CFA CFA I Exam Prep
CFA Level I Chartered Financial Analyst (Page 369 )

• 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.

• 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.

• B — Both inner and outer classes can be declared as with sharing.

• C — Inner classes do not inherit sharing settings from the container class.

apex 
public with sharing class OuterClass { 
    public with sharing class InnerClass { 
        // Explicitly uses sharing rules 
    } 
}

• Leaf switches provide access ports for servers, users, and other devices.
• Spine switches provide the backbone between leaf switches.
• Every leaf switch connects to every spine switch, creating a predictable, full-mesh fabric between the two layers.
• Leaf switches do not connect directly to other leaf switches, and spine switches do not connect directly to other spine switches.

• A: Adding both a spine and leaf is unnecessary for simply adding access ports.
• B: It focuses on uplink speed, not the scalable topology.
• D: A single spine connection creates a bottleneck and a single point of failure.

• \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.

• 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.

• 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.

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.

• B: Não é preciso implantar o modelo em um endpoint do Amazon SageMaker, pois o Bedrock já oferece a infraestrutura de inferência.
• C: O SageMaker Model Registry é usado para gerenciar modelos no SageMaker, não é requisito para modelos customizados no Bedrock.
• D: Não existe uma etapa geral de “conceder acesso” ao modelo customizado como requisito principal de uso. O ponto essencial é adquirir o Provisioned Throughput.

• Portfolio definition cycle — establishes and maintains the portfolio strategy, objectives, and management framework.
• Portfolio delivery cycle — coordinates and monitors the delivery of change initiatives, ensuring the portfolio remains aligned with strategic objectives and delivers value.

• Practice — a structured area of portfolio management activity, such as risk management or resource management.
• Technique — a method used to perform an activity; it is not the term for portfolio delivery itself.
• Principle — a guiding rule for effective portfolio management.

• 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.

• Microservices: An application design approach that divides software into small services; it does not specifically reduce the number of operating systems.
• Containerization: Uses isolated containers that share the host OS kernel—best match.
• Virtualization: Creates separate virtual machines, and each typically requires its own guest OS, so it does not minimize OS instances as effectively.
• Infrastructure as code: Automates deployment and management of infrastructure; it does not describe the architecture being used.

• # Development
• # Testing
• # Production

• Separate endpoints: relate to compute or connectivity, not dashboard labels.
• Separate queries: retrieve or transform data but do not designate visual sections.
• Direct text written into the dashboard in editing mode: dashboards use text boxes, typically with Markdown formatting, rather than arbitrary text placed directly on the canvas.

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

• IaaS: You deploy and manage virtual machines, including the operating system and installed software. Azure manages the physical datacenter, hosts, and networking infrastructure.
• PaaS: Azure manages the infrastructure and operating system, while you deploy and manage your application code. Examples include Azure App Service and Azure Functions.

• s3:GetObject for the relevant objects
• s3:ListBucket if listing is required
• Appropriate bucket and object resource permissions

• B: Making the bucket public is insecure and unnecessary.
• C: Prompt engineering cannot override AWS IAM or encryption permissions.
• D: Data sensitivity does not determine whether the role can access it.

• Disabling a compromised account
• Blocking a malicious IP address
• Isolating an endpoint
• Creating or escalating an incident ticket

• Virus signatures: Primarily associated with antivirus or endpoint protection.
• Security agent deployment: Usually handled by endpoint-management or security-agent platforms.
• Vulnerability scanning: Typically performed by vulnerability-management tools.

• 10 TB with maximum I/O performance: Use EC2 instance store. It provides very high-throughput, low-latency local storage suitable for temporary video-processing data. The application must tolerate data loss because instance store is ephemeral.
• 300 TB of highly durable media: Use Amazon S3, which is designed for highly durable object storage and can scale to this size.
• 900 TB of inactive archival media: Use S3 Glacier, which provides lower-cost storage for data that is rarely accessed.

• A: Amazon EBS offers high performance but is not the best fit for the question’s “maximum possible I/O” requirement compared with local instance store.
• B: Amazon EFS is durable and shared, but is generally more expensive and less suitable for very large archival storage.
• C: Uses EC2 instance store for performance, but incorrectly uses EFS for the 300-TB durable tier and S3 rather than Glacier for archival data.

1. Wireless AP

1. Router

1. Firewall

1. Device placement

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.

• 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 ????

• 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.

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

• sn_si_admin is an SIR administrator role.
• The prefix helps prevent naming conflicts between applications.
• It does not refer to a “Secure Identity token” or an instance security check.

• 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.

• A — Use a custom controller: An Apex class can contain the page’s logic.
• C — Use a standard controller with extensions: The standard controller provides basic CRUD behavior, while an extension adds custom logic.
• E — Use a standard controller: Useful when the page works mainly with one Salesforce object and needs standard functionality.

• A page with no controller for static or controller-free content.
• A custom controller with extensions; extensions are not limited only to standard controllers.

• 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.

• vBond — orchestration plane: Authenticates devices, helps them discover each other, and assists with NAT traversal and initial control-connection setup.
• vSmart — control plane: Distributes routing and policy information to WAN Edge devices using the overlay control plane.
• vManage — management plane: Provides centralized configuration, monitoring, and orchestration through its GUI/API.
• WAN Edge — data plane: Forwards user traffic across the SD-WAN fabric.

• Espionage: Stealing confidential information, often for a competitor or government.
• Data exfiltration: Unauthorized transfer of data outside the organization. This could occur, but the question focuses on using unapproved access methods.
• Nation-state attack: An attack sponsored or conducted by a government.
• Shadow IT: Employees using technology or access methods outside the organization’s approved security controls.

• Active remediation actions role in Microsoft Defender for Endpoint

• Security Reader role in Azure AD/Entra ID

• Security Administrator is broader than necessary because it grants extensive security-management permissions, violating least privilege.
• Compliance Data Administrator is intended for compliance data management, not Defender for Endpoint remediation approvals.

• Financial performance
• Customer perspective
• Internal business processes
• Learning and growth

• Increasing the number of indicators can make the scorecard cluttered and less useful. Measures should be limited to those that are strategically important.
• The scorecard is mainly a tool for implementing and monitoring strategy, not for formulating strategy.
• It should contain both leading indicators and lagging indicators. Leading indicators predict future performance, while lagging indicators measure results already achieved.

• Actions that call external APIs
• Subflows
• Connection and credential aliases
• Supporting integration logic

• Action — A reusable operation within a flow, such as “Create a record” or “Send email.”
• Connection — Defines how ServiceNow authenticates and communicates with an external system.
• Integration step — A general flow step, not the name for the packaged integration.

• 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.

• Due diligence: Investigating and evaluating a third party before entering a business relationship.
• Attestation: An independent auditor’s examination and formal report—such as the SOC 2 report itself. The analyst is reviewing the attestation, not performing it.
• Internal audit: Examines the organization’s own processes and controls.
• Penetration testing: Actively tests systems for exploitable vulnerabilities.

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

• Highly polished, organization-wide presentations
• Advanced dashboard design and customization
• Broader business-user distribution and interaction
• Specialized BI governance and modeling features

• C — Some risks cannot be eliminated.

• D — Accepting residual risk does not imply recklessness.

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

• 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.

• Crowd-sourced evaluation: Requires recruiting and managing many evaluators.
• Human-worker evaluation: Provides human judgment but requires coordination, labeling instructions, and quality control.
• RLHF: Is a training and alignment process, not simply a low-overhead model comparison method.
• Automatic model evaluation: Quickly evaluates outputs using predefined toxicity or quality metrics with minimal manual effort.

• 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.

• Input validation: Prevents malicious or malformed input within an application; it does not authenticate a software package.
• Secure cookies: Protect web-session cookies; they do not protect downloadable software.
• Fuzzing: Tests software by supplying unexpected input to find vulnerabilities; it does not verify software integrity.

• Assign endpoints to a group based on the result of one policy.
• Use that group as the scope of another policy.
• This effectively passes the endpoints from one policy’s processing flow to another.

• Microservices: An application-design approach that divides an application into smaller services. It does not inherently reduce the number of operating systems.
• Virtualization: Creates virtual machines, but each VM generally requires its own complete operating system. This improves isolation but does not minimize OS instances as effectively.
• Infrastructure as code: Uses code to automate infrastructure deployment and configuration. It improves consistency but does not determine how many operating systems are used.

• 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.

• Outer packet: 10.5.1.1 > 52.165.16.154
• IPv4 protocol field: 41, which indicates IPv6 encapsulation
• Inner packet: IPv6 traffic between 2001:... addresses

• MAC address spoofing: Changes Layer 2 addressing; it does not explain the IPv6-in-IPv4 structure.
• Steganography: Hides data inside files or media, not visibly in a tunneled protocol.
• Broken encryption: No evidence of encryption being cracked.
• On-path sniffing: Involves intercepting traffic, not sending data to an external host.

• Set credit quotas for an account or individual virtual warehouses.
• Define monitoring intervals.
• Trigger actions when usage reaches thresholds, such as sending notifications or suspending a warehouse.
• Help control unexpected warehouse spending.

• Account Usage: Provides historical usage and billing data; it does not enforce credit limits.
• Warehouse Limit Parameter: Not the Snowflake object used for account-wide credit controls.
• Credit Consumption Tracker: Not a standard Snowflake object.

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.

• 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.

• Employees can use approved devices from remote locations or worldwide offices.
• Users do not need to carry or insert extra hardware.
• It helps prevent account takeovers from unknown devices.

• Geotagging: Restricts access based on location, which could interfere with remote work and travel.
• Smart cards: Require additional physical equipment and card readers.
• Time-based logins: Limit access according to time but do not strongly bind access to an authorized user device.

• Limiting the number of MAC addresses allowed on a switch port
• Restricting ports to specific known MAC addresses
• Taking an action—such as dropping frames or shutting down the port—when the limit is exceeded

• Load balancer: Distributes application traffic; it does not protect switch MAC tables.
• IPS: May detect some attack traffic, but is not the primary control for switch-port MAC limits.
• NGFW: Filters network traffic at the firewall, but does not directly control MAC addresses learned by a switch.