ASIS ASIS-PSP Exam Actual Questions
Physical Security Professional (PSP) (Page 27 )

• 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.

• 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.

• Custom domains
• 10 GB storage per web app
• Each app runs on dedicated compute
• Load balancing between instances is included
• Costs minimized

• Answer: A (Standard)

• Why:

• Note: In App Service, multiple apps in the same plan share compute resources. If you truly need isolation per app, you’d typically use separate App Service Plans, which increases cost beyond a single Standard plan.

• Answer: No.

• Why: Microsoft Managed Desktop (MD) is a managed service for end-user desktops (Windows devices used by people), not a service for provisioning, managing, or lifecycle-managing large fleets of virtual machines. It won’t help automate weekly creation and deletion of many VMs, especially with mixed OS (Windows and Linux).

• Relevant concept: To reduce administrative effort for rapidly provisioning and tearing down VMs, an Azure service like Azure DevTest Labs is appropriate. DevTest Labs lets you:

• Takeaway: The proposed solution (MD) does not meet the goal; the correct approach is to use a lab-oriented service such as Azure DevTest Labs for frequent, ephemeral VM deployments.

• 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.

• Approval publish: Request approval from a manager of the knowledge base before moving the article into the publish state.
• Instant Publish: Immediately publishes a draft article without requiring an approval.
• Instant Retire: Immediately retires a published article without requiring an approval.
• Retire Knowledge: Moves a knowledge article to the retired state.

• These are the base knowledge workflows that control how articles move between states (Draft, Published, Retired) and whether approvals are required.
• The other options describe different lifecycle actions, but these four cover the standard publish/retire workflows in ServiceNow.

• ProductSearchModel.getProductSearchHits() — option C
• ProductSearchHit.getRepresentedProducts() — option B

• ProductMgr.queryAllSiteProducts() (A) queries every product in the site, which is heavy and not scalable for large catalogs.
• Category.getProducts() (D) retrieves all products in a category; this can be slow for large categories.
• Using the search model and hits (B and C) leverages the search index, supports paging, and avoids scanning the entire catalog, making it more scalable.

• 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.

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

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

• 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.

• 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.

• The correct answer is A: CCTV recordings are not regularly reviewed.

• CCTV is a monitoring/control mechanism. If recordings aren’t reviewed, security events (break-ins, policy violations, equipment tampering) can go undetected and unaddressed.
• Regular review is essential for deterrence, incident response, and forensic evidence. Without it, the entire CCTV control provides little value.

• B (records deleted after one year) affects forensic availability, but it’s a data-retention issue rather than the ongoing effectiveness of the surveillance program.
• C (footage not recorded 24x7) creates gaps in coverage, which is a concern, but regular review of available footage still supports detection; 24x7 coverage is a separate policy/perimeter issue.
• D (cameras not in break rooms) is more about privacy and space planning than core data-center security monitoring.

• Equipment and hardware
• Facilities
• Inventory
• Backup media
• Supplies stored at an alternate or remote location

• Personal belongings of staff: Usually not organizational assets.
• DR line-item revenues: Revenue is a financial impact, not a physical asset.
• Cloud-based applications: These are primarily logical or information-processing assets, even though they depend on physical infrastructure.

• Why this is correct: In Azure Virtual Desktop, user access to a host pool is controlled through App Groups. The default app group for a host pool publishes the full desktop, so adding members to that app group grants them sign-in and access to the desktop (and any RemoteApps in that group). This is the standard way to give users access to AVD resources.

• Why the other options are not correct:

• Practical steps (high level):

• Amazon GuardDuty: Detects suspicious activity and threats using security-related data sources; it is not primarily a software vulnerability scanner.
• Amazon Detective: Helps investigate and analyze the root cause of security findings after an event.
• Amazon Cognito: Provides user authentication and authorization for applications.

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

• Correct answer: D — use the same hashing algorithm as the sender's to create a numerical representation of the file.

• Integrity is verified by recomputing the hash on the received data and comparing it to the sender’s hash. This must use the same hash function; if you use a different algorithm, the digests won’t match even if the data is intact.
• The hash output is a fixed-length digest (a numerical representation). Whether you call it a “binary image” or a “numerical representation,” the key is that you generate the same type of digest with the same algorithm and compare them.

• A: same algorithm but the result is described as a binary image instead of a digest; you still compare the digest, but the phrasing is less precise.
• B/C: using a different algorithm would produce a different digest, causing false mismatch or failure to verify integrity.

• 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.

• Each statement is evaluated as True (Yes) or False (No) independently.
• Key Azure facts to recall:

• The correct option is B: AWS Storage Gateway.

• Why: The scenario requires backing up on-prem data to AWS without changing existing backup workflows. AWS Storage Gateway provides a hybrid storage solution; specifically, the Tape Gateway emulates a physical tape library, allowing your existing backup software to write to virtual tapes that are stored in AWS (in S3 or S3 Glacier). This lets you back up 10 TB to the cloud while preserving current backup workflows and on-prem infrastructure.

• How it would work: Deploy a gateway appliance or VM on-site, connect your tape-based backup software to the virtual tape library, and start writing to virtual tapes. The data is then archived in AWS, freeing up local storage.

• Why the others aren’t suitable:

• Quick tip: If you weren’t using tape, File Gateway could be another option for file-based backups; Tape Gateway is the right pick for tape-based workflows.

• 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.

• Assign users or their team an appropriate security role.
• Ensure the role has the required table privileges, such as read, create, write, and append.
• Share the app with that security role in the app designer.

• Dynamics administration center: Used for environment and service administration, not routine app access configuration.
• Manage Roles: Not the specific Dataverse area used to define app and data permissions.
• Security Roles: Define what users can access and which operations they can perform.

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

• 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.

• State is stored remotely in Terraform Cloud/Enterprise, not as a local file.
• Terraform runs (plan/apply) can be executed on remote infrastructure, with results visible in the remote workspace UI.
• Supports workspace-based organization, state locking, and concurrency control.
• Useful for team collaboration, centralized governance, and auditable logs.

• In your configuration, you use a backend block like backend "remote" { ... }.
• You still run terraform init to configure/migrate to the remote backend.
• After setup, terraform plan/terraform apply may be executed remotely, and the outputs/logs appear in the Terraform Cloud/Enterprise UI rather than (only) in your local terminal.

• Other backends store state remotely but typically do not provide remote execution; with the remote backend you get remote runs and a collaborative UI, not just remote state storage.

Simple explanation

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

• 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:

• 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.

• A. Implement retries with exponential backoff

• C. Reduce the frequency and/or size of requests

• B. Use PutRecord instead of PutRecords — PutRecord sends one record per call and does not remove the underlying throughput limitation. It may increase request overhead.
• D. Use Amazon SNS instead — SNS is not a direct fix for Kinesis shard throttling and changes the required streaming architecture.
• E. Reduce KCL consumers — KCL consumers read from Kinesis; they do not solve producer-side PutRecords throttling.

• wyjasnic istniejace pytania z tej strony,
• wskazac, dlaczego dana odpowiedz jest poprawna lub bledna (z uwzglednieniem celów egzaminu),
• omówic koncepcje zwiazane z Google Cloud AI.

• Correct answer: B — A reservation for the server based on the MAC address.

• Why this is the best choice:

• Why the other options are less suitable:

• Quick takeaway: Use a DHCP reservation to give the file server a fixed IP while still benefiting from centralized DHCP management.