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| Section | Weight | Objectives |
|---|---|---|
| Security Architecture and Defense Design | - Enterprise security architecture design
| |
| Security Operations Strategy | - Security operations planning
| |
| Security Data Management | 20% | - Security data integration strategies
|
| Advanced Threat Intelligence and Analysis | 5% | - Adversary modeling and emulation
|
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NEW QUESTION # 148
An organization is migrating from their current firewalls to a next generation firewall system. As they begin to collect telemetry from their new firewalls, which of the following methods will ensure continuity of existing detections?
Answer: D
Explanation:
Data normalization preserves detection continuity by mapping telemetry from the new firewall system into the same common field names and event structure used by existing detections. This allows searches, correlation rules, dashboards, and analytics to continue working even when the underlying firewall vendor or log format changes.
NEW QUESTION # 149
Buttercup Games' incident-response team has identified IOCs associated with the "Water Curse" campaign in its development environment. Suspicious activity indicates unauthorized access to developer workstations and possible manipulation of source code in its version-control software, GitLow. Given "Water Curse's" known weaponization of open-source dependencies, a forensic investigation is necessary to establish the breach's full scope, identify affected systems, and gather evidence.
To support a forensic investigation of the "Water Curse" compromise at Buttercup Games, which triage steps should be performed?
Choose three
Answer: A,B,D
Explanation:
The suspected compromise involves both endpoint intrusion and potential software supply-chain manipulation. Forensic triage must therefore preserve evidence while examining developer activity, workstation artifacts, and network communications.
Reviewing commits and pull requests helps identify unauthorized code changes, suspicious dependency updates, altered build scripts, and activity performed through potentially compromised developer identities.
Investigators should correlate repository activity with authentication logs, access-token usage, approval records, and build-pipeline execution history.
Collecting volatile memory and disk images preserves potentially significant forensic evidence. Memory acquisition may reveal active processes, injected code, network connections, and malware artifacts that would disappear when a device is powered down.
Disk acquisition supports analysis of persistent files, scripts, execution artifacts, and evidence of unauthorized changes.
Analyzing network traffic can identify command-and-control communication, suspicious external connections, data exfiltration, and interactions with malicious software distribution infrastructure.
Deep packet inspection can provide additional visibility where traffic is available and readable; encrypted communications may require analysis of metadata or approved decryption capabilities.
Immediately re-imaging compromised workstations would destroy valuable evidence before investigators establish the incident ' s scope.
Appropriate containment should still be performed, but destructive remediation should follow evidence- preservation procedures whenever operationally feasible.
Official reference / study topic: Splunk certification blueprint Objectives 3.3, 1.3 and 5.3: forensics and supply-chain incidents.
NEW QUESTION # 150
How can a threat intelligence team discover additional Indicators Of Compromise (IOCs) from threat actor payloads?
Answer: B
Explanation:
Splunk Attack Analyzer is designed to analyze suspicious payloads and artifacts, extract related observables, and identify additional indicators of compromise. This helps threat intelligence teams expand their understanding of attacker infrastructure, files, URLs, and other related threat evidence.
NEW QUESTION # 151
Danielle is a security architect at a multinational retail company. She is evaluating threat intelligence feeds to add to her company's security monitoring program. What is the primary benefit that threat intelligence data can provide?
Answer: B
Explanation:
Threat intelligence data adds external context to detection content by identifying known malicious indicators, adversary tactics, infrastructure, malware, and campaign details. This helps security monitoring distinguish higher-risk activity, prioritize investigations, and create more actionable detections.
NEW QUESTION # 152
What benefits result from having data in a normalized schema?
Choose three
Answer: A,B,C
Explanation:
A normalized schema establishes consistent field definitions and event classifications across heterogeneous security data sources, improving analytical interoperability and reducing detection-engineering complexity.
Standard field names allow analysts to reference equivalent event attributes consistently. For example, Splunk Common Information Model (CIM) defines common fields for authentication events even when the underlying data originates from different identity providers.
Summarization and acceleration are supported through standardized data models. Splunk can create accelerated data-model summaries, allowing commands such as tstats to retrieve aggregated security information efficiently.
However, acceleration requires appropriate configuration; normalization does not automatically activate or guarantee accelerated searches.
Simplified detection development follows from the ability to write reusable correlation searches against common fields and event categories instead of maintaining separate vendor-specific logic.
For example, a single normalized authentication detection can evaluate failed login activity from multiple systems without requiring a separate search for every source format.
Option D is incorrect because the availability of raw-event fields is determined by data ingestion, retention, search-time extraction, and access permissions.
CIM normalization preserves the underlying raw data where retained, but it does not inherently guarantee that every raw field has been extracted or is searchable as an individual field.
These capabilities make normalized schemas a foundational component of scalable SIEM architecture.
Official reference / study topic: Splunk Common Information Model, Normalize Data and Accelerate Data Models.
NEW QUESTION # 153
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