Is it a problem to have some uncorrelated factors in a CFA? I have a CFA with four factors - they are all intercorrelated except for two. 
Is this a problem for the model to have two factors uncorrelated?
 A: @Richiemorrisroe has provided a concise answer, but here's a little elaboration.
In CFA you choose to permit factors to correlate (e.g., in path diagrams by adding double headed arrows between factors). Part of interpreting the model involves examining the relative size of correlation between factors. 
It sounds like you were expecting all the factors to correlate. Just as it is possible  in a set of observed variables for some to intercorrelate and others not to, it is possible in a set of latent variables for some to intercorrelate and others not to.
Assuming the CFA model is appropriate for the data, your aim should be to understand, among other things, what the pattern of factor intercorrelations mean.
A few other things you could explore:


*

*Compare fits when constraining particular covariances to zero

*Compare fit to a model where all covariances are constrained to be equal

*Explore a hierarchical factor model (the pattern of factor correlations may suggest that a higher level factor underlies some but not all the latent factors)

