Let $\mu$ be a Gaussian measure on a separable Banach space $X$ and $q$ is the covariance operator of $\mu$. I am reading a proof for
$$\operatorname {supp} \mu = \bigcap_{q(f, f) = 0} \ker f =: E$$
but there is a step I don't understand. So far I understand that the intersection is over an uncountable number of sets all having measure $1$ so the real issue is showing that the "measure $1$" property doesn't get lost in the uncountable intersection.
As we have separability, we can find a dense set $\{x_n\}$ of $E^c$, thus: $\forall n\in\mathbb N~ \exists f_n:~ q(f_n,f_n) = 0$ but $f_n(x_n) \neq 0$.
Now as $\{f_n\}_n$ is a subset of all of the linear functionals having the property $q(f,f) = 0$, we obviously have
$$E = \bigcap_{q(f, f) = 0} \ker f \subset \bigcap_{n} \ker f_n $$
What I don't understand is the other inclusion, i.e.
$$\bigcap_{n} \ker f_n \subset E$$
I was trying to show the contrapositive, i.e. that for any $y\in E^c$ we find a $f_n$ such that $f_n(y) \neq 0$.
Using separability, for any $\epsilon > 0$ we find a $x_m$ such that $\|y-x_m\| < \epsilon$. Then
$$f_m(y) = f_m(x_m) + f_m(y-x_m)$$
Now I know that the first term is non-zero (and I could have easily set $f_n(x_n) = 1$ above). But how can I be sure that the norms $\|f_m\|$ don't grow like $1/\epsilon$ such that both $f_m(x_m) = 1$ and $\|y-x_m\| < \epsilon$ but $f_m(y) = 0$?