Forcepoint Certified Forcepoint DSPM - Professional: Deploy and Administer Exam DSPM- Deploy-and-Administer Exam Dumps: Updated Questions & Answers (July 2026)

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 .

Path Detectors = Monitor storage locations of sensitive data

Content Detectors = Analyze data within files for sensitive data

Attribute Detectors = Identify meta-data within documents

Forcepoint DSPM separates detector logic into path, content, and attribute-based functions so classification can be driven by where data is stored, what the file contains, and what scan-derived attributes describe the file. Path Detectors evaluate file path information, including directory location, filename, and extension. Forcepoint describes them as identifying and classifying files based on directory location and file extensions, which aligns with monitoring storage locations where sensitive data resides.

Content Detectors inspect the actual contents of files. Forcepoint states that content detectors analyze file content and categorize based on keywords, phrases, positive and negative terms, or patterns, making them the correct match for analyzing data within files for sensitive data.

Attribute Detectors operate on scan-result attributes rather than raw text content alone. Forcepoint describes them as defining criteria for “critical” and “sensitive” based on attributes in scan results, including ML output or path/content detector hits. This maps most closely to identifying metadata or scan-derived characteristics within documents. References/topics: Detectors, Path Detectors, Content Detectors, Attribute Detectors, AI Mesh, Classification Model .

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 .

The correct answer is D. To monitor the progress of ongoing data scans . The Scan Status dashboard is used to track scan execution and understand where a scan is in the discovery and classification lifecycle. Forcepoint’s scan analytics documentation describes scan status views that show the current discovery-stage status, last status update, discovered-file count, and detailed scan analytics for a selected data-source configuration. It also explains that the Scan Progress tab shows the selected scan configuration, discovery-stage status, last discovered file time, scan start time, scan number, classification status, and classification timing.

This makes the dashboard operationally useful for administrators who need to verify that scans are running, determine whether discovery or classification is still in progress, and identify whether scan activity has stalled or produced errors. It is not intended to display encrypted files, track department membership, or monitor network traffic. Department-level visibility is handled through Compliance Hub and Data Asset Inventory workflows, while network activity monitoring is outside the scope of the Scan Status dashboard. References/topics: Dashboard, Scan Status, Scan Analytics, Scan Progress, Discovery Status, Classification Status, Data Source Scanning .

The correct answer is A. Resolves Incident Reporting . Data Mapping in Forcepoint DSPM is a governance configuration capability within Policy Center > Compliance Hub , not an incident-resolution mechanism. Forcepoint defines Data Mapping, also referred to as Security Posture Policy Controls , as the building blocks for the Data Asset Inventory framework. It allows administrators to define the fields available in the Data Asset Inventory so data owners can assign metadata tags to critical data. Examples include retention period, business owner, regulatory scope, review status, and project name .

Those functions clearly support the valid benefits in the option set. Data Mapping improves data management by standardizing asset metadata. It enhances compliance by capturing regulatory scope and review-related fields. It also streamlines internal processes by giving departments a consistent structure for documenting ownership, retention, review status, and business context. Forcepoint also notes that only one data mapping configuration is available, so it should be designed generically enough for all departments, reinforcing its role as an enterprise-wide governance framework.

Incident reporting is handled separately through DSPM incident and controls-orchestration workflows. Data Mapping may enrich incident context, but it does not “resolve” incident reporting. References/topics: Compliance Hub, Data Mapping, Security Posture Policy Controls, Data Asset Inventory, Metadata Governance .

In Forcepoint DSPM, data ownership is treated as an explicit governance assignment tied to the organisation’s data asset inventory and data sources, not as a passive attribute inferred only from file metadata or imported directory fields. The closest correct option is C , because ownership is assigned at the data storage/data source or data asset level so that accountability, alert routing, review responsibility, and remediation workflows have a clearly identified business owner.

Forcepoint documentation describes the Data Asset Inventory workflow as requiring organisations to “assign an owner” for each asset and states that DSPM can “assign specific data owners to each data source.” This aligns with DSPM’s governance model: the owner is the accountable stakeholder for the data asset, not merely the technical file creator or last modifier. Release notes also describe a Data Owner column on the Data Assets page, where ownership may be automatically selected based on department owner and manually changed by the user.

Therefore, A is incorrect because policies define controls and requirements, not the owner itself. B is too narrow because imported user properties support identity context but do not alone define data ownership. D is incorrect because file owner metadata is not the authoritative ownership model for DSPM governance. References/topics: Data Register, Data Asset Inventory, Data Ownership, Controls Orchestration, Access Governance .

The correct selections are Regular expressions and Classification tags . In Forcepoint DSPM pattern matching, a pattern is built around a RegEx , meaning the text sequence or structure the system searches for during file scans. Forcepoint defines RegEx as “a sequence or pattern that is searched for in text,” and defines a pattern as the RegEx plus the rules associated with its detection. That makes regular expressions the core detection mechanism for custom pattern matching.

Classification tags are also a key configuration component because they define how matching files should be labelled after the pattern is detected. In the Add New Pattern workflow, Forcepoint lists Classifications as a configurable field and describes it as the “Classification tagset value.” The same workflow states that selected Classification, Compliance, and Distribution values override machine-learning model output during endpoint suggestions and file scans.

The remaining options are not primary pattern-matching configuration components. Applicable Country is not listed as a core pattern field in the documented pattern workflow. User credentials belong to identity and access management, not detection logic. Data sensitivity keys is not the documented configuration term used for pattern creation. References/topics: Pattern Matching, RegEx Detection, Classification Tags, Compliance Tags, Distribution Tags, Scan Classification Overrides .

Select the Actions drop-down in the upper-right corner of the LDAP provider screen, then choose Sync all users or Sync changed users .

Manual synchronization is initiated from the LDAP provider configuration page inside Keycloak User Federation, not from the general DSPM dashboard or from the Users page. The correct UI location is the Actions menu at the upper-right of the LDAP provider screen. In the screenshot, this is the open drop-down containing options such as Sync all users , Sync changed users , Unlink users , and Remove imported . To force synchronization after a successful connection test, choose Sync all users for a full import or Sync changed users when only deltas are required.

Forcepoint DSPM uses Keycloak for Active Directory import. The official DSPM documentation states that AD users are added through Keycloak , with administrators selecting the gv realm, navigating to User Federation , and adding/configuring an LDAP provider. It also identifies synchronization settings such as Import users , Periodic full sync , and Periodic changed users sync as the mechanisms used to bring LDAP users into Keycloak and then into DSPM.

Therefore, the click target is the upper-right Actions drop-down on the LDAP provider page , specifically the sync command within that menu. References/topics: User Federation, LDAP Provider, Active Directory Import, Keycloak gv Realm, Synchronization Settings .

The correct answer is A. Encrypting data transfers . Detectors in Forcepoint DSPM are classification and discovery components, not transport-security controls. A detector is used to analyze file content, file paths, attributes, keywords, phrases, regular expressions, and positive or negative match terms so the platform can identify and categorize data during scans. Forcepoint describes Content Detectors as tools that “analyze file content to detect and categorize” based on keywords, phrases, or patterns, making them directly relevant to finding sensitive information.

Detectors also support compliance and breach-prevention outcomes because their findings contribute to the broader DSPM visibility model: identifying where sensitive data exists, how it is classified, and where risk-reduction actions may be needed. Forcepoint describes DSPM as providing visibility and risk remediation across cloud and on-premises environments, and notes that AI technology combined with Detectors and Compliance Hub helps organizations protect sensitive information and maintain regulatory requirements.

Encryption of data transfers, however, is handled by transport protocols, connector configuration, network security controls, or platform security architecture—not by detector logic. Detectors can help discover sensitive data that may require protection, but they do not encrypt traffic. References/topics: Detectors, Content Detectors, AI Mesh, Sensitive Data Discovery, Compliance Hub, Risk Remediation .

Administration > Taxonomy

Taxonomy tags are managed from the Administration menu, specifically under Administration > Taxonomy . In the screenshot, Adam should not select Policy Center ; the currently open menu shows Compliance Hub, Data Register, Controls Orchestration, and Incidents, but taxonomy management is not located there. The correct UI action is to open the Administration drop-down on the top navigation bar and select Taxonomy .

Forcepoint’s DSPM documentation states that the Taxonomy page displays predefined AI Mesh tags, which cannot be removed, and also allows administrators to add custom tags for pattern matching and detection rules. It further explains that taxonomy mapping can connect AI Mesh tags with data-source taxonomies so mapped tags can be written back as the organization’s own labels.

This location is important because taxonomy governs the classification language DSPM applies to scanned data. By updating taxonomy tags, Adam aligns DSPM classification output with the company’s internal handling policies, sensitivity labels, and compliance terminology. Forcepoint also notes that new taxonomy tags are created from the Taxonomy tab under the Administration section, and that applied tags are visible in the Data Asset Inventory. References/topics: Administration, Taxonomy, AI Mesh Tags, Classification Tags, Pattern Matching, Detection Rules .