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.
anti
0def6f7e37