Per-request HTTP fingerprint derived from the header dict we already log. Captures: - order_hash: SHA-256 prefix (16 hex) over the lowercased header-name sequence, minus volatile/per-request headers (Content-Length, Cookie, Authorization, XFF family, trace IDs). Stable identity for a given client stack regardless of which target / path is hit. - casing_hash: same shape but over the per-header casing category (Title-Case / lower / UPPER / mixed). Attackers frequently spoof User-Agent but forget their stack sends `user-agent` while browsers send `User-Agent`. - tool_guess: prefix match against curl / python-requests / Go-http-client / nmap-nse signatures. Cheap, best-effort — the hash is the hard signal. - duplicates: reserved for when the HTTP template switches from dict(request.headers) to a list form; today it always fires empty because dict() collapses duplicates. Payload is a fingerprint bounty (bounty_type="fingerprint", fingerprint_type="http_quirks"). Bounty dedup collapses identical hashes per attacker — one row per distinct fingerprint — so a chatty scanner doesn't spam the vault, but a tool-chain change from the same IP surfaces as a new row. UI renderer (FpHttpQuirks) shows the two hashes, tool guess badge in violet, casing/count tags, and a collapsible header-order list. Added to the passiveTypes group so it nests with JA3/JA4L/etc. in the AttackerDetail fingerprints panel. One library note: the naive "title-case" classifier failed on tokens like `X-Forwarded-For` because Python's "".islower() returns False so `p[1:].islower()` rejects single-letter tokens like the `X`. Fix: explicitly accept single-char tokens when uppercase.
28 KiB
28 KiB