Context. X-ray absorbing column densities (N_H) are used as a parameter to quantify the amount of absorbing material along the line of sight. The high values found for long gamma ray bursts (LGRBs) confirmed that these events take place in dense, star-forming environments, joining as an indirect proof the observation of supernovae associated to the bursts and the location in the brightest galaxy regions. Recently, the simultaneous detection of a short gamma ray burst (SGRB) and a gravitational wave signal occurred, strongly supporting the hypothesis that SGRBs instead originate from the merger of compact objects. The different predictions of the two progenitor scenarios for short and long GRBs should be reflected in a difference in the amount of absorbing matter between the two populations, with SGRBs occurring in less dense environments. Previous studies found that the two column density distributions were indistinguishable when compared in the same redshift range. The samples, though, were relatively small (10–12 SGRBs), and spanned a redshift range z ≲ 1. Aims. We update a flux-limited complete sample of Swift-based SGRBs, the SBAT4, bringing it to 25 events and doubling its previous redshift range. We then evaluate the column densities of the events in the updated sample, in order to compare them with the N_H distribution of LGRBs, using the sample BAT6ext. Methods. We relied on Monte Carlo simulations of the two populations and compare the computed N_H distributions with a two sample Kolmogorov–Smirnov (K–S) test. We then studied how the K–S probability varies with respect to the redshift range we consider. Results. We find that the K–S probability keeps decreasing as redshift increases until at z ∼ 1.8 the probability that short and long GRBs come from the same parent distribution drops below 1%. This testifies for an observational difference among the two populations. This difference may be due to the presence of highly absorbed LGRBs above z ∼ 1.3, which have not been observed in the SGRB sample yet, although this may be due to our inability to detect them, or to the relatively small sample size.