In this delightfully “bad” dive into password hygiene, we scrape millions of leaked passwords for the first dictionary word they contain. The top ten words (love, baby, password…) barely scratch 5% of the total, and a whopping 21k words appear only once. We also compare happy vs. angry vocab. Turns out love trumps f**k by a healthy margin. The takeaway? Stick to random passphrases; dictionary words are a playground for attackers and a source of endless amusement for analysts.

In this delightfully “bad” foray into malware hunting, we ask whether the sheer amount of printable text inside a binary can betray its nefarious nature. By hashing (oops, counting) strings of lengths 2‑6 bytes in ~500 malicious samples versus 200 tidy Windows libraries, we compute “strings‑per‑KB”. The results are modest but tasty: at a 4‑byte cutoff, benign binaries sport roughly 22 % more strings per kilobyte than their shady cousins—a hint that packed or encrypted malware keeps its chatter to a whisper. Short 2‑byte fragments are just random noise, while 5‑ and 6‑byte strings level out, possibly thanks to debug messages. Bottom line? String density offers a cheeky heuristic, but it’s no silver bullet—still fun to poke at, especially when you love sprinkling a dash of Python over binary mysteries.

In this delightfully “bad” foray into password cracking, we tally two‑ and three‑character combos from millions of leaked passwords and compare them to a subtitle‑derived English word list. Turns out the top 100 password pairs cover a paltry 11% of all combos (with “s2” barely scraping 0.15%), while the same slice of English captures a whopping 60%. Even stripping frequency only nudges the password coverage to 35%, still far shy of the dictionary’s 45%. The takeaway? Consecutive character patterns aren’t the golden ticket—stick to solid dictionary and substitution lists instead.