Python Code to generate quasi random standard normal numbers using sobol sequences gives erroneous values

I have a Python code to generate quasi random standard normal numbers using sobol sequences, however some values generated are greater than 1. Hence I must be doing something wrong. Code:

import sobol_seq

def i4_sobol_generate_std_normal(dim_num, n, skip=1):
    """
    Generates multivariate standard normal quasi-random variables.
    Parameters:
      Input, integer dim_num, the spatial dimension.
      Input, integer n, the number of points to generate.
      Input, integer SKIP, the number of initial points to skip.
      Output, real np array of shape (n, dim_num).
    """

    sobols = sobol_seq.i4_sobol_generate(dim_num, n, skip)

    normals = norm.ppf(sobols)

    return normals

NoOfPaths = 8

rand = i4_sobol_generate_std_normal(1, NoOfPaths)
lRand = []
for i in range(len(rand)):
    a = rand[i][0]
    lRand.append(a)
rand = np.array(lRand)

Output : 
Out[34]:
array([ 0.        ,  0.67448975, -0.67448975, -0.31863936,  1.15034938,
        0.31863936, -1.15034938, -0.88714656])

References : Recommendations for Low Discrepancy (e.g. Sobol) quasi-random sequences in Python/SciPy? and https://github.com/naught101/sobol_seq

I want to use the generated values in monte carlo simulations. Any help is appreciated.