ICF ICF-ACC Exam Prep
Associate Certified Coach (Page 2 )

• PC A: 192.168.1.10/24
• PC B: 192.168.2.10/24

• Both PCs have a correct default gateway
• A router or Layer 3 switch connects the subnets
• Routing and firewall rules allow the traffic

• Security groups
• Dynamic security groups
• Cloud-only or synchronized security groups

• Microsoft 365 groups
• Distribution groups
• Mail-enabled distribution groups

• Which batches and markets are affected
• Whether the deficiency affects product quality, efficacy, or patient safety
• Whether the issue is an ongoing manufacturing problem
• Whether immediate containment or distribution suspension is needed

• A — Withdraw the product: may be necessary, but is premature before assessing the risk.
• B — “Dear Dr.” letter: may be appropriate later, depending on the risk.
• C — Notify global authorities: may become mandatory, but the scope and urgency depend on the assessment.

• What information each stakeholder needs
• When and how often it should be communicated
• Which format or channel should be used
• Who is responsible for communicating it

• A: The team should not decide stakeholder communications without first checking the established plan and CEO’s needs.
• B: An executive summary may be appropriate, but choosing a solution before reviewing the plan is premature.
• D: The stakeholder engagement plan addresses how to engage stakeholders, but this is primarily a communication planning issue.

• Azure Machine Learning Studio is designed to build, test, train, and deploy machine-learning models, including predictive analytics.
• Azure Cosmos DB is a globally distributed NoSQL database. It can store data used by an AI solution, but it is not the primary service for developing and deploying predictive models.
• Therefore, the appropriate recommendation is Azure Machine Learning Studio, as shown in Question 15.

• A — .gitignore: Controls Git tracking; it does not configure Copilot exclusions.
• B — copilot.ignore: This is not the standard GitHub Copilot Business exclusion mechanism.
• D — Renaming files: Adding _no_copilot has no recognized effect.

• Data source: Folder
• Transformation: Remove the Content column (or keep only the file-metadata columns)

Why

• File name
• Extension
• Date modified
• Folder path
• Content — the binary contents of the file

• Access List: controls whether a client is allowed or denied.
• Connect List: controls which wireless networks/APs a station may connect to.

• Base table — the table containing common inherited fields
• Parent table — the table directly extended by the child
• Other tables in the hierarchy

• JDBC
• SnowSQL
• Snowflake Web Interface (UI)
• ODBC
• Python connector

• 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

• Installing software
• Applying configuration changes
• Calling PowerShell scripts
• Running setup or customization commands

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

• GPO logon script: Runs only when a user logs on and depends on domain/GPO processing.
• GPO startup script: Runs during startup, but requires the VM to be domain joined and receives the applicable GPO.
• Place scripts in a VHD: Merely makes the scripts available; it does not automatically execute them.

• Data Cloud combines data from multiple systems.
• It resolves and organizes that data into a unified customer view.
• That unified view enables downstream actions such as personalized campaigns, segmentation, analytics, and activation.

• A = core platform value
• D = a resulting business use case or benefit

• Standardize which services users can deploy
• Apply governance and access controls
• Manage approved product versions
• Give users self-service access to authorized resources

• AWS Control Tower: Sets up and governs a multi-account AWS environment.
• AWS Cloud Map: Provides service discovery for applications.
• AWS Clean Rooms: Enables privacy-preserving collaboration on data analysis.

• Instant messaging/chat: Can be abused to send malicious links or attachments, but P2P file sharing is the more direct high-risk source.
• E-mail: A common malware delivery method, but this question specifically emphasizes an application type associated with direct file exchange.
• End-to-end applications: This describes communication protection or architecture, not a specific application category known for malware distribution.

1. Horizontal scaling — Yes

1. Vertical scaling — Yes

1. Scaling can manage costs — Yes

• Horizontal = more or fewer instances
• Vertical = larger or smaller instances

• Wireshark captures packets and allows you to examine their contents, potentially revealing usernames and passwords sent without encryption.
• Netcat creates network connections and can send or receive data, but it is not primarily a packet-analysis tool.
• Nessus scans for known vulnerabilities and configuration issues; it generally would not prove that credentials are visible in transit.
• Nmap performs network discovery and port/service scanning, not detailed packet-content inspection.

• Red team: Simulates attackers and tests exploitability.
• Blue team: Defends, monitors, detects, and responds to attacks.
• Purple team: Combines red- and blue-team activities to improve cooperation and defenses.
• White team: Manages and oversees the rules, scope, and authorization of the exercise.

• The Speech resource subscription key
• The Azure region
• Optional endpoint and speech settings

python 
speech_config = speechsdk.SpeechConfig( 
    subscription=key, 
    region=region 
)

• SpeechSynthesizer converts text to speech.
• It uses a SpeechConfig, but it does not configure the service connection itself.

• AudioConfig: Defines audio input or output sources.
• AudioOutputConfig: Defines where synthesized audio should be sent.
• SpeechConfig: Configures the Azure Speech service connection.

• A Screen Flow can present a form that inspectors complete and submit on an Experience Cloud page.
• It can collect inspection findings, validate the input, and create or update records.
• An Autolaunched Flow has no user interface, so it cannot directly provide the form.
• A Related List only displays related records, and Record Detail is primarily for viewing or editing an existing record—not for a custom inspection submission form.

• state preserves the client’s original context, such as the specific idea URL the user requested.
• The portal sends that value in the OAuth authorization request.
• Salesforce returns it after authorization, allowing the portal to redirect the user to the original idea rather than the Ideas home page.

• Shared capacity

• Fabric capacity — F SKUs

• Fabric trial capacity

• Existing Power BI Premium — P SKUs

• Namespace: The namespace associated with the code where the checkpoint was set.
• Time: When the checkpoint was captured or executed.

• Exception: Exceptions are viewed through debug logs or execution results, not as the primary Checkpoints tab information.
• Debug Statement: System.debug() output belongs in the Logs tab. A checkpoint captures program state, such as variables and their values, at a specific point in execution.

• Storage usage of files stored in Microsoft Teams: SharePoint site usage report

• Number of active users per team: Microsoft Teams usage report

1. SharePoint site usage report
2. Microsoft Teams usage report

• A. PsFile — Correct: Displays files opened remotely on a system. This reveals shared resources and user activity.
• B. UserInfo — Correct: Gathers information about user accounts, supporting account and privilege enumeration.
• C. PsPasswd — Answer key lists it: This is questionable. PsPasswd is primarily used to change passwords remotely, not enumerate information. The key may classify it broadly as a Windows account-management tool, but it is not a strong enumeration example.
• D. WinSSLMiM — Incorrect: Used for SSL man-in-the-middle activity, not enumeration.

1. Search & Intelligence in the Microsoft 365 admin center — No

1. Audit in the Microsoft Defender portal — Yes

1. Audit in the Microsoft Purview portal — Yes

• Azure Cosmos DB is a globally distributed NoSQL database service. It stores and retrieves application data, but it does not provide the complete environment for building, testing, and deploying predictive analytics models.
• Azure Machine Learning is the appropriate service for this requirement. It supports creating experiments, training and testing models, and deploying them for predictions.
• Azure Machine Learning Studio provides the browser-based interface for these tasks.

• Note the question number before leaving—for example, Question 38.
• Use the exam’s question navigator or Back/Previous button to return to that number.
• If you close or refresh the page, your position may not be saved, depending on the site. Reopen the page and select the question number again.
• Avoid using the browser’s Back button if it causes the exam page to reload; use the exam’s built-in navigation instead.

• Lower order numbers appear first.
• For example, a variable with order 100 appears before one with order 200.
• The Sequence field is not the control used for catalog variable display order.
• The Default Value sets a value, not placement.
• The Choice field defines selectable options, not the variable’s position.

• A is incorrect: Flow Debugger is for debugging Salesforce Flows, not Trust Layer masking.
• B is incomplete/misleading: Requesting audit data may be part of reviewing the results, but collection and storage must first be enabled.
• C is correct: It describes the initial validation step.

• A: Knowledge of IT platforms, networks, and methodologies — Useful technical knowledge, but the CISO does not need to be the deepest technical expert.
• C: Regulatory and project management knowledge — Important, but compliance and projects must still support the organization’s broader needs.
• D: Managing people and resources — Essential for execution, but effective management of the wrong security priorities will not produce good results.

• Layer 1: Check cables, power, and link lights.
• Layer 2: Check switching, VLANs, and MAC learning.
• Layer 3: Check IP addressing, routing, and gateways.
• Higher layers: Check services, applications, and user settings.

• Create a plan of action: Decide how to implement the fix.
• Implement the solution: Apply the selected fix.
• Verify functionality: Confirm the problem is resolved and systems work normally.

• 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.

• Install unauthorized or unapproved applications
• Access system areas normally restricted
• Add features unavailable in the default software
• Modify the device’s operating system

• SQL injection (SQLi): Attacks databases by inserting malicious SQL commands.
• Cross-site scripting (XSS): Injects malicious scripts into web pages viewed by users.
• Sideloading: Installs an application from outside the official app store, but it does not necessarily remove the phone’s operating-system restrictions.

• On-premises resources, such as an existing database
• Cloud resources, such as Azure services or virtual machines
• Connectivity that allows the application to use both environments

• Public cloud: resources are entirely provided through a public cloud provider.
• Private cloud: resources are dedicated to one organization, typically on-premises or privately hosted.

• A is correct: It establishes the revised dates and identifies the effect on the critical path.
• B is premature: Stakeholders should be informed after the impact has been assessed and the updated schedule is understood.
• C is not automatically appropriate: Fast-tracking may introduce additional risk and should be considered only after analyzing schedule options.
• D is premature: Adding resources may not resolve a dependency and could increase costs without addressing the actual constraint.

Box 1: No

• configure_azure_monitor() configures Azure Monitor and the OpenTelemetry pipeline.
• LangChain requires its own instrumentation or callback tracer, such as AzureAIOpenTelemetryTracer.
• You must pass the tracer to the LangChain execution configuration so chains, tools, prompts, and model calls become spans in Application Insights.

Box 2: Yes

text 
OTEL_SERVICE_NAME=customer-agent 
OTEL_SERVICE_NAME=invoice-agent

• An active relationship is used automatically when filters are evaluated. An inactive relationship does not propagate filters unless explicitly activated in DAX, so it would not reliably enforce the required security behavior.
• Apply security filter in both directions allows RLS filters to propagate across the relationship in both directions. This ensures that bidirectional filtering respects the RLS rules applied to both tables.
• Assume referential integrity is unrelated to RLS. It is mainly a DirectQuery optimization that allows Power BI to use an inner join when matching keys are guaranteed to exist.
• The relationship must therefore be active, with security filtering enabled in both directions.

• On VirtualNetworkA: enable Allow gateway transit.
• On VirtualNetworkB: enable Use remote gateways.

• Input validation: Prevents malicious or malformed input within an application; it does not authenticate a software package.
• Secure cookies: Protect web-session cookies; they do not protect downloadable software.
• Fuzzing: Tests software by supplying unexpected input to find vulnerabilities; it does not verify software integrity.

• Asynchronous inference is designed for applications that submit individual inference requests, place them in a queue, and retrieve results later. It is useful when requests may take a long time or when traffic is intermittent.
• Batch transform is designed specifically to run inference over an entire large dataset stored in Amazon S3 and produce an output dataset.

• Large dataset/offline processing ? Batch transform
• Large or slow individual requests processed later ? Asynchronous inference

1. CALCULATE
2. AND
3. FILTER

DAX 
Transaction Category = 
CALCULATE( 
    MAX('Transaction Size'[Size]), 
    FILTER( 
        'Transaction Size', 
        AND( 
            Sales[Sales Amount] >= 'Transaction Size'[Minimum], 
            Sales[Sales Amount] <= 'Transaction Size'[Maximum] 
        ) 
    ) 
)

• FILTER examines the rows in the Transaction Size table.
• AND ensures the sales amount falls between the category’s minimum and maximum values.
• CALCULATE evaluates the result in the modified filter context and returns the matching category.