anti
09f598ce47
* careful — operator hits OPSEC_HISTORY_TOKENS AND tail-K commands include _CLEANUP_TOKEN_HASHES (re-imported from temporal.py). * learning — history hit without cleanup-tail follow-through. * careless — no history-clearing vocabulary at all. Confidence 0.45 (small lexicon, soft); 0.30 below MIN_COMMANDS_FOR_FULL_CONFIDENCE.
112 lines
3.9 KiB
Python
112 lines
3.9 KiB
Python
"""``operational.*`` feature functions (Phase G).
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Step G.1: ``operational.objective``.
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Step G.2: ``operational.opsec_discipline`` (lands later).
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Step G.3: ``operational.cleanup_behavior`` (lands later).
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Step G.4: ``operational.multi_actor_indicators`` (lands later).
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"""
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from __future__ import annotations
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import collections
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from typing import Iterator
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from decnet_behave_core.spec.envelope import Observation
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from decnet.profiler.behave_shell._ctx import SessionContext
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from decnet.profiler.behave_shell._features._emit import make_observation
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from decnet.profiler.behave_shell._features.temporal import (
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_CLEANUP_TOKEN_HASHES,
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)
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from decnet.profiler.behave_shell._intent import (
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OPSEC_HISTORY_TOKENS,
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classify_intent,
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)
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from decnet.profiler.behave_shell._thresholds import (
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EXIT_BEHAVIOR_LOOKBACK_K,
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INTENT_FULL_CONFIDENCE_MIN,
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INTENT_MIN_COMMANDS,
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MIN_COMMANDS_FOR_FULL_CONFIDENCE,
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)
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def objective(ctx: SessionContext) -> Iterator[Observation]:
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"""Emit ``operational.objective`` ∈ {recon, exfil, persistence,
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lateral, destructive}.
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Walk every command's ``first_token_hash`` through
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:func:`classify_intent` (fixed precedence:
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``destructive > persistence > exfil > lateral > recon``).
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Commands that don't classify (token not in any set) are skipped —
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the registry has no ``unknown`` value here, so a session of pure
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``vim`` / ``ls`` operations is allowed to fall through and emit
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``recon`` only if at least :data:`INTENT_MIN_COMMANDS` commands
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actually classify.
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Skip emission when fewer than ``INTENT_MIN_COMMANDS`` classified
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hits — too thin to call. Otherwise majority vote (ties broken by
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precedence order via ``most_common(1)``-stable sort over the
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insertion order, which mirrors the precedence walk).
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Confidence: 0.40 below :data:`INTENT_FULL_CONFIDENCE_MIN`; 0.60
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above. v0.1 lexicon — corpus tuning revisits in v0.2.
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"""
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if not ctx.commands:
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return
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counter: collections.Counter[str] = collections.Counter()
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for cmd in ctx.commands:
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label = classify_intent(cmd.first_token_hash)
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if label is not None:
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counter[label] += 1
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n_classified = sum(counter.values())
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if n_classified < INTENT_MIN_COMMANDS:
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return
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value = counter.most_common(1)[0][0]
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confidence = 0.60 if n_classified >= INTENT_FULL_CONFIDENCE_MIN else 0.40
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yield make_observation(
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ctx,
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primitive="operational.objective",
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value=value,
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confidence=confidence,
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)
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def opsec_discipline(ctx: SessionContext) -> Iterator[Observation]:
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"""Emit ``operational.opsec_discipline`` ∈ {careful, careless, learning}.
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* ``careful`` — operator hits ``OPSEC_HISTORY_TOKENS`` AND the
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tail-K (=``EXIT_BEHAVIOR_LOOKBACK_K``) commands include cleanup
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vocabulary (locally re-derived; we do **not** read prior
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observations).
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* ``learning`` — operator hits ``OPSEC_HISTORY_TOKENS`` but does
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NOT close with cleanup tokens. Half-discipline.
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* ``careless`` — no ``OPSEC_HISTORY_TOKENS`` hits at all.
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Skip emission when no commands. Confidence 0.45 (small lexicon,
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soft); 0.30 below ``MIN_COMMANDS_FOR_FULL_CONFIDENCE`` (=5).
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"""
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if not ctx.commands:
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return
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has_history = any(
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c.first_token_hash in OPSEC_HISTORY_TOKENS for c in ctx.commands
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)
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tail = ctx.commands[-EXIT_BEHAVIOR_LOOKBACK_K:]
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has_cleanup_tail = any(
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c.first_token_hash in _CLEANUP_TOKEN_HASHES for c in tail
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)
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if not has_history:
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value = "careless"
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elif has_cleanup_tail:
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value = "careful"
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else:
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value = "learning"
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if len(ctx.commands) < MIN_COMMANDS_FOR_FULL_CONFIDENCE:
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confidence = 0.30
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else:
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confidence = 0.45
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yield make_observation(
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ctx,
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primitive="operational.opsec_discipline",
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value=value,
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confidence=confidence,
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)
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