Splunk MCP for SOC Operations
Enables AI-driven SOC investigations by providing automated Splunk querying, threat intelligence enrichment, and response actions through natural language. Includes tools for IP pivoting, lateral movement detection, and label harvesting.
README
Splunk MCP for SOC Operations
An AI-native MCP (Model Context Protocol) server for SOC operations with Splunk, featuring automated investigation tools, label harvesting, and DeepTempo integration capabilities.
🎯 Overview
This project extends the capabilities of livehybrid/splunk-mcp with SOC-specific enrichment tools and security controls designed for AI-driven security investigations via Claude Desktop and other MCP clients.
Key Features
- Traditional SOC Workflows - IP pivoting, lateral movement detection, data exfiltration analysis
- AI-Native Investigation - Cross-platform correlation, attack timeline reconstruction
- Label Harvesting - Automatic discovery and mapping of Splunk field labels
- Production Security - Input validation, audit logging, output sanitization
- Multi-Mode Operation - SSE, STDIO, and API modes for flexible deployment
🚀 Quick Start
Prerequisites
- Python 3.10 or higher
- Splunk Enterprise or Cloud instance
- pip (included with Python)
Installation
-
Clone the repository:
git clone https://github.com/mando222/splunk-mcp-soc.git cd splunk-mcp-soc -
Install dependencies:
Using pip (recommended):
pip install -r requirements.txtOr with UV:
uv syncOr with Poetry:
poetry install -
Configure environment variables:
Create a
.envfile:SPLUNK_HOST=localhost SPLUNK_PORT=8089 SPLUNK_USERNAME=admin SPLUNK_PASSWORD=your-password SPLUNK_SCHEME=https VERIFY_SSL=false -
Test the connection:
python test_connection.py -
Run the MCP server:
# STDIO mode (for Claude Desktop) python splunk_mcp.py stdio # SSE mode (default) python splunk_mcp.py # API mode python splunk_mcp.py api
🛠️ Available MCP Tools
Core Operations
- health_check - Verify Splunk connectivity and available apps
- ping - Check MCP server status
- current_user - Get authenticated user information
- list_users - List all Splunk users and roles
Index & Search Management
- list_indexes - List all accessible indexes
- get_index_info - Get detailed information about a specific index
- indexes_and_sourcetypes - Comprehensive index and sourcetype mapping
- search_splunk - Execute Splunk search queries with time ranges
- list_saved_searches - View saved searches
KV Store Operations
- list_kvstore_collections - List all KV store collections
- create_kvstore_collection - Create new collections
- delete_kvstore_collection - Remove collections
SOC Investigation Tools
- pivot_by_ip - Investigate all activity from a specific IP address
- find_lateral_movement - Detect lateral movement patterns
- calculate_data_exfiltration - Analyze and quantify data exfiltration
- build_attack_timeline - Construct chronological attack timelines
- correlate_with_deeptempo_finding - Cross-reference with DeepTempo findings
Threat Intelligence Integration
- enrich_ip_with_threat_intel - Enrich IPs with reputation data from multiple sources
- Queries AbuseIPDB, AlienVault OTX, and internal Splunk threat lists
- Provides reputation score, threat types, and confidence levels
- check_ioc_reputation - Quick reputation check for any IOC (IP, domain, hash, URL)
- Auto-detects IOC type and provides actionable verdict
- add_to_threat_list - Add confirmed IOCs to Splunk threat intelligence
- Supports expiration and automatic cleanup
- get_mitre_attack_context - Get detailed MITRE ATT&CK technique information
- Maps findings to tactics, techniques, and procedures
- Includes detection methods and mitigations
Automated Response Actions
- block_ip_address - Block malicious IPs at firewall/proxy level
- Temporary or permanent blocking
- Auto-unblock capability with configurable duration
- isolate_host - Quarantine compromised hosts from network
- Full, partial, or monitoring-only isolation levels
- Integrates with NAC and endpoint security tools
- create_incident_ticket - Auto-create tickets in ITSM platforms
- ServiceNow, Jira, or native Splunk incident tracking
- Automatic priority and SLA calculation
- send_alert_notification - Push alerts to communication channels
- Slack, Microsoft Teams, PagerDuty, email, SMS
- Severity-based routing
Advanced Analytics & Anomaly Detection
- detect_anomalies - Statistical anomaly detection on time-series data
- Z-score based detection with configurable sensitivity
- Identifies spikes, dips, and unusual patterns
- identify_rare_events - Find statistically rare occurrences
- Detects new processes, domains, or behaviors
- Useful for zero-day and APT detection
- baseline_normal_behavior - Establish behavioral profiles
- Learn normal patterns for users, hosts, or services
- Enables deviation-based threat detection
Label Harvesting
- harvest_labels - Discover field labels and schemas from Splunk indexes
- Configurable scope (all indexes, specific indexes, or CIM fields only)
- Returns field names, types, sample values, and metadata
- Supports filtering by index and time range
- get_field_summary - Get detailed information about a specific field
- Deep dive into field values, distribution, and relationships
- Useful for understanding individual field usage
- export_labels_to_deeptempo - Export labels in DeepTempo-compatible format
- Generic JSON structure that can be adapted to DeepTempo's needs
- Optional file export for integration workflows
📊 Demo Scenarios
Scenario 1: IP Investigation
Query: "Show me all activity from IP 10.1.42.42"
Results:
- 65 total events discovered
- 47 unique destinations contacted
- 10+ lateral movement attempts detected
- 1.2 GB data exfiltration identified
Scenario 2: Attack Timeline
Query: "Build attack timeline for 10.1.42.42 and correlate with DeepTempo"
Results:
- 32-day attack timeline reconstructed
- Initial compromise → lateral movement → exfiltration
- 12 similar incidents identified
- Complete MITRE ATT&CK mapping
Scenario 3: Threat Hunting
Query: "Hunt for similar C2 beaconing patterns across all hosts"
Results:
- 3 additional compromised hosts found
- Common service account identified (jenkins_service)
- Botnet infrastructure mapped
🧪 Testing
Generate and ingest test security data:
# Generate test data
python generate_test_data.py
# Ingest into Splunk
python ingest_test_data.py your-password
This creates an mcp_demo index with 115 security events:
- 50 C2 beaconing events
- 40 authentication/lateral movement events
- 20 DNS tunneling events
- 5 data exfiltration events
Run the test suite:
pytest tests/
🐳 Docker Support
Run with Docker Compose
- SSE Mode (default):
docker compose up -d mcp
- API Mode:
docker compose run --rm mcp python splunk_mcp.py api
- STDIO Mode:
docker compose run -i --rm mcp python splunk_mcp.py stdio
Run Tests in Docker
./run_tests.sh --docker
🔧 Configuration
Environment Variables
| Variable | Description | Default |
|---|---|---|
SPLUNK_HOST |
Splunk server hostname | localhost |
SPLUNK_PORT |
Splunk management port | 8089 |
SPLUNK_USERNAME |
Authentication username | admin |
SPLUNK_PASSWORD |
Authentication password | - |
SPLUNK_TOKEN |
Optional: Use token instead of user/pass | - |
SPLUNK_SCHEME |
Connection scheme (http/https) | https |
VERIFY_SSL |
Enable SSL certificate verification | true |
FASTMCP_LOG_LEVEL |
Logging level | INFO |
SERVER_MODE |
Server mode (sse/api/stdio) | sse |
Claude Desktop Integration
Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"splunk-soc": {
"command": "python",
"args": [
"/path/to/splunk-mcp-soc/splunk_mcp.py",
"stdio"
],
"env": {
"SPLUNK_HOST": "localhost",
"SPLUNK_PORT": "8089",
"SPLUNK_USERNAME": "admin",
"SPLUNK_PASSWORD": "your-password"
}
}
}
}
📚 Documentation
| Document | Purpose |
|---|---|
| SETUP_INSTRUCTIONS.md | Detailed setup guide |
| DEMO_TOOLS_SPEC.md | Complete tool specifications |
| SOC_PLAYBOOKS.md | Investigation workflow examples |
| CONTRIBUTING.md | Development guidelines |
| DEMO_TESTING_GUIDE.md | Testing procedures |
🏗️ Architecture
Claude Desktop / MCP Client
│
├── Splunk MCP Server (this project)
│ ├── SOC Investigation Tools
│ ├── Label Harvesting
│ └── Splunk SDK Integration
│
└── DeepTempo MCP Server (separate)
├── Embedding Similarity Search
├── MITRE ATT&CK Mapping
└── LogLM Analysis
🔐 Security Considerations
Current Implementation
- ✅ SSL/TLS support with configurable verification
- ✅ Token-based and credential-based authentication
- ✅ Environment variable configuration
- ✅ Input validation on all tools
- ✅ Audit logging support
Best Practices
- Never commit
.envfiles - Use
VERIFY_SSL=truein production - Rotate credentials regularly
- Monitor audit logs
- Use least-privilege Splunk accounts
🤝 Contributing
Contributions are welcome! Please see CONTRIBUTING.md for guidelines.
📝 Credits
This project is built upon livehybrid/splunk-mcp v0.3.0 and extends it with:
- SOC-specific investigation tools
- Label harvesting capabilities
- DeepTempo integration support
- Enhanced security controls
Dependencies
- FastMCP - MCP server framework
- Splunk SDK for Python - Splunk API client
- python-decouple - Configuration management
📄 License
Apache License 2.0 - See LICENSE for details.
🐛 Troubleshooting
Connection Issues
# Test Splunk connectivity
python test_connection.py
# Check logs
tail -f splunk_mcp.log
No Data in Splunk
# Ingest test data
python ingest_test_data.py your-password
# Verify in Splunk UI
index=mcp_demo | stats count by event_type
MCP Server Won't Start
- Verify
.envfile exists with correct values - Check Python version (3.10+ required)
- Ensure Splunk is accessible
- Review error logs
📞 Support
For issues and questions:
- Check documentation
- Review error logs
- Open an issue on GitHub
Built with FastMCP for AI-native security operations 🚀
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