Test Prep LSAT Test Exam Prep
Law School Admission Test: Logical Reasoning, Reading Comprehension, Analytical Reasoning (Page 43 )

• 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.

• netstat: Shows local network connections and listening ports, but not which WAN path carries the traffic.
• nslookup: Resolves domain names to IP addresses.
• ping: Tests reachability and latency but does not show the route.

• The application failing to start or becoming unhealthy
• An incorrect probe path, port, or protocol
• The application needing more startup time
• Dependency or configuration failures
• A liveness probe being too aggressive

bash 
kubectl describe pod <pod-name> 
kubectl logs <pod-name> --previous

• Scale to more replicas: may hide the issue but does not diagnose it.
• Decrease initialDelaySeconds: makes probes run earlier and could worsen startup failures.
• Drain and reboot the node: node metrics are normal, so rebooting is not justified as the first step.

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

• Unfamiliar locations or IP addresses
• Anonymous or malicious IP addresses
• Leaked credentials
• Unusual sign-in behavior

• 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.

• 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.

• 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.

• 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.

• Disaster recovery backups
• Long-term backup retention
• Data archiving that still needs occasional access

• Multi-Regional Storage: Intended for frequently accessed data needing broad geographic availability; it costs more.
• Regional Storage: Suitable for frequently accessed data within one region.
• Nearline Storage: Intended for data accessed roughly once per month, such as monthly backups.
• Coldline Storage: Better fit for backups accessed only during a disaster or occasional recovery event.

• 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.

• Accept: Acknowledging the risk without taking additional action.
• Mitigate: Reducing the likelihood or impact through controls, such as patching or employee training.
• Avoid: Eliminating the activity or condition that creates the risk.
• Transfer: Shifting the consequences—usually financial—to another party, such as an insurer.

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

• 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.

• B. Versioned configuration files — Infrastructure is defined in machine-readable files and tracked in version control, allowing repeatable provisioning and change history.
• D. Docker files — Assuming “Doctor files” is a typo for Dockerfiles, a Dockerfile declaratively defines how to build a container image and is commonly considered infrastructure/configuration as code.

• A. Cloned virtual machine images — These are prebuilt infrastructure artifacts, but cloning an image is not itself a code-based infrastructure definition.
• C. Change management database records — A CMDB records information about infrastructure; it does not define or provision that infrastructure.

• Azure Machine Learning is the overall Azure service.
• Machine Learning designer is the visual, drag-and-drop interface within Azure Machine Learning.
• Microsoft may refer to the broader product as Azure Machine Learning studio, while “Designer” remains the specific visual workflow tool.

• Azure Logic Apps: Workflow and integration automation.
• Azure Batch: Large-scale parallel or batch compute.
• Azure Cosmos DB: Globally distributed NoSQL database.

1. Define Power Platform DLP policies

1. Add custom prompt modifications

1. Conduct adversarial testing

• 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.

• Espionage: Stealing information for intelligence or competitive purposes.
• Data exfiltration: Unauthorized removal or transfer of data.
• Nation-state attack: A sophisticated attack sponsored by a government.
• Shadow IT: Unapproved technology or access methods used by employees.

• The requirement is to obtain an assessment of the Azure environment’s design.
• The proposed solution is the Premier support plan.
• Premier can provide this type of guidance, but it is a higher-tier, more expensive option.
• The question specifically says to keep costs to a minimum. A lower tier—typically Professional Direct in the support-plan model used by this question—provides architectural/design guidance.

• 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.

• Existing measures
• Relationships
• Calculated columns
• Tables and fields
• Existing transformations in the model

• SharePoint folder: Reconnects to the source files. You would likely need to recreate the model and measures.
• Power BI dataflows: Primarily provide reusable data preparation and storage, but they do not automatically provide the existing semantic model and measures.
• Excel workbook: Connects directly to the source file and would also require rebuilding the model and measures.

• Open or insecure ports
• Enabled legacy or insecure protocols
• Known vulnerabilities and misconfigurations
• Weak services and outdated software

• curl tests web requests and HTTP-based services.
• Wireshark captures and analyzes network traffic; it does not normally scan servers for weaknesses.
• netcat can test connectivity to individual ports and sometimes grab service banners, but it is not a comprehensive vulnerability scanner.

• Ease of exploitation
• Required privileges
• User interaction
• Impact on confidentiality, integrity, and availability

• CVE: Identifies and names a specific publicly known vulnerability; it does not measure severity.
• OSINT: Refers to intelligence gathered from publicly available sources.
• SOAR: Automates and coordinates security operations, such as alert response and playbooks.

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

• 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.

• Inherent risk: Risk that exists before controls are implemented.
• Avoided risk: Risk eliminated by choosing not to perform the risky activity.
• Operational risk: Risk arising from failures in processes, people, systems, or daily operations.

• 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.

• 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.

• 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.

• Accept: Acknowledges the risk without taking additional action.
• Transfer: Shifts the risk or financial impact to another party, such as an insurer.
• Mitigate: Reduces the likelihood or impact through controls like patching, MFA, or segmentation.
• Avoid: Eliminates the activity that creates the risk.

• 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.

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.

• Configure row-level security (RLS) using the sales region and the HR manager’s identity.
• Publish the reports and datasets through a Power BI app.
• Grant the HR managers permission to use the app, but do not add them as workspace members.
• App users can view and interact with reports while RLS limits them to their region.
• They cannot modify the report layout because they do not have workspace editing permissions.

• Adding them to the workspace gives them workspace permissions that may allow report or dataset changes, depending on the assigned role.
• Creating copies is unnecessary and creates maintenance and security problems.
• Hosting datasets and reports in different workspaces does not, by itself, provide the required controlled access.

• File hashes
• Strings and metadata
• Binary or code structure
• Known malicious patterns
• Embedded indicators or signatures

• Sandbox: Executes the file in an isolated environment; useful for observing behavior, but usually slower.
• Network traffic analysis: Examines communications generated by a system or application, not the file itself.
• Package monitoring: Tracks software packages or installations and is not the primary method for examining malware signatures.

• Encryption to preserve confidentiality
• Integrity protection to detect alteration
• Authentication of the server through certificates

• SHA-256: A hashing algorithm; it does not encrypt data for transmission.
• SSL 3.0: Obsolete and insecure. It should not be used.
• AES-256: A strong encryption algorithm, but by itself it does not provide the complete secure communication protocol needed for data in transit.

• The current and previous versions
• Which clauses were changed
• When each revision occurred
• Potentially, who made the changes

• Version validation: Verifies a version’s accuracy or integrity but does not primarily track revisions.
• Version changes: Not the standard name for a formal document-management process.
• Version updates: Describes updating a document, not the complete process of managing and tracking its revisions.

• Digitally signing the software: Verifies authenticity and integrity. It does not hide how the software works.
• Limiting third-party libraries: May reduce dependencies and attack surface, but does not directly prevent reverse engineering.
• Using compile flags: Some compiler options can remove debugging information or optimize code, which may provide limited protection, but this is not the primary technique identified for preventing reverse engineering.

• A password cracker would normally be identified by behavior such as loading password hashes or attempting dictionary/brute-force attacks.
• The question describes a routine audit, not password recovery.
• Simply encountering a protected file during an audit is characteristic of a misconfigured or insufficiently privileged FIM.

• 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.

1. Create or verify cost groups

1. Set up the item model group

1. Create the costing version

1. Enter or calculate item costs

1. Activate the standard costs

• How quickly the vendor must respond to an incident or request
• Target resolution times
• Availability or uptime requirements
• Performance metrics and penalties for not meeting them

• SOW (Statement of Work): Describes the project’s scope, tasks, deliverables, and timeline.
• MOA (Memorandum of Agreement): Documents a formal agreement to cooperate or perform specific activities.
• MOU (Memorandum of Understanding): Records a mutual understanding or intent, often less binding than a contract.

• Access controls — ensuring only authorized users can access it.
• Encryption — protecting the data if it is intercepted or exposed.

• Restrict a port to a defined number of MAC addresses
• Use statically configured 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 traffic but is not the primary control for switch-port MAC limits.
• NGFW: Filters routed network traffic, not the switch’s CAM/MAC address table directly.

• 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.

• 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

• CSIRT: A Computer Security Incident Response Team that handles and coordinates incident response.
• CVSS: A scoring system used to rate the severity of vulnerabilities.
• SOAR: Security Orchestration, Automation, and Response technology used to automate security workflows.

• 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.

• Restarting the device: May fix software glitches, but would not usually make cable orientation matter.
• Swollen battery: A safety concern, but it would not typically cause recognition only in one cable orientation.
• Failing cable: Possible, but less likely because the problem occurs with this particular device and not other devices of the same type.