Microsoft AI-103 Exam Prep
Developing AI Apps and Agents on Azure (Page 3 )

• Personally identifiable information (PII) detection

• Prompt Shields

• Self-harm content filtering addresses self-harm-related content.
• Violence content filtering addresses violent content.
• Neither protects customer PII or detects document-based prompt injection.

• Internal hostnames and subdomains
• Network structure and naming conventions
• Servers and services
• Relationships between systems

• Determining ISP-assigned address space: Usually involves external registration and DNS information, not internal host discovery.
• Bypassing DNS sinkholing: Would require evidence that malicious DNS requests avoided redirection.
• Initial access: DNS queries alone do not show that the attacker gained access.
• Exfiltrating data: DNS tunneling can do this, but the snippet would typically show encoded or unusually long DNS queries.

• Compare each server’s drive specifications and performance data.
• Identify the drive that is faulty, slow, or mismatched.
• Replace it with a drive that matches the required interface, capacity, and performance characteristics.
• Avoid selecting a slower drive, because storage performance can bottleneck the entire server.
• In a redundant array, use a compatible replacement so rebuilding does not create unnecessary performance degradation.

• Works across SaaS and internal applications: TOTP is widely supported by authentication systems and can be integrated into many applications.
• Device manufacturer agnostic: A hardware token or authenticator application can generate the code without depending on a specific computer or phone manufacturer.
• Offline capability: The code is generated locally using a shared secret and the current time; an internet connection or cellular service is not required.

• Username and password: May work offline but provides weaker authentication and does not meet the intended improvement in security.
• Biometrics: Can depend on device hardware, operating-system support, and enrollment mechanisms.
• SMS verification: Requires cellular connectivity and is vulnerable to threats such as SIM swapping.

• 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.

• B. The community must be built with the Customer Account Portal template.

• C. An experience ID (expid) or placeholder parameter must be used in the URL.

• A: The Visualforce + Salesforce Tabs template does not provide this dynamic branding capability.
• D: An external CMS is not required. The branding configuration is handled within Salesforce Experience Cloud.

• The selling division receives a credit based on a favourable transfer price, often market price or full cost plus a profit margin.
• The receiving division is charged a lower amount, such as marginal cost or another agreed price.
• The difference is accounted for centrally by head office or a corporate adjustment.

• Azure Resource Manager (ARM) templates define the virtual machines and related Azure resources declaratively. You can deploy the same template repeatedly, ensuring consistent VM sizes, networking, storage, extensions, and other infrastructure settings.

• PowerShell DSC extension applies and maintains the required Windows configuration inside each VM. DSC is state-based: if a setting changes or becomes incorrect, DSC can bring it back to the desired configuration.

• Azure Pipelines deployment groups organize deployment targets, but they do not primarily enforce ongoing VM configuration.
• Custom Script Extension runs setup scripts, but it is generally less maintainable and does not continuously enforce configuration like DSC.
• Pipeline stage templates reuse pipeline workflow definitions; they do not configure the VMs themselves.

• Amazon EC2 instances — ???????? ?? ?? ??????? CPU, memory ??? instance size ???????? ???????
• AWS Lambda functions — memory configuration ?????????? ???????
• Amazon EBS volumes — volume type ?? size optimize ???? ???????
• ??????? ECS workloads — resource configuration ? cost optimization-?? ???????

• Memory ? compute usage ?????????? ???? custom code ????? ???? development ? maintenance ??????
• Cost allocation tags ???? ????? ??? ?????? ???? ??????? ???; inefficient resource ??????? ?? recommendation ???? ???
• CloudTrail resource ???? ?? API activity ??????, resource utilization ????

• Espionage: Stealing information for intelligence or competitive purposes.
• Data exfiltration: Unauthorized removal or transfer of data.
• Nation-state attack: A sophisticated attack sponsored by a government.
• Shadow IT: Unapproved technology or access methods used by employees.

• Code signing: Verifies the software’s authenticity and integrity; it does not hide the source code or prevent reverse engineering.
• Tokenization: Replaces sensitive data with tokens, mainly for protecting data such as payment information—not software logic.
• Blockchain: Provides a tamper-resistant record of transactions or data; it does not protect compiled code from analysis.

• Red team: Simulates attackers; exploits weaknesses to test security.
• Blue team: Defends systems; monitors, detects, and responds to attacks.
• Purple team: Combines red- and blue-team efforts to improve detection and defense.
• White team: Oversees or manages the test, defining rules, scope, and authorization.

• The servers are powered on.
• The network is functioning.
• Devices can still reach the server network.

• ARP poisoning: Redirects or intercepts local network traffic; it usually affects communication paths rather than overwhelming a service.
• Jamming: Disrupts wireless or radio signals. It would not fit a system that remains accessible from devices on the server network.
• Kerberoasting: Attempts to crack service-account credentials from Kerberos tickets; it does not normally cause an immediate outage.

• Encryption to preserve confidentiality
• Integrity protection to detect alteration
• Authentication of the server through certificates

• SHA-256: A hashing algorithm; it does not encrypt data for transmission.
• SSL 3.0: Obsolete and insecure. It should not be used.
• AES-256: A strong encryption algorithm, but by itself it does not provide the complete secure communication protocol needed for data in transit.

Statement 1 — Correct

Statement 2 — Correct

1. Install a Cassandra-compatible ODBC driver.
2. Configure a data source name (DSN), if required.
3. In Power BI Desktop, select Get Data > ODBC.
4. Choose the configured DSN and connect.

• Microsoft SQL Server database: Connects to SQL Server, not Cassandra.
• OLE DB: Requires a compatible OLE DB provider; this is not the standard choice for Cassandra in Power BI.
• OData: Requires Cassandra data to be exposed through an OData service, which is not the normal direct connection method.

• Future costs — Only costs occurring in the future can be affected by the investment decision. Past costs are sunk and irrelevant.
• Incremental costs — These are additional costs caused by choosing the investment. They are relevant because they differ between alternatives.
• Cash flows — Capital investment decisions are based on future cash inflows and outflows, usually discounted to present value.

• Committed costs have already been agreed or incurred and generally cannot be changed by the decision.
• Unavoidable costs will arise regardless of which option is selected, so they do not affect the choice.

• Blue team: Defends systems, monitors activity, and responds to attacks.
• Purple team: Coordinates red- and blue-team activities to improve defenses.
• White team: Oversees or manages the exercise, including rules and scope.

• How quickly the vendor must respond to an incident or request
• Target resolution times
• Availability or uptime requirements
• Performance metrics and penalties for not meeting them

• SOW (Statement of Work): Describes the project’s scope, tasks, deliverables, and timeline.
• MOA (Memorandum of Agreement): Documents a formal agreement to cooperate or perform specific activities.
• MOU (Memorandum of Understanding): Records a mutual understanding or intent, often less binding than a contract.

• Data loss prevention (DLP): Helps detect or prevent sensitive data from being copied or transmitted, but it does not primarily protect a stolen laptop’s stored data.
• Operating system hardening: Reduces vulnerabilities and attack surface but does not encrypt files if the device is stolen.
• Boot security: Helps ensure that only trusted software starts, but it does not fully protect the drive if an attacker accesses it offline.

• Accept: Acknowledge the risk and take no additional action.
• Transfer: Shift the risk or financial impact to another party, such as through insurance or a contract.
• Mitigate: Reduce the likelihood or impact using controls, such as firewalls, training, or backups.
• Avoid: Eliminate the activity that creates the risk.

• CSIRT: A Computer Security Incident Response Team that handles and coordinates incident response.
• CVSS: A scoring system used to rate the severity of vulnerabilities.
• SOAR: Security Orchestration, Automation, and Response technology used to automate security workflows.

• Active-active routers: Provide redundant Internet connections/devices. Both can operate, so traffic can fail over or be load-balanced.
• Active-active firewalls: Avoid a single firewall becoming a failure point while maintaining security inspection.
• Load balancers: Distribute requests across multiple web servers. If one server fails, traffic can go to the other.
• Redundant power supplies: A server with separate power supplies should connect to independent power sources or circuits.
• UPS A and UPS B: Provide backup power and redundancy. Ideally, each power supply is connected to a different UPS.
• SONET ring: A ring topology provides alternate paths if a fiber link or segment fails.

• Cloud architecture
• Data architecture
• Platform engineering
• Data engineering
• Provisioning and modernization

• Data protection is associated mainly with security and risk management.
• Data governance belongs to the governance perspective.
• Data science is not an AWS CAF capability.

• A — Correct: Flow Builder is declarative and visual, so administrators and other non-developers can participate in designing and improving business processes without writing Apex.
• D — Correct: Flow Builder provides visual debugging tools, allowing an admin to test paths, inspect variable values, and identify where a specific business case fails.
• E — Correct: A flow’s visual structure documents the logic and makes later maintenance easier than reading and updating custom Apex code.

• B — Incorrect: Flow debugging does not attach a debugger to live customer sessions. The admin uses Flow Builder’s debug functionality with test inputs; this is not live-session debugging and should not be used to monitor real customer transactions.

• Owner, Contributor, and Network Contributor provide sufficient management permissions.
• Reader can view Traffic Analytics data but cannot enable or configure it.

• Suspended an operator who correctly refused to use unsafe equipment.
• Rewarded another operator for using the equipment despite the broken safety guard.

• A — Management is not particularly concerned with managing risks.

• B — Employees will perceive that management does not care about health and safety risks.

• C — This factory’s safety record is likely to be poor.

• B — Single customer login across properties: Customer 360 Identity provides centralized identity services, allowing an organization to recognize a customer across multiple digital properties and applications. This helps UC understand authenticated activity as part of a broader customer identity.

• C — Multi-brand support: Customer 360 Identity can support multiple brands and user experiences. Identity services can remain centralized while correlating a customer’s activity across different corporate brands or channels.

• A: Customer 360 Identity does not automatically populate all data into Customer 360 Data Manager and Customer 360 Audiences. Integration and data configuration are still required.
• D: Tracking anonymous activity and linking it after sign-up may be possible through broader customer-data and tracking implementations, but it is not the primary Customer 360 Identity benefit tested here. Identity focuses mainly on authentication, registration, and cross-property identity correlation.

• 255.255.255.128 = /25: 128 total, 126 usable
• 255.255.255.192 = /26: 64 total, 62 usable
• 255.255.255.224 = /27: 32 total, 30 usable
• 255.255.255.240 = /28: 16 total, 14 usable

• One for the network address
• One for the broadcast address

• 8 total addresses
• 6 usable addresses
• Mask: 255.255.255.248

• Online payment fraud
• Account takeover
• Fake account creation
• Suspicious transactions

• Documented and evaluated
• Assessed for security, cost, and operational impact
• Reviewed and approved by the appropriate personnel
• Tested before implementation
• Tracked with version history and rollback procedures

• Risk management process: May help assess the issues, but it does not authorize and manage design changes.
• Product design process: Applies primarily while creating a new design.
• Design review process: Normally evaluates a design before release; this design is already released.

• Approve major information security policies
• Allocate funding and resources
• Set the organization’s risk appetite
• Ensure security supports business objectives

• Evaluating vendors is generally handled by security, procurement, or technical teams.
• Assessing risks is typically performed by security and risk-management professionals, with management accepting or prioritizing the risks.
• Monitoring regulatory adherence is usually handled by compliance, audit, or security functions.

• File hashes
• Strings and metadata
• Binary or code structure
• Known malicious patterns
• Embedded indicators or signatures

• Sandbox: Executes the file in an isolated environment; useful for observing behavior, but usually slower.
• Network traffic analysis: Examines communications generated by a system or application, not the file itself.
• Package monitoring: Tracks software packages or installations and is not the primary method for examining malware signatures.

• GPS coordinates
• Date and time the image was taken
• Camera or device information
• Image dimensions and software used

• Log data: Records generated by systems or applications, not normally embedded in image files.
• Encrypted data: Information intentionally encoded to prevent unauthorized access.
• Sensitive data: A broad classification, not the specific type of information being extracted.

• Crowd-sourced evaluation: Requires recruiting and managing many evaluators.
• Human-worker evaluation: Provides human judgment but requires coordination, labeling instructions, and quality control.
• RLHF: Is a training and alignment process, not simply a low-overhead model comparison method.
• Automatic model evaluation: Quickly evaluates outputs using predefined toxicity or quality metrics with minimal manual effort.

Why this is correct

• Each user authenticates with their own Google account.
• Google manages the user’s SSH key association.
• IAM controls who can access instances.
• Access can be audited by user identity, so security can determine who accessed a VM.
• Granting the role to a Google group avoids managing permissions individually.

Why the others don’t apply

• A: A shared private key is difficult to distribute securely and cannot reliably identify which employee used it.
• B: Manually collecting and deploying keys on every instance is operationally inefficient and complicates auditing.
• D: A project-wide shared key has the same identity and key-management problems as option A. It also does not provide per-user accountability.

• A — Correct: Identify the data required by Salesforce, its dependencies, and how it should be validated. Verification scripts help confirm record counts, relationships, field mappings, and data integrity after migration.
• D — Correct: Use a full sandbox and perform trial migrations using realistic—or appropriately masked—legacy data. This exposes transformation, volume, dependency, and integration issues before production cutover.
• B — Less appropriate: Phased user migration and parallel operation primarily address user adoption and rollout risk, not the technical risks of data migration.
• C — Less appropriate: Although sandbox testing and integration testing are valuable, the option emphasizes test-data generation rather than validating the migration with representative legacy data. “A full sandbox for all systems” may also be impractical.

• SQL injection
• Cross-site scripting (XSS)
• Malicious or malformed web requests
• Some application-layer abuse

• Layer 4 firewall: Filters based mainly on IP addresses, ports, and connections; it lacks detailed web-request inspection.
• NGFW: Provides broader network security, but a WAF is more specialized for protecting web applications.
• UTM: Combines multiple security functions, but it is not necessarily optimized for web-application protection.

• A. IDS attack signatures: An IDS primarily detects suspicious network activity; it is not the best control for scanning uploaded documents for malware.
• C. Load balancer: Distributes traffic among servers and improves availability, but does not inspect files for malware.
• D. WAF: Protects web applications against attacks such as SQL injection and command injection. It may help secure the upload function, but malware scanning is the key requirement here.

• Error correction (ECC): Improves data reliability but does not maximize bandwidth.
• RAM voltage: Increasing voltage may affect stability or speed, but it is not the primary method for increasing module bandwidth.
• Physical module size: Refers to the capacity or form factor of the RAM, not its data-transfer bandwidth.

• MAC flooding: Overwhelms a switch’s MAC address table, potentially causing traffic to be broadcast.
• DNS spoofing: Provides false DNS responses to redirect users.
• ARP poisoning: Sends false ARP information to associate an attacker’s MAC address with another device’s IP address.

• 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.

• T?o m?t Systems Manager Automation runbook d? ch?y l?nh kh?i d?ng l?i ?ng d?ng trên các EC2 instance.
• T?o m?t Amazon EventBridge rule ph?n ?ng khi CloudWatch alarm chuy?n sang tr?ng thái ALARM.
• Ð?t Automation runbook làm target c?a EventBridge rule.

1. Log c?a ?ng d?ng du?c ghi vào CloudWatch Logs.
2. CloudWatch alarm phát hi?n nhi?u l?i liên quan d?n vi?c restart.
3. Alarm chuy?n sang tr?ng thái ALARM.
4. EventBridge nh?n s? ki?n thay d?i tr?ng thái này.
5. EventBridge g?i Systems Manager Automation runbook.
6. Runbook restart ?ng d?ng trên các EC2 instance, không restart c? instance.

• A: SNS không tr?c ti?p g?i Systems Manager Automation runbook nhu m?t target native.
• B: Lambda có th? th?c hi?n vi?c restart, nhung ph?i t? x? lý vi?c xác d?nh instance và ch?y l?nh t? xa.
• C: Lambda ch? làm trung gian d? g?i runbook, không c?n thi?t vì EventBridge có th? g?i runbook tr?c ti?p.

• Users logging in more frequently than average
• Logins occurring during non-business hours
• Patterns that may indicate compromised credentials or suspicious access

• Login History: Shows individual login attempts and basic details, but does not provide behavioral analysis or averages.
• Login Inspector: Used to troubleshoot or inspect a specific login attempt, rather than analyze organization-wide patterns.
• Login Report: May provide reportable login information, but it is not the specialized tool for forensic behavioral analysis.

• A — If there is no demand, there should be no production.

• B — Not all sales equal profit.

• C — Stocking up on inventory is bad for business.

• D — All costs, except materials, are considered fixed.

• E — Departments should operate at full capacity regardless of bottlenecks.

• 16 VMs: one failure loses 25 GB and 10 cores—only 6.25% of memory.
• 8 VMs: one failure loses 12.5% of memory.
• 4 VMs: one failure loses 25%.
• 1 VM: one failure loses the entire application environment.

• Secret scope: A named container that groups related secrets and defines access permissions. Example: finance-prod.
• Secret key: The name of an individual secret stored inside that scope. Example: db-password.

text 
Scope: finance-prod 
  Key: db-username 
  Key: db-password

python 
dbutils.secrets.get( 
    scope="finance-prod", 
    key="db-password" 
)

• Deploy five individual VMs: This does not create a VM scale set.
• Modify Availability Zones or Size settings: These actions do not create the required scale set and add unnecessary steps.
• VM orchestration mode: This is Flexible orchestration, intended for more individually managed VMs and mixed configurations. It is not the best choice for a straightforward group of identical instances.

1. Select Exchange email as a location.
2. Use the built-in Azure Storage Account key sensitive information type as the condition.
3. Configure the DLP action to encrypt the email—for example, using Microsoft Purview Message Encryption.