Python Tool Uses LLMs to Auto-Triage SIEM Alerts and Cut Noise by 80%

Security operations centers routinely face alert fatigue, with analysts typically reviewing only a fraction of the thousands of alerts a SIEM generates each shift. A developer has published a working Python implementation that feeds enriched SIEM alerts into a large language model to automate first-pass triage. The pipeline pulls raw alerts, enriches them with context such as IP reputation, user roles, and asset criticality, then sends the payload to an LLM for a structured verdict. By handling the large volume of clearly benign or clearly high-priority alerts, the system aims to reduce noise by around 80% and free analysts for complex investigations. The implementation uses OpenAI's Python SDK and supports any compatible endpoint, including locally hosted models.