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Splunk SPLK-5002 Prüfungsplan:

Thema	Einzelheiten
Thema 1	Auditing and Reporting on Security Programs: This section tests Auditors and Security Architects on validating and communicating program effectiveness. It includes designing security metrics, generating compliance reports, and building dashboards to visualize program performance and vulnerabilities for stakeholders.
Thema 2	Building Effective Security Processes and Programs: This section targets Security Program Managers and Compliance Officers, focusing on operationalizing security workflows. It involves researching and integrating threat intelligence, applying risk and detection prioritization methodologies, and developing documentation or standard operating procedures (SOPs) to maintain robust security practices.
Thema 3	Detection Engineering: This section evaluates the expertise of Threat Hunters and SOC Engineers in developing and refining security detections. Topics include creating and tuning correlation searches, integrating contextual data into detections, applying risk-based modifiers, generating actionable Notable Events, and managing the lifecycle of detection rules to adapt to evolving threats.
Thema 4	Data Engineering: This section of the exam measures the skills of Security Analysts and Cybersecurity Engineers and covers foundational data management tasks. It includes performing data review and analysis, creating and maintaining efficient data indexing, and applying Splunk methods for data normalization to ensure structured and usable datasets for security operations.
Thema 5	Automation and Efficiency: This section assesses Automation Engineers and SOAR Specialists in streamlining security operations. It covers developing automation for SOPs, optimizing case management workflows, utilizing REST APIs, designing SOAR playbooks for response automation, and evaluating integrations between Splunk Enterprise Security and SOAR tools.

>> SPLK-5002 Lernressourcen <<

Splunk SPLK-5002 Prüfungsvorbereitung, SPLK-5002 Prüfungen

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Splunk Certified Cybersecurity Defense Engineer SPLK-5002 Prüfungsfragen mit Lösungen (Q67-Q72):

67. Frage
Which features of Splunk are crucial for tuning correlation searches? (Choose three)

A. Enabling event sampling
B. Using thresholds and conditions
C. Optimizing search queries
D. Reviewing notable event outcomes
E. Disabling field extractions

Antwort: B,C,D

Begründung:
Correlation searches are a key component of Splunk Enterprise Security (ES) that help detect and alert on security threats by analyzing machine data across various sources. Proper tuning of these searches is essential to reduce false positives, improve performance, and enhance the accuracy of security detections in a Security Operations Center (SOC).
Crucial Features for Tuning Correlation Searches
1. Using Thresholds and Conditions (A)
Thresholds help control the sensitivity of correlation searches by defining when a condition is met.
Setting appropriate conditions ensures that only relevant events trigger notable events or alerts, reducing noise.
Example:
Instead of alerting on any failed login attempt, a threshold of 5 failed logins within 10 minutes can be set to identify actual brute-force attempts.
2. Reviewing Notable Event Outcomes (B)
Notable events are generated by correlation searches, and reviewing them is critical for fine- tuning. Analysts in the SOC should frequently review false positives, duplicates, and low-priority alerts to refine rules.
Example:
If a correlation search is generating excessive alerts for normal user activity, analysts can modify it to exclude known safe behaviors.
3. Optimizing Search Queries (E)
Efficient Splunk Search Processing Language (SPL) queries are crucial to improving search performance.
Best practices include:
Using index-time fields instead of extracting fields at search time.
Avoiding wildcards and unnecessary joins in searches.
Using tstats instead of regular searches to improve efficiency.
Example:
Using:
| tstats count where index=firewall by src_ip
instead of:
index=firewall | stats count by src_ip
can significantly improve performance.

68. Frage
In which threat intelligence KV store would a list of malicious domains (FQDNs) be stored?

A. http_intel
B. certificate_intel
C. ip_intel
D. service_intel

Antwort: D

Begründung:
The correct collection is service_intel . Splunk Enterprise Security ' s Threat Intelligence Framework separates indicators into intelligence collections according to the type of observable being represented. Fully Qualified Domain Names are service-oriented network identifiers and are handled through the service intelligence collection in the context tested by this question.
This classification matters because the Threat Intelligence Framework must know which event fields and indicator types can be meaningfully compared. A domain such as malicious.example.com is semantically different from a raw IPv4/IPv6 address, a certificate fingerprint, or a complete HTTP URL. The ip_intel collection is intended for IP-oriented indicators, while certificate_intel deals with certificate-related intelligence. http_intel is associated with HTTP-oriented indicators such as URLs and related HTTP observables rather than the standalone FQDN type being asked about here.
Detection engineering depends on this normalization because matching searches must compare compatible indicator types. Correct placement also supports deduplication, expiration, weighting, threat matching, and downstream enrichment of security findings.
Study Guide topics: Threat Intelligence Framework, KV Store collections, indicator normalization, FQDN intelligence, threat matching, intelligence enrichment.

69. Frage
Which of the following is a methodology to help prevent malicious lateral movement?

A. Breakglass
B. Zero Trust
C. Lockheed Martin Cyber Kill Chain
D. MITRE ATT & CK

Antwort: B

Begründung:
Zero Trust is the methodology among these choices that directly supports reducing and preventing malicious lateral movement. Zero Trust architectures reject implicit trust based solely on network location and instead continuously evaluate identities, devices, applications, permissions, and access conditions.
Lateral movement occurs when an adversary who has gained an initial foothold attempts to access additional systems, credentials, services, or network segments. Zero Trust limits this ability through principles such as least privilege, strong identity verification, access segmentation, constrained authorization, device posture evaluation, and continuous monitoring. An attacker compromising one endpoint should therefore not automatically gain trusted access to adjacent resources.
The Lockheed Martin Cyber Kill Chain models stages of adversary activity and can help defenders understand attack progression, but it is not itself an access-control methodology designed to prevent lateral movement. MITRE ATT & CK catalogs adversary tactics and techniques, including lateral-movement techniques, but primarily provides a knowledge framework rather than the preventive architecture requested.
A breakglass mechanism provides emergency privileged access and must itself be tightly governed.
Zero Trust therefore most directly addresses the architectural conditions that enable lateral movement.
Study Guide topics: Zero Trust; lateral movement; least privilege; segmentation; identity-centric security; access control; adversary containment.

70. Frage
When building detections using the Authentication Data Model, which values are recommended for use against the action field?

A. allowed, blocked, inactivity, error
B. allowed, blocked, processing, error
C. success, failure, pending, error
D. success, denied, pending, error

Antwort: C

Begründung:
Within the CIM Authentication Data Model , the action field represents the outcome or state of an authentication operation. The recommended normalized values represented by the question are success, failure, pending, and error .
Normalization is critical because authentication technologies use highly variable native terminology. A Windows event may represent an authentication result through one event code, a VPN appliance through another vendor-specific status, and a cloud identity provider through a JSON result field. CIM maps those source-specific outcomes into common semantic values. A detection engineer can therefore write logic such as:
action= " failure "
without separately accounting for every vendor ' s native representation.
allowed and blocked are more naturally associated with access or network-control decisions and do not describe the normalized authentication outcome being tested. Likewise, denied does not replace the CIM- normalized failure value in the answer set.
Consistent use of the expected action vocabulary directly affects detection reliability. Incorrect mappings can cause failed authentications to disappear from CIM-based searches, dashboards, accelerated data-model queries, and threshold detections.
Study Guide topics: Authentication Data Model; CIM; action; normalized authentication outcomes; data mapping; cross-source detection engineering.

71. Frage
Which sourcetype configurations affect data ingestion? (Choose three)

A. Data retention policies
B. Timestamp extraction
C. Event breaking rules
D. Line merging rules

Antwort: B,C,D

Begründung:
The sourcetype in Splunk defines how incoming machine data is interpreted, structured, and stored. Proper sourcetype configurations ensure accurate event parsing, indexing, and searching.
1. Event Breaking Rules (A)
Determines how Splunk splits raw logs into individual events.
If misconfigured, a single event may be broken into multiple fragments or multiple log lines may be combined incorrectly.
Controlled using LINE_BREAKER and BREAK_ONLY_BEFORE settings.
2. Timestamp Extraction (B)
Extracts and assigns timestamps to events during ingestion.
Incorrect timestamp configuration leads to misplaced events in time-based searches.
Uses TIME_PREFIX, MAX_TIMESTAMP_LOOKAHEAD, and TIME_FORMAT settings.
3. Line Merging Rules (D)
Controls whether multiline events should be combined into a single event.
Useful for logs like stack traces or multi-line syslog messages.
Uses SHOULD_LINEMERGE and LINE_BREAKER settings.

72. Frage
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