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You have general SIEM or security operations experience but limited or no exposure to CrowdStrike Falcon Next-Gen SIEM. You need to learn the platform from scratch.
Week 1Review the CCSE exam guide and objectives. Set up access to Falcon Next-Gen SIEM if possible. Learn platform navigation, user roles, and access management fundamentals
Week 2Study data ingestion fundamentals: understand first-party vs third-party data sources, built-in data connectors, and the difference between connector types (API-based, syslog, HEC)
Week 3Deep dive into the Falcon Log Collector: installation, configuration, fleet management, sizing specifications, and syslog/HEC sink architecture
Week 4Learn the CrowdStrike Parsing Standard (CPS): its relationship to Elastic Common Schema (ECS), vendor-prefixed fields, parser templates, and normalization concepts
Week 5Practice parser development: log format recognition, parser validation test cases, cloning existing parsers, building custom parsers from scratch, and AI-assisted parser generation
Week 6Study CQL (CrowdStrike Query Language): pipe syntax, filter operators, aggregation functions (groupBy, stats, top), field manipulation (rename, replace, eval), regex, and time functions
Week 7Learn content creation: lookup files, pre-built dashboards, custom dashboard building, correlation rule creation and tuning, and vendor-native vs external detection sources
Week 8Cover automation and integration: Falcon Fusion SOAR workflows, API authentication credentials, and FalconPy SDK integration patterns
Week 9Practice questions across all domains. Take a full mock exam. Focus on Parsing (30%) and Data Ingestion (27%) which together are 57% of the exam
Week 10Review all incorrect answers, retake weak areas. Take another mock exam aiming for 85%+. Schedule your real exam when consistently scoring above 80%
Exam Overview
Format
60 questions, 90 minutes. Multiple choice questions covering practical SIEM engineering scenarios.
Scoring
Percentage-based scoring 0-100%. Passing: 80%. No penalty for wrong answers — always answer every question.
Domains & Weights
- User Management7%
- Data Ingestion27%
- Parsing30%
- Content Creation26%
- Automation and Integration10%
Registration
$250 USD. Available at Pearson VUE testing centers or online proctored. Exam fee is $250 USD. Certification valid for 3 years; recertification requires passing the current exam version.
Topic Priority Table
Not all topics are tested equally. Focus your study time on Tier 1 first, then Tier 2. Tier 3 topics rarely appear — just recognize what they do.
Domain 17% of exam
User Management
This domain covers configuring user roles, permissions, and establishing custom role structures for platform access control within Falcon Next-Gen SIEM. While the smallest domain by weight, it tests foundational knowledge that underpins all other SIEM operations.
Key Topics
RBACUser RolesCustom RolesPermissionsAccess Control
Must-Know Concepts
- How to configure user roles and permissions within Falcon Next-Gen SIEM for appropriate access control
- Role-based access control (RBAC) implementation for secure platform management and data access separation
- Custom role creation to establish granular access structures tailored to organizational needs and security requirements
- The relationship between user permissions and data visibility, including repository-level access controls
- Administrative vs analyst vs read-only role distinctions and when to apply each level of access
Common Exam Traps
Custom roles must be explicitly created and assigned — there is no automatic role inheritance from organizational hierarchy
User permissions affect what data sources, dashboards, and SOAR workflows a user can access, not just login capability
Repository-level access controls are separate from platform-level role assignments — both must be configured correctly
Domain 227% of exam
Data Ingestion
The second-heaviest domain covering how data enters Falcon Next-Gen SIEM. You must understand first-party vs third-party data sources, built-in data connectors, Falcon Log Collector deployment and management, connector architecture, sizing specifications, and troubleshooting ingestion issues. This domain is highly practical and scenario-based.
Key Topics
Data ConnectorsFalcon Log CollectorHECSyslogFleet ManagementFirst-Party DataThird-Party Data
Must-Know Concepts
- How to categorize first-party data (native Falcon telemetry) vs third-party data (external security tools, cloud services, network devices) and their ingestion differences
- Selecting the appropriate integration method: API-based data connectors for cloud/SaaS sources vs Falcon Log Collector for on-premises syslog/file sources
- Setting up and maintaining built-in data connectors including authentication, scheduling, and data flow configuration
- Standard components of third-party connector architecture: source, transport protocol, authentication, parsing pipeline, and destination repository
- Falcon Log Collector sizing specifications: CPU, memory, disk, and network requirements based on events per second (EPS) throughput
- Installing and configuring the Falcon Log Collector: supported operating systems (Windows, Mac, Linux), syslog sources (UDP/TCP on port 1514), and HEC sink configuration
- Fleet management operations: centralized collector management, health monitoring, configuration updates, and scaling strategies
- Diagnosing and resolving common ingestion complications: missing events, parsing errors, connectivity issues, authentication failures, and throughput bottlenecks
Common Exam Traps
Data connectors are API-based cloud integrations. Falcon Log Collector is deployed software for syslog/file collection. Do not confuse the two integration methods
HEC (HTTP Event Collector) is the transport mechanism for sending data to SIEM, not a data source itself. Log Collectors use HEC sinks to forward data
First-party Falcon data is automatically ingested and parsed. Third-party data often requires custom connector configuration AND custom parser development
Sizing the Falcon Log Collector incorrectly leads to data loss — the exam tests whether you know the relationship between EPS throughput and resource requirements
Fleet management is about managing COLLECTORS, not endpoints. Do not confuse log collector fleet management with Falcon sensor management
Domain 330% of exam
Parsing
The heaviest domain at 30% — expect roughly 18 questions on parsing topics. Covers the CrowdStrike Parsing Standard (CPS), data normalization, log format recognition, parser validation, custom parser development, AI-assisted parser generation, advanced parsing syntax, and parser troubleshooting. This domain requires both conceptual knowledge and practical parser-building skills.
Key Topics
CPSECSVendor-Prefixed FieldsParser ValidationCustom ParsersAI ParserLog FormatsNormalization
Must-Know Concepts
- CrowdStrike Parsing Standard (CPS) framework: based on ECS 8.x, with documented deviations and extensions. CPS-compliant parsers standardize data for detection, dashboards, and analytics
- Data normalization using CPS: mapping raw vendor fields to standard ECS field names, ensuring consistent query capability across all data sources
- Vendor-prefixed fields: fields not in ECS are prefixed with 'Vendor.' to maintain clean namespace separation between standard and vendor-specific data
- Recognizing various log format structures: JSON, CSV, syslog (RFC 3164/5424), CEF, LEEF, key-value pairs, XML, and unstructured text formats
- Developing parser validation test cases: creating sample log entries, testing field extraction, verifying CPS compliance, and validating edge cases
- Cloning and adjusting existing parser configurations: duplicating parsers as starting points and modifying field mappings for similar but different sources
- Building custom parser logic from scratch: regex extraction, field assignment, conditional parsing, and multi-format handling
- AI-assisted parser generation: using the AI Parser feature to automatically generate parser configurations from sample logs and refining the output
- Advanced syntax features: nested field extraction, conditional logic, multi-line log handling, and complex regex patterns for parser development
- Identifying and correcting parsing operation failures: debugging field extraction errors, handling format changes, and resolving CPS compliance issues
Common Exam Traps
CPS is based on ECS but is NOT identical to ECS. It has documented deviations and extensions — do not assume all ECS rules apply directly to CPS
Non-ECS fields are prefixed with 'Vendor.' — not dropped or ignored. ALL fields from the raw log should be made available as LogScale fields
Parser validation must include test data. CrowdStrike requires parsers to include test cases — a parser without validation tests is not CPS-compliant
AI-assisted parsers are a starting point, not production-ready. They often require manual review, refinement, and additional test cases before deployment
Log format recognition is tested — you must identify whether a log sample is JSON, syslog, CEF, CSV, or unstructured text before building a parser
Domain 426% of exam
Content Creation
This domain covers creating operational content within Falcon Next-Gen SIEM: managing lookup data, using pre-built dashboards, writing and optimizing CQL queries, building custom dashboards, creating and tuning correlation rules, and understanding detection source types. This domain is heavily CQL-focused and requires strong query-writing skills.
Key Topics
CQL QueriesDashboardsCorrelation RulesLookup FilesDetection SourcesQuery Optimization
Must-Know Concepts
- Managing lookup data files: creating, uploading, and referencing lookup data for event enrichment and threat correlation in CQL queries
- Using pre-built dashboards for system activity observation: understanding default dashboards, their data sources, and how to interpret visualizations
- CQL query construction: pipe syntax, filter expressions, comparison operators, logical operators (AND, OR — note OR binds closer than AND), field selection, and aggregation
- CQL functions: groupBy() for deduplication, stats(count()) for aggregation, top() for ranking, eval() for calculated fields, regex() for pattern extraction, rename(), replace(), sort(), formatTime()
- CQL query optimization: reducing query scope with time ranges and filters, using efficient aggregation, minimizing regex on large datasets, and leveraging indexed fields
- Building custom dashboard visualizations: widget types, data source binding, interactive drill-down, and real-time vs historical data views
- Creating correlation rules: defining detection logic in CQL, setting severity levels, assigning MITRE ATT&CK techniques, and configuring alert actions
- Tuning correlation rule behavior: adjusting thresholds, adding exclusions, refining time windows, and reducing false positives without losing true positives
- Categorizing vendor-native vs external detection sources: understanding which detections come from CrowdStrike modules vs third-party forwarded alerts
Common Exam Traps
In CQL, OR binds closer than AND — this is different from most programming languages. Parentheses may be needed to ensure correct logical evaluation
The eval() function uses := syntax for field assignment, not = which is used for comparison. field := value creates a new field; field = value filters
Pre-built dashboards require specific data sources to be ingested. If the underlying data connector is not configured, the dashboard will show no data — this is not a dashboard error
Correlation rules and CQL search queries use the same syntax but serve different purposes: rules are persistent detections, queries are ad-hoc investigations
Tuning a correlation rule means adjusting its LOGIC, not disabling it. The exam tests whether you can refine rules to reduce false positives while maintaining detection coverage
Domain 510% of exam
Automation and Integration
This domain covers automating security operations using Falcon Fusion SOAR workflows, generating API authentication credentials, and implementing API integrations using the FalconPy SDK. While the smallest domain by weight, it tests practical automation skills that bridge SIEM data with response actions.
Key Topics
Falcon Fusion SOARFalconPy SDKAPI CredentialsWorkflow AutomationOAuth 2.0
Must-Know Concepts
- Falcon Fusion SOAR workflow capabilities: no-code visual builder, scheduled/on-demand/event-triggered workflows, first-party and third-party actions, and natural language workflow generation
- SOAR workflow action types: device queries, email notifications, Jira ticket creation, log writing, host containment, and custom HTTP actions
- API authentication credential generation: creating OAuth 2.0 Client ID and Client Secret pairs, scoping permissions, and managing credential lifecycle
- FalconPy SDK implementation: Service Classes (per-API-collection) vs Uber Class (single interface), automatic token management, and basic API interaction patterns
- HTTP Actions in SOAR: three authentication methods (API keys, OAuth 2.0, CrowdStrike-specific), integration with external tools and services
Common Exam Traps
Falcon Fusion SOAR is NO-CODE — workflows are built visually, not through programming. But API integrations via FalconPy DO require Python code
FalconPy handles OAuth token management automatically — you do not need to manually refresh tokens. But you DO need to provide Client ID and Client Secret
SOAR workflows can be triggered by correlation rule detections, but they are configured separately from the rules themselves
The Workflow Generation Agent uses natural language to CREATE workflows, but executing custom actions still requires proper API credentials and permissions
Concepts You Must Not Confuse
These pairs appear on nearly every exam. Learn the difference and you'll avoid the most common traps.
Top Mistakes to Avoid
Confusing data connectors (API-based cloud integrations) with Falcon Log Collector (deployed software for syslog/file collection) — each serves different data source types
Assuming CPS is identical to Elastic Common Schema (ECS) — CPS is based on ECS 8.x but has documented deviations and extensions specific to CrowdStrike
Forgetting that non-ECS fields are prefixed with 'Vendor.' in CPS — they are NOT dropped or ignored, all raw log fields must be preserved
Using = instead of := in CQL eval() statements — = is for comparison/filtering, := is for field assignment and creation
Not knowing that OR binds closer than AND in CQL — this differs from most programming languages and can cause incorrect query logic without parentheses
Treating AI-assisted parsers as production-ready without validation — AI-generated parsers are starting points that require manual review and test case verification
Confusing correlation rules (persistent automated detections) with CQL search queries (ad-hoc investigations) — both use CQL syntax but serve fundamentally different purposes
Mixing up Falcon Log Collector fleet management with Falcon sensor management — fleet management refers to managing log collectors, not endpoint agents
Thinking Falcon Fusion SOAR requires coding — SOAR uses a no-code visual builder, while API integrations via FalconPy require Python
Underestimating the Parsing domain (30%) and Data Ingestion domain (27%) — together they account for 57% of the exam and require practical knowledge
Exam-Ready Checklist
Can explain all 5 exam domains and their relative weights (7%, 27%, 30%, 26%, 10%)
Understand the CrowdStrike Parsing Standard (CPS) including its relationship to ECS, vendor-prefixed fields, and parser compliance requirements
Can write CQL queries using key functions: groupBy(), stats(), top(), eval(), regex(), rename(), replace(), sort(), formatTime()
Know the difference between data connectors (API-based) and Falcon Log Collector (syslog/file-based) and when to use each
Can build and validate custom parsers from scratch, clone existing parsers, and use AI-assisted parser generation
Understand correlation rule creation, tuning, and the difference between vendor-native and external detection sources
Can configure Falcon Fusion SOAR workflows with triggers, actions, and integrations including understanding no-code vs API approaches
Know Falcon Log Collector installation, sizing specifications, fleet management, and HEC sink architecture
Understand RBAC user management including custom roles, repository-level access, and permission scoping
Can troubleshoot common issues: ingestion failures, parsing errors, missing events, connector authentication problems, and query performance
Know FalconPy SDK authentication (OAuth 2.0 Client ID/Secret), Service Classes vs Uber Class, and automatic token management
Scored 80%+ on at least two full mock exams — the passing threshold is 80%, leaving very little room for error across 60 questions
Recommended Resources
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