Use the Characteristic function. It is well known that,
$$\varphi_Y(s) := \mathbb E\left[e^{is^\intercal Y}\right] = e^{-\frac12s^\intercal \Sigma s}.$$
So \begin{align}
\frac{\partial^2 \varphi_Y}{\partial^2 s_1} = \mathbb E\left[-Y_1^2e^{is^\intercal Y}\right] = \frac{\partial}{\partial s_1}\left[\left(-\sigma_{11}s_1-\sigma_{12}s_2\right)e^{-\frac12s^\intercal \Sigma s}\right] = \left(-\sigma_{11} + \left(\sigma_{11}s_1 + \sigma_{12}s_2\right)^2\right)e^{-\frac12s^\intercal \Sigma s}
\end{align}
Put $s_1 = 0$ and you will have:
$$-\mathbb E\left[Y_1^2 e^{is_2Y_2}\right] = \left(-\sigma_{11} + \sigma_{12}^2s_2^2\right)e^{-\frac12\sigma_{22}s_2^2}$$
and then,
$$\mathbb E\left[Y_1^2 Y_2^2e^{is_2Y_2}\right] = \frac{\partial^2}{\partial s_2^2}\mathbb E\left[-Y_1^2 e^{is_2Y_2}\right] = \frac{\partial}{\partial s_2}\left[\left(2\sigma_{12}^2s_2 +\sigma_{11}\sigma_{22}s_2 - \sigma_{12}^2 \sigma_{22}s_2^3\right)e^{-\frac12\sigma_{22}s_2^2}\right] = \left(2\sigma_{12}^2 + \sigma_{11}\sigma_{22} -3\sigma_{12}^2\sigma_{22}s^2_2-2\sigma_{12}^2\sigma_{22}s^3_2 - \sigma_{11}\sigma^2_{22}s^2_2 + \sigma_{12}^2 \sigma_{22}^2s_2^4\right)e^{-\frac12\sigma_{22}s_2^2}$$
Put $s_2 = 0$ and you will have:
$$\mathbb E\left[Y_1^2Y_2^2\right] = 2\sigma_{12}^2 + \sigma_{11}\sigma_{22}$$
It is worth it to mention that with this method you can compute all:
$$\mathbb E\left[Y_1^kY_2^\ell\right]$$