Checkpoint 156-315.81 Exam Actual Questions
Check Point Certified Security Expert R81 (Page 47 )

• In a Check Point cluster, the number of cores used for the Firewall-kernel on each device is limited by the device with the fewest cores in the cluster. In other words, the cluster uses the minimum core count among all members (the "lowest common denominator").

• Current gateway: 2 cores
• New gateway: 4 cores
• Minimum cores among members = 2
• Therefore, each cluster member (including the 4-core device) can use only 2 Firewall-kernel cores.

• The correct answer is 2 cores per device. The provided answer (4 cores) is incorrect because it ignores the minimum-core rule across the cluster. If both devices had 4 cores, then you could use 4 cores per device.

• Answer: C — Spot Instances

• Why: The workload is a test environment that can be interrupted and does not need to run continuously. Spot Instances let you bid on unused EC2 capacity at a deep discount, making them the most cost-effective option for interruptible workloads.

• Why not the others:

• Quick tips:

• The requirement: the support plan must allow opening new support requests (technical support incidents).
• Azure’s Basic plan does not include technical support incidents—only billing/subscription support and access to community support.
• Therefore, you must choose a paid plan to open new technical support requests: Developer, Standard, Professional Direct, or Premier.

• 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.

• On-prem you generalize and capture the VM as a VHD.
• Upload the VHD to Azure with Add-AzVhd.
• Register the VHD as an image in Azure with Add-AzImage (or New-AzImage) so it appears as a selectable image.
• Create new VMs from that image (e.g., with New-AzVM -Image ...).

• A assigned without var becomes a global variable (in non-strict mode). So after myFunction(), a = 5 is accessible.
• b is declared with var inside the function, so it’s local to that function (function-scoped). It’s not defined in the outer (global) scope.

• console.log(a) prints 5.
• console.log(b) throws a ReferenceError: b is not defined.

• 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.

• Correct answer: C: Amazon Comprehend.

• Why: The library wants to classify books based on their text content. This is an NLP (natural language processing) task. Amazon Comprehend is AWS’s managed NLP service that can perform content classification (including creating custom classifiers) and extract meaningful information from text. The other services are not focused on text classification:

• Quick note: In practice, you’d store the books in S3, extract text if needed (e.g., from PDFs with Textract), and then use Comprehend to classify the documents into topics or genres.

• Windows 10 VMs
• Windows Server 2012 or later VMs
• Running VMs—they do not need to be shut down
• Debian 8.2+ VMs, assuming the specific version is supported
• Stopped or deallocated VMs

• What the dataflow options mean:

• Why C fits best:

• 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.

• The missing piece is to configure an event source mapping between the DynamoDB stream and the Lambda function. Enabling DynamoDB Streams alone doesn’t trigger the function—you must wire the stream to Lambda so events invoke the function.
• Note that changing StreamViewType (A) only affects what data is delivered (e.g., NEW_IMAGE) and does not trigger invocations. Options C and D are not required for invocation: you don’t need SNS, and increasing the timeout won’t enable the trigger.

• 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.

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.

• A Storage Gateway File Gateway provides an on-premises NFS/SMB file share that's backed by objects in S3. This is exactly what you need to migrate an NFS workload: applications continue using NFS, while the actual data moves to and is stored in S3.
• It can cache frequently accessed data locally for performance, while uploads go to an S3 bucket.
• Why the other options aren’t suitable:

• To use a custom foundation model (CFM) with Amazon Bedrock, you must register the model with the SageMaker Model Registry. This provides versioning, governance, and a concrete reference that Bedrock can load and invoke.

• “Purchase Provisioned Throughput” is not a concept used for Bedrock/custom models.
• Bedrock handles the model hosting and scaling; you don’t need to buy provisioned throughput for the custom model.

• After registering the model, you’ll need to grant Bedrock access to the model (D) so Bedrock can execute it. However, the essential initial step that makes the custom model usable in Bedrock is C.

• The requirement: SQL authentication cannot be used for any databases on Server1, and the solution must be enforced centrally at the server level.
• Correct choice (C): Enable Microsoft Entra-only authentication for Server1.

• Why not the others:

• MFA verifies a user’s identity using additional authentication factors, such as a phone prompt or security token.
• It helps prevent unauthorized access even if a password is compromised.
• It does not provide secure storage or encryption of credentials used during automated deployment.

• Answer: No (B)

• SaaS (Software as a Service) delivers applications over the internet; you don’t manage the underlying infrastructure or OS.
• Deploying Azure virtual machines requires provisioning and managing virtual machines, OS, updates, and networking—this is classic IaaS (Infrastructure as a Service).
• PaaS is for managed runtime environments (apps hosted on a platform), not for VM deployment.

• Correct answer: All four statements are true (A, B, C, and D). The given key (A,B) is likely incorrect.

• A) Customers can change the size of the Warehouse after creation — Yes. You can resize a virtual warehouse after it’s created using ALTER WAREHOUSE ... SET WAREHOUSE_SIZE.
• B) A Warehouse can be resized while running — Yes. Snowflake supports online resizing; you can change the size without stopping queries.
• C) A Warehouse can be configured to suspend after a period of inactivity — Yes. You can enable auto-suspend with a delay (AUTO_SUSPEND).
• D) A Warehouse can be configured to auto-resume when new queries are submitted — Yes. You can enable auto-resume (AUTO_RESUME) so a suspended warehouse automatically resumes on new queries.

• Example commands:

• Even if a warehouse is resizing or auto-suspending, queries will be queued and then executed once the warehouse has the appropriate capacity.

• Ethical red-teaming is adversarial testing aimed at uncovering weaknesses and potential exploits in an AI system before deployment.
• A (improving accuracy) is not the primary?? of red-teaming.
• B (simulate model risk scenarios) is related but narrower; red-teaming centers on finding vulnerabilities and risk exposure, not just simulating risks.
• D (ensure compliance) is not the main goal of red-teaming.

• 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.

• ?????? CPU
• ?????????????????
• ??????????????????????????
• ???????????? throughput
• ??????????????????????????????

• A ??????? system software ????????????????????????????????? ??????????????????????????????????
• B ?????????????????????????? ????????????????????????? ?????????????????????????????
• D ????????????????????????? ?????????????? ?????????????????????????????????????????

• Answer: D) Out-of-band management

• Why this is correct:

• Why the other options aren’t suitable here:

• Side loading means installing software from sources outside official or trusted repositories.
• This process can bring in malicious payloads because the installed software hasn’t been vetted. A rootkit is a type of malware that hides its presence and maintains privileged access, making it a prime risk when using untrusted sources.
• Why not the other options:

• Only install apps from trusted sources; verify signatures.
• Use application whitelisting and security controls to block sideloading.
• Keep systems updated and use anti-malware tools capable of detecting rootkits.

• prompt: the input or instruction given to the model
• completion: the desired response

json 
{"prompt":"Summarize this customer complaint.","completion":"The customer reports a delayed shipment."}

• B: A .txt file containing CSV-style lines is not automatically a valid fine-tuning dataset. The required structure and format must match the selected Bedrock model.
• C: Provisioned Throughput provides dedicated inference capacity; it does not fine-tune a model.
• D: Journals and textbooks might support domain adaptation or pretraining, but they do not provide the prompt-to-answer examples typically required for supervised fine-tuning.

• Enable the owner dimension
• Allocate a standard costing inventory model

• Owner dimension (B): This dimension Lets you track who owns the stock. By enabling the owner dimension, items can be configured as either company owned or consignment (vendor-owned) when you create or edit items. Without enabling this dimension, you can’t designate ownership per item.
• Standard costing inventory model (D): Selecting a costing model determines how item costs are calculated and posted. Standard costing provides a fixed cost per unit, which is commonly used for agreed pricing scenarios like consignment arrangements for easier accounting and valuation. It helps ensure consistent cost treatment across transactions for items that can be owned by the company or on consignment.

• Batch dimension (A): Batch tracking is unrelated to ownership and isn’t required to support company-owned vs. consignment configurations.
• Moving average costing (C): This is an alternative costing method. It’s not required to enable ownership config, and the exam’s expected choice focuses on standard costing for this scenario.

• Source: on-premises SQL Server Database1
• Destination: Fabric Warehouse Warehouse1
• Connectivity: on-premises data gateway

• Dataflow Gen1: Primarily for Power Query transformations and isn’t the best Fabric-native choice for this copy operation.
• KQL queryset: Queries data; it does not orchestrate copying from SQL Server.
• Notebook: Could perform custom code-based movement, but it is unnecessary and less direct than a pipeline.

• Strongest encryption algorithms: Choose the strongest available encryption and integrity options, typically AES with the largest key size and a secure integrity algorithm.
• Encrypt all traffic: Select tunnel mode rather than transport mode. Tunnel mode encrypts the entire original IP packet, which is appropriate for a site-to-site VPN between branch networks.
• Secret-password authentication: Configure a pre-shared key (PSK) on both VPN concentrators. The key must match at both ends.

• Quick context: In a three-tier network (Access, Distribution, Core), roles are:

• Why A is correct: The Distribution layer runs Layer 2 and Layer 3 technologies. It often handles VLAN access (L2) and can perform inter-VLAN routing or connect to the core (L3). So it makes sense for the distribution layer to support both L2 and L3.

• Why B is correct: The Core layer is designed to maintain continuous connectivity when devices fail. It is built for high availability and redundancy, providing multiple paths so the network remains reachable even if some components fail.

• Why the others are not correct:

• The page you shared does not list domain names for individual questions, so I can’t confirm the exact domain from the question text alone.
• My best guess: this question relates to change management and configuration control, which typically maps to Governance, Risk, and Compliance (GRC) in Security+ mappings. It also touches on Operations concepts, but the governance aspect fits best.

• Answer: False. Agents and managers CAN create knowledge articles from Community questions.

• Why: In ServiceNow, a Community question can be converted into a Knowledge article using the Create Knowledge (or Convert to Knowledge) action. This allows what customers asked to become a reusable article for others.

• How it works (high level):

• Permissions: This ability depends on having the right roles/permissions (e.g., agents or knowledge managers). If you don’t see the option, check your role assignments or the knowledge-management configuration.

• Quick take: If a question in Community is valuable for others, a trained agent can turn it into a Knowledge article, making it available for self-service.

• Amazon Kendra is a managed enterprise search service that can index content stored in S3 and support natural-language queries to find text inside documents (PDFs, Word files, etc.).

• Rekognition analyzes images/videos, not document text search.
• Polly is a text-to-speech service.
• Lex is a chatbot service.

• Create a Kendra index.
• Add a data source of type S3 and point it to your bucket (with an IAM role that allows access).
• Configure/document conversion if needed, then index the data.
• Use the Kendra API or console to run natural-language queries against your indexed documents.

• Review iteration length: Changing duration does not resolve unclear requirements.
• Limit work in progress: Useful when excessive multitasking is the problem, but it does not directly clarify requirements.
• Review individual performance: The issue is a process and backlog-quality problem, not necessarily an individual performance problem.

• Correct answer: only new data added to the eventhouse (option E).
• Why: When you enable OneLake availability for the eventhouse, OneLake starts syncing data going forward. It does not automatically backfill or copy over data that already exists in the eventhouse before the enablement.
• What that means in practice: Any data added to the eventhouse after you enable OneLake will appear in OneLake (and be visible from OneLake file explorer). Pre-existing data in the eventhouse stays there unless you perform a separate backfill/copy operation outside the standard OneLake enablement.
• How to verify: add a small new dataset to the eventhouse after enabling OneLake availability, then check OneLake to confirm the new dataset appears.

• Assign a Teams license to a user — Licenses are assigned through the Microsoft 365 admin center, Microsoft Entra ID, or PowerShell.
• Deploy the Teams client — The Teams admin center manages Teams policies and apps, but it is not the primary tool for deploying the desktop client.
• Prevent users from creating teams — Team creation depends on controlling the creation of Microsoft 365 groups, generally configured through Microsoft Entra ID and PowerShell rather than directly in the Teams admin center.

• You have a 42U rack and 19 servers that are each 1U tall. To maximize airflow while fitting all servers, allocate the largest uniform space per server that still fits: floor(42 / 19) = 2U.
• 19 servers × 2U = 38U, which fits in 42U (leaving 4U for additional spacing/blanking). If you tried 3U per server, you’d need 57U, which won’t fit.

• 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.

• An IDS monitors network traffic for signs of attacks and raises alerts. It can be deployed out-of-band (via a SPAN/mirror port or a tap) so it analyzes traffic without being inline, meaning it doesn’t measurably affect latency.
• An IPS (intrusion prevention system) is inline and can block threats, but that processing can introduce some latency and potential throughput impact.
• A firewall also inspects traffic and can add latency, though usually modest with proper hardware, but its primary purpose isn’t continuous passive analysis.
• A load balancer distributes traffic and isn’t used for intrusion analysis.

• The two correct options are:

• The two incorrect options:

• A) You can only apply a single template BOM to a service object.

• C) You can modify or delete lines in a BOM template regardless of whether the template has been associated to a service object, or not.

• B) You can apply many template BOMs to a service object — false; typically only one template per service object.
• D) You can modify/delete lines only if not associated — false; you can modify templates even after association (per C).

• According to the provided answer key, the four options are: Upload File, User Criteria, HR Profiles, HR Criteria (options B, D, F, G).

• Upload File: Filter by a file you upload (e.g., CSV) that provides data for bulk case creation.
• User Criteria: Filter by criteria related to users (e.g., role, department) to select target users.
• HR Profiles: Filter by HR profile data associated with users.
• HR Criteria: Filter by HR-related criteria or attributes.

• Storage accounts: storage1, storage2, and storage3
• Log Analytics workspace: Analytics3

• Azure Backup reports can send the AzureBackupReports diagnostic log to eligible storage accounts. The storage account’s subscription and region do not have to match the Recovery Services vault, so all three listed storage accounts are valid.
• The Log Analytics workspace must be in the same region as the Recovery Services vault for this configuration. Vault1 and Analytics3 are both in West Europe, making Analytics3 the valid workspace.

• En Cisco SD-Access, el fabric overlay se extiende hasta lo inalámbrico; los APs son nodos de borde del fabric y su tráfico queda dentro del overlay.
• El cliente inalámbrico genera tráfico que viaja por el overlay, pero no es un componente del fabric en sí.
• El WLC es principalmente una herramienta de gestión y control, no forma parte del overlay; el underlay es el transporte físico.

• Correct answer: No (B).

• To deploy and manage Azure VMs, you use Infrastructure as a Service (IaaS). IaaS provides the actual virtual machines you configure, patch, and control.
• Platform as a Service (PaaS) abstracts infrastructure and OS management and is used for hosting applications (e.g., web apps) on managed runtimes, not for provisioning and managing individual VMs.

• Pull: Downloads changes from the central repository and updates the local repository.
• Push: Sends local commits to the central repository.
• Commit: Records local changes in the repository’s history.
• Merge: Combines changes from different branches.
• Clone: Creates a new local copy of a repository.

• Answer: D

• The strongest security comes from enforcing access at the storage layer. An IAM policy scoped to the Cognito identity prefix restricts each user to their own S3 prefix (folder), so users can only access their own files regardless of client or server code.
• This per-user isolation reduces risk of cross-user data access and is more robust than UI validation or Lambda/API validation alone.
• Implementation note: attach a policy to the Cognito identity role that allows actions on arn:aws:s3:::your-bucket/${cognito-identity.amazonaws.com:sub}/* (per-user prefix). Ensure TLS in transit and enable at-rest encryption (SSE-S3 or SSE-KMS). Use multipart upload for large files up to 300 MB.