Cyber AB CMMC-CCA Exam Actual Questions
Certified CMMC Assessor (CCA) (Page 11 )

• Box 1: Azure Lighthouse — ??? ??????? ? ?????????? ????????? ? ?????????? Entra tenants. ??? ??????????? ??? ??? ????? ????? ? VM ? ?????? ?????????/????????.
• Box 2: Azure Monitor Agent ? ?????????????? Data Collection Rules (DCR) — AMA ???????? ??????? Windows (????????, Security Logs) ? DCR ??????????, ????? ??????? ???????? ? ???? ?????????? (? ?????? Log Analytics workspace).

• The correct answer is Mass Transfer Tool.

• The Mass Transfer Records tool is Salesforce’s built-in way to reassign ownership of existing records in bulk. In this scenario, you need to transfer ownership of the departed rep’s accounts and opportunities to a new rep while keeping the team structure intact.

• Go to Setup > Data Management > Mass Transfer Records.
• Choose the object: Accounts (and then Opportunities, if needed).
• Set “Transfer From” (the leaving rep) and “Transfer To” (the new rep).
• Decide whether to transfer related records as well (e.g., opportunities tied to accounts) and proceed.
• Review and confirm.

• Data Loader / Data Import Wizard are for bulk import/export, not bulk reassigning ownership.
• Dataloader.io is a third-party tool; the built-in Mass Transfer tool is the standard Salesforce method for this task.

• The Act requires:

• It does not, as a public obligation, mandate publishing a detailed report on the training data used.
• Also, the Act does not specify a fixed “six months” retention for system logs in a way that would clearly make A required; logs for traceability are implied, but the six-month period is not a defined, universal requirement.

• Answer: D. Select an IdP

• Why: To reduce the number of credentials across multiple SaaS apps, implement a single sign-on approach via an Identity Provider. The first step is choosing the IdP; once selected, you can enable SAML (A) or OAuth as supported by apps. Password vaulting (C) is not a true SSO solution, and B is not the foundational step.

• Alice is co-resident on the same physical host and exploits shared hardware (the processor cache) to infer secrets. This is the classic definition of a side-channel attack—information leakage through implementation details (like timing or cache behavior) rather than by breaking a protocol or injecting code.

• Observing cache timing or access patterns to deduce cryptographic keys or plaintext data from the victim VM.

• Man-in-the-cloud attack: targets cloud trust/auth, not local hardware sharing.
• SQL injection: exploits input to run SQL commands, not a VM/caching vector.
• Service hijacking: takes control of a service, not about covert data leakage via shared hardware.

• Notice phrases like “shared hardware resources,” “co-resident,” or “cache”—these indicate a side-channel vector.

• A. Number ? Decimal — Correct. Salesforce Number fields are represented in Apex as Decimal.
• D. Date/Time ? Datetime — This is correct conceptually, but “Dateline” is not an Apex type. If the option literally says “Dateline,” it is incorrect.
• E. Checkbox ? Boolean — Correct. A checkbox contains true or false.

• Number ? Integer — A Number field maps to Decimal, even when its scale is zero.
• Text Area ? List<String> — A text area maps to a single String, not a list.

• Goal: Guests should not use cameras, but company users can.
• Correct configuration: Guest access settings in the Org-wide settings.

• External access: Controls external-domain communication, not guest capabilities inside Teams.
• Teams settings in Org-wide settings: Too generic; doesn’t specifically target guest capabilities.
• Audio & Video in the default Meeting Policy: Would affect everyone assigned to that policy. To meet the requirement without impacting internal users, you’d need separate policies or guest-specific settings; the exam focuses on the guest-access policy.

• 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

• If the account name includes the parsed search string, show the element; otherwise hide it.
• In CSS, to show an element you can set display to a visible value (commonly 'block' for block-level elements), and to hide you set display to 'none'.

• The ternary should map true to a visible display value and false to 'none'.
• Therefore the placeholder should be replaced with 'block' : 'none' (so the code becomes: accountName.includes(parsedSearchString) ? 'block' : 'none').

• There are several typos in the snippet (e.g., quesrySelectorAll, toLOwerCase, Style.display). In a working version you’d also fix those to document.querySelectorAll, account.innerHTML.toLowerCase(), and account.style.display.

• 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.

• A — SCIM synchronizes changes to user attributes from the identity provider to GitHub.
• B — SCIM deactivates GitHub accounts when users are removed or deactivated in the identity provider.
• D — SCIM automates user provisioning when new users are added to the identity provider.

• C: SCIM does not delete organization repositories.
• E: SCIM does not generate REST API authentication tokens.
• F: SCIM handles identity lifecycle management, not repository permission configuration based on roles.

• Users retain their existing usernames and passwords.
• Existing accounts can be used to access Azure-based resources.
• Administrators avoid manually recreating thousands of accounts.
• The transition is less disruptive before the on-premises data center is retired.

• What D means: In Security Command Center (SCC), a posture combines both preventative controls (predefined and custom organization policies) and detective controls (predefined and custom Security Health Analytics [SHA] modules). Scope this posture to the business unit folder to enforce those controls across the Vertex AI environment.

• Why this is correct: You need both preventative guardrails (policies) and detective guardrails (SHA findings) to meet internal security requirements. A posture provides a unified, scalable way to apply and monitor these controls to a specific organizational unit.

• Why the other options are weaker:

• If you want, I can break down the exact components of a SCC posture and how to apply it to a Vertex AI project.

• IPsec: Protects traffic at the network layer, commonly for VPNs; it is not WPA2’s authentication protocol.
• SSL: Protects specific application sessions and has largely been replaced by TLS.
• SSH: Secures remote command-line administration.

• VPC: A logically isolated virtual network in a cloud environment; it describes networking, not shared application access.
• NFV: Replaces dedicated network appliances with virtualized network functions.
• SaaS: A cloud service model in which users consume an application without managing its infrastructure. It could describe how the application is delivered, but the question emphasizes serving multiple user groups, which points to multitenancy.

• The standard Enterprise Architecture domains are: Business, Data, Application, Technology (BDAT).

• A: Business, strategy, application and technology — includes business and application/tech but uses “strategy” instead of data.
• B: Zachman, TOGAF, Cobit, and Heath architectures — names frameworks, not domains.
• C: Business, data, infrastructure and technology — has business, data, and technology; lacks a distinct application domain (uses “infrastructure” instead).
• D: Process, database, software and technology — covers data (database), application (software), and technology, but omits business.

• The four BDAT domains (business, data, application, technology) is the conventional model you should study.
• None of the options perfectly lists all four BDAT domains. The closest are C (if you map infrastructure to technology) and D (data/application/technology but no business).

• 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.

• 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.

• Version control provides a single source of truth for metadata changes and tracks every modification.
• It supports branching and merging, so each feature can be developed in isolation and later merged without overwriting others.
• It allows diffs and conflict resolution, making it easier to manage dependencies across features and ensure a stable release.

• Setup Audit Trail: only logs who/change when something happened; it doesn’t prevent overwriting or manage cross-feature dependencies.
• Change Sets: used to deploy changes between orgs, not to coordinate parallel development or prevent conflicts across ongoing sprints.

• Answer: D: Making business cases for improvement action

• Continual Improvement focuses on identifying and planning improvements and ensuring they’re funded and prioritized. Creating a business case for an improvement action is part of justifying and obtaining support/resources to implement improvements.
• A (Identifying the cause of incidents) aligns with Problem Management.
• B (Authorizing changes) aligns with Change Enablement.
• C (Logging/managing incidents that result in improvement opportunities) aligns with Incident Management, not Continual Improvement.

• 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.

• The AWS Support Concierge is a specialized team within Enterprise Support whose primary role is handling billing and account questions and helping with account setup and getting started.
• They are not the source for architecture guidance or development assistance; those services are provided by Technical Account Managers (TAMs) or Solutions Architects as part of Enterprise Support.
• For technical support cases, customers typically interact with AWS Support engineers or the TAMs, not the Concierge. The Concierge may route or coordinate related requests, but they don’t provide the technical resolution.

• What Concierge does: billing and account inquiries, onboarding help, coordination with AWS support.
• What Concierge does not do: provide architecture/design guidance or in-depth technical support case resolutions.

• RPO (Recovery Point Objective) — maximum acceptable data loss, measured in time. It specifies how far back in time you can tolerate data loss. Example: RPO of 2 hours means backups must occur at least every 2 hours.

• ARO (Annualized Rate of Occurrence) — expected frequency of a threat occurring per year. It estimates how often a risk is likely to happen on average (used in risk calculations).

• MTTR (Mean Time To Recover) — average time to recover/restore service after an incident. It includes detection, repair, and restoration time, and helps gauge downtime and alignment with RTO.

• 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

• 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.

• Why: A multi-modal embedding model maps both text and images into a shared vector space, enabling cross-modal similarity and retrieval (e.g., find images matching a text query or text matching an image).

• What it does: Enables efficient similarity search using a vector database or nearest-neighbor indexing.

• Why the other options aren’t suitable:

• Quick implementation note: you’d typically pair the embeddings with a vector store (e.g., ANN index) and possibly fine-tune on domain data for better alignment across modalities.

• The question asks why some tasks appear locked in the HR Guided Setup Module’s Task view.
• The options are:

• C) They require other tasks to be completed first. In guided setup flows, tasks are usually gated by prerequisites to ensure proper sequencing and data/configuration dependencies. You typically unlock a task only after the necessary preceding tasks are finished.

• A) Elevated roles can restrict access in some contexts, but guided setup tasks are commonly gated by prerequisites rather than solely by role.
• B) Deprecation isn’t the general pattern for “locked” tasks in the guided setup.
• D) A plugin activation could unlock certain features, but the common gating mechanism is task dependencies, not plugin state.

• The page shows the answer as D, but based on how HR Guided Setup usually works, the more accurate reason is typically C (prerequisites). If you’re studying, treat C as the conceptual answer and be aware the listed key may be incorrect. If you want, I can walk through each option in more detail.

• The stage has a default file format defined (e.g., when you create the stage with FILE_FORMAT = (...)), and Snowflake will use that default.

• You use a named file format attached to the stage, or you specify an inline format in the COPY command, e.g., COPY INTO my_table FROM @my_stage FILE_FORMAT = (TYPE = 'CSV');

• Use a stage default: omit FILE_FORMAT in COPY.
• Or rely on a named/inline format: specify FILE_FORMAT in COPY or set a format on the stage.

• 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.

• 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.

• S3 Versioning stores all versions of an object. If an object is overwritten or deleted, you can recover the previous version using its version ID.
• This protects against accidental deletion or overwriting because the original data remains accessible as an older version.
• How to enable:

• Practical notes:

• S3 Lifecycle rules: automate moving/expiring data, not specifically protection against deletion.
• S3 bucket policies: control access but don’t inherently preserve previous data.
• S3 server-side encryption: protects data at rest, not against deletion/overwrite.

• Control plane: Managed by Databricks and contains the Databricks web application, workspace services, cluster management, and job orchestration.
• Data plane: Runs in your cloud account and contains compute resources such as:

• Worker node: Data plane compute.
• Driver node: Data plane compute.
• JDBC data source: Usually an external data system.
• Databricks Filesystem (DBFS): Provides storage access and is backed by cloud object storage rather than being entirely part of the control plane.

• Actual filename: Document.xml.txt
• Explorer displays: Document.xml
• File type: Text Document (.txt)

text 
Document.txt ? Document.xml

• Correct answer: Day 3 (Option B)

• Why: In Engagement Studio, when the program is paused, the prospects’ wait times are also paused and do not count down. They resume from the same point when the program restarts. Here, the prospect was at day 3 of a 5-day wait when paused, so they resume on day 3 after the 1-day pause.

• In the source query: apply UPPER() or LOWER() to the column.
• In Power Query Editor: use Text.Upper or Text.Lower on the column, then load.

• This fixes the root cause when comparisons/joins depend on case.
• In DirectQuery, transformations are pushed to the source or query layer; ensure the transformation is supported by your data source/connector.
• After normalization, verify relationships and any downstream visuals that rely on that column.

Why B works

• AWS KMS keys are Regional resources. A normal customer managed key in Region A cannot be used directly in Region B.
• A customer managed multi-Region KMS key (MRK) has related key replicas in both Regions. The replicas share key material and key ID, although each has a Regional ARN.
• With client-side encryption, the application encrypts the data before storing it in S3. Cross-Region replication then copies already-encrypted objects, so S3 does not need to decrypt and re-encrypt them with a different Regional key.

Why the other choices are weaker

• A and C: SSE-S3 uses Amazon-managed S3 keys, not the required customer managed KMS key.
• D: SSE-KMS can work only if the solution creates and configures the appropriate KMS key or multi-Region key replica in each Region. As written, it says to create a customer managed KMS key in each Region, which implies separate keys—not the same KMS key. Replication also requires additional KMS permissions and destination encryption configuration.

• 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.

• 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.

• Cutover: The old system is replaced immediately. It may be fast, but any failure can cause significant disruption.
• Phased: The system is introduced in stages, which reduces implementation risk but may prolong the transition.
• Pilot: The system is first deployed to a limited group or location. This is useful for testing but does not necessarily minimize downtime for the entire organization.

• 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).

• Answer: D) Shadow IT

• Why: Shadow IT is when employees use unsanctioned tools or bypass IT controls (like the VPN) to access services, often without IT oversight. It’s an internal behavior, not an external attacker’s activity.

• Not these:

• Quick note: This creates risk due to lack of visibility and control. Mitigations include a defined approved-tools list, enforcing VPN usage, device management, and continuous monitoring.

• 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.

• Why: The data is unlabeled, so you can’t train a model with known input-output pairs. Unsupervised learning discovers structure in the data by grouping similar customers into clusters or tiers without labels.
• What it does: Clustering and segmentation (e.g., k-means, hierarchical clustering, DBSCAN, Gaussian mixtures) to form meaningful groups.
• Why the other options aren’t as suitable:

• Correct answer: D. AWS CloudShell

• Why: AWS CloudShell is a browser-based shell that runs in the AWS Console and uses the current authenticated session. It provides a pre-authenticated, ready-to-use command-line environment directly from the Management Console, with AWS CLI and common tools installed.

• Why the other options aren’t correct:

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• ???????????

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• Answer: A) Clear the Windows event logs

• Windows event logs (System, Security, Application) are key forensic artifacts. If an attacker clears these logs, there’s no built-in local record of actions taken, making it harder for investigators to trace what happened.

• Modify the system time: may misalign timestamps but does not erase past events and can be easily detected.
• Alter log permissions: could prevent new log entries, but it doesn’t remove existing ones and can raise alarms due to permission changes.
• Reduce log retention settings: affects only future logs; it doesn’t wipe already recorded activity.

• In real environments, defenders mitigate this risk with tamper-evident, centralized logging (remote SIEM, write-once storage, log integrity checks) to preserve evidence even if a host is compromised.

• Why: Table.Profile returns a per-column profile that includes statistics such as count, null count, distinct count, and standard deviation. It also provides min/max and average where applicable, which matches the requested metrics (Count, Average, Null count, Distinct count, Standard deviation).
• Syntax: Table.Profile(table as table, optional additionalAggregates as nullable list) as table
• How it helps: After running Table.Profile on your table, you can extract the per-column stats you need and display them in your semantic model or report.