  Context. Transient astronomical events that exhibit no discernible
association with a host galaxy are commonly referred to as hostless. These rare
phenomena are associated with extremely energetic events, and they can offer
unique insights into the properties and evolution of stars and galaxies.
However, the sheer number of transients captured by contemporary high-cadence
astronomical surveys renders the manual identification of all potential
hostless transients impractical. Therefore, creating a systematic
identification tool is crucial for studying these elusive events. Aims. We
present the ExtragaLactic alErt Pipeline for Hostless AstroNomical Transients
(ELEPHANT), a framework for filtering hostless transients in astronomical data
streams. Methods. We used Fink to access all the ZTF alerts produced between
January/2022 and December/2023, selecting only those associated with
extragalactic transients. We then processed the associated stamps using a
sequence of image analysis techniques to retrieve hostless candidates. Results.
We find that less than 2% of all analyzed transients are potentially hostless.
Among them, approximately 10% have a spectroscopic class reported on TNS, with
Type Ia supernova being the most common class, followed by SLSN. Among the
hostless candidates retrieved by our pipeline, there was SN 2018ibb, which has
been proposed to be a PISN candidate; and SN 2022ann, one of only five known
SNe Icn. When no class is reported on TNS, the dominant classes are QSO and SN
candidates, the former obtained from SIMBAD and the latter inferred using the
Fink ML classifier. Conclusions. ELEPHANT represents an effective strategy to
filter extragalactic events within large and complex astronomical alert
streams. There are many applications for which this pipeline will be useful,
ranging from transient selection for follow-up to studies of transient
environments.
