feat(profiler/behave_shell): G.0 intent lexicon + lexical counter pass

Phase G shared infrastructure (no primitive yet emitted):

* New `_intent.py` — five precomputed first-token-hash sets (recon /
  exfil / persistence / lateral / destructive) with documented
  precedence, plus opsec-history and three lexeme sets (positive /
  negative / obscenity) for the typed-text counter pass. Stop words
  that collide with registry value vocabulary (`no`, `hell`, `ok`)
  are deliberately excluded — the PII regression test catches such
  collisions.

* `_typed_char_histograms()` extended with five integer counters
  populated in the same single-pass walk: `obscenity_hits`,
  `positive_lex_hits`, `negative_lex_hits`, `caps_run_max`,
  `bang_run_max`. Longest-suffix match against bounded lexicon
  (`LEXEME_MAX_LEN`); paste-class events excluded.

* `SessionContext` widened by the same five fields. Drives G.5
  (valence), G.6 (arousal), G.8 (frustration_venting) without retaining
  raw operator text.

* Bump twisted >= 26.4.0rc2 to clear CVE-2026-42304 (pre-existing,
  caught by pre-commit pip-audit). Adjust ftp template type-ignore
  code from attr-defined to misc to match the new Twisted typing.

PII discipline: same shape as F.4 — fixed-vocabulary integer counters
on ctx, never on observations.

decnet/profiler/behave_shell/_intent.py

@@ -0,0 +1,115 @@
+"""Phase G — shared command-intent + lexical-counter vocabulary.
+
+Used by:
+* ``operational.objective``        (G.1)  via ``INTENT_SETS``
+* ``operational.opsec_discipline`` (G.2)  via ``OPSEC_HISTORY_TOKENS``
+* ``emotional_valence.valence``    (G.5)  via ``POSITIVE_LEXEMES`` / ``NEGATIVE_LEXEMES``
+* ``emotional_valence.frustration_venting`` (G.8) via ``OBSCENITY_LEXEMES``
+
+All ``*_TOKENS`` frozensets contain ``hash_token()`` SHA256 hexes — the
+only PII-safe handle on a command's first token. Lexeme frozensets
+contain lowercased word forms (used by the typed-text counter pass in
+``_ctx.py`` to *count* matches without retaining text).
+
+Set membership is intentionally overlapping. ``rm`` rides in
+``DESTRUCTIVE_TOKENS`` AND in the cleanup vocabulary; ``unset`` rides
+in ``OPSEC_HISTORY_TOKENS`` AND in cleanup. G.1's classifier resolves
+multi-membership by fixed precedence (see :data:`INTENT_PRECEDENCE`).
+"""
+from __future__ import annotations
+
+from decnet.profiler.behave_shell._parse import hash_token
+
+# ── operational.objective intent sets (G.1) ────────────────────────────────
+RECON_TOKENS: frozenset[str] = frozenset(
+    hash_token(t) for t in (
+        "ls", "pwd", "whoami", "id", "uname", "ps", "netstat", "ss",
+        "cat", "find", "which", "env", "printenv", "hostname", "w",
+        "who", "date", "uptime", "df", "du", "free", "lsof", "lsblk",
+    )
+)
+EXFIL_TOKENS: frozenset[str] = frozenset(
+    hash_token(t) for t in (
+        "curl", "wget", "scp", "rsync", "nc", "ncat", "socat", "tar",
+        "base64", "xxd", "python", "python3", "openssl",
+    )
+)
+PERSISTENCE_TOKENS: frozenset[str] = frozenset(
+    hash_token(t) for t in (
+        "crontab", "systemctl", "useradd", "usermod", "passwd", "chsh",
+        "at", "service", "chkconfig", "update-rc.d", "authorized_keys",
+    )
+)
+LATERAL_TOKENS: frozenset[str] = frozenset(
+    hash_token(t) for t in (
+        "ssh", "telnet", "rsh", "rlogin", "ftp", "sftp", "mosh",
+        "kubectl", "docker", "psql", "mysql", "redis-cli",
+    )
+)
+DESTRUCTIVE_TOKENS: frozenset[str] = frozenset(
+    hash_token(t) for t in (
+        "rm", "dd", "mkfs", "shred", "wipe", "kill", "pkill", "killall",
+        "truncate", "fdisk",
+    )
+)
+
+# G.1 majority-vote classifier walks first_token_hash → category in this
+# order; first hit wins. ``destructive`` outranks ``persistence`` because
+# a session that destroys outweighs one that also installs cron jobs;
+# ``exfil`` outranks ``lateral`` because pulling data is the more
+# specific signal.
+INTENT_PRECEDENCE: tuple[tuple[str, frozenset[str]], ...] = (
+    ("destructive",  DESTRUCTIVE_TOKENS),
+    ("persistence",  PERSISTENCE_TOKENS),
+    ("exfil",        EXFIL_TOKENS),
+    ("lateral",      LATERAL_TOKENS),
+    ("recon",        RECON_TOKENS),
+)
+
+
+def classify_intent(first_token_hash: str) -> str | None:
+    """Return the registry intent label for ``first_token_hash``.
+
+    ``None`` if the hash isn't in any intent set.
+    """
+    for label, hashes in INTENT_PRECEDENCE:
+        if first_token_hash in hashes:
+            return label
+    return None
+
+
+# ── operational.opsec_discipline (G.2) ─────────────────────────────────────
+# History-clearing / log-tampering vocabulary (first-token).
+OPSEC_HISTORY_TOKENS: frozenset[str] = frozenset(
+    hash_token(t) for t in (
+        "history", "unset", "export", "set", "script",
+    )
+)
+
+
+# ── emotional_valence lexicons (G.5 / G.8) ────────────────────────────────
+# Lowercased lexeme word-forms. Membership-tested against typed-text
+# tokens during the single-pass histogram walk in ``_ctx.py``. No raw
+# text retained — only per-set integer counters.
+#
+# Stop-word collisions with registry values (``no``, ``none``, ``ok``,
+# ``hell``→``shell_type``) are excluded — registry value strings travel
+# through observations and would trigger PII regression checks. Kept
+# lexemes are those that don't collide with primitive value vocabulary.
+POSITIVE_LEXEMES: frozenset[str] = frozenset({
+    "thanks", "nice", "cool", "great", "okay",
+    "perfect", "love", "awesome",
+})
+NEGATIVE_LEXEMES: frozenset[str] = frozenset({
+    "wtf", "damn", "crap", "ugh", "broken", "stupid",
+    "hate", "stuck", "wrong",
+})
+OBSCENITY_LEXEMES: frozenset[str] = frozenset({
+    "fuck", "fucking", "fucked", "shit", "bitch", "ass", "cunt",
+    "dick", "asshole",
+})
+
+ALL_LEXEMES: frozenset[str] = (
+    POSITIVE_LEXEMES | NEGATIVE_LEXEMES | OBSCENITY_LEXEMES
+)
+LEXEME_MAX_LEN: int = max((len(x) for x in ALL_LEXEMES), default=0)