The Open Group OGEA-103 Exam Prep
TOGAF Enterprise Architecture Combined Part 1 and Part 2 (Page 9 )

• Honeypots: Decoy systems designed to attract attackers. Legitimate users should not access them, so activity there is a strong indication of unauthorized access.
• DNS sinkholes: Redirect requests for known malicious domains to a controlled internal destination instead of the real attacker infrastructure. Security teams can then identify infected systems making those requests.

• Tokenization: Replaces sensitive data with non-sensitive tokens; it protects data but does not detect intruders.
• CI/CD: Software development and deployment processes.
• Threat modeling: Identifies potential threats before or during system design, rather than detecting successful infiltration.
• Data obfuscation: Makes information harder to understand, but is not an attacker-detection mechanism.

• Determine risk tolerance: Tolerance defines how much variation or exposure the organization is willing to accept. Scenarios may help apply tolerance, but they do not primarily determine it.
• Determine risk appetite: Risk appetite is established at an enterprise or governance level. Scenarios help compare risks with the appetite; they do not normally establish it.
• Develop risk responses: Once risks are identified and assessed, scenarios support response planning. However, response development comes later.

• Bronze: Raw ingested data
• Silver: Cleaned, validated, and transformed data
• Gold: Business-level data for analytics, dashboards, and reporting

• 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

• 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.

• C. Case after-insert trigger that publishes a Platform Event

• D. Custom Apex controller that publishes a Platform Event

• A. Trigger with a callout: Salesforce triggers should not make direct synchronous callouts, and this tightly couples transaction processing to the external system.
• B. Workflow Rule with Outbound Message: This can react to record changes, but it cannot reliably capture a user clicking a menu item. It also does not provide the same flexible event-driven model as Platform Events.

• Accept terms of use
• Enter a temporary code or credentials
• Provide basic registration information

• Enterprise authentication — Authenticates organizational users, often with centralized identity services; it is not specifically designed for temporary guest access.
• Ad hoc network — A temporary device-to-device network, not an authentication process.
• WPA3 — A wireless security standard. It protects Wi-Fi access but does not provide the web-based temporary access workflow described here.

• The message came from the claimed sender (authentication)
• The message was not altered (integrity)
• The sender cannot easily deny sending it (non-repudiation)

• Attackers can send unsigned phishing emails.
• Attackers may compromise a legitimate account and send signed malicious emails.
• Users may still be tricked by a validly signed message.

• Technical platform interfaces: Important for integration and interoperability, but they should support—not drive—the architecture.
• Scalability of the network: Valuable as the organization grows, but a scalable solution is ineffective if it does not meet business or security needs.
• Development methodologies: Relevant to implementation, but they do not define the organization’s fundamental security requirements.

• LastName: Required.
• FirstName: Optional.
• AccountId: Optional; a Contact may be associated with an Account later or remain private, depending on organization settings.
• Name: A compound display field made from first and last name; it isn’t entered as a separate field.

• 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.

• Unsafe images: Requires image/content moderation before the image is processed.
• Hidden instructions embedded in images: These are indirect prompt injections contained in untrusted image content or extracted text, not necessarily in the user’s typed prompt.

• Frequency/likelihood = how often or how likely the risk is to occur.
• Severity/impact = how damaging or costly the consequences would be.

• A minor equipment fault occurring frequently may have high frequency but low severity.
• A major cyberattack occurring rarely may have low frequency but high severity.
• A risk that happens often and causes substantial losses has high frequency and high severity.

• A business-hours greeting
• An after-hours greeting
• A holiday greeting

• Weekday evenings/nights
• Saturdays and Sundays

1. Auto attendant 1

1. Auto attendant 2

• Data owners: Decide who should have access and approve the access rules.
• Business process owners: May help define business requirements, but normally do not enforce technical permissions.
• Security steering committee: Provides governance and direction; it does not manage individual access rights.
• Security administrators: Apply and enforce the approved access controls.

• Virus signatures: Primarily associated with antivirus or antimalware tools.
• Security agent deployment: Usually handled by endpoint-management or endpoint-security platforms.
• Vulnerability scanning: Performed by vulnerability-assessment tools, although a SIEM may ingest their results.

• 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.

• Extracted text and images
• Page numbers and bounding polygons for citation or grounding
• Structured tables, including tables that continue across multiple pages
• Document structure such as sections and figures

• Document Extraction: Extracts basic text and images, but does not provide the full layout and structural metadata required here.
• Azure Content Understanding in Foundry Tools: A broader content-analysis service, not the single built-in Azure AI Search skill expected by this question.
• GenAI Prompt: Can transform or interpret content but does not inherently produce reliable document geometry and page-level polygons.

• Key-based authentication: Provides an endpoint secured with API keys.
• Real-time REST access: Supports online inference through an HTTP/REST endpoint.
• No VM vCPU quota consumption: Microsoft hosts and manages the underlying infrastructure, so your subscription’s VM quota isn’t used.

• Batch: Intended for asynchronous, large-volume processing rather than real-time requests.
• Self-hosted container: You manage the infrastructure and typically need compute resources and quota.
• Standard: This is not the clearest deployment type for the stated requirements; the specific Foundry option is serverless API.

• 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.

• Marketing users: Dynamic Forms can show all fields.
• Support users: Field visibility rules can display only the Support preference fields on the record page.
• Reporting: Both profiles can still report on all fields because Dynamic Forms controls page visibility, not the underlying field access.

• A — Two record types and page layouts: Page layouts can control field placement and editability, but they are less flexible for conditional field visibility and would not be the best fit here.
• C — Muting permission set: Permission-set muting is used with permission-set groups; it does not conditionally hide fields on a page.
• D — Field-Level Security: FLS would remove field visibility at the security level. If fields are hidden by FLS, users generally cannot report on or access those fields, conflicting with the requirement that both users report on all data.

1. Yes — Microsoft Foundry provides a secure, governed environment for building and managing generative AI applications and agents. It brings together models, data, tools, evaluation, deployment, and monitoring.

1. Yes — Foundry is designed for enterprise workloads and supports scaling AI applications as usage grows. Scalability comes from the underlying Azure services and managed infrastructure.

1. Yes — Foundry can be used in solutions involving image recognition and computer vision. Applications can use vision-capable models and Azure AI vision capabilities for tasks such as image analysis, object detection, and OCR.

• 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.

• 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.

Step 1: Calculate the rights issue price

Step 2: Calculate the number of new shares

Step 3: Calculate the value after the issue and project

• Rights issue proceeds: $21.6m
• Project NPV: $5m

Step 4: Calculate the theoretical ex-rights price

• Required response and resolution times
• Availability or uptime targets
• Performance standards
• Support obligations
• Remedies or penalties for failing to meet the terms

• SOW (Statement of Work): Defines the project’s scope, tasks, deliverables, and schedule.
• MOA (Memorandum of Agreement): Describes agreed responsibilities between parties, often for a specific activity.
• MOU (Memorandum of Understanding): Records a mutual understanding or intention, usually less formal than a contract.

• 10.2.1.0 — network address
• 10.2.1.1 — usable host
• 10.2.1.2 — usable host
• 10.2.1.3 — broadcast address

• New investment: $536,500
• Resulting NPV: $0

1. Open Notepad as Administrator.
2. Open:

1. Remove or correct the line mapping the website to the wrong IP address.
2. Save the file.
3. Optionally run:

cmd 
   ipconfig /flushdns

• No servers or database infrastructure to provision.
• Uses standard SQL.
• Supports formats such as JSON, CSV, Parquet, and ORC.
• You typically define the table structure with AWS Glue Data Catalog or Athena’s own schema definitions.
• Charges are generally based on the amount of data scanned, so partitioning and columnar formats can reduce cost.
• It does not copy the data into a separate database; it reads the files in S3 when you run a query.

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

• 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.

• 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.

• Dark web: A place where leaked credentials may be sold or shared, not usually the original source.
• Threat feeds: Collections of intelligence about threats, not a typical leakage source.
• State actors: A type of attacker, not an accidental corporate disclosure source.
• Vulnerability databases: Track known vulnerabilities, rather than leaked credentials.

• 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.

• 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.

• NTLM: Uses Windows challenge-response authentication and does not provide the normal web-based MFA redirect flow.
• Single Sign-On: Automatically reuses existing credentials; it is intended to avoid prompting, not to support an MFA workflow.
• Transparent: Intercepts the session without redirecting the user to a separate authentication page.

• Deterrent control: The signs warning people they may be filmed discourage unauthorized or malicious behavior. They may prevent incidents by influencing behavior, but their primary purpose is to deter.
• Detective control: The CCTV system monitors and records activity so security personnel can identify suspicious or unauthorized actions.

• Preventive: Blocks or prevents an incident, such as a lock or access-control system.
• Corrective: Fixes or restores systems after an incident.
• Directive: Tells people what they must do, typically through policies or procedures.
• Compensating: Provides an alternative control when the preferred control cannot be used.

• Scanning is not essential during a power outage.
• A scanner can consume UPS battery power without helping the user save cloud documents or shut down safely.
• The UPS should be reserved for the computer, monitor, and necessary network equipment.
• The surge protector helps protect the scanner from voltage spikes, but it will not keep it running during an outage.

• nmap - 10.11.1.130 — a network scanning command; mitigated with controls such as firewalls, monitoring, or access restrictions.
• “Click this link to get your free gift card.” — a phishing or social-engineering message; addressed through user awareness, email filtering, and authentication controls.
• “Your connection is not private.” — indicates a certificate or TLS validation problem; addressed by correcting the certificate or secure-connection configuration.

• Understating expenses and liabilities
• Overstating profit
• Misleading users of the financial information
• Potentially breaching integrity, objectivity, and professional competence and due care

• An Adj-SID does not necessarily need manual configuration.
• It can often be dynamically allocated by the router, although manual configuration may also be possible.
• The adjacency information is advertised through the IGP, such as IS-IS or OSPF.

• It is identified by an Adj-SID.
• It represents a particular adjacency of a node.
• Its meaning is generally local to the advertising node; unlike a Node-SID, it is not a globally reusable instruction across the network.

• Compute: Not used; no virtual warehouse is required.
• Data Storage: Not scanned again.
• Metadata: May help Snowflake manage and validate cached results, but it is not the Snowflake architectural layer identified as serving the request.
• Cloud Services: Handles query coordination, metadata services, authentication, and result-cache access.

• Enforce organizational rules, such as allowed regions or required tags
• Audit resources for compliance
• Deny noncompliant deployments
• Aggregate compliance results across subscriptions

• File1 contains the evaluation configuration—for example, evaluators, test data, thresholds, or evaluation parameters.
• The GitHub Actions workflow must reference that file through the evaluation-config input so the action knows which evaluation to run.
• project-endpoint identifies the Microsoft Foundry project, but it does not identify the evaluation definition. It is also typically required, but it does not answer the specific requirement about using File1.

• Recovery Services vault — stores Site Recovery configuration and recovery metadata.
• Hyper-V site — represents the on-premises Hyper-V environment.
• Azure virtual network — the target network where the replicated VM will run after failover. Since Azure VMs already use the same virtual network, that VNet can be selected as the target.
• Storage account or managed-disk target, depending on the ASR configuration and portal version.
• Provider/agent on the Hyper-V server — enables replication from Hyper-V to Azure.

• A: Describes an update-set conflict, not a Dictionary Override.
• B: Describes a configuration item or change concept.
• C: Describes an approval or workflow activity.

• Windows 11 Pro ? Windows 11 Enterprise
• Windows 10 Pro ? Windows 10 Enterprise

• COE: Identifies the Center of Excellence, such as Payroll or Benefits.
• Topic Detail: Classifies the HR service within its COE; it does not identify the catalog item.
• Template: Supplies default values or case configuration.
• Record Producer: Represents the catalog item that employees use to submit the request and create the case.

1. Start with the number of devices: 260 usable addresses.
2. Use the formula:

1. Test the host-bit values:

1. IPv4 has 32 total bits:

• /24: 254 usable — too small
• /23: 510 usable — sufficient
• /22: 1,022 usable — more waste
• /21: 2,046 usable — even more waste