SPLK-5001 Exam Dumps - Splunk Certified Cybersecurity Defense Analyst

The MITRE ATT&CK framework categorizes Tactics, Techniques, and Procedures (TTPs) used by attackers. It is a globally accessible knowledge base of adversarial tactics and techniques based on real-world observations, and it is widely used by cybersecurity professionals to understand and defend against various cyber threats.

Tactics, Techniques, and Procedures (TTPs):

Tactics:The high-level goals that attackers aim to achieve during an attack. For example, gaining initial access to a network.

Techniques:The specific methods used to achieve these tactics, such as phishing or exploiting a vulnerability.

Procedures:The detailed steps and tools that attackers use to implement a technique.

MITRE ATT&CK Framework:MITRE ATT&CK organizes these TTPs into a matrix that reflects different stages of an attack lifecycle, from initial access to exfiltration. The framework helps security teams by:

Mapping Detection and Defense:Organizations can map their existing detection capabilities against the ATT&CK matrix to identify gaps.

Threat Hunting:Security teams use the framework to guide their threat-hunting activities, focusing on specific techniques associated with known adversaries.

Incident Response:During incident response, analysts can use the ATT&CK framework to understand the behaviors exhibited by an attacker, which helps in creating effective containment and eradication strategies.

Why MITRE ATT&CK:Unlike compliance-focused frameworks like NIST 800-53 or ISO 27000, which provide security controls and best practices, MITRE ATT&CK is specifically focused on the behavior of adversaries. This focus makes it an invaluable resource for understanding how attacks unfold and how to counteract them.

Thetstatscommand in Splunk is designed for highly efficient querying of large datasets because it operates primarily onindexed metadatarather than the full raw event data. Indexed metadata consists of pre-extracted, summarized information such as field values, timestamps, and host information, which is stored in a highly optimized format. This allowststatsto return results much faster than thestatscommand, which processes raw event data after retrieval.

tstatsqueries accelerated data models or index metadata directly, reducing disk I/O and CPU usage.

statsoperates on raw events, which can be expensive in terms of resources for large datasets.

The SQL-like syntax oftstats(Option C) is a convenience but not the reason for its performance benefits.

tstatsdoes not search raw logs for extracted fields; that is the domain of thestatscommand.

Splunk’s official documentation and theCybersecurity Defense Analyst Study Guideemphasize the importance oftstatsfor performance-optimized queries in security operations and large-scale data analysis.

To investigate which process initiated a network connection, an analyst would use theEndpointdata model in Splunk Enterprise Security. The Endpoint data model contains fields related to processes, file activity, and host-level data, which are essential for tracing back the source of suspicious network activity to the specific process or application that initiated it. This is crucial for understanding the scope of an attack and determining the origin of malicious network traffic.

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The Splunk Security Content library, which includes apps like ESCU (Enterprise Security Content Update) and SSE (Splunk Security Essentials), primarily consists of Dashboards, Reports, and Correlation Searches.Validated architecturesare not a component of these content libraries. Instead, validated architectures refer to predefined, best-practice designs for deploying and configuring Splunk in a way that ensures optimal performance and scalability, which is separate from the content libraries focused on delivering security detections and visualizations.

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The key requirement is to calculate arunning total of distinct IP addressesover time, which involves both aggregation (stats dc(clientip) by _time) and cumulative calculation (streamstats dc(ipa) as "Cumulative total").

Option Acorrectly bins events by day (bin _time span=1d), calculates distinct counts (dc(clientip)) per day, and then applies streamstats to compute the running (cumulative) count across the timeline.

Option Bcalculates daily distinct counts but does not provide a running total.

Option Csimply formats a table without aggregation.

Option Daggregates by user, not by day, and misses cumulative counts.

TheSplunk Search Manualrecommends using streamstats with distinct count fields to obtain running totals for time series data.