feat(correlation/attribution): wire bus handler, persist state (Phase 4)

attribution_worker.handle_observation_event now executes the full
end-to-end path:

* ensure stub identity (Phase 1)
* observations_for_identity_primitive() — new repo helper joining
  observations through attackers.identity_id, so v1's clusterer
  gets cross-attacker rollup for free
* aggregate_observations() with ValueKind dispatched off the BEHAVE
  PRIMITIVE_REGISTRY; unknown primitives default to categorical
* upsert_attribution_state() — last_change_ts locked when state is
  unchanged so the dashboard can render "stable since X"
* publish attribution.profile.state_changed only on transition;
  idempotent re-runs over the same observation set fire nothing
  (loop-prevention invariant matching ttp.tagged)

Tests:
* 5 end-to-end attribution scenarios over in-memory SQLite + FakeBus.
* test_base_repo's DummyRepo + coverage body now stub every abstract
  surface BaseRepository declares — the 6 added by this branch plus
  the 12 left un-stubbed by earlier work (BEHAVE Phase 1, TTP
  rollups, iter helpers). The coverage test could not previously
  even instantiate.
* test_aggregate_categorical's dispatcher rejection updated for the
  Phase 3 + 4 contract — ValueError on unknown kinds, not
  NotImplementedError.
This commit is contained in:
2026-05-09 02:16:12 -04:00
parent c39802a4bb
commit dd265d7520
6 changed files with 536 additions and 17 deletions

View File

@@ -26,12 +26,25 @@ from decnet.bus import topics as _topics
from decnet.bus.base import BaseBus
from decnet.bus.factory import get_bus
from decnet.bus.publish import (
publish_safely,
run_control_listener_signal as _run_control_listener_signal,
run_health_heartbeat as _run_health_heartbeat,
)
from decnet.correlation.attribution.aggregate import aggregate_observations
from decnet.logging import get_logger
from decnet.web.db.repository import BaseRepository
try:
from decnet_behave_shell.spec import (
PRIMITIVE_REGISTRY,
ValueKind,
)
_BEHAVE_REGISTRY_AVAILABLE = True
except ImportError: # pragma: no cover
PRIMITIVE_REGISTRY = {}
ValueKind = None
_BEHAVE_REGISTRY_AVAILABLE = False
log = get_logger("correlation.attribution_worker")
_WORKER_NAME = "attribution"
@@ -156,13 +169,103 @@ async def handle_observation_event(
attacker_uuid,
)
return
# Phase 4 will run the merger here and emit
# ``attribution.profile.state_changed`` on transition. Phase 1
# ends with stub materialisation only.
log.debug(
"attribution worker: stub identity=%s for attacker=%s primitive=%s",
identity_uuid, attacker_uuid, primitive,
primitive_str = str(primitive)
# Load the full per-(identity, primitive) observation series.
# v0 with 1:1 stub identities, this is the single attacker's
# series; v1's clusterer makes it a cross-attacker union.
observations = await repo.observations_for_identity_primitive(
identity_uuid, primitive_str,
)
if not observations:
log.debug(
"attribution worker: no observations yet for identity=%s "
"primitive=%s (race with upsert)",
identity_uuid, primitive_str,
)
return
# Run merger.
value_kind = _value_kind_for(primitive_str)
new_state = aggregate_observations(observations, value_kind=value_kind)
# Load prior state to detect transitions.
prior = await repo.get_attribution_state(identity_uuid, primitive_str)
state_changed = prior is None or prior.get("state") != new_state.state
# Persist. last_change_ts is locked to the prior row when state is
# unchanged so the dashboard's "stable since" timestamp doesn't
# reset on every observation.
if prior is not None and not state_changed:
last_change_ts = float(prior.get("last_change_ts", new_state.last_observation_ts))
else:
last_change_ts = new_state.last_observation_ts
await repo.upsert_attribution_state({
"identity_uuid": identity_uuid,
"primitive": primitive_str,
"current_value": new_state.current_value,
"state": new_state.state,
"confidence": new_state.confidence,
"observation_count": new_state.observation_count,
"last_change_ts": last_change_ts,
"last_observation_ts": new_state.last_observation_ts,
})
# Emit state_changed only on transition. Idempotent re-runs (same
# observations, same merger output) produce no event — matches
# the loop-prevention invariant that ttp.tagged uses.
if state_changed and bus is not None:
await publish_safely(
bus,
_topics.attribution(_topics.ATTRIBUTION_PROFILE_STATE_CHANGED),
{
"identity_uuid": identity_uuid,
"primitive": primitive_str,
"old_state": prior.get("state") if prior else None,
"new_state": new_state.state,
"current_value": new_state.current_value,
"confidence": new_state.confidence,
"observation_count": new_state.observation_count,
"ts": new_state.last_observation_ts,
},
event_type=_topics.ATTRIBUTION_PROFILE_STATE_CHANGED,
)
log.info(
"attribution worker: identity=%s primitive=%s %s -> %s confidence=%.2f",
identity_uuid, primitive_str,
(prior or {}).get("state") or "<new>", new_state.state,
new_state.confidence,
)
def _value_kind_for(primitive: str) -> str:
"""Resolve a BEHAVE primitive name to the merger's ValueKind tag.
Maps the BEHAVE registry's ``ValueKind`` enum onto the three
mergers the engine ships:
* ``CATEGORICAL`` / ``BOOL`` / ``FREE_STRING`` / ``ARRAY`` →
``"categorical"`` (BOOL is a 2-cardinality categorical;
FREE_STRING and ARRAY collapse to opaque-token categorical
until a v1 specialised merger lands)
* ``NUMERIC`` → ``"numeric"``
* ``HASH`` → ``"hash"``
Unknown primitives (registry miss) default to categorical — the
safest fallback because the categorical merger is one-outlier-
tolerant and won't lie about confidence on noisy categorical
data the way a numeric merger would on non-numeric values.
"""
if not _BEHAVE_REGISTRY_AVAILABLE:
return "categorical"
spec = PRIMITIVE_REGISTRY.get(primitive)
if spec is None or ValueKind is None:
return "categorical"
if spec.kind is ValueKind.NUMERIC:
return "numeric"
if spec.kind is ValueKind.HASH:
return "hash"
return "categorical"
def _payload_of(event: Any) -> dict[str, Any]: