Build collaborative forensic incident timelines using Timesketch to ingest, normalize, and analyze multi-source event data for attack chain reconstruction and investigation documentation.
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Build collaborative forensic incident timelines using Timesketch to ingest, normalize, and analyze multi-source event data for attack chain reconstruction and investigation documentation.
["Executable Denylisting","Execution Isolation","File Metadata Consistency Validation","Content Format Conversion","File Content Analysis"]
nist_csf
["RS.MA-01","RS.MA-02","RS.AN-03","RC.RP-01"]
Building Incident Timeline with Timesketch
Overview
Timesketch is an open-source collaborative forensic timeline analysis tool developed by Google that enables security teams to visualize and analyze chronological data from multiple sources during incident investigations. It ingests logs and artifacts from endpoints, servers, and cloud services, normalizes them into a unified searchable timeline, and provides powerful analysis capabilities including built-in analyzers, tagging, sketch annotations, and story building. Timesketch integrates with Plaso (log2timeline) for artifact parsing and supports direct CSV/JSONL ingestion for rapid timeline construction during active incidents.
When to Use
When deploying or configuring building incident timeline with timesketch capabilities in your environment
When establishing security controls aligned to compliance requirements
When building or improving security architecture for this domain
When conducting security assessments that require this implementation
Prerequisites
Familiarity with incident response concepts and tools
Access to a test or lab environment for safe execution
Python 3.8+ with required dependencies installed
Appropriate authorization for any testing activities
Architecture and Components
Core Components
Timesketch Server: Web application with REST API for timeline management
OpenSearch/Elasticsearch: Backend storage and search engine for timeline events
PostgreSQL: Metadata storage for sketches, stories, and user data
Redis: Task queue management for background processing
Celery Workers: Asynchronous processing of timeline uploads and analyzers
Data Flow
Evidence Sources --> Plaso/log2timeline --> Plaso storage file (.plaso)
| |
v v
CSV/JSONL --> Timesketch Importer --> OpenSearch Index
|
v
Timesketch Web UI
(Search, Analyze, Story)
Deployment
Docker Deployment (Recommended)
# Clone Timesketch repository
git clone https://github.com/google/timesketch.git
cd timesketch
# Run deployment helper script
docker
docker compose up -d
cd
sudo
# Default access: https://localhost:443
# Admin credentials generated during first run
System Requirements
Minimum 8 GB RAM (16+ GB recommended for large investigations)
4 CPU cores minimum
SSD storage for OpenSearch indices
Docker and Docker Compose installed
Data Ingestion Methods
Method 1: Plaso Integration (Comprehensive)
# Process disk image with log2timeline
log2timeline.py --storage-file evidence.plaso /path/to/disk/image
# Process Windows event logs
log2timeline.py --parsers winevtx --storage-file windows_events.plaso /path/to/evtx/
# Process multiple evidence sources
log2timeline.py --parsers "winevtx,prefetch,amcache,shimcache,userassist" \
--storage-file full_analysis.plaso /path/to/mounted/image/
# Import Plaso file into Timesketch
timesketch_importer -s "Case-2025-001" -t "Endpoint-WKS01" evidence.plaso
{"message":"Suspicious logon from 10.1.2.3","datetime":"2025-01-15T08:30:00Z","timestamp_desc":"Event Recorded","source_short":"Security","hostname":"DC01"}
Method 4: Sigma Rule Integration
# Upload Sigma rules for automated detection
timesketch_importer --sigma-rules /path/to/sigma/rules/
Analysis Workflow
Step 1: Create Investigation Sketch
1. Log into Timesketch web interface
2. Create new sketch (investigation case)
3. Add relevant timelines to the sketch
4. Set sketch description and tags
Step 2: Run Built-in Analyzers
Timesketch includes analyzers that automatically identify:
Browser Search Analyzer: Extracts search queries from browser history
Chain of Events Analyzer: Links related events (download -> execute)
Domain Analyzer: Extracts and categorizes domain names
Geo Location Analyzer: Maps events to geographic locations
Similarity Scorer: Finds similar events across timelines
Sigma Analyzer: Matches events against Sigma detection rules
Account Finder: Identifies user account activity patterns
Tagger: Applies labels based on predefined rules
Step 3: Search and Filter
# Search examples in Timesketch query language
# Find all events related to specific user
source_short:Security AND message:"john.admin"
# Find PowerShell execution events
data_type:"windows:evtx:record" AND event_identifier:4104
# Find lateral movement indicators
source_short:Security AND event_identifier:4624 AND xml_string:"LogonType\">3"
# Find events within specific time range
datetime:[2025-01-15T00:00:00 TO 2025-01-15T23:59:59]
# Find file creation events
data_type:"fs:stat" AND timestamp_desc:"Creation Time"
# Search with tags
tag:"suspicious" OR tag:"lateral_movement"
Step 4: Build Investigation Story
1. Create new story within the sketch
2. Add search views that support each finding
3. Annotate key events with investigator notes
4. Link events to MITRE ATT&CK techniques
5. Document the attack narrative chronologically
6. Export story for inclusion in incident report
Advanced Features
Collaborative Investigation
Multiple analysts work on the same sketch simultaneously
Comments and annotations persist on events
Saved searches shared across the team
Investigation stories document findings in context
API Automation
from timesketch_api_client import config
from timesketch_api_client import client as ts_client
# Connect to Timesketch
ts = ts_client.TimesketchApi(
host_uri="https://timesketch.local",
username="analyst",
password="password"
)
# Get sketch
sketch = ts.get_sketch(1)
# Search events
search = sketch.explore(
query_string='event_identifier:4624 AND LogonType:3',
return_fields='datetime,message,hostname,source_short'
)
# Add tags to eventsfor event in search.get('objects', []):
sketch.tag_event(event['_id'], ['lateral_movement'])
Integration with Dissect
# Use Dissect for faster artifact parsing (alternative to Plaso)
target-query -f timesketch://timesketch.local/case-001 \
targets/hostname/ -q "windows.evtx" --limit 0
