In　VANETs,　malicious　nodes　launch　Sybil　attacks　using　false　traffic　information　by　forging　basic　safety　messages,　leading　to　erroneous　decisions　and　ultimately　causing　traffic　accidents　that　threaten　the　lives　of　passengers.　Existing　Sybil　attack　detection　methods　can　only　mitigate　the　impact　of　Sybil　attacks　and　cannot　trace　the　attack　back　to　find　malicious　nodes.　Meanwhile,　malicious　nodes　can　suppress　the　performance　of　tracing　methods　with　the　help　of　pseudonym　exchange　policy.　This　study　proposes　a　fast　Sybil　attack　tracing　method　in　VANETs　to　address　the　above　challenges.　The　method　quickly　identifies　suspicious　BSMs　through　cascading　operations.　Finally,　the　results　of　cascading　operations　are　used　to　perform　source　estimation　and　complete　the　attack　tracing.　Experimental　results　show　the　method＇s　precision　＞=　97%　and　recall　＞=　96%.