Cross-correlation of maximum length sequence with noise
I assume that this is a discrete-time problem where the maximum-length sequence is a pseudorandom sequence $x[k]$ of $\pm 1$ values and the noise is a sequence $n[k]$ of independent identically distributed (iid) zero-mean random variables with variance $\sigma^2$.  Then, $\sum_{k=0}^{N-1} x[k]n[k]$ is also a sum of $N$ iid random variables and its variance is $N\sigma^2$, that is, the noise power increases in proportion to the length of the filter, exactly as you have conjectured.  So, the crosscorrelation of the maximum length sequence and the noise is a zero-mean random variable with variance $N\sigma^2$ where $N$ is the length of the sequence being correlated against. If the noise is modeled as Gaussian, then crosscorrelation value is also a Gaussian random variable.