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.
One campaign, one DSL actor, ip_pool: rotating + rotation_count: 5
across 5 synthetic private-use ASNs (RFC 6996 64512-64516). Stable
JA3, HASSH, and payload_hash across every rotation — these are the
"signals the attacker can't cheaply rotate" per IDENTITY_RESOLUTION.md
and the load-bearing reason all 5 observation rows must resolve to
one identity / one campaign.
Two new reference clusterers in fixture_harness.py:
* fingerprint_clusterer — groups by (ja3, hassh). Un-fingerprinted
rows stay singleton so it doesn't trivially fuse all noise into one
mega-cluster. Approximates the stable-signal arm of the planned
similarity graph.
* asn_clusterer — deliberately-bad reference for fixture 2's
adversarial test. Group-by-ASN shatters the campaign into 5
singletons; completeness collapses to 0.
Four tests in test_vpn_hopping_fixture.py: corpus shape (5 rows, 1
identity, 1 campaign, 5 distinct ASNs/IPs, stable fingerprints),
pass at campaign level, pass at identity level (asserts ARI exactly
1.0), asn_clusterer breaches the completeness floor.
