I built LogSentinel because I needed to analyze Nginx/Syslogs logs with AI, but strict data policies prevented me from sending raw logs to OpenAI/Claude.
How it works:
It tails log files in real-time.
Masks PII (IPs, emails, credit cards) using Regex before inference.
Sends the sanitized context to a local LLM (Ollama running Llama 3) to find anomalies.
Stores patterns in SQLite to avoid re-analyzing known errors (caching).
It's an MVP, written in Python. I'd love to hear your feedback on the architecture or how you handle local log analysis securely.
I built LogSentinel because I needed to analyze Nginx/Syslogs logs with AI, but strict data policies prevented me from sending raw logs to OpenAI/Claude.
How it works:
It's an MVP, written in Python. I'd love to hear your feedback on the architecture or how you handle local log analysis securely.