You could simply calculate the covariance matrix of the feature vector and check the off-diagonal elements.  Uncorrelated features will have a diagonal covariance matrix.

You can use the correlation matrix to find the correlated features,The correlation matrix of n random variables X1, ..., Xn is the n  ×  n matrix whose i,j entry is corr(Xi, Xj). If the measures of correlation used are product-moment coefficients, the correlation matrix is the same as the covariance matrix of thestandardized random variables Xi / σ (Xi) for i = 1, ..., n. This applies to both the matrix of population correlations (in which case "σ" is the population standard deviation), and to the matrix of sample correlations (in which case "σ" denotes the sample standard deviation). Consequently, each is necessarily a positive-semidefinite matrix.

The correlation matrix is symmetric because the correlation between Xi and Xj is the same as the correlation between Xjand Xi.