Runs the chained identity + campaign clustering pipeline against all
seven fixtures via from_synthetic / from_synthetic_identity adapters
and ratchets every YAML floor to 1.0 — the production clusterer
(and the reference clusterers used in the per-fixture tests) all
score perfectly across ARI / homogeneity / completeness /
singleton_recall on each fixture.
Three substrate fixes surfaced by the ratchet:
- Tuning: shared_infra now Jaccards payload+C2 only; decky_set moved
into cohort_weight to prevent fleet-scarcity false-merges (F1's
shared_wordlist failure mode). Tier weight raised to 1.0 so
shared payload+C2 alone crosses threshold (F5's intended pass).
- Adapter: from_synthetic_identity now reads SyntheticSession
started_at + duration_s for session_windows and per-decky
timestamps (the production-row adapter still uses start_ts/end_ts
when available).
- Fixture data: paused_campaign.yaml's JA3 collided exactly with
vpn_hopping.yaml's (same TLS extension list). The collision
fused two unrelated campaigns under the chained identity layer
in the noise_floor composite. Made paused's JA3 distinct.
Also wires Campaign / CampaignsResponse into models/__init__.py's
__all__ that was missed in the schema commit.
Multi-month APT campaign modeling real APT operational tempo: recon
over weeks, exploitation later, action-on-objectives later still.
The unique signal this fixture stresses is TIME-AGNOSTIC IDENTITY
across multi-week silences — a clusterer that silently expires old
edges fragments any campaign that operates over months.
Three DSL actors represent the operator's three operational windows
(week 2, month 2, month 3 of a 90-day campaign), all sharing JA3 +
HASSH + payload + C2 callback. Campaign-level fixture only — the
three actors mint distinct truth_identity_id rows by design (same
modeling caveat as fixtures 4 and 5).
The fixture's narrative mirrors how an APT works a deep nested
topology (DECNET MazeNET mode): map decoy networks for weeks, only
then commit to exploitation. Slow-and-low pacing is the signal.
recency_decay_clusterer added to fixture_harness — same edge
construction as composite_signals_clusterer, but each edge weighted
by exp(-time_distance / half_life_days) and dropped below a
threshold. Adversarial reference for slow_burn: with 14-day half-
life and 0.5 threshold, edges between operational windows (24+ days
apart) decay below threshold and drop. The campaign fragments into
three clusters; completeness collapses.
This is the canonical production failure mode for graph clusterers
that bound memory or bias toward "what's hot" by silently expiring
old edges. Catching it in synthetic data is what fixture 7 exists
for; the replay tier will surface real-world drift / dwell patterns
that calibrate the half-life threshold the real algorithm should
tolerate.
Four tests: corpus shape (window-isolated sessions, stable
fingerprint), pipeline pass via composite_signals_clusterer (time-
agnostic — folds all three windows), adversarial fragmentation
(3 clusters at 14-day half-life), long-half-life sanity (gentle
decay unions everything; confirms behavior depends on the half-life
parameter, not on something unrelated).
