Now you tricked yourself with too much linearity.
While relu is nonlinear globally (else we would famously not have the universal representation property) it is linear in a neighborhood of almost every input (if you pardon the mathematics lingo), rendering your network linear in a neighborhood of your inputs.
Taking a more global view, the derivative is piecewise constant, and the second derivative 0 where defined.