In this tongue‑in‑cheek post we dive deep—actually deeper than usual—into the world of malware string analysis by counting individual characters. After pulling roughly 500 malicious samples from theZoo and dasMalwerk and comparing them against a hefty collection of benign binaries, we discovered that a handful of seemingly innocuous characters (v, j, ;, , 4, q, 5, /) pop up more often in the bad guys’ code. By looking at raw counts and then normalising those counts by file size, we expose why naïve “character‑frequency” heuristics are both amusing and alarmingly unreliable. The piece is deliberately over‑the‑top, aiming to entertain seasoned security folks while reminding everyone that good malware hunting requires more nuance than a simple character checklist.
A breezy, tour of fast‑flux botnets, those sneaky DNS tricks that let malicious actors hop around like digital grasshoppers. We’ll peek at how dynamic DNS and round‑robin magic keep the bad guys’ command‑and‑control servers slippery, and glance at the cat‑and‑mouse game of detection (TTL tricks, activity indexes, and the occasional semantic sleuthing). Spoiler: it’s a wild ride, but the good news is there are ways to shine a flashlight on the flux.
A recap of my master’s thesis that proves you can sniff out nasty traffic using only one‑way packet metadata (TTL, ports, timing)—no payload inspection required.