  We consider solutions of L\'evy-driven stochastic differential equations of
the form $\mathrm{d} X_t=\sigma(X_{t-})\mathrm{d} L_t$, $X_0=x$ where the
function $\sigma$ is twice continuously differentiable and maximal of linear
growth and the driving L\'evy process $L=(L_t)_{t\geq0}$ is either vector or
matrix-valued. While the almost sure short-time behavior of L\'evy processes is
well-known and can be characterized in terms of the characteristic triplet,
there is no complete characterization of the behavior of the process $X$. Using
methods from stochastic calculus, we derive limiting results for stochastic
integrals of the from $\smash{t^{-p}\int_{0+}^t\sigma(X_{t-})\mathrm{d} L_t}$
to show that the behavior of the quantity $t^{-p}(X_t-X_0)$ for $t\downarrow0$
almost surely mirrors the behavior of $t^{-p}L_t$. Generalizing $t^p$ to a
suitable function $f:[0,\infty)\rightarrow\mathbb{R}$ then yields a tool to
derive explicit LIL-type results for the solution from the behavior of the
driving L\'evy process.

Probability