---
title: Cordon - Log Anomaly Detection
emoji: 🔍
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 6.2.0
app_file: app.py
pinned: false
license: apache-2.0
short_description: Find anomalies in logs using AI. Paste logs, get insights.
hardware: zero-gpu
tags:
- log-analysis
- anomaly-detection
- semantic-search
- embeddings
- transformers
- devops
- sre
- observability
- debugging
- nlp
- text-analysis
- machine-learning
- ai-tools
---

# Cordon

**Reduce logs to their semantically anomalous parts.**

Cordon uses AI to understand the *meaning* of your logs and find the parts that are semantically unusual—reducing massive log files to just the anomalous sections worth investigating.

## How It Works

1. **Segmentation** — Logs are split into non-overlapping windows
2. **Embedding** — Each window is vectorized using transformers
3. **Scoring** — Distance to nearest neighbors identifies unusual patterns
4. **Thresholding** — Top anomalies are selected
5. **Output** — XML-tagged blocks ready for LLM analysis

## Use Cases

- **Debug faster** — Find the needle in the haystack
- **LLM pre-processing** — Reduce logs to fit in context windows
- **Incident response** — Surface unusual events quickly
- **Exploratory analysis** — Discover patterns you didn't know to search for

## Key Insight

> Repetitive patterns (even errors) are filtered out. Cordon surfaces the *rare* and *unusual* events that stand out from the bulk of your logs.

## Links

- [GitHub Repository](https://github.com/calebevans/cordon)
- [PyPI Package](https://pypi.org/project/cordon/)
- [Red Hat Developer Article](https://developers.redhat.com/articles/2025/12/09/semantic-anomaly-detection-log-files-cordon)