MimeLens: Position-Agnostic Content-Type Detection for Binary Fragments 事件

MimeLens: Position-Agnostic Content-Type Detection for Binary Fragments arXiv:2606.04171v1 Announce Type: cross Abstract: File-type classification underlies many workflows like malware triage, forensic carving, packet inspection, and storage indexing. Learned systems such as Google's Magika assume whole-file access at a known offset, so they break on the inputs many of these tasks actually produce, like a single packet payload, a header-less carved fragment, a random disk block, or a chunked up