookie attribute primarily helps mitigate CSRF, not XSS. It should not generally be described as an XSS prevention measure.

• The JSON files contain one billion items, so this is a big-data workload.
• PySpark uses Apache Spark’s distributed, parallel processing, allowing the data to be processed across multiple compute nodes.
• It can read and transform data directly from OneLake, helping minimize unnecessary data movement or duplication.
• A Fabric notebook can also support exploration and visualization, as well as Spark-based analytics and anomaly-detection workflows.

• Pandas is primarily in-memory and generally suited to smaller datasets. One billion records would be impractical on a typical single machine.
• A Power BI report with core visuals is appropriate for visualization and sharing, but it is not the best tool for large-scale transformation, parallel processing, or anomaly detection. It would normally consume prepared data rather than perform the entire workload.

• Accept: Acknowledging the risk and choosing not to take additional action.
• Transfer: Shifting the risk or financial consequences to another party, such as an insurer.
• Mitigate: Reducing the likelihood or impact through controls, such as patching or access restrictions.
• Avoid: Eliminating the activity that creates the risk.

• 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.

• 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.

• New investment: $536,500
• Resulting NPV: $0

• GPS coordinates
• Date and time the image was taken
• Camera or device information
• Image dimensions and software used

• Log data: Records generated by systems or applications, not normally embedded in image files.
• Encrypted data: Information intentionally encoded to prevent unauthorized access.
• Sensitive data: A broad classification, not the specific type of information being extracted.

Manager role

DAX 
Country[Manager] = USERPRINCIPALNAME()

• Sales
• Human Resources

CFO role

• See sales for all countries
• See no Human Resources data

• Do not restrict the Country table or Sales table.
• Apply a filter to Human Resources that always returns false, such as:

DAX 
FALSE()

• Tracking who accessed or changed customer information
• Detecting unauthorized activity
• Supporting accountability and investigations
• Providing evidence for compliance and incident response

• Single sign-on not enabled: SSO improves convenience and centralized authentication, but it is not essential for access control.
• Complex passwords not required: This weakens authentication, but other controls may reduce the risk.
• Security baseline not consistently applied: A concern, but it is less specific and less immediately damaging than having no activity records at all.

• Each Case must follow defined support steps.
• Each step must be completed within a specified time limit.

• Case Escalation Rules: Escalate Cases based mainly on age or criteria; they do not model a complete sequence of service steps.
• Process Builder with Scheduled Actions: Can automate time-based actions but is not the standard framework for Case service-level commitments.
• Omni-Channel Routing: Routes work to agents based on capacity and priority; it does not track Case lifecycle deadlines.

• Undefined or blank values
• Relationship matching problems
• Duplicate or conflicting keys
• Errors when querying the model

• Normalize all values to upper- or lowercase in the source query or Power Query.
• Add an index or surrogate key when values that differ only by case must remain distinct.

• Penetration test: Tests for exploitable vulnerabilities; it does not provide a broad opinion on whether security controls operate effectively.
• Annual self-assessment: Not independent, so it provides less assurance.
• Allow each client the right to audit: Inefficient because every customer may conduct a separate audit, creating duplicated effort and disruption.

• MFA: Protects sign-in and authentication.
• Azure Key Vault: Protects deployment secrets and credentials.
• Answer: No (B).

• Minimum and maximum values
• Number of distinct values
• NULL information
• Other metadata used for pruning

• A PostToolUse hook for file writes under src/api/ that runs the linter.
• A separate PostToolUse hook for API/data processing that normalizes payloads to snake_case.

• 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.

• A business-hours greeting
• An after-hours greeting
• A holiday greeting

• Weekday evenings/nights
• Saturdays and Sundays

1. Auto attendant 1

1. Auto attendant 2

• Static IP address: Not needed if the workstation already has network connectivity.
• Subnet mask: Incorrect subnetting would usually prevent local communication, including pinging the server.
• Default gateway: Primarily affects communication outside the local network; it does not normally prevent finding an internal domain controller.

• Scanning is not essential during a power outage.
• A scanner can consume UPS battery power without helping the user save cloud documents or shut down safely.
• The UPS should be reserved for the computer, monitor, and necessary network equipment.
• The surge protector helps protect the scanner from voltage spikes, but it will not keep it running during an outage.

• A. IDS attack signatures: An IDS primarily detects suspicious network activity; it is not the best control for scanning uploaded documents for malware.
• C. Load balancer: Distributes traffic among servers and improves availability, but does not inspect files for malware.
• D. WAF: Protects web applications against attacks such as SQL injection and command injection. It may help secure the upload function, but malware scanning is the key requirement here.