Cisco 820-605 Exam Prep
Cisco Customer Success Manager (CSM) (Page 12 )

• Threat perspective: Focuses on possible attacks, but may seem technical or hypothetical.
• Compliance perspective: Can motivate action, but compliance alone does not demonstrate the broader business value of governance.
• Policy perspective: Policies are important, but they are a means of implementing governance, not its primary business justification.

• 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.

• Issuer: Identifies the party issuing a SAML message, commonly the IdP in the SAML assertion. It is not the Salesforce setting used to distinguish Salesforce from other service providers.
• Identity Provider Login URL: Specifies where Salesforce sends users for authentication; it does not identify Salesforce.
• SAML Identity Location: Specifies where the user identity is found in the SAML assertion, such as the subject or an attribute.

• 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.

• ARP poisoning: Redirects or intercepts local network traffic; it would more likely affect communication paths or cause man-in-the-middle behavior.
• Jamming: Interferes with wireless signals. The scenario does not indicate a wireless outage.
• Kerberoasting: Attempts to obtain service-account password hashes from Kerberos; it is a credential attack, not typically a direct service outage.

• B. Data loss prevention (DLP): Helps prevent sensitive data from being copied, emailed, or exfiltrated. It is not the primary control for protecting a stolen laptop’s stored data.
• C. Operating system hardening: Reduces vulnerabilities by disabling unnecessary services and applying secure settings, but it does not necessarily protect the files if the disk is accessed directly.
• D. Boot security: Helps ensure the device starts only through trusted software or approved processes. It supports platform integrity but does not itself encrypt stored files.

• 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.

• SOW
• SLA
• MOA
• MOU

• 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.

• The VM keeps its configuration, disks, IP settings, and associated resources.
• The operation may cause downtime.
• You cannot guarantee that it will move specifically to Host2; Azure selects the new host.
• Update management is for update configuration, not host relocation.
• Moving to another subscription does not move the VM to a different physical host.
• Usage location is unrelated to VM placement.

• 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.

• 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.

• 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.

• Disable default accounts: Default or unused accounts may have predictable names or credentials and can be abused by attackers. They should be disabled, removed, or secured with strong credentials where necessary.
• Remove unnecessary services: Every running service can contain vulnerabilities or provide an entry point. Removing services the server does not need reduces exposure.

• Add the server to the asset inventory: Important for asset management, but it does not directly harden the system.
• Document default passwords: Default passwords should be changed or disabled—not recorded for continued use.
• Send logs to the SIEM: Supports monitoring and detection, rather than directly reducing the attack surface.
• Join the corporate domain: A deployment/configuration decision, not inherently a hardening measure.

• SharePoint search: Finds documents based on search terms, but it does not reliably identify every 32-character account number for DLP enforcement.
• A hunting query in Microsoft 365 Defender: Used for security investigations, not for defining sensitive content in a DLP policy.
• Azure Information Protection: Uses classification and labeling; it does not automatically identify this specific account-number pattern unless configured with a matching sensitive information type.
• RegEx pattern matching: Best suited for structured identifiers with a known format, such as account numbers, employee IDs, or policy numbers.

• 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.

• A: Person Accounts cannot be merged directly with standard Contact records.
• C: There is no Account Setup option that automatically merges Person Account duplicates.
• D: Matching rules and duplicate rules can help identify or prevent duplicates, but they do not automatically merge Person Accounts. Also, relationship considerations do not change the basic merge capability.

• 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.

• Matching hashes suggest the file has not changed.
• Different hashes indicate that the file was modified, whether authorized or unauthorized.

• Backup: Helps recover the previous version but does not identify or stop unauthorized changes.
• File labels: Classify or mark files; they do not verify integrity.
• Security audit: May discover weaknesses or improper changes, but is periodic and not a direct technical integrity control.

• You normally do not create a new sensitive information type for credit card numbers. Microsoft Purview already provides a built-in Credit Card Number sensitive information type.
• The required sequence should generally be:

kusto 
Event | where EventType == "error"

• == is the KQL equality operator.
• -eq is a PowerShell operator, not KQL.
• is is not the correct equality operator in this context.

text 
Event | where EventType –eq "error"

• Event | search "error" — valid, broad search.
• search in (Event) "error" — valid, broad search.
• Event | where EventType == "error" — valid, targeted filter.

• Compensating control: The server is end-of-life, so it may no longer receive security patches or support. Placing it on a restricted VLAN provides an alternative layer of protection by reducing who can access it and limiting its exposure.
• Technical control: VLAN segmentation and access control lists (ACLs) are technology-based mechanisms that enforce network access restrictions automatically.

• Managerial: Policies, procedures, and governance—not network configuration.
• Physical: Locks, guards, or barriers.
• Corrective: Restores systems after an incident.
• Detective: Identifies suspicious activity rather than restricting access.
• Deterrent: Discourages behavior but does not enforce access rules.

• A — Correct: Flow Builder is declarative and visual, so administrators and other non-developers can participate in designing and improving business processes without writing Apex.
• D — Correct: Flow Builder provides visual debugging tools, allowing an admin to test paths, inspect variable values, and identify where a specific business case fails.
• E — Correct: A flow’s visual structure documents the logic and makes later maintenance easier than reading and updating custom Apex code.

• B — Incorrect: Flow debugging does not attach a debugger to live customer sessions. The admin uses Flow Builder’s debug functionality with test inputs; this is not live-session debugging and should not be used to monitor real customer transactions.

• staff use the new system;
• transactions and reports are checked;
• problems are corrected;
• feedback is collected.

• Phased changeover: different parts or functions are introduced in stages, often according to a planned sequence.
• Pilot changeover: one representative department, branch or group acts as a test site before wider implementation.
• Parallel changeover: old and new systems operate at the same time.
• Direct changeover: the old system is stopped and the new one starts immediately.

• 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.

• Secret scope: A named container that groups related secrets and defines access permissions. Example: finance-prod.
• Secret key: The name of an individual secret stored inside that scope. Example: db-password.

text 
Scope: finance-prod 
  Key: db-username 
  Key: db-password

python 
dbutils.secrets.get( 
    scope="finance-prod", 
    key="db-password" 
)

• Accept: Acknowledge the risk and choose not to take additional action.
• Transfer: Shift the risk or its financial impact to another party, such as through insurance or outsourcing.
• Mitigate: Reduce the likelihood or impact of the risk, such as by implementing security controls.
• Avoid: Eliminate the activity or condition that creates the risk.

• 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.

• Guiding principles
• Governance
• Service value chain
• Practices
• Continual improvement

• Guiding principles: Recommendations that guide decisions and actions; they do not describe the entire system.
• Four dimensions: Perspectives used to ensure a balanced approach to service management.
• Service relationship: Describes cooperation between a service provider and service consumer, rather than the whole value-creation system.

• 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.

yaml 
clusterIP: None

• CronJob: Runs Jobs on a schedule and normally does not need stable networking.
• Deployment: Manages interchangeable, stateless replicas and usually uses a regular Service.
• DaemonSet: Runs a Pod on selected nodes but does not inherently require stable Pod identities.

• Snapshot: Captures a point-in-time state for rollback. It is not an independent running VM and does not protect against failure of the underlying host or storage.
• Convert to dynamic disks: Changes disk allocation behavior; it does not provide redundancy or high availability.
• P2V: Converts a physical machine into a virtual machine. That is a migration process, not an availability solution.

• 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.

• Store privileged credentials securely
• Grant the consultant only the access needed
• Provide temporary or time-limited access
• Rotate passwords automatically
• Record or monitor administrator sessions

• TACACS+: Centralizes authentication and authorization, commonly for network devices, but does not primarily provide password vaulting and privileged-session control.
• SAML: Enables web-based federation and single sign-on, not privileged credential management.
• SSO platform: Reduces the number of passwords users need, but does not necessarily protect administrative credentials or control privileged sessions.
• Role-based access control (RBAC): Assigns permissions based on job roles, but does not by itself prevent password sharing or securely broker administrator access.

• B — Single customer login across properties: Customer 360 Identity provides centralized identity services, allowing an organization to recognize a customer across multiple digital properties and applications. This helps UC understand authenticated activity as part of a broader customer identity.

• C — Multi-brand support: Customer 360 Identity can support multiple brands and user experiences. Identity services can remain centralized while correlating a customer’s activity across different corporate brands or channels.

• A: Customer 360 Identity does not automatically populate all data into Customer 360 Data Manager and Customer 360 Audiences. Integration and data configuration are still required.
• D: Tracking anonymous activity and linking it after sign-up may be possible through broader customer-data and tracking implementations, but it is not the primary Customer 360 Identity benefit tested here. Identity focuses mainly on authentication, registration, and cross-property identity correlation.

• Filtering or reshaping columns
• Joining with an analysis-specific dataset
• Creating calculated fields
• Applying business logic for a particular project

• Data blending: Combining different data sources, not specifically the final processing step.
• Data enhancement: A broad term for enriching data.
• Data testing: Checking data quality or pipeline correctness.
• Last-mile ETL: The precise term for additional transformations performed after the main pipeline, often directly before analytics or reporting.

• 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.

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

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

• Aggregation happens once, during the scheduled job.
• Dashboard users query a relatively small, precomputed table.
• Repeated users do not trigger expensive aggregations against the detailed sales table.
• Overwriting is appropriate because the summary is rebuilt for the reporting period.

• B: Structured Streaming is unnecessary for data that only needs daily refreshes and adds operational/compute overhead.
• C: A view recomputes the aggregation at query time, increasing latency and query cost.
• D: Delta caching may improve reads but does not replace the need to materialize the expensive aggregation, and cache availability is not the main design guarantee.

• 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 and usually does not provide dedicated file-upload malware scanning. It is generally detective rather than preventive.
• C. Load balancer: Distributes traffic among servers and improves availability; it does not inspect documents for malware.
• D. WAF: Helps block web-application attacks such as SQL injection, command injection, and XSS. Although a WAF may inspect upload requests, malware detection in PDF files is more directly addressed by antivirus or content-scanning functionality.

• A. Microsoft 365 group with Assigned membership
• C. Microsoft 365 group with Dynamic User membership

Why?

• Assigned membership: You explicitly add User1, User2, and User3.
• Dynamic User membership: Membership is automatically determined by a rule based on user attributes.

Why the other options are incorrect

• B and D: Security groups do not support the Microsoft 365 group expiration policy.
• E: Dynamic Device groups are intended for devices, not these users, and are also security groups.

• 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.

• Date: 2018-12-31
• Time: 08:59

• B: The original value contains the text at, so it cannot be converted directly to a date.
• A: The last characters contain the time, not the date.
• D: Extracting the first 11 characters can leave an unwanted space and does not properly separate the time component.

• Identity provider (IdP): Authenticates users and asserts their identity.
• Service provider (SP): The application being accessed—in this case, Salesforce/the employee portal.
• Identity store: A directory that stores user identities, such as Active Directory.
• Authentication store: A system used to validate credentials.

• 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.

• A valid input returns the expected result
• An invalid input raises an error
• Boundary values are handled correctly

• B: Copilot may help generate tests, but it does not automatically write all necessary tests.
• C: Writing the implementation does not verify that it works correctly.
• D: Copilot can suggest test commands or test code, but the developer or development environment must execute and validate the tests.

• A: Allow SAN certificates — SANs are used to identify valid hostnames in a certificate. They do not bypass trust validation.
• C: Open the secure LDAP port — A blocked port would normally cause a timeout or connection-refused error, not certificate errors.
• D: Increase the TLS version on the RA — The issue concerns certificate trust, not the organization’s registration authority.

• 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.