  We close an unexpected gap in the literature of stochastic differential
equations (SDEs) with drifts of super linear growth (and random coefficients),
namely, we prove Malliavin and Parametric Differentiability of such SDEs. The
former is shown by proving Ray Absolute Continuity and Stochastic G\^ateaux
Differentiability. This method enables one to take limits in probability rather
than mean square which bypasses the potentially non-integrable error terms from
the unbounded drift. This issue is strongly linked with the difficulties of the
standard methodology from Nualart's 2006 work, Lemma 1.2.3 for this setting.
Several examples illustrating the range and scope of our results are presented.
  We close with parametric differentiability and recover representations
linking both derivatives as well as a Bismut-Elworthy-Li formula.
