The distance distribution from the mean for an n-dimensional normal(Gaussian) distribution

Let's say we have an n-dimensional normal distribution with identity covariance matrix and 0 mean. When we draw random points in this distribution, how do I get the distribution of the distance from the mean (0) in terms of d?

This is a chi distribution with $n$ degrees of freedom, so called because it is the square root of a chi-square distribution.
Its density for $x\gt 0$ is $$\frac{2^{1-n/2}x^{n-1}e^{-x^2/2}}{\Gamma(n/2)}.$$