Multivariate Gaussian Model with Covariance matrix returns incorrect answer in some cases

I have been trying to apply an Anomaly Detection model using Spark MLib.

As an input, I feed the model with a mean vector and a Covariance matrix. ,assuming my features contain Co-variance.

Here are my input for the model ,and the model returns zero for each data point for this input.

MU vector -
1054.8, 1069.8, 1.3 ,1040.1
Cov' matrix -
165496.0 , 167996.0, 11.0 , 163037.0
167996.0, 170631.0, 19.0, 165405.0
11.0, 19.0 , 0.0, 2.0
163037.0, 165405.0 2.0 , 160707.0

Conversely, for the non covariance case, represented by this matrix ,the model is working and returns results as expected
165496.0, 0.0 , 0.0, 0.0
0.0, 170631.0, 0.0, 0.0
0.0 , 0.0 , 0.8, 0.0
0.0 , 0.0, 0.0, 160594.2