ACAMS CAMS7 Exam Prep
Certified Anti-Money Laundering Specialist (the 7th edition) (Page 3 )

• B: Intégrez des résultats de due diligence tels que les évaluations de risque client.

• C: Utilisez des correspondants en aval pour enquêter et signaler les activités suspectes.

• Problème: le système d’alertes signale des fluctuations tout en manquant les activités qui restent anormalement constantes sur une période longue. Il faut donc un scénario qui capte les anomalies qui se maintiennent dans le temps plutôt que les pics ponctuels.
• Peer: permet de comparer un client à ses pairs; utile pour repérer des écarts relatifs, mais ne cible pas nécessairement les motifs d’anomalie persistante sur plusieurs périodes.
• Revenus mapping: relie les transactions à des sources ou flux de revenus; utile pour l’analyse des fonds, mais pas directement pour détecter une anomalie longue durée.
• Below-the-line: conçu pour détecter des activités qui passent en dessous des seuils habituels ou qui demeurent anormales sur une longue période, comblant ainsi la faiblesse des alertes à long terme.

• Espionage: Stealing confidential information, often for a competitor or government.
• Data exfiltration: Unauthorized transfer of data outside the organization. This could occur, but the question focuses on using unapproved access methods.
• Nation-state attack: An attack sponsored or conducted by a government.
• Shadow IT: Employees using technology or access methods outside the organization’s approved security controls.

• BCP (Business Continuity Plan): è più ampio e mira a mantenere le funzioni essenziali dell’organizzazione durante un’interruzione. Il DRP è una componente più specifica del BCP.
• Communication plan: stabilisce come comunicare con dipendenti, cittadini e altre parti interessate, ma non ripristina i sistemi.
• IRP (Incident Response Plan): gestisce la risposta iniziale a un incidente di sicurezza, come un attacco informatico, non principalmente il recupero da un disastro fisico.

• Custom domain: miami.weyland.com requires a paid App Service tier; Free and Shared are unsuitable.
• Two instances: Standard supports scaling to multiple instances.
• SSL: Standard includes SSL support.
• 12 GB storage: Basic provides only about 10 GB, so it does not meet the requirement. Standard provides substantially more storage.
• Cost minimization: Standard is the lowest tier among the choices that satisfies all requirements.

• Custom domains are supported.
• It provides dedicated compute instances.
• It offers enough storage for the applications.
• It supports multiple instances with load balancing between them.
• It is less expensive than higher tiers such as Premium.

• Free and Shared use shared compute and have limited storage, so they cannot meet the dedicated-instance requirement.
• Basic provides dedicated compute and custom domains, but the question’s requirement for the broader multi-instance/load-balancing capability is intended to point to Standard.

• VPC: A logically isolated virtual network within a cloud provider; it describes network design, not the user-access model.
• NFV: Runs network services as software instead of on dedicated hardware.
• SaaS: Delivers software over the internet. Although the application may be delivered as SaaS, the question emphasizes its availability to multiple user groups, which points to multitenancy.

• contoso.onmicrosoft.com
• contoso1.onmicrosoft.com

• onmicrosoft.com domains: Maximum of five per tenant.
• Custom domains: Domains that your organization owns and verifies in Microsoft 365.

• 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: Unapproved technology or methods used to access organizational resources.

1. Yes — Microsoft Foundry provides a secure, governed environment for building and managing generative AI applications and agents. It brings together models, data, tools, evaluation, deployment, and monitoring.

1. Yes — Foundry is designed for enterprise workloads and supports scaling AI applications as usage grows. Scalability comes from the underlying Azure services and managed infrastructure.

1. Yes — Foundry can be used in solutions involving image recognition and computer vision. Applications can use vision-capable models and Azure AI vision capabilities for tasks such as image analysis, object detection, and OCR.

• A. IDS attack signatures: An IDS primarily detects suspicious network activity; it is not the best tool for scanning uploaded files.
• C. Load balancer: Improves availability and distributes traffic but does not inspect files for malware.
• D. WAF: Protects web applications against attacks such as SQL injection and command injection. It may inspect HTTP requests, but malware scanning of uploaded PDFs is the key requirement here.

• Microservices: An application design approach that divides software into small services; it does not specifically reduce the number of operating systems.
• Containerization: Uses isolated containers that share the host OS kernel—best match.
• Virtualization: Creates separate virtual machines, and each typically requires its own guest OS, so it does not minimize OS instances as effectively.
• Infrastructure as code: Automates deployment and management of infrastructure; it does not describe the architecture being used.

• The requirement is to obtain an assessment of the Azure environment’s design.
• The proposed solution is the Premier support plan.
• Premier can provide this type of guidance, but it is a higher-tier, more expensive option.
• The question specifically says to keep costs to a minimum. A lower tier—typically Professional Direct in the support-plan model used by this question—provides architectural/design guidance.

• Warehouse size: Larger warehouses use more credits per unit of time than smaller ones.
• Number of clusters: A multi-cluster warehouse can run multiple clusters, and each active cluster consumes credits. Therefore, increasing the maximum or active cluster count can increase consumption.

• Number of users: More users may cause more workload, but users themselves do not consume credits.
• Amount of data processed: Snowflake warehouses are not charged directly by the amount of data scanned. However, processing more data may cause the warehouse to run longer, indirectly increasing credits.

• Liability accounts (2000–2999) would incorrectly require dimensions, although they should have none.
• Expense accounts (6000–6998) would incorrectly require Customer, which should be optional.
• Account 6999 needs a separate rule because it requires all four dimensions, including Customer.

• 2000–2999: no dimensions
• 4000–4999: Department and Division required; Project and Customer optional
• 6000–6998: Department, Division, and Project required; Customer optional
• 6999: Department, Division, Project, and Customer required

• A — VARIANT "null" values are not the same as SQL NULL values: True

• B — Frequent, single-row DMLs: False

• C — Validate data before loading into the target table: True

• D — Use staging tables to manage MERGE statements: True

1. The specific table — for example, incident
2. The parent table — for example, task
3. The wildcard table — *, which applies broadly

• 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.

• 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.

• Deterrent control: The signs warning people they may be filmed discourage unauthorized or malicious behavior. They may prevent incidents by influencing behavior, but their primary purpose is to deter.
• Detective control: The CCTV system monitors and records activity so security personnel can identify suspicious or unauthorized actions.

• Preventive: Blocks or prevents an incident, such as a lock or access-control system.
• Corrective: Fixes or restores systems after an incident.
• Directive: Tells people what they must do, typically through policies or procedures.
• Compensating: Provides an alternative control when the preferred control cannot be used.

• Correct exam answer: A — HKEY_LOCAL_MACHINE
• The relevant location is associated with HKEY_LOCAL_MACHINE\SAM.
• The SAM does not store passwords in plain text; it stores password hashes.

• HKEY_CURRENT_USER contains settings for the currently logged-in user, not the account-password database.
• HKEY_USERS contains user profiles and settings loaded for users.
• HKEY_CURRENT_CONFIGURATION contains hardware/profile configuration information.

• Access controls — ensuring only authorized users can access it.
• Encryption — protecting the data if it is intercepted or exposed.

• Atomicity: a write fully succeeds or does not appear.
• Consistency: table state remains valid.
• Isolation: concurrent operations do not corrupt one another.
• Durability: committed changes persist.

• Flexible schemas: common data lakes often support flexible or schema-on-read data.
• Open-source formats: common data lakes commonly use open formats such as Parquet.
• Scalable storage: cloud data lakes already provide scalable storage.

• Driver node: Coordinates Spark jobs and runs in the compute environment.
• Worker node: Executes tasks and processes data.
• Databricks Filesystem (DBFS): Provides storage access for data used by compute resources.

• Report on the discount approval time for quotes

• Dashboard of opportunity stage duration

• Lead conversion trends measure lead-generation effectiveness, not opportunity closing time.
• Campaign ROI evaluates marketing performance, not delays in the sales process.

• Due diligence: Researching and evaluating a third party before entering or continuing a business relationship.
• Internal audit: Evaluates controls within the organization itself.
• Penetration testing: Actively tests systems for exploitable vulnerabilities.
• Attestation: A formal statement or report—such as a SOC 2 report—provided by an independent party about an organization’s controls.

• 50% memory utilization baseline: The environment can be provisioned with excess capacity, leaving room for growth and workload spikes.
• Storage scalability: Cloud storage can generally be expanded as needed without redesigning the physical platform.
• Single circuit failure resilience: A properly designed IaaS provider uses redundant power circuits and infrastructure, so failure of one circuit should not take the platform offline.

• A — Dual PDUs: Helps with power redundancy but does not provide storage scalability.
• C — Network load balancing: Provides network-path resilience, not memory or storage scalability, and does not address a power-circuit failure.
• D — Multiple NAS devices: May improve storage capacity, but does not inherently provide power resilience or the required compute-capacity baseline.

• Power BI dataset — Reuses the existing tables, relationships, and measures. You mainly create new visualizations.
• SharePoint folder — Connects to the source files, but you would need to rebuild the model and measures.
• Power BI dataflows — Primarily provide reusable data preparation; they do not automatically provide the existing report’s measures and model.
• Excel workbook — Requires reconnecting to and modeling the source data again.

• Ramen is a Linux worm associated with Red Hat Linux 6.2 and 7.0 systems.
• It spreads by scanning randomly generated IP addresses using tools such as synscan.
• It exploits vulnerable network services, including web-related services, and may leave malicious files or altered web content.
• The tar.gz file is also a clue because it is a common Linux archive/package format.

• Code Red: Primarily targeted Microsoft IIS servers running Windows.
• LoveLetter: Spread mainly through email attachments.
• Nimda: A Windows-based worm that spread through email, web servers, and network shares.

• C. Case after-insert trigger that publishes a Platform Event

• D. Custom Apex controller that publishes a Platform Event

• A. Trigger with a callout: Salesforce triggers should not make direct synchronous callouts, and this tightly couples transaction processing to the external system.
• B. Workflow Rule with Outbound Message: This can react to record changes, but it cannot reliably capture a user clicking a menu item. It also does not provide the same flexible event-driven model as Platform Events.

• Third-party enterprise application with embedded AI: The provider manages most security controls. The customer mainly manages users, data, and configuration.
• Application using an existing third-party FM: The customer controls the application and its inputs/outputs, but the provider controls the underlying model and infrastructure.
• Fine-tuning a third-party FM: The customer has additional responsibility for training data, data protection, and model behavior, but still depends on the provider’s base model and platform.
• Building and training a model from scratch: The customer controls the model, training data, application, deployment, and many security safeguards. This creates the greatest security ownership.

• Assign endpoints to a group based on the result of one policy.
• Use that group as the scope of another policy.
• This effectively passes the endpoints from one policy’s processing flow to another.

• B — Sales staff will tender for riskier contracts:

• C — Sales staff will encroach on other territories:

• D — Sales staff will look for new jobs:

• Regression predicts continuous numeric outcomes, such as house price, temperature, or sales amount.
• Linear regression assumes the target can be estimated from a linear relationship between the input features and the target.
• In Azure Machine Learning, you use a labeled dataset containing:

• Classification predicts a category or class, such as “spam” or “not spam.”
• Clustering groups similar records without a known label; it is an unsupervised learning technique.

• MFA adds an additional authentication factor, such as a phone notification or verification code.
• It helps prevent unauthorized sign-ins, even if a password is compromised.
• It does not encrypt, store, or protect credentials used by deployment processes.

• Domain controllers, because the requirement specifically excludes them. However, note that both member servers and domain controllers run Windows Server, so OS targeting alone cannot distinguish them unless the targeting option allows selecting the relevant server role/version. In the usual exam interpretation, target the applicable server OS category.
• Client computers, because they run a client Windows operating system.

• Domain: Targets membership in a domain, not the computer’s operating-system type.
• Security Group: Would require creating and maintaining a group containing all member servers, increasing administrative effort.
• Environment Variable: Not designed to reliably identify member servers.

• Remote and global work: Access is based on the approved device, not a specific office or geographic location.
• Seamless login: Users may not need to repeatedly enter credentials on a recognized device.
• Limited equipment: It uses devices employees already have rather than requiring separate hardware.

• Geotagging: Restricts access based on location and may prevent legitimate remote work.
• Smart cards: Require issuing and managing additional physical equipment.
• Time-based logins: Limit access by time and do not provide a seamless authentication experience.

CIMA P3 topics

• IT governance and systems strategy
• Systems development and implementation
• Change and project governance
• Strategic and business risk

• A — Plan for new systems: The committee should help identify and prioritise systems requirements and ensure planned systems support organisational needs.
• D — Consider competitive issues: New information systems may affect Y’s competitive position, service quality and efficiency. These strategic implications should be considered.
• E — Ensure the system meets company goals: This is a key governance responsibility. The committee should ensure the project remains aligned with Y’s objectives and delivers business value.

• B — Develop new systems: Detailed system development should be performed by IT specialists and project teams, not the steering committee.
• C — Manage the project: The project manager should handle day-to-day project management. The steering committee should provide oversight, challenge and key decisions, rather than manage daily activities.

• New investment: $536,500
• Resulting NPV: $0

• 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.

• Penetration test: Tests for exploitable vulnerabilities; it does not provide a broad opinion on whether security controls operate effectively.
• Annual self-assessment: Not independent, so it provides less assurance.
• Allow each client the right to audit: Inefficient because every customer may conduct a separate audit, creating duplicated effort and disruption.

• Sets a high initial price for a new product.
• Targets customers willing to pay more, often called early adopters.
• Gradually reduces the price to attract more price-sensitive customers as the product becomes less novel and competition increases.

• Penetration pricing: starts with a low price to gain market share quickly.
• Premium pricing: maintains a high price to communicate superior quality or status; it does not necessarily involve later price reductions.
• Loss leader pricing: sells one product at a very low price, sometimes below cost, to attract customers who may buy other products.

• D — Managers focus on keeping costs low in the short term to maximise profits.

• E — Managers are given incentives to meet or undercut budgets.

• F — Managers delegate responsibility simply to reduce their workload.

• C — Some risks cannot be eliminated.

• D — Accepting residual risk does not imply recklessness.

• E — Most companies in this industry will say something similar.

• A. Adjust resolution: Incorrect because an incompatible resolution usually causes no display, distortion, or an unsupported-mode message—not intermittent flickering.
• B. Swap the HDMI cable: Correct. Replacing the common, easily tested component is the appropriate troubleshooting step.
• C. Replace the projector: Incorrect because the issue also occurs with a monitor.
• D. Configure refresh rate: A mismatched refresh rate can cause visual problems, but the repeated flicker across displays points more strongly to the cable.

• S3 Glacier Deep Archive is designed for long-term archival data with very infrequent access and has a lower storage cost than S3 One Zone-IA.
• The documents are copies stored elsewhere, so reduced availability and delayed retrieval are acceptable.
• An S3 interface VPC endpoint allows private access from the VPC without exposing the bucket through the public internet.
• A bucket policy can restrict access to requests coming through that endpoint.

• Outer packet: 10.5.1.1 > 52.165.16.154
• IPv4 protocol field: 41, which indicates IPv6 encapsulation
• Inner packet: IPv6 traffic between 2001:... addresses

• MAC address spoofing: Changes Layer 2 addressing; it does not explain the IPv6-in-IPv4 structure.
• Steganography: Hides data inside files or media, not visibly in a tunneled protocol.
• Broken encryption: No evidence of encryption being cracked.
• On-path sniffing: Involves intercepting traffic, not sending data to an external host.

• B — Incorporate contextual output encoding/escaping: Encode untrusted data based on its context—HTML, attribute, JavaScript, or URL—so the browser treats it as data rather than executable code.
• D — Run untrusted HTML input through an HTML sanitization engine: Sanitization removes or neutralizes dangerous elements and attributes, such as script-related content, while preserving safe HTML where needed.

• A: Enabling client-side scripts does not prevent XSS. Script restrictions may reduce risk in some environments, but “enable” is not a general XSS control.
• C: Cookie inspection is unrelated to preventing injected scripts.
• E: The SameSite cookie attribute primarily helps mitigate CSRF, not XSS. It should not generally be described as an XSS prevention measure.

• Confirming the data has the required columns and data types
• Handling missing or duplicate records
• Converting data into a suitable format
• Selecting or engineering useful features
• Splitting it into training, validation, and test sets

1. Prepare the training data
2. Select an algorithm or configure AutoML
3. Train the model
4. Evaluate its performance
5. Tune hyperparameters if needed
6. Deploy the model