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alirezaaminzadeh/
logbert-event-embedder

Name: logbert-event-embedder
Availability: InStock

self-supervised-learning

soc

alirezaaminzadeh/logbert-security-events

mit

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LogBERT Event Embedder

Self-supervised security event embedding and anomaly detection models.

Models Included

File	Description
`tokenizer.json`	Event type vocabulary (22+ tokens)
`isolation_forest.joblib`	Classical anomaly baseline
`one_class_svm.joblib`	One-class SVM detector
`lof.joblib`	Local Outlier Factor
`pca.joblib`	PCA reconstruction error
`lstm_autoencoder.pt`	LSTM sequence autoencoder
`transformer_event_model.pt`	Transformer masked event model
`contrastive_encoder.pt`	Contrastive session embedder

Usage

python

from pathlib import Path
import sys
sys.path.insert(0, "src")
from logbert.pipeline import LogBERTPipeline

pipeline = LogBERTPipeline(model_dir=Path("model"))
result = pipeline.process(open("logs.jsonl").read())
print(result.anomaly_count)

Training

Trained on synthetic endpoint security event sequences. See project README for reproduction.

Limitations

Synthetic training data; fine-tune on your organization's logs for production
CPU-optimized small models; scale up for enterprise volume
Event taxonomy covers common endpoint scenarios

Ethical Considerations

Designed for defensive security monitoring. Do not use for unauthorized surveillance.

alirezaaminzadeh/logbert-event-embedder