In recent years, the rise of harmful narratives online has highlighted the need for advancedhate speech detection models. One emergingchallenge is the phenomenon of Faux Hate, anew type of hate speech that originates fromthe intersection of fake narratives and hatespeech. Faux Hate occurs when fabricatedclaims fuel the generation of hateful language,often blurring the line between misinforma-tion and malicious intent. Identifying suchspeech becomes especially difficult when thefake claim itself is not immediately apparent.This paper provides an overview of a sharedtask competition focused on detecting FauxHate, where participants were tasked with de-veloping methodologies to identify this nu-anced form of harmful speech.