Given the standard bivariate normal density with correlation coefficient $\rho$ for $X$ and $Y$:
$$f_{X,Y}(x,y)=\frac{1}{2\pi\sqrt{1-\rho^2}}e^{-(x^2-2\rho xy+y^2)/2(1-\rho^2)}$$
Is there a way to work backwards and show that $X$ and $Y$ are standard normal density without the assumption of independence?
Integrate out one of the variables.
$$f_X(x) = \int \frac{1}{2\pi \sqrt{1-\rho^2}}\exp\left(-\frac{x^2-2\rho xy+y^2}{2(1-\rho^2)}\right)\,dy$$ $$ = \frac{1}{2\pi \sqrt{1-\rho^2}}\exp\left(-\frac{x^2(1-\rho^2)}{2(1-\rho^2)}\right)\int \exp\left(-\frac{\rho^2x^2-2\rho xy+y^2}{2(1-\rho^2)}\right)\,dy$$ Notice that I've pulled out a piece of the exponential that doesn't depend on $y$ in order to get the numerator inside the integral to have $\rho^2x^2$ in it. $$ = \frac{1}{2\pi \sqrt{1-\rho^2}}\exp\left(-x^2/2\right)\int \exp\left(-\frac{(y-\rho x)^2}{2(1-\rho^2)}\right)\,dy$$ Letting $u=\frac{y-\rho x}{\sqrt{1-\rho^2}}$, we have $dx = \sqrt{1-\rho^2}\,du$, and $$ = \frac{1}{2\pi \sqrt{1-\rho^2}}\exp\left(-x^2/2\right)\int \exp\left(-u^2/2\right)\sqrt{1-\rho^2}\,du$$ $$ = \frac{1}{2\pi }\exp\left(-x^2/2\right)\sqrt{2\pi} = \frac{e^{-x^2/2}}{\sqrt{2\pi}}.$$
Thus $X\sim \mathcal{N}(0,1)$, as desired.