⚠️ Disclaimer:
This repository contains a project description only.
The actual code is confidential and proprietary.
Contact for demo access or SIEM consulting services.
The Enterprise SIEM Parser Generator automates the creation of custom parsers for Security Information and Event Management (SIEM) systems, streamlining the process of onboarding new log sources and enhancing threat detection capabilities.
This tool empowers SOC teams to parse logs from new devices, cloud platforms, and applications, without waiting for vendor-specific updates.
Built for enterprise SOC environments, the framework boosts detection capabilities and reduces the time to integrate new technologies.
- 🔍 Automatic Log Pattern Detection: Uses regex and ML to identify fields in new log sources.
- ⚙️ SIEM Parser Generation: Supports formats for Splunk, IBM QRadar, Elastic Stack, and others.
- 🚀 Rapid Deployment: Generates deployable parser configurations in seconds.
- 🛡️ Custom Enrichment: Adds geo-IP, user attribution, and severity mapping.
- 📊 Validation Module: Tests generated parsers against live or sample log streams.
| Scenario | Description |
|---|---|
| SOC Automation | Automate onboarding of new log sources into SIEM. |
| Threat Detection Enhancement | Improve parsing for better alerting and correlation. |
| Log Source Normalization | Standardize logs from custom or legacy applications. |
| Incident Response | Quickly enable visibility on newly deployed technologies. |
- Python 3.x
- Regex / PyParsing
- YAML / JSON parser configuration templates
- ML algorithms for pattern detection (optional)
- Supported SIEMs: Splunk, QRadar, Elastic Stack, Graylog
The parser generation algorithms and SIEM integrations are enterprise-grade automation scripts that could be misused to manipulate or disrupt SOC environments.
Access is restricted to security teams and SOC engineers.
Need help automating SIEM log parsing?
→ Contact Muhammad Usama for SOC automation consulting.