GARP 2016-FRR Exam Prep
Financial Risk and Regulation (FRR) Series (Page 6 )

• Manage multiple organizations from one hierarchy.
• Enterprise-wide policies, including repository visibility, forking, and GitHub Copilot policies.
• Centralized identity and access management, such as SAML SSO, SCIM provisioning, and—where applicable—Enterprise Managed Users.
• Centralized billing and licensing, including organization and Copilot seat management.
• Enterprise audit log, which aggregates activity across organizations.
• Security and compliance oversight, such as organization security visibility and enterprise-wide controls.
• Enterprise support and account management features, depending on the plan.

• Organization: manages its own repositories, teams, members, and local policies.
• Enterprise: governs multiple organizations and can enforce policies across them.

• Prevent connections to malware command-and-control servers
• Identify infected systems making those DNS requests
• Collect information for incident response

• A: Attackers do not normally use sinkholes to map a company’s domain structure.
• B: Redirecting employees from legitimate sites to attacker-owned sites describes malicious DNS manipulation, not a defensive sinkhole.
• D: Attracting attackers away from real resources is more closely associated with a honeypot or deception system.

• 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.

• 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.

• 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.

• Accept: Acknowledging the risk without taking additional action.
• Mitigate: Reducing the likelihood or impact through controls, such as patching or employee training.
• Avoid: Eliminating the activity or condition that creates the risk.
• Transfer: Shifting the consequences—usually financial—to another party, such as an insurer.

• 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

cmd 
powershell.exe -ExecutionPolicy Bypass -File C:\Scripts\Configure-VM.ps1

• GPO logon script: Runs only when a user logs on, so configuration may be delayed and is user-dependent.
• GPO startup script: Can work, but requires the VMs to be domain-joined and introduces GPO dependency. It is not specifically tied to Windows deployment.
• Place scripts in a VHD: Merely makes the files available; it does not execute them.

• Input feature distributions differ from training data ? Analyze dataset drift metrics

• Model accuracy drops without code changes ? Analyze dataset drift metrics

• Endpoint latency increases under load ? Investigate scaling and infrastructure metrics

• SOW
• SLA
• MOA
• MOU

• 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.

• Premium file shares: contoso104 only
• Blob access tiers: contoso101, contoso102, and contoso103

• Premium Azure Files shares require a storage account with the FileStorage account kind. This is a specialized account type and is not used for blob storage.
• Blob access tiers such as Hot, Cool, and—where supported—Archive apply to blob-capable accounts, such as General-purpose v2 or BlobStorage accounts shown in the exhibit.
• contoso104 is therefore excluded from the blob-tier selection because it is the premium Files account.

• Forecasting lets sales leaders predict revenue for upcoming fiscal periods, compare forecasts with targets, and review performance by salesperson or team.
• Opportunity Stages help determine the likelihood that opportunities will close. Each stage can have a probability, which contributes to forecast calculations.

• Sales Quotes: Used to present pricing or product proposals to customers; they do not provide revenue forecasting.
• Opportunity List View: Helps users filter and view opportunities, but it is not the forecasting tool.

• VM CPU, memory, disk, and network usage
• Storage transactions and latency
• App Service response time
• Database DTU or CPU utilization

• Azure Traffic Analytics analyzes network traffic flows and security patterns; it is not the general infrastructure metrics tool.
• Azure Activity Log records subscription-level control-plane operations, such as resource creation, deletion, or configuration changes.
• Azure Advisor provides recommendations about cost, security, reliability, performance, and operational excellence, but it is not the primary tool for investigating live metrics.

• Customer contains one row per customer and the customer’s Address ID.
• Address contains one row per address and the corresponding location details.

1. Select the Customer query.
2. Choose Merge Queries.
3. Match Customer[Address ID] with Address[Address ID].
4. Use a Left outer join so every customer is retained.
5. Expand the merged Address column and select City, State/Region, and Country.

• Append adds rows vertically and is used for tables with the same structure.
• Group By summarizes rows rather than adding related columns.
• Transpose switches rows and columns and does not establish a relationship.

• A — Can help keep costs down and improve quality: The provider may have specialist expertise, efficient systems and economies of scale.
• B — There is a known fee if agreed in advance: A fixed or agreed fee can make costs more predictable and support budgeting.
• C — Allows management to focus on core operations and issues: Senior managers spend less time supervising routine finance processes and more time on strategic matters.

• Increased control: Control may decrease because the activity is performed externally.
• Increased independence: The organisation becomes dependent on the supplier.
• Increased understanding of the outsourcing business: The internal organisation usually has greater business knowledge; the provider may initially lack it.
• Increased confidentiality: Sharing financial information externally may create confidentiality risks.
• Internal expertise improved: Outsourcing can reduce opportunities to develop internal finance skills.

• 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. Configure prompt modifications to enforce tone, disclaimers, and refusal behavior at the system level.

• D. Configure Power Platform DLP policies to restrict unauthorized data connectors.

• B: Manual topic-by-topic disclaimer edits are specifically discouraged.
• C: Channel settings do not replace agent-level Responsible AI controls.
• E: Publishing before enabling safety filters violates the stated deployment sequence. Responsible AI filters should be enabled before publication, not afterward.

• Entradas grandes, de até aproximadamente 1 GB.
• Processamentos demorados, que podem levar até cerca de 1 hora.
• O cliente envia a solicitação e consulta o resultado depois, sem precisar manter uma conexão aberta durante todo o processamento.

• Real-time inference: indicada para respostas imediatas, com entradas menores e processamento rápido.
• Serverless inference: adequada para cargas variáveis e solicitações menores; não é ideal para processamento longo e arquivos grandes.
• Batch transform: processa grandes volumes em lote, mas não atende à necessidade de respostas próximas do tempo real.

• Who performed the action
• What action occurred
• When it occurred
• Where it originated
• Whether it succeeded or failed

• Investigating suspicious activity: Important, but investigation depends on having adequate audit data first.
• Storage allocation: Necessary for retention, but storage does not help if the records lack meaningful details.
• Actions after audit failure: Part of operational planning, not the primary assessment of the application’s audit capability.

• Incidents & alerts — see how the phishing activity was detected, correlated, and investigated.
• Threat Explorer — search for the malicious messages, recipients, URLs, attachments, and campaign activity.
• Email and collaboration reports — assess how many users or messages were affected.
• Remediation details — verify whether messages were quarantined, removed, or otherwise contained.

• Microsoft 365 admin center — general tenant administration.
• Microsoft Entra admin center — identity and access management.
• Exchange admin center — mail-flow and Exchange configuration, rather than full phishing-incident investigation.

• A limited lifetime
• Permissions defined by an IAM role or policy
• The ability to access AWS APIs without using long-term IAM user credentials

• Amazon API Gateway — Builds and manages APIs; it does not generally issue AWS credentials for applications.
• IAM users — Usually use long-term credentials, which are less suitable for applications.
• IAM instance profiles — Provide temporary role credentials to applications running on EC2 instances, but are specifically tied to EC2. The broader requirement described is best met by AWS STS.

Simple explanation

• The Azure VPN gateway to connect to
• Authentication settings
• Routes for networks that the client can access

• Issuer: Identifies the party issuing a SAML message—usually the identity provider in the assertion. It is not the Salesforce-specific identifier the architect should provide for differentiating Salesforce.
• Identity Provider Login URL: The endpoint where users are sent to authenticate.
• SAML identity location: Determines where the user identity is found in the SAML assertion, such as the subject or an attribute.

• Honeypots: Decoy systems or services designed to attract attackers. Legitimate users should not access them, so activity on a honeypot is a strong indicator of unauthorized activity. Security teams can also observe attacker behavior.

• DNS sinkhole: Redirects requests for known malicious domains to a controlled internal server or blocks them. If an infected workstation attempts to contact command-and-control infrastructure, the sinkhole records the request and helps identify the compromised device.

• Tokenization: Protects sensitive data by replacing it with tokens.
• CI/CD: Automates software development and deployment.
• Threat modeling: Identifies potential risks before or during system design.
• Data obfuscation: Makes data harder to understand, but does not detect intruders.

• 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.

• 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.

• Answer: No

• Why: Using several Azure AD directories (tenants) would create separate identity stores for each division, which significantly increases administrative overhead. You’d need cross-tenant access management, separate governance, and duplicated admin efforts, which goes against the goal of minimizing administrative work.

• How to meet the goal instead:

• Increase/decrease the number of epochs: Changes how long training runs, but does not reuse a pre-trained model.
• Unsupervised learning: Trains from unlabeled data and does not specifically address adapting an existing model.

• Geo-redundant storage (GRS) replicates data to a secondary Azure region, but the secondary copy is normally unavailable for read access.
• RA-GRS provides geo-replication and read-only access to the secondary region, satisfying all requirements.
• Zone-redundant storage (ZRS) replicates data across availability zones within the same Azure region, not separate geographic regions.
• Locally redundant storage (LRS) keeps copies within a single datacenter or region and does not provide geographic resiliency.

• netstat: Shows local network connections and listening ports, but not which WAN path carries the traffic.
• nslookup: Resolves domain names to IP addresses.
• ping: Tests reachability and latency but does not show the route.

• Context: You’re configuring a Windows Autopilot deployment profile (Profile1) for Windows 11 devices. The hotspot asks you to pick the correct behavior for two statements based on the profile’s settings.

• Box 1: “can modify the desktop settings only for themselves”

• Box 2: “Cortana settings” with options like computer name, keyboard layout, etc.

• Planning – identifying the need, objectives, scope and resources.
• Analysis – understanding business requirements and current problems.
• Design/development – determining how the system will work.
• Implementation – installing the system and putting it into operation.

1. Which host originated the infection

1. Which remaining hosts are infected

• The legacy system creates a signed JWT assertion.
• Salesforce validates the assertion using a certificate configured on a Connected App.
• Salesforce issues an access token for the integration user.
• No refresh token is required; the system can request a new access token when needed.

• Web Server Flow: normally uses a client secret and authorization/refresh tokens.
• Username-Password Flow: requires storing Salesforce credentials and is discouraged for integrations where stronger options are available.
• User Agent Flow: intended for user-interactive applications, not unattended server-to-server processing.

• B — Prompts and suggestions retained for 28 days
• C — User engagement data kept for two years

• The key distinction is between content data—your prompts, code context, and generated suggestions—and engagement data, such as usage activity.
• Do not confuse retention with training: enterprise Copilot data is generally not used to train GitHub’s models without appropriate authorization.
• For a current exam, verify the policy version cited by the exam provider. The key’s C is likely correct, but B should be treated cautiously and may no longer reflect the current policy.

• Short answer: The correct term is Anti-forensics (option D), not “Felony.”

• Why: The actions described—hiding files in slack space, changing file headers, placing suspicious files in executables, and altering metadata—are classic anti-forensics techniques. They’re used to hinder or obscure forensic analysis, not to label the act as a legal category.

• About the options:

• Note: The provided answer key lists B (Felony), which is misleading for this exam objective. The exam typically tests knowledge of forensics concepts, where anti-forensics is the correct category.

• 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.

• Developed and maintained independently
• Deployed without changing the entire application
• Scaled separately based on demand
• More resilient when another service has problems

• A: Functional testing is useful, but it is not the main practice described.
• B: Automation helps deployment, but the scenario focuses on architectural decomposition.
• C: Multiple locations improve availability, not application modularity.

• Batch processing, such as scheduled data transformations
• Streaming processing, such as continuously ingesting events

• Manipulating data with multiple languages: Mainly a benefit of Databricks and Spark.
• Real-time notebook collaboration: A workspace/notebook feature.
• Alerts for query failures: A Databricks SQL or job-monitoring feature.
• Distributing complex operations: Primarily a Spark compute capability.

sql 
SELECT COUNT(*) FROM table;

• A: It does not normally need to scan all data files for this operation.
• B: Results are not simply reused from a query cache every time. Caching is separate from Delta’s metadata optimization.
• D: The relevant metadata is maintained through the Delta transaction log, not directly treated as a Parquet-file metadata operation in this context.

json 
{ 
  "Effect": "Deny", 
  "NotAction": [ 
    "iam:*", 
    "route53:*", 
    "cloudfront:*", 
    "support:*" 
  ], 
  "Resource": "*", 
  "Condition": { 
    "StringNotEquals": { 
      "aws:RequestedRegion": "eu-west-1" 
    } 
  } 
}

• SCPs set maximum permissions; they do not grant permissions. The default SCP allows actions, so the restriction must be an explicit Deny.
• aws:RequestedRegion checks the Region targeted by an API request.
• StringNotEquals: eu-west-1 denies requests directed to every other Region.
• NotAction allows designated global services to remain usable because they do not operate in a single AWS Region.
• Attaching the SCP to the OU makes it apply to existing accounts and accounts later added to that OU.

• Writing with Apache Spark, typically as Delta tables.
• Reading with Apache Spark for processing and analysis.
• Reading with T-SQL through the lakehouse’s automatically generated SQL analytics endpoint.
• Reading with KQL through Fabric’s query capabilities that can access lakehouse data.

• Eventhouse: Optimized for real-time and KQL workloads, but it is not the natural destination for Spark-based writes or general lakehouse storage.
• Datamart: Intended mainly for relational analytics and Power BI; it is not designed for Spark-based data ingestion.
• Warehouse: Primarily T-SQL-based and structured. It does not provide the same native Spark write experience or flexibility for semi-structured data.

• A. Modify CommunitiesSelfRegController

• C. Configure Communities registration to use a custom Visualforce page

• B. Modify the self-registration trigger — There is no standard “self-registration trigger” intended for this configuration. The registration logic is handled by the Visualforce controller.
• D. Configure a custom Apex controller — The standard approach is to modify the provided CommunitiesSelfRegController, rather than simply selecting a separate controller configuration.

• Correct answer: A
• What this is saying: You need to write a Transact-SQL query that uses REGEXP_SUBSTR to extract the ID from MessageText, and you should apply STRING_ESCAPE(MessageText, 'json') before calling REGEXP_SUBSTR.

• MessageText may contain JSON characters (quotes, backslashes, etc.). Escaping the JSON content first ensures the string you pass to the regex is safe and won’t confuse the regex engine.
• The pattern you apply with REGEXP_SUBSTR would then extract the first substring that matches your ID pattern from the (escaped) text.

• Example (conceptual):

• The question implies REGEXP_SUBSTR is available in this environment; some SQL Server and Fabric contexts don’t expose it natively in all versions. If REGEXP_SUBSTR isn’t available, you’d need an alternative approach (e.g., using built-in regex-like capabilities or CLR/UDFs).
• If you need the ID specifically from the first paragraph, you might first isolate the first paragraph and then apply REGEXP_SUBSTR, or compose a single pattern that anchors to the first paragraph.

• A — Add a Path for Stage: A Path lets users update the Opportunity’s Stage directly from the record page, without opening the full edit form. It can also display guidance and key fields.
• B — Use a Kanban list view: Users can move Opportunities between stages by dragging records between columns, which is ideal when Stage is the only field they normally change.

• 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.

• A single Construction Job can use multiple Machinery records.
• A single Machinery record may be used on multiple Construction Jobs.
• This is a many-to-many relationship, which Salesforce models using a junction object.
• The junction object can contain fields such as:

• Master-detail to Machinery
• Master-detail to Construction Job
• Date and cost fields

sql 
CREATE TABLE my_table 
USING CSV 
OPTIONS (path '/path/to/csv');

sql 
CREATE TABLE my_table 
USING CSV 
LOCATION '/path/to/csv';

• USING CSV specifies the file format.
• path or LOCATION specifies where the files are stored.
• USING DELTA would be used only when the source data is in Delta format.
• FROM is used in a SELECT statement, not normally as the format declaration in CREATE TABLE.