PEOPLECERT MOR Exam Prep
Management of Risk Foundation (MOR) (Page 3 )

• MOR health checks assess how risk management is implemented and embedded, and identify improvements and ROI opportunities.
• They’re about process health, governance, and capability, not about listing or snapshotting the actual risks themselves.

• Identify areas for improvement — yes; a health check should highlight gaps.
• Help gain maximum value from investment in risk management — yes; it supports value realization.
• Provide a snapshot of the current status of identified risks — not the primary goal; risk status is typically captured in risk registers/reports, not the health of the risk management process.
• Review how well risk management practices have been embedded — yes; a core objective.

• Product Owner: May attend, but is not required unless also working as a Developer.
• Scrum Master: May attend to help facilitate or coach, but is not required.
• Developers: Must participate because the event is specifically for them.

• Sensitive document shared during a Teams chat: Teams chat
• Sensitive document stored/shared in a Teams channel: Teams channel messages

• Files shared in a chat are generally stored in the sender’s OneDrive, but the relevant DLP context is the Teams chat message and its attachment.
• Files shared in a channel are stored in the team’s SharePoint site, but the relevant context is the Teams channel message.
• The DLP rule can then use an action such as restrict access to the content to prevent guest users from opening the sensitive document.

• Supervised learning requires labeled examples to learn how to classify customers.
• Reinforcement learning learns through actions, rewards, and penalties, which is not the main task here.
• RLHF uses human feedback to improve model behavior, typically for generative AI, not customer segmentation.

• Multiple nodes: Data is replicated several times in the primary region.
• Separate geography: A copy is asynchronously replicated to a secondary Azure region.
• Readable secondary: RA-GRS provides read-only access to the secondary replica, even when the primary region is available.

• GRS: Replicates to another region but the secondary copy isn’t normally readable.
• ZRS: Replicates across availability zones in the same region, not a separate geographic region.
• LRS: Keeps replicas within a single datacenter or region and provides no geographic redundancy.

• A — Custom Button: A button can launch a flow, typically by passing the flow’s URL and record context.
• D — From a Process: A Process can invoke a flow using an Apex action configured for flow invocation. However, this is automation-triggered, not directly accessed by a user.
• B — Quick Action: In current Salesforce functionality, a Flow Quick Action can launch a screen flow directly from a record page. This makes B a valid modern method.
• C — Visual Workflow Launcher: This is not generally listed as a standard access method in current Salesforce terminology; Salesforce commonly uses the Flow component on Lightning pages instead.

• A: Using an external OAuth 2.0 identity provider could provide unified identity, but it does not specifically address Salesforce capacity or high-volume login limits.
• B: Making the Experience Cloud community a SAML identity provider and using JIT provisioning is a possible federation pattern, but it may not be appropriate for this scale without Salesforce validation.
• C: A default account is unrelated to solving identity unification and high login throughput. Person Accounts can be supported in appropriate B2C Commerce integrations.

• Use one Azure AD directory for the organization.
• Separate divisions with subscriptions and/or resource groups.
• Assign each division’s administrator appropriate Azure role-based access control (RBAC) permissions, scoped to their subscription or resource group.

• 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.

1. Determine which host was infected first—the originating host.
2. Decide whether each other host is clean or infected based on communication and event logs.

• Compare timestamps and find the earliest suspicious event.
• Look for the host that initiated the malicious connection, file transfer, exploit, or command—not merely a host that later received traffic.
• Follow the timeline through the firewall:

• A host is likely infected if it both receives suspicious activity and then initiates related malicious traffic.
• A host may be clean if the firewall blocked the connection and there is no evidence of execution or follow-on communication.

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.

• Workspace: Stores notebooks, libraries, jobs, and other project resources.
• Notebooks: Interactive documents containing code, queries, visualizations, and explanations. Common languages include Python, SQL, Scala, and R.
• Clusters: Groups of virtual machines that run Spark workloads. Clusters can be started, stopped, and automatically scaled.
• Data access: Databricks can read from services such as Azure Data Lake Storage, Azure Blob Storage, and Azure SQL.
• Jobs: Automate notebooks or data-processing workflows on a schedule or in response to events.

• Azure Cosmos DB is a globally distributed NoSQL database service. It stores and retrieves application data, but it does not provide the tools needed to build, test, and deploy predictive analytics models.
• Azure Machine Learning—including the historical Azure Machine Learning Studio—is designed for the machine-learning lifecycle:

• Conserve public IPv4 addresses: IPv4 addresses are limited, so many internal devices share a smaller number of public addresses through NAT.
• Reduce direct exposure: Private addresses are not directly routable from the public Internet, which helps reduce unsolicited access to internal devices.

• A: Security groups do not control traffic to an S3 gateway endpoint in this way. Gateway endpoints are configured through route tables.
• B: An S3 bucket policy may be needed for authorization, but the error specifically indicates a connectivity or endpoint-routing problem.
• C: Glue connection settings do not require a fully qualified domain name to resolve this endpoint issue.

• Blue team: Defends systems, monitors activity, and responds to attacks.
• Purple team: Coordinates red- and blue-team activities to improve defenses.
• White team: Oversees or manages the exercise, including rules and scope.

• Updating the CRL: Revokes compromised certificates, but does not fix the CA flaw that allowed them to be created.
• Changing passwords: May be necessary if accounts were compromised, but it does not address the certificate-generation vulnerability.
• Implementing SOAR: Improves security automation and response; it does not remediate the underlying PKI weakness.

• Exploitability
• Attack complexity
• Required privileges
• User interaction
• Impact on confidentiality, integrity, and availability

• CVE: Identifies and tracks a specific vulnerability; it does not primarily measure severity.
• OSINT: Open-source intelligence gathered from publicly available sources.
• SOAR: Security orchestration, automation, and response technology used to automate security workflows.

• The inference container image or built-in algorithm
• The location of model artifacts in Amazon S3
• IAM permissions through the execution role
• Optional environment variables and networking settings

1. Create AWS::SageMaker::Model
2. Create an AWS::SageMaker::EndpointConfig that references the model
3. Create AWS::SageMaker::Endpoint that references the endpoint configuration

• AWS::SageMaker::Endpoint hosts a model but does not define the model itself.
• AWS::SageMaker::NotebookInstance provides a development environment.
• AWS::SageMaker::Pipeline orchestrates ML workflow steps.

• MAC flooding: Overwhelms a switch’s MAC address table, potentially causing traffic to be broadcast.
• DNS spoofing: Provides false DNS responses to redirect users.
• ARP poisoning: Sends false ARP information to associate an attacker’s MAC address with another device’s IP address.

• A is correct: Days beyond the included period incur an extra daily charge.
• D is incorrect: Daily use after 10 days is not free.
• B and C: Data-transfer pricing can depend on the direction and service terms. The exam’s intended distinction is that the included device usage period is the clearly stated no-cost benefit.

• Data loss prevention (DLP): Helps detect or prevent unauthorized data transfers, but does not directly protect data on a stolen, powered-off laptop.
• Operating system hardening: Reduces vulnerabilities and attack surface, but does not adequately protect stored data if the device is stolen.
• Boot security: Helps prevent unauthorized operating systems or boot media from loading. It supports device security but is not the primary solution for protecting the data itself.

1. Product + ProductSubCategory: Inner join

1. Result + ProductCategory: Left outer join

• Modelo de embeddings multimodal: transforma texto e imagens em vetores no mesmo espaço semântico. Isso permite comparar uma consulta textual com imagens, ou uma imagem com textos relacionados.
• Modelo generativo multimodal: interpreta diferentes modalidades e gera conteúdo, mas não é a escolha específica para indexação e busca vetorial.
• Modelo de geração de imagens: cria imagens, portanto é inadequado.
• Modelo de embeddings de texto: não atende consultas com imagens.

• Accept: Acknowledging the risk without taking additional action.
• Transfer: Shifting the risk’s impact to a third party, such as through insurance or outsourcing.
• Mitigate: Reducing the likelihood or impact of the risk through security controls.
• Avoid: Eliminating the activity or process that creates the risk.

text 
interface GigabitEthernet0/0.10 
 encapsulation dot1Q 3

• .10 is the router’s local subinterface number.
• dot1Q 3 identifies the 802.1Q VLAN tag carried on the trunk.

text 
interface GigabitEthernet0/0.3 
 encapsulation dot1Q 3

text 
interface GigabitEthernet0/0.2 
 encapsulation dot1Q 2

1. Start with the 48-bit MAC address.
2. Split it into two 24-bit halves.
3. Insert FF:FE between the halves, creating a 64-bit value.
4. Invert the U/L bit—the seventh bit from the left in the first MAC byte.

text 
MAC:       00:1A:2B:3C:4D:5E 
EUI-64:    02:1A:2B:FF:FE:3C:4D:5E

• FE80 is the prefix commonly used for an IPv6 link-local address, not part of the EUI-64 interface ID.
• The interface ID is not random.
• The MAC address is modified by inserting FF:FE and changing the U/L bit.

• Business
• People
• Governance
• Platform
• Security
• Operations

• Cloud financial management
• Portfolio and program management
• Risk management
• Data governance
• Compliance and oversight

• Application management: Controls which apps can be installed or used; it does not remove existing data after theft.
• Full-disk encryption: Protects data when the device is powered off or locked, but it may not help if the attacker has already unlocked the device.
• Containerization: Separates corporate data from personal data, but the attacker may still access the corporate container using the stolen credentials.

• Approve major information security policies
• Allocate funding and resources
• Set the organization’s risk appetite
• Ensure security supports business objectives

• Evaluating vendors is generally handled by security, procurement, or technical teams.
• Assessing risks is typically performed by security and risk-management professionals, with management accepting or prioritizing the risks.
• Monitoring regulatory adherence is usually handled by compliance, audit, or security functions.

• An Azure pay-as-you-go subscription follows an operational expenditure (OpEx) model.
• With OpEx, the organization pays for services as they are used, typically based on consumption.
• There is no need to purchase and maintain physical servers upfront.
• This contrasts with capital expenditure (CapEx), where the company makes a significant upfront investment in infrastructure, such as on-premises Hyper-V hosts.

• A Layer 2 switch checks the destination MAC address in its MAC address table (CAM table).
• If the destination MAC is unknown, the switch cannot select a specific outgoing port.
• It therefore performs unknown-unicast flooding, sending the frame out every other port in that VLAN.
• The frame is not sent back through the port where it arrived.

• Create a record-triggered Flow on Opportunity.
• Run it when the record is created or updated.
• Add entry criteria such as Probability > 50%.
• Use Create Records to create the related Sales Demo Request, populating its Opportunity lookup.

• Apex Trigger: Possible, but unnecessary custom code for a straightforward automation requirement.
• Workflow Rule: Cannot create a related custom record.
• Process Builder: Could create a record, but Flow is Salesforce’s preferred and more capable declarative automation tool.

1. Which host originated the infection

1. Which remaining hosts are infected

• Normalize casing in the data source—for example, convert all values to uppercase or lowercase.
• Add an index key to provide a unique, stable identifier for each row or value.

• 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.

Flat organisation

• Few levels of management
• A wide span of control—managers supervise many employees
• Shorter communication channels
• More employee autonomy and quicker decisions
• Fewer formal promotion levels

Tall organisation

• Many levels of management
• A narrow span of control—managers supervise relatively few employees
• A clear hierarchy and reporting structure
• More formal supervision and communication channels
• More obvious promotion and career stages

• Leaf switches provide access ports for servers, endpoints, and other devices.
• Spine switches form the fabric’s backbone.
• Every leaf connects to every spine, creating a predictable, high-bandwidth, low-latency path.

• A: Adding both a spine and leaf is unnecessary for simply adding access ports.
• B: Adding a spine does not directly provide endpoint access ports.
• D: A single connection to one spine creates a bottleneck and a single point of failure.

• A: Daily involvement is unnecessary and may not solve the availability problem.
• C: Clarifying all requirements at the start conflicts with agile’s iterative refinement.
• D: Simply reviewing based on availability leaves the problem unresolved and allows rework to continue.

• Password spraying: Tries a few common passwords against many accounts; no indication of repeated login attempts.
• Remote-access Trojan (RAT): Could install malware, but it does not explain how the attacker obtained the administrator’s credentials.
• Dictionary attack: Tries words or common passwords against an account; again, the scenario specifically highlights Telnet’s lack of encryption.

• Each Azure VM must have at least one network interface (NIC).
• A single NIC can have:

• Therefore, each of the five VMs needs only one NIC:

• The servers are powered on.
• The network is functioning.
• Devices can still reach the server network.

• ARP poisoning: Redirects or intercepts local network traffic; it usually affects communication paths rather than overwhelming a service.
• Jamming: Disrupts wireless or radio signals. It would not fit a system that remains accessible from devices on the server network.
• Kerberoasting: Attempts to crack service-account credentials from Kerberos tickets; it does not normally cause an immediate outage.

• Authentication — verifies who the user is.
• Authorization — determines what the authenticated user is allowed to access.
• Accounting — records session activity, such as login time and resource usage.

• CIA — confidentiality, integrity, and availability; core security objectives.
• ACL — access control list; rules that permit or deny traffic or access.
• PEM — Privacy Enhanced Mail, an older email security standard.

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.

• 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.

• R-squared (R²): mede quanto da variação dos valores reais é explicada pelo modelo. É mais usado em regressão, não em classificação.

• Accuracy (acurácia): mede a proporção de previsões corretas em relação ao total. É adequada para a classificação de imagens da questão.

• RMSE (Root Mean Squared Error): mede o tamanho médio dos erros entre valores previstos e reais, penalizando erros maiores. É usado principalmente em regressão.

• Learning rate (taxa de aprendizado): controla o tamanho dos ajustes feitos pelo modelo durante o treinamento. Não é uma métrica de avaliação; é um hiperparâmetro.

• B — AWS DataSync: Transfers data between storage systems, such as S3, file systems, and on-premises storage. It is not a marketplace or catalog for third-party datasets.
• C — Kinesis Data Streams and CodeCommit: CodeCommit is a source-code repository, not a third-party data provider. Kinesis is for streaming data ingestion.
• D — Kinesis Data Streams and ECR: ECR stores container images, not datasets. Kinesis does not provide access to ECR data as an external dataset source.

• Idioma: “Responda em português.”
• Tamanho: “Responda em até três frases.”
• Formato: “Use uma lista com três recomendações.”
• Objetivo: “Recomende produtos com base nas necessidades do cliente.”

• Mudar o tamanho do LLM: pode alterar capacidade e custo, mas não garante idioma ou respostas curtas.
• Aumentar a temperatura: aumenta a criatividade e a aleatoriedade; não controla diretamente o tamanho ou idioma.
• Aumentar o Top K: permite considerar mais tokens prováveis, aumentando a variedade; também não é o mecanismo principal para controlar idioma ou comprimento.

• Subject: The entity that initiates an action—here, Derrick/user account.
• Object: The resource being accessed— the file.
• Action: Reading the file.