Context.TheGaiathird Data Release (GDR3) presents a catalogue of 474 026 stars (detected by processing a sample of about 30 million late-type stars) with variability induced by magnetic activity. About 430 000 of these stars are newly discovered variables. For each star, the catalogue provides a list of about 70 parameters among which the most important are the stellar rotation periodP, the photometric amplitudeAof the rotational modulation signal, and the Pearson correlation coefficientr₀between magnitude and colour variation.Aims.In the present paper we highlight some features of theGaiaphotometric time series used to obtain the catalogue and we present the main attributes of the catalogue.Methods.The Specific Objects Study (SOS) pipeline, developed to characterise magnetically active stars withGaiadata, was described in the paper accompanying theGaiasecond rata release (DR2). Here we describe the changes made to the pipeline and a new method developed to analyseGaiatime series and to reveal spurious signals induced by instrumental effects or by the peculiar nature of the investigated stellar source. Such a method is based on the measurement of the per-transit-corrected-excess-factor (c*) for each time-series transit, wherec* is a parameter that allows us to check the consistency betweenG,G_BP, andG_RPfluxes in a given transit.Results.The period–amplitude diagram obtained with the DR3 data confirms the DR2 findings that is, the existence of a family of low-amplitude fast rotators never seen by previous surveys. The GDR3 data permit, for the first time, the analysis of patterns in magnitude–colour variation for thousands of magnetically active stars. The measuredr₀values are tightly correlated with the star positions in the period–amplitude diagram.Conclusions.The relationship between theP,A, andr₀parameters inferred for thousands of stars are potentially very useful for improving our understanding of stellar magnetic fields and ameliorating theoretical models, especially in the fast rotation regime. The method developed to reveal the spurious signals can be applied to each of the releasedGaiaphotometric time series and can be exploited by anyone interested in working directly withGaiatime series.