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.
5.1 KiB
5.1 KiB