What type of Anomaly Detection Model could I use?

I would like to create an anomaly detection model that assigns a probability of risk instead of labels (1 or 0). My problem is that I only know for sure which records are anomalous but not which are Normal.

Regarding this, would be better to work on Unsupervised anomaly detection instead of semi-supervised or supervised?

Note: I have high dimensional data (20-40+ features). And a few hundreds of anomalies while around a thousand that I do not know.