ServiceNow CIS-VR Exam Prep
Certified Implementation Specialist - Vulnerability Response (Page 3 )

• Two-part tariff pricing: $10 per unit
• Dual pricing: $20 per unit

Two-part tariff pricing

Dual pricing

• Division X, the seller, is credited with the market price: \(\$20\)
• Division Y, the buyer, is charged the marginal cost: \(\$10\)

• Domínios personalizados.
• Armazenamento suficiente.
• Instâncias dedicadas.
• Balanceamento de carga.
• Menor custo entre os planos que atendem a tudo.

• Advanced Persistent Threat (APT): A sustained, targeted attack campaign or attacker group—not a vulnerability.
• Trojan: Malware disguised as legitimate software.
• Stealthware: A general term for malware designed to avoid detection; it does not specifically mean an unknown vulnerability.

• A: It allows for branching and merging...

• C: It allows multiple engineers to work against the same code and configuration files and manage differences and conflicts.

• B: Build automation and infrastructure provisioning are handled by CI/CD and automation tools, not by version control alone.
• D: User Stories and backlogs are managed by project-management tools.
• E: Version control stores and tracks code, but it does not itself ensure that developers write effective unit tests.

• Standardize which services users can deploy
• Apply governance and access controls
• Manage approved product versions
• Give users self-service access to authorized resources

• AWS Control Tower: Sets up and governs a multi-account AWS environment.
• AWS Cloud Map: Provides service discovery for applications.
• AWS Clean Rooms: Enables privacy-preserving collaboration on data analysis.

• AB’s own PPE: $100m
• CD’s PPE in its individual accounts: $50m
• Fair value uplift at acquisition: $40m
• Remaining useful life: 10 years
• Extra depreciation each year: $40m ÷ 10 = $4m
• Four years’ extra depreciation to 31 December 20X4: 4 × $4m = $16m
• Remaining fair value uplift: $40m - $16m = $24m

• 10 minutes have elapsed, or
• 20 MB of accounting data has accumulated

• DB1 (500 TB): Azure Data Box Heavy

• Virtual machines: Azure Migrate

• 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.

• 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.

• Training data for potential bias before model training
• Trained models for bias in predictions
• Model features to help explain how they influence predictions

• A: RAG workflows are typically built using services such as Amazon Bedrock, knowledge bases, and data sources.
• B: Monitoring model quality in production is primarily associated with SageMaker Model Monitor.
• C: Documenting model details is handled by capabilities such as SageMaker Model Cards.

• 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 ????

• 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.

• Measurement bias: Errors in how features or labels are measured, such as unreliable camera data or inconsistent labeling.
• Observer bias: A human evaluator’s subjective judgment influencing observations or labels.
• Confirmation bias: Favoring information that supports an existing belief.

• 24 cores: Available in the Business Critical provisioned-compute configurations.
• Approximately 124 GB memory: Matches the memory capacity of the relevant Business Critical hardware configuration.
• More than 50,000 IOPS: Business Critical uses local SSD storage and provides the high I/O performance required here.
• 500 GB storage: Well within the tier’s supported capacity.

• Premium: The DTU-based Premium tier does not provide the required combination of compute, memory, and I/O characteristics.
• Hyperscale: Hyperscale is primarily intended for very large databases and independent storage scaling. It is not the best match for these specific high-memory and high-IOPS requirements.

• Data owners: Decide who should have access and approve the access rules.
• Business process owners: May help define business requirements, but normally do not enforce technical permissions.
• Security steering committee: Provides governance and direction; it does not manage individual access rights.
• Security administrators: Apply and enforce the approved access controls.

• Reconnaissance: Gathering information about the target.
• Weaponization: Creating or combining a malicious payload with a delivery method.
• Delivery: Sending the payload, such as through phishing.
• Exploitation: Triggering a vulnerability or weakness to gain execution or access.

• The selling division receives a credit based on a favourable transfer price, often market price or full cost plus a profit margin.
• The receiving division is charged a lower amount, such as marginal cost or another agreed price.
• The difference is accounted for centrally by head office or a corporate adjustment.

• Create the field in the CRM on the relevant person records—typically Lead and Contact in Salesforce.
• Give the Marketo Sync User read/write access to the field.

• Namespace: The namespace associated with the code where the checkpoint was set.
• Time: When the checkpoint was captured or executed.

• Exception: Exceptions are viewed through debug logs or execution results, not as the primary Checkpoints tab information.
• Debug Statement: System.debug() output belongs in the Logs tab. A checkpoint captures program state, such as variables and their values, at a specific point in execution.

• The audience and stakeholders
• The complexity and type of requirements
• The communication method and level of detail needed
• Whether to use diagrams, models, documents, demonstrations, or slides

• B: Authority to host the presentation is not the key preparation activity.
• C: Stakeholder sign-off may occur later; presenting requirements does not always require formal approval beforehand.
• D: A scribe may be useful in a meeting, but hiring one is not a core preparation requirement for presenting.

• 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.

• A. IDS attack signatures: Detects suspicious network activity, but is not primarily designed to scan uploaded files for malware.
• C. Load balancer: Distributes traffic among servers and improves availability; it does not inspect files for threats.
• D. WAF: Protects web applications from attacks such as SQL injection and command injection, but its primary role is not malware scanning of uploaded documents.

1. Which host originated the infection
2. Whether each other host is clean or infected
3. Which firewall or host logs provide evidence of the infection’s movement

• Find the earliest infection-related event. The host associated with that event is the likely origin.
• Follow the timeline: outbound connections from that host may indicate propagation or command-and-control activity.
• A host receiving suspicious traffic is not automatically infected; look for evidence that it executed or initiated malicious activity.
• A firewall log can show traffic paths, but endpoint logs are usually needed to confirm infection.
• Mark a host clean only when the logs show no indicators of compromise or malicious activity.

• 25 — Traditional SMTP server-to-server mail delivery; often restricted and not the usual client submission port.
• 110 — POP3, used for retrieving email; normally unencrypted.
• 143 — IMAP, used for retrieving and synchronizing email; normally unencrypted.

• Sustainability
• Performance efficiency
• Reliability

• Storage usage of files stored in Microsoft Teams: SharePoint site usage report

• Number of active users per team: Microsoft Teams usage report

1. SharePoint site usage report
2. Microsoft Teams usage report

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

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

• Where to find the TiMOS runtime image
• Which configuration file to load
• The IP address and related settings for the CPM management Ethernet port

• A: User authorization is configured in the router’s security configuration, not primarily in the BOF.
• C: Hardware initialization is performed by the boot process and system software.
• D: The system date and time are configured separately, often through NTP or CLI settings.

• Record changes — a flow can start when a record is updated or otherwise changes.
• Schedules — a flow can run at a specified date/time or on a schedule.
• Record inserts — a flow can start when a new record is created.

• Subflows are reusable flow components called by another flow; they are not normally trigger types.
• Record views do not generally initiate a Flow Designer flow.

• 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.

• Act as the default gateway for devices in that VLAN
• Route traffic between different VLANs
• Provide management access to the switch

text 
interface vlan 10 
 ip address 192.168.10.1 255.255.255.0

• Sales processes: Define the available Opportunity stages for each team.
• Record types: Connect each team to its appropriate sales process and page layout.
• Page layouts: Control which fields and related sections each team sees.

• Solar market team 1
• Solar market team 2
• Installation Services team

• One sales process: Cannot provide different Opportunity stages for each team.
• One page layout: Cannot provide different field arrangements or fields by team.
• Three page layouts alone: Page layouts control fields, but not the available stages.

• 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.

• 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.

• A single summarized value, such as total annual sales
• Progress toward a defined target or goal
• Whether performance is below, near, or above the target

• Table: Displays detailed records or summarized rows, but not goal progress visually.
• Stacked Bar: Compares multiple categories and their parts.
• Donut: Shows how a total is divided among categories, not progress toward a target.

• A. Remove rows where Sales[Status] is Canceled

• E. Remove Sales[Canceled Date]

• B: Removing Sales_Date would remove information users need—the date portion.
• C: Changing Delivery_Time to Integer could alter its meaning or precision and is not necessarily safe.
• D: Splitting the date/time column creates additional columns rather than simply removing unnecessary data.

1. Initiation

1. Planning

1. Execution

1. Monitoring and controlling

1. Closing

• 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.

• terraform apply
• terraform destroy

• Matching hashes: The software is likely unchanged.
• Different hashes: The software or its contents have been modified.

• Encryption: Protects confidentiality, not primarily integrity.
• Baselines: Document expected configurations and support comparison, but hashing is more directly suited to verifying file integrity.
• Tokenization: Replaces sensitive data with tokens and is unrelated to software tampering.

1. Install a Cassandra-compatible ODBC driver.
2. Configure a data source name (DSN), if required.
3. In Power BI Desktop, select Get Data > ODBC.
4. Choose the configured DSN and connect.

• Microsoft SQL Server database: Connects to SQL Server, not Cassandra.
• OLE DB: Requires a compatible OLE DB provider; this is not the standard choice for Cassandra in Power BI.
• OData: Requires Cassandra data to be exposed through an OData service, which is not the normal direct connection method.

• Fine-tuning requires a properly formatted training dataset.
• For classification or instruction-style fine-tuning, examples are supplied in JSONL format.
• Each line represents one training example, typically containing the input prompt and the desired completion or label.
• The file must then be uploaded or made available to the Microsoft Foundry fine-tuning workflow.

• A: Prompt Flow is useful for prompt experimentation, but it is not required to start fine-tuning.
• B: You do not need to deploy the base model to an online endpoint before fine-tuning.
• C: Tracing supports observability and evaluation, but it does not prepare the fine-tuning job or dataset.

• Disable high concurrency: This changes session-sharing behavior but does not provide dedicated compute or true workload separation.
• Modify the number of executors: Adjusts resources within a Spark job; it does not isolate bronze and silver processes.
• Set the default environment: Controls libraries and runtime configuration, not compute isolation.

• 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.

• A — .gitignore: Controls Git tracking; it does not configure Copilot exclusions.
• B — copilot.ignore: This is not the standard GitHub Copilot Business exclusion mechanism.
• D — Renaming files: Adding _no_copilot has no recognized effect.

• Azure Cosmos DB is a globally distributed NoSQL database service. It stores and retrieves application data, but it does not provide the complete environment for building, testing, and deploying predictive analytics models.
• Azure Machine Learning is the appropriate service for this requirement. It supports creating experiments, training and testing models, and deploying them for predictions.
• Azure Machine Learning Studio provides the browser-based interface for these tasks.