CIMA F1 Exam Prep
Financial Reporting (Page 5 )

• Used for communication on the local link or LAN segment
• Automatically generated on IPv6-enabled interfaces
• Not routed by routers to other networks
• Commonly used by devices to communicate with their local IPv6 router
• Begins with FE80 through FEBF

• FC00::/7 — unique local unicast
• FE80::/10 — link-local unicast
• FF00::/8 — multicast
• 2000::/3 — global unicast

• Post-Incident Review (A) is the after-action step used to capture lessons learned, identify process gaps, and drive improvements across the incident response lifecycle. This directly supports process maturity and a stronger security posture.
• Incident Analysis (D) focuses on investigating root causes during/after an incident, which is important but more of a diagnostic activity than a standalone baseline improvement to maturity.
• Fast Eradication (B) and Incident Containment (C) are tactical actions aimed at stopping the incident, not on maturing the process.

• Answer: C – netstat -an

• netstat -an lists all active connections and listening ports with numeric addresses, without resolving names. This lets you spot DoS patterns such as a flood of connections to a specific port or many connections from a single or few IPs.
• The other options don’t help as directly:

• Windows: netstat -an and look for numerous ESTABLISHED connections to a service or many SYNs to a port.
• Filter by port, e.g., netstat -an | findstr :80, or on Linux: ss -tunap | grep ':80'.

• Netstat provides a snapshot. DoS detection often benefits from continuous monitoring, flow data, and IDS/IPS logs.

• A — conformant: Incorrect because one explicit requirement is violated.
• B — consistent: “Consistent” is not sufficient where the implementation contradicts a mandatory specification. The RPC mechanism is covered by the architecture, and the implementation differs from it.
• C — consistent: Incorrect reasoning: the RPC mechanism does have a defined architectural requirement, so conformance must be assessed.
• D — non-conformant: Correct because the implementation fails to follow the specified RPC/threading requirement.

• Why: Crisis management relies on established, repeatable procedures for responding to an incident (activation of the crisis team, escalation paths, communications, containment actions). This ensures a coordinated, timely, and auditable response.

• Why not the others:

• A separate scope using a /32 subnet: A /32 identifies one host, but it is not a practical DHCP scope for this purpose.
• A static IP within the DHCP range: This can cause an IP address conflict if DHCP assigns that address to another device.
• SLAAC: Used for automatic IPv6 address configuration, not for assigning a predictable IPv4 address through DHCP.

• 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.

• Answer: No.

• Why:

• If you need such an assessment while controlling costs, you’d generally pursue a paid MCS engagement or another option outside of the basic Premier entitlement.

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.

• IaaS: You manage the virtual machine’s operating system, configuration, applications, and data. Azure manages the physical infrastructure and virtualization platform.
• PaaS: You deploy applications without managing the underlying operating system or servers.
• SaaS: You consume a complete application managed by the provider, such as Microsoft 365.

• Drops packets when traffic exceeds a certain bitrate: This describes traffic policing, not shaping.
• Fragments large packets and queues them: Shaping does not fragment packets as its primary congestion-control action.
• Drops packets randomly from lower-priority queues: Packet dropping may occur if a shaping queue becomes full, but it is not the defining behavior.

• Shaping: buffers and delays excess traffic.
• Policing: drops or marks traffic that exceeds the configured rate.

• App Tag: a label that reflects the app’s enterprise readiness based on its Cloud Confidence Index (CCI) rating. It lets you quickly group apps (e.g., Poor, Average, Good) for policy decisions.
• App Score: a numeric value representing the CCI score. It provides a precise threshold you can use to enforce policies (e.g., block apps with Score below 50).

• You can create policies that block or restrict apps with a Poor App Tag or with an App Score under a chosen threshold.
• These two aspects let you filter cloud apps by CCI ratings during policy evaluation.

• CCL isn’t described as a real-time policy facet in this scenario.
• GDPR Readiness is a separate consideration and not the two CCI aspects used for real-time protection policy in this context.

• Help the team identify the causes of delays.
• Encourage continuous improvement through retrospectives.
• Support the team in changing its process, tools, or collaboration methods.
• Help remove impediments that the team cannot resolve independently.

• A: An impediment log may help, but simply maintaining it does not ensure the impediments are resolved.
• B: Directing the team to solutions conflicts with agile self-management.
• C: Adding impediments to the product backlog could delay their resolution and treats them like product features.

• Correct answer: C) After installing ES on the search head(s) and running the distributed configuration management tool.

• ES requires the Splunk_TA_ForIndexes.spl add-on on indexers to apply index-time configurations. It should be deployed via the distributed configuration management (DCM) flow after ES is installed on the search heads, so the indexers receive the proper configuration in a controlled, versioned bundle.

• A) Deploying when adding apps to the deployment server isn’t the ES-specific order; it bypasses the ES-instantiated workflow.
• B) Installing Splunk_TA_ForIndexes.spl first isn’t the recommended order; ES needs to be installed on the search heads first.
• D) It isn’t limited to indexer cluster sites or cluster master commands; the standard flow uses DCM to push the TA to indexers in general.

• Goal: Identify the host that originated the infection, then label each remaining host as infected or clean based on log evidence.

• Logs to review (across hosts and firewall):

• How to identify the origin:

• How to classify other hosts:

• Quick tip: use the Reset All option if you want to re-run the scenario and practice again.

• Amazon S3 — Object storage, not a database.
• Amazon DynamoDB — Fully managed NoSQL key-value and document database.
• Amazon Redshift — Managed data warehouse designed for analytics, not primarily transactional MySQL workloads.

• Customers access the portal without needing a full Dynamics 365 license.
• They submit case information through portal forms.
• The submitted data is stored in Dataverse tables, such as the Case table.
• Security is controlled using web roles and table permissions, so customers can access only appropriate records.

• Dynamics 365 Connector — connects apps to Dynamics 365 data but is not the portal’s underlying data platform.
• Microsoft SharePoint — useful for documents and collaboration, not the standard case-management data source for portals.
• Microsoft Azure Storage — stores files or other data, but is not the native portal business-data platform.

• The explanation states that Traffic Analytics can be enabled by a user with one of these subscription-level roles:

• Question 34 — Network Contributor: Yes
• Question 35 — Owner: Yes
• Question 36 — Reader: Yes, according to the stated explanation and documentation

• The two correct options are:

• The two incorrect options:

• Correct answer: A. Inbound data transfer from the internet

• Why: AWS does not charge for data transferred into AWS from the internet. Inbound data transfer is free, regardless of the amount (in this case, 2 TB). The other options involve data leaving AWS or moving between AWS regions/AZs, which incur costs:

• Permanent table (E): Correct. A dropped permanent table can be restored with UNDROP TABLE during its Time Travel retention period. Permanent tables also have Fail-safe protection.
• Transient table: It can also generally be restored during its shorter Time Travel period, although it has no Fail-safe. Therefore, excluding it makes the question questionable.
• Temporary table: Usually cannot be recovered after it is dropped; its lifecycle is limited to the session.
• Materialized view (D): The answer key treats it as recoverable, but recovery behavior depends on the specific Snowflake object/version capabilities. It should not be confused with an ordinary view.

• Hardware and infrastructure
• System software
• Networks and communications
• Technology platforms and services

• Business Architecture: Defines business strategy, organization, functions, and processes.
• Data Architecture: Defines the structure and management of enterprise data.
• Application Architecture: Describes application systems and how they interact to support business and data processing.

• A: True. You can change the size of a Virtual Warehouse after creation (via UI or ALTER WAREHOUSE).

• B: True. A warehouse can be resized while it’s running; the resize will take effect without needing to stop queries.

• C: True. A warehouse can be configured to suspend after a period of inactivity (AUTO_SUSPEND).

• D: True. A warehouse can be configured to auto-resume when new queries are submitted (AUTO_RESUME).

• Reusing features across different models and teams
• Consistent feature definitions
• Managing feature versions and metadata
• Using features for both training and inference

• SageMaker Data Wrangler: Prepares and transforms data; it is not primarily a shared feature repository.
• SageMaker Clarify: Helps detect bias and explain model predictions.
• SageMaker Model Cards: Documents models, including intended use, risks, and evaluation results.

• 6-phone boxes: 6x
• 8-phone boxes: 8x

• Basic: Self-help only; no technical support or design assessment.
• Developer/Standard: Technical support, but generally not the full proactive architecture guidance required here.
• Professional Direct: Includes proactive guidance and architecture recommendations.
• Premier: Also supports this, but is not the minimum-cost option.

• AWS IoT Greengrass supports local ML inference using models trained in Amazon SageMaker.
• The model and inference code run on the factory’s local server, so processing continues even when internet connectivity is unavailable.
• A Greengrass component can:

• This provides low latency and avoids sending images to AWS for every inference.

• A: Uses AWS-hosted services and therefore depends on internet connectivity. It would fail during an outage.
• C: Snowball Edge is unnecessary for this use case and adds deployment complexity. A local Greengrass server is the intended edge-inference solution.
• D: Amazon Monitron is designed for monitoring industrial equipment health, not analyzing camera images with a custom SageMaker model.

• A) configure matching hold and delay timers

• B) configure matching key-strings

• C) configure matching priority values

• D) configure unique virtual IP addresses

• Correct options: C and D.

• The AWS Cloud Adoption Framework (CAF) security perspective focuses on capabilities to protect information and manage security risk.
• Observability (A) is primarily an operations/monitoring capability, not a core security capability under CAF.
• Incident and problem management (B) is IT service management/operations, not specifically a CAF security capability.
• Incident response (C) is a security-focused capability: detecting, containing, and recovering from security incidents.
• Infrastructure protection (D) involves applying security controls to protect the underlying infrastructure, which fits the security perspective.

• Wiping securely overwrites the drive so the original data cannot reasonably be recovered. It is generally less expensive than physically destroying the device.
• Recycling could expose the data if the drive is not securely erased first.
• Shredding physically destroys the drive and is effective, but usually more costly and prevents reuse.
• Deletion only removes file references; it is not a secure sanitization method.

• Correct answer: D) Amazon Aurora Serverless

• Aurora Serverless is serverless, so compute capacity scales automatically and can pause during idle periods. This minimizes ongoing administration and you pay only for actual usage, which is ideal for infrequent workloads.
• PostgreSQL on EC2 requires full OS and DB administration.
• RDS for PostgreSQL is managed but still involves provisioning capacity and some maintenance tasks.
• Aurora PostgreSQL (non-Serverless) is managed but requires you to manage capacity, though with some automation; it’s not as hands-off as Serverless for intermittent usage.

• Multi-factor authentication
• A secure password change for users whose credentials may be compromised

• Startup scripts run at computer startup, before any user logs on, making them ideal for machine-wide configuration on each new VM.
• They execute under the Local System account, which is appropriate for initial setup tasks.
• Linking a GPO to the OU ensures every new VM in that domain automatically receives the configuration—great for scalability.

• A) SetupComplete.cmd runs only once, right after Windows Setup, not on every boot, so it isn’t ideal for provisioning multiple VMs consistently.
• B) Logon scripts run per user, not per machine, so they aren’t reliable for initial VM configuration before a user signs in.
• D) Placing scripts in a VHD doesn’t automatically execute them.

• Correct answer: Power BI dataset

• The scenario says the data model already contains several measures and you want to create a report from the existing data with minimal development. Reusing a published Power BI dataset lets you inherit the existing measures and data model, so you don’t have to recreate them.
• How to do it: In Power BI Desktop, use the connector Power BI datasets (Get Data > Power BI datasets) and connect to the existing dataset, then build visuals using the pre-defined measures.
• Why the other options are less suitable:

• Correct choices: A and D.

• Why not B, C, or E?

• 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.

python 
def add_integers(a, b): 
    return a + b

• Uses def to define a function.
• Accepts two parameters, a and b.
• Uses return to send their sum back to the caller.
• Uses indentation to define the function body.

python 
result = add_integers(3, 4) 
result is 7

• Correct answer: B — From the code repository, modify Startup.cs (in ASP.NET Core you configure the Application Insights SDK in code, not with ApplicationInsights.config).

• Why the other options aren’t correct:

• How to implement fixed-rate sampling (ASP.NET Core):

var builder = WebApplication.CreateBuilder(args); 


    builder.Services.Configure<TelemetryConfiguration>(telemetryConfiguration => 
    { 
        var builder = telemetryConfiguration.DefaultTelemetrySink.TelemetryProcessorChainBuilder; 
        double fixedSamplingPercentage = 10; // 10% sampling 
        builder.UseSampling(fixedSamplingPercentage); 
    }); 


    builder.Services.AddApplicationInsightsTelemetry(new ApplicationInsightsServiceOptions 
    { 
        EnableAdaptiveSampling = false 
    }); 


    var app = builder.Build();

• Drop violating frames
• Log or alert on the violation
• Shut down or restrict the port

• Load balancer: Distributes application traffic; it does not control switch MAC learning.
• IPS: May detect some network attacks but is not the primary control for switch MAC-table exhaustion.
• NGFW: Protects traffic crossing network boundaries, while MAC flooding occurs at the switching/LAN layer.

• Primary and core nodes: Use On-Demand Instances because the workload is business-critical. These nodes manage the cluster and store/process HDFS data.
• Task nodes: Use Spot Instances in an instance fleet. Task nodes are suitable for interruption because they do not hold essential cluster data and can be replaced or diversified across instance types.
• Terminate the entire cluster after processing: The job runs only about six hours each morning, and EMRFS stores data in Amazon S3. Keeping the cluster running for the rest of the day would waste money.

• A: Using Spot for primary and core nodes risks interruption of the critical cluster.
• C: All On-Demand is reliable but unnecessarily expensive; terminating the cluster helps, but Spot task nodes provide greater savings.
• D: Leaving primary and core nodes running after the task finishes continues to incur costs. Savings Plans also are less appropriate for this intermittent workload.

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

• Program and project management
• Risk management
• Cloud financial management
• Data governance
• Portfolio management

• Sustainability
• Performance efficiency
• Reliability

• Which Security policy matches
• Which NAT rule/translation is selected
• Which PBF rule applies
• Which route is used

text 
test security-policy-match ... 
test nat-policy-match ... 
test pbf-policy-match ... 
test routing fib-lookup ...

• In Microsoft Teams Phone System, a single Auto Attendant can handle multiple time-based greetings by using separate schedules for office hours, after hours, weekends, and holidays.
• You can configure one Auto Attendant with four distinct greetings mapped to:

• Open the Teams admin center > Voice > Auto attendants, edit or create an Auto Attendant.
• Under Time-based routing, define four rules:

• Create a Holiday schedule with the relevant dates (e.g., Easter, Christmas) and assign the Holiday greeting.
• Save the configuration.

• If your environment cannot separate weekend from after-hours within a single Auto Attendant, you might technically need more than one Auto Attendant.

Why

cmd 
PowerShell.exe -ExecutionPolicy Bypass -File C:\Scripts\ConfigureVM.ps1

Why the other options are less suitable

• GPO logon script: Runs only when a user logs on and may not run during initial VM provisioning.
• GPO startup script: Can work, but requires the VM to be joined to the domain and the policy to be applied. It is also normally evaluated at each startup.
• Place scripts in a VHD: Merely placing scripts on a disk does not cause them to execute.

• Port 515: LPD/LPR line-printer service
• Port 631: IPP — Internet Printing Protocol
• Port 9100: JetDirect/RAW printing, commonly used by network printers

• Linux machine: Linux could run these services, but the three printer-specific ports strongly indicate a printer.
• Router: Routers may use Telnet and HTTP, but normally would not expose ports 515, 631, and 9100 together.
• Windows machine: Windows can share printers, but this particular service combination is more characteristic of a network printer’s embedded operating system.

• What the scenario asks: You have a Power BI semantic model that pulls from multiple sources (Azure SQL Database and SharePoint Online), must support a single dataset for three reports, keep data current (daily refresh by 7 AM PT), and apply RLS to limit sales data by region. You need to choose a storage mode for the tables.

• Correct choice: Dual storage mode.

• Why Dual fits:

• Key concepts:

• The correct AAA mapping (per Cisco objectives) is:

• Why the given options aren’t fully correct:

• Quick takeaway: when you configure AAA, you should conceptually map them as:

• Example commands (to reinforce concepts):

• L2TP uses UDP port 1701 for the L2TP control channel.
• The destination port is 1701; the source port is a dynamically chosen ephemeral port on the client (not 1701).
• Therefore the statement that both source and destination ports are 1710 is incorrect (and 1710 is not the standard L2TP port).

• The destination port should be 1701, not 1710.
• The source port should be an ephemeral port chosen by the client, not 1701.

• S3 Lifecycle rules automate actions such as transitioning objects to different storage classes or deleting old objects.
• S3 bucket policies control access permissions; they do not preserve earlier object versions.
• S3 server-side encryption protects data confidentiality by encrypting objects at rest, but it does not prevent deletion or overwriting.

• Accidental deletion or overwriting ? S3 Versioning
• Unauthorized access ? bucket policies and IAM
• Data encryption ? server-side encryption