building-incident-timeline-with-timesketch skill
Build collaborative forensic incident timelines using Timesketch to ingest,
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Install the building-incident-timeline-with-timesketch skill
A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.
git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git /tmp/Anthropic-Cybersecurity-Skills mkdir -p ~/.claude/skills cp -r /tmp/Anthropic-Cybersecurity-Skills/skills/building-incident-timeline-with-timesketch ~/.claude/skills/building-incident-timeline-with-timesketch
In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub
The instructions your agent would load
SKILL.md as published, without the frontmatter. Read it on GitHub
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
cd docker
sudo docker compose up -d
# Default access: https://localhost:443
# Admin credentials generated during first runSystem 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.plasoMethod 2: CSV Import (Quick Ingestion)
message,datetime,timestamp_desc,source,hostname
"User login detected","2025-01-15T08:30:00Z","Event Recorded","Security Log","DC01"
"PowerShell execution","2025-01-15T08:31:15Z","Event Recorded","PowerShell","WKS042"# Import CSV directly
timesketch_importer -s "Case-2025-001" -t "Quick-Triage" events.csvMethod 3: JSONL Import (Structured Data)
{"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 tagsStep 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
- Feature Extraction Analyzer: Identifies IPs, URLs, hashes
- 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 reportAdvanced 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 events
for 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 0Key Data Sources for Timeline Building
MITRE ATT&CK Mapping
References
- Timesketch Official Documentation
- Timesketch GitHub Repository
- CISA Timesketch Resource
- Hunt and Hackett: Scalable Forensics with Dissect and Timesketch
- Plaso (log2timeline) Documentation
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