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| Section | Objectives |
|---|---|
| Topic 1: Administration and User Management | - User synchronization and management - User federation and Active Directory integration - Role-based access control (RBAC) |
| Topic 2: Forcepoint DSPM Architecture and Overview | - Deployment models (cloud / standalone) - DSPM system components and platform overview |
| Topic 3: Data Sources and Integration | - Streaming and event integration - Database discovery and structured data scanning - Configuring data sources - SIEM and external integrations |
| Topic 4: Monitoring, Analytics, and Reporting | - Scan progress and risk visibility - Dashboards and analytics widgets - Data lineage and compliance monitoring |
| Topic 5: Data Classification and Detection | - Pattern matching and classification models - Detectors and detector groups - Taxonomy and labeling mechanisms |
| Topic 6: Deployment and Installation | - Initial setup and configuration - Standalone DSPM deployment workflow - System requirements and prerequisites |
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질문 # 25
What is the purpose of assigning compliance tags to data patterns in Forcepoint DSPM?
정답：B
설명：
Compliance tags in Forcepoint DSPM are used to associate detected data patterns with regulatory or compliance obligations. The correct answer is B because these tags help the platform identify files and data objects that may fall under privacy, security, or industry-specific regulatory regimes. Forcepoint's pattern- matching terminology defines Compliance as tags that help organizations conform to regulatory regimes, and gives the example of applying tags such as GDPR/PII to a Social Security number pattern so related documents can be identified.
Operationally, this means a pattern is not only detecting a technical string, such as a national identifier, payment card number, or health-related value; it is also attaching compliance meaning to the match. That compliance context can then support classification, filtering, analytics, remediation prioritisation, and audit evidence. Forcepoint also states that when adding a new pattern, selected Classification, Compliance, and Distribution values can override machine-learning model output during scans, making the assigned tags authoritative for scan results.
The other options are adjacent but incorrect. User monitoring and reporting are downstream analytics activities, encryption policy management is not the core purpose of pattern compliance tagging, and user credentials are handled through identity and access management workflows. References/topics: Pattern Matching, Compliance Tags, Classification Model, AI Mesh, Regulatory Data Identification .
질문 # 26
If LDAP searching and updating is set to READ_ONLY mode, which synchronization option becomes irrelevant?
정답：D
설명：
The correct answer is Sync Registrations . In Forcepoint DSPM, Active Directory users are imported through Keycloak User Federation . The Forcepoint DSPM administration workflow directs administrators to access Keycloak, select the gv realm, navigate to User Federation , and add an LDAP provider for AD integration.
In Keycloak LDAP configuration, READ_ONLY edit mode means Keycloak can read LDAP-backed user data, but it cannot modify mapped LDAP attributes such as username, email, first name, last name, or passwords. Keycloak's own administration guide states that READ_ONLY prevents user attribute changes and password updates, while WRITABLE mode is the mode that allows changes to be synchronized back to LDAP.
That makes Sync Registrations irrelevant in READ_ONLY mode because Sync Registrations is specifically used when newly created Keycloak users should also be added to LDAP. Since READ_ONLY mode prevents Keycloak from writing new or modified user objects back to LDAP, registration synchronization has no useful effect in that configuration. By contrast, Import users , Periodic full sync , and Periodic changed users sync remain relevant because they are read-oriented synchronization mechanisms that bring LDAP/AD identities into DSPM's Keycloak-backed identity layer. References/topics: Keycloak User Federation, LDAP Edit Mode, READ_ONLY Mode, AD Import, Synchronization Settings .
질문 # 27
Which of the following statements is true about Forcepoint DSPM pattern matching?
정답：D
설명：
The correct answer is A . Forcepoint DSPM pattern matching is designed to let administrators define and tune custom detection logic for organisation-specific sensitive data. The documented pattern-matching function identifies particular information in documents by using Regular Expressions , and Forcepoint notes that pattern matching uses Golang RegEx syntax, which is separate from Detector syntax.
When a new pattern is added under Administration > Pattern Matching , the configuration includes Pattern Name , Regular Expression , enablement state, hidden RegEx handling, and tag assignments for Classification , Compliance , and Distribution . Forcepoint states that the Regular Expression is "the sequence to be matched," and that selected tags can override machine-learning model output during endpoint suggestions and file scans. This supports the principle that custom patterns can be adjusted so the RegEx better matches an organisation's data formats, identifiers, project codes, or regulatory artifacts.
The other statements do not match the documented pattern workflow. Country assignment is not presented as a core custom-pattern field. Export/import of data patterns is not part of the stated pattern-matching configuration flow. Default or preconfigured patterns are provided as built-in detection content and should not be treated as administrator-editable RegEx templates. References/topics: Pattern Matching, Add New Pattern, RegEx, Classification Tags, Compliance Tags, Distribution Tags .
질문 # 28
Which of the following is an option to aid the process of reviewing the incidents generated from triggered rules in Controls Orchestration?
정답：A
설명：
The correct answer is B . Forcepoint DSPM Controls Orchestration rules are built around query-driven rule logic. In the rule configuration workflow, administrators select a dataset such as Files , Trustees , or Agent Activities , then configure the rule condition using GQL syntax . This GQL condition defines which records match the rule and therefore which results appear as incidents when the rule is triggered. Forcepoint documentation states that Controls Orchestration rules identify data matching specific criteria and that the Condition field uses GQL syntax to filter the selected dataset.
When reviewing incidents, Forcepoint's Incidents page provides a top-down view of orchestration rules and available match results. Selecting an incident card opens a results preview, and choosing View in the Page displays those matched files in Enterprise Search , where additional review and action options are available.
Enterprise Search is specifically designed to narrow scanned-file results using GetVisibility Query Language
, and Forcepoint notes that GQL filtering helps reduce the result set to a more manageable subset for analysis and action.
Timestamp, Risk type, and keyword filtering may be useful in other contexts, but the documented advanced review mechanism for these results is GQL-based filtering. References/topics: Controls Orchestration, Incidents, Enterprise Search, GQL Filtering, Rule Match Review .
질문 # 29
Which statement best describes what happens when a detector group is selected while creating a content detector?
정답：C
설명：
The correct answer is B . In Forcepoint DSPM, content detectors analyze file contents using configured search logic such as keywords, phrases, positive and negative terms, or regular expressions. During detector creation, administrators can associate the detector with a detector group. Forcepoint states that when a detector group is selected, the detector becomes part of the AI Mesh and contributes to classification results. If the administrator does not want the detector to influence classification, a non-AI Mesh detector group should be selected instead.
This is important because detector grouping controls whether detector hits are merely informational or actively influence classification decisions. A payroll detector, for example, may search for terms such as salary, payslip, compensation, or payroll. If tied into the AI Mesh, those hits can help classify files as sensitive or confidential. The other options misrepresent detector behavior. Detectors do not automatically revoke permissions, convert keywords directly into taxonomy labels, or disappear from scan results when grouped. References/topics: Administration > Detectors, Content Detectors, Detector Groups, AI Mesh, Classification Results, Contain/Not Contain Logic .
질문 # 30
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