Palo Alto Networks PCCSA Exam Prep
Palo Alto Networks Certified Cybersecurity Associate (Page 5 )

• Matching hashes: The software is likely unchanged.
• Different hashes: The software or its contents have been modified.

• Encryption: Protects confidentiality, not primarily integrity.
• Baselines: Document expected configurations and support comparison, but hashing is more directly suited to verifying file integrity.
• Tokenization: Replaces sensitive data with tokens and is unrelated to software tampering.

• Formatting: May remove file-system references but often leaves recoverable data.
• Degaussing: Uses a magnetic field to erase data, but can damage or make magnetic drives unusable.
• Defragmentation: Rearranges data for performance; it does not securely erase information.

• Streams — track change data for tables or views.
• External tables — reference data stored in an external cloud storage location.

• Role — account-level security object.
• Warehouse — account-level compute resource.
• User — account-level security object.
• Share — account-level object used to share data.

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

• Where to find the TiMOS runtime image
• Which configuration file to load
• The IP address and related settings for the CPM management Ethernet port

• A: User authorization is configured in the router’s security configuration, not primarily in the BOF.
• C: Hardware initialization is performed by the boot process and system software.
• D: The system date and time are configured separately, often through NTP or CLI settings.

• desktopwidth:i:1280
• desktopheight:i:1024

• Connection information: Controls connection-related settings, not the desktop resolution.
• Scaling plan: Controls when session hosts start, stop, or scale based on demand.
• Session behaviour: Controls behavior such as disconnect or logoff handling.
• Display settings: Specifically controls RDP display properties, making it the appropriate choice.

• Form layout
• Related lists
• Dictionary settings
• UI policies
• Client scripts
• Views and field visibility

• Personalization usually affects only the individual user.
• System configuration can affect other users, depending on its scope and conditions.

• D — Managers focus on keeping costs low in the short term to maximise profits.

• E — Managers are given incentives to meet or undercut budgets.

• F — Managers delegate responsibility simply to reduce their workload.

• Correct exam answer: A — HKEY_LOCAL_MACHINE
• The relevant location is associated with HKEY_LOCAL_MACHINE\SAM.
• The SAM does not store passwords in plain text; it stores password hashes.

• HKEY_CURRENT_USER contains settings for the currently logged-in user, not the account-password database.
• HKEY_USERS contains user profiles and settings loaded for users.
• HKEY_CURRENT_CONFIGURATION contains hardware/profile configuration information.

• Virtual introductions: Team members share their role, experience, location, and working preferences.
• Online icebreakers: Short, informal activities such as “two truths and a lie.”
• Virtual coffee chats: Pair team members for informal, non-project conversations.
• Collaborative problem-solving: The team works together on an online puzzle or scenario.
• Retrospectives: The team discusses what went well, what did not, and how to improve.
• Working-agreement sessions: The team agrees on response times, meeting etiquette, communication channels, and handoffs.
• Recognition sessions: Members acknowledge one another’s contributions.
• Remote workshops: Teams jointly create plans, diagrams, or schedules using collaboration tools.

Correct sequence

1. Merge Sales_Region with Sales_Manager using an inner join

1. Merge Region_Manager with Manager using an inner join

1. Merge Sales_Region and Region_Manager using a right join as a new query

• Annual interest payments net of tax relief (A): future cash outflows for the issuer.
• Redemption value (B): the final cash outflow when the bond is redeemed.
• Market value now (C): the cash proceeds received now, acting as the initial cash flow in the IRR calculation.

• 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.

• MFA: Protects sign-in and authentication.
• Azure Key Vault: Protects deployment secrets and credentials.
• Answer: No (B).

• 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.

• Box 1: No — The rule requires user.department to equal Engineering. Engineer does not match, so User1 is not in AU1. Admin1 cannot reset User1’s password.
• Box 2: No — Admin1’s role is scoped to AU1 and cannot manage users outside that AU.
• Box 3: Yes — Admin2 is a Global Administrator and can reset User3’s password.

• Architects design overall Splunk infrastructure and data strategy.
• Administrators manage configuration, access, and system operations.
• Knowledge Managers create and maintain knowledge objects such as data models, field extractions, and event types. They may support pivots, but they are not the primary users of them.

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

• Business risks
• Potential financial, operational, legal, or reputational impact
• How governance reduces risk to organizational objectives
• How much risk the organization is willing to accept

• Smartphones and tablets
• Laptops and workstations
• Other mobile or endpoint computing devices

• Tokens: Individual units of text processed by a model, such as words, subwords, or characters.
• Models: Systems that learn patterns and generate predictions or outputs.
• Binaries: Data represented using the binary number system, not semantic representations.

• 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.

• The application stores data on Amazon EBS volumes, so the encryption should be applied directly to those volumes.
• EBS encryption uses AWS-managed cryptographic operations and is designed to provide encryption at rest with minimal performance impact.
• The volumes are created during initial deployment, so they can be configured as encrypted when provisioned.

• B: Moving data to an encrypted S3 bucket changes the storage design and does not encrypt the EBS data the application uses.
• C: A custom encryption algorithm adds application overhead and is unnecessary.
• D: Ephemeral disks are temporary storage and can lose data when instances stop or terminate. Encrypting only the AMI’s root volume does not protect data stored elsewhere.

• Additional running costs: $800
• Less depreciation: $300

• The $100 reduction in fixed production overhead absorbed is only an accounting reallocation. It does not represent an actual saving in total fixed overhead.

• Response and resolution times
• Availability or uptime
• Performance targets
• Support obligations
• Penalties for failing to meet commitments

• SOW (Statement of Work): Describes the work, deliverables, scope, and tasks.
• MOA (Memorandum of Agreement): Documents a formal agreement about roles or responsibilities.
• MOU (Memorandum of Understanding): Records a general mutual understanding, often without detailed service metrics.

Statement 1 — Correct

Statement 2 — Correct

• Customers may boycott V’s products.
• Supermarket customers may stop buying from V.
• Investors may view V as having higher legal, ethical and reputational risk.
• V could face fines, lawsuits, contract losses and higher costs.
• Expected future profits may fall.

• Azure DevOps Analytics views are accessed through the Power BI Azure DevOps (Boards only) connector.
• This connector authenticates directly to Azure DevOps Services and lets you select an Analytics view.
• Analytics views allow filtering and shaping data in the cloud before Power BI loads it.
• Azure DevOps Server (Boards only) is for an on-premises Azure DevOps Server instance, not Azure DevOps cloud.
• A generic OData Feed connection can access OData endpoints, but it is not the purpose-built connector for Azure DevOps Analytics views.
• “OData queries” describes the underlying technology or query approach, not the most appropriate Azure DevOps connector choice here.

• Security controls
• Processes and procedures
• Compliance evidence
• Performance against contractual requirements

• Service-level agreement (SLA): Defines expected service performance, such as uptime and response times.
• Memorandum of agreement (MOA): Documents a general agreement between parties, but does not necessarily provide audit rights.
• Supply chain analysis: Identifies risks across suppliers and dependencies, but is not a contractual mechanism for reviewing vendor controls.

• 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

• C. An auto-labeling policy for a retention label
• D. A retention label

1. Create a retention label configured to:

1. Create an auto-labeling policy that detects the built-in Credit Card Number sensitive information type (SIT) and automatically applies the retention label to matching messages and documents.

• The JSON files contain one billion items, so this is a big-data workload.
• PySpark uses Apache Spark’s distributed, parallel processing, allowing the data to be processed across multiple compute nodes.
• It can read and transform data directly from OneLake, helping minimize unnecessary data movement or duplication.
• A Fabric notebook can also support exploration and visualization, as well as Spark-based analytics and anomaly-detection workflows.

• Pandas is primarily in-memory and generally suited to smaller datasets. One billion records would be impractical on a typical single machine.
• A Power BI report with core visuals is appropriate for visualization and sharing, but it is not the best tool for large-scale transformation, parallel processing, or anomaly detection. It would normally consume prepared data rather than perform the entire workload.

• Deterministic approve/reject results
• Strict adherence to predefined rules
• Consistent, reproducible outcomes
• Auditability and regulatory compliance

• Disable default accounts: Default or unused accounts may have known usernames or predictable settings, making them targets. They should be disabled, removed, or securely configured.
• Remove unnecessary services: Every running service creates potential vulnerabilities. Removing services the server does not need reduces exploitable entry points.

• Add the server to the asset inventory: Important for asset management, but not a hardening step.
• Document default passwords: Default passwords should be changed or eliminated—not documented for continued use.
• Send server logs to the SIEM: Valuable for monitoring and detection, but generally performed as part of logging/monitoring configuration.
• Join the server to the corporate domain: May be necessary operationally, but does not itself harden the server.

• Relationship cardinality:

• Filter direction:

• Active versus inactive relationships: only active relationships automatically propagate filters.
• Blank or unmatched values: a fact-table value without a matching dimension row can create the model’s blank/unknown member.
• Uniqueness: the “one” side must contain unique values; duplicate keys generally belong on the “many” side.

• IDS attack signatures: Primarily detects suspicious network activity; it is not the best control for scanning uploaded documents.
• Load balancer: Distributes traffic and can improve availability, but does not inspect files for malware.
• WAF: Helps block web attacks such as command injection and SQL injection, but it is not primarily a malware-scanning solution.

• Defender for Servers is the Defender for Cloud plan that protects Azure VMs and generates security alerts that can be reviewed in Defender for Cloud.
• Azure Diagnostics extension collects guest OS monitoring data, but it does not onboard VMs to Defender for Cloud or provide Defender security alerts.
• Data connectors are used for Sentinel integrations.
• Azure Storage Analytics and workflow automation do not provide VM protection.

• Un AG puede tener réplicas en Windows y Linux desde SQL Server 2017; por tanto, una réplica Windows y otra Linux es posible.
• Sin embargo, las réplicas de un AG deben utilizar normalmente la misma versión principal de SQL Server. Una instancia SQL Server 2017 no puede tener directamente una réplica secundaria SQL Server 2019 como configuración normal y permanente.
• En tu escenario, SQL Server 2017 en Windows y SQL Server 2019 en Linux no se pueden añadir directamente como réplicas equivalentes de AG1. Primero habría que realizar un proceso de actualización/migración compatible, por ejemplo mediante una actualización gradual o una tecnología de migración como log shipping o distributed availability groups, según el diseño.

• Tipo de clúster y mecanismo de quorum.
• Failover normalmente manual en configuraciones multiplataforma.
• Edición y características compatibles.
• Configuración de endpoints y permisos.
• Limitaciones específicas de SQL Server en Linux.

• A. IDS attack signatures: Detects suspicious network activity, but is not primarily designed to scan uploaded files for malware.
• C. Load balancer: Distributes traffic among servers and improves availability; it does not inspect files for threats.
• D. WAF: Protects web applications from attacks such as SQL injection and command injection, but its primary role is not malware scanning of uploaded documents.

• Label applied does not automatically exclude a file from Copilot.
• Encryption/usage rights determine whether Copilot can access the file’s content.
• If the user has no permission under Label2, File3 should be unavailable to Copilot for that user.
• File3’s label might be inherited by derived content only if File3 was actually processed and contributed by an authorized user; it should not be treated as contributing merely because it exists in the source set.

• 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.

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

• Layer 4 firewall: Filters based mainly on IP addresses, ports, and transport protocols; it cannot deeply inspect web application content.
• NGFW: Provides advanced network filtering and may include application awareness, but a WAF is more specifically designed to protect web applications.
• UTM: Combines several security functions in one appliance, but it is not the most targeted solution for a web portal.

• Deterrent control: The signs warning that people may be filmed can discourage unauthorized activity. They do not physically prevent the activity, but they may influence behavior.
• Detective control: CCTV detects or records activity so security personnel can identify incidents and investigate them later.

• Preventive: Stops an incident from occurring, such as a locked door.
• Corrective: Restores systems after an incident, such as backups.
• Directive: Instructs people what to do, such as security policies or warning instructions.
• Compensating: Provides an alternative control when the preferred control cannot be used.

• API tool matcher: runs a deterministic normalization command after the API tool returns.
• Write/Edit matcher: checks whether the target path begins with src/api/ and runs the linter.

json 
{ 
  "hooks": { 
    "PostToolUse": [ 
      { 
        "matcher": "api_tool", 
        "hooks": [ 
          { "type": "command", "command": "normalize-to-snake-case" } 
        ] 
      }, 
      { 
        "matcher": "Write|Edit", 
        "hooks": [ 
          { "type": "command", "command": "lint-if-under-src-api" } 
        ] 
      } 
    ] 
  } 
}

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

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

• S3 Glacier Deep Archive is designed for long-term archival data with very infrequent access and has a lower storage cost than S3 One Zone-IA.
• The documents are copies stored elsewhere, so reduced availability and delayed retrieval are acceptable.
• An S3 interface VPC endpoint allows private access from the VPC without exposing the bucket through the public internet.
• A bucket policy can restrict access to requests coming through that endpoint.

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

• 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.

• 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.