I am not a full expert in time series, but I think this is not correct. It is true, that the mean of $W_t$ is restricted to be the same for all $t$ as by imposing weak stationarity, the process must satisfy, that
$$E[X_t]=E[X_{t+\tau}]\text{ } \forall \tau \in \mathbb{N} $$ which would probably imply that $E[W_t]=E[W_{t+\tau}]\text{ } \forall \tau \in \mathbb{N}$. But secondly we have by weak stationarity, that
$$E(X_t−E[X_t])(X_{k}−E[X_t])=E(X_{t+\tau}−E[X_{t}])(X_{k+\tau}−E[X_t]) =\gamma(t-k)$$ which does to covariance function $\gamma$ restrict to depend on the the shift in time $t-k$. From this, the expectation of $W_t$ must indeed stay the same, but the covariance is not restricted to be zero on the off-diagonal. Therefore, my opinon is that the statment is false in general.
If a violation of of the $\phi_p \neq 0$ condition is allowed, we have the trival case $$X_t = \mu + W_t $$ with weak stationarity the autocovariance of $W_t$ is allowed to depend on the shift of time $t-k$ and is hence not iid in the sence that the realizations of the process $\{W_t\}_{t=1}^{T}$ are independent.