75 lines
2.6 KiB
Python
75 lines
2.6 KiB
Python
"""
|
|
End-to-end pipeline test for fixture 3 (lone_wolf).
|
|
|
|
Loads the YAML spec, runs the synthetic generator, applies the
|
|
identity-clusterer placeholder (each attacker → its own cluster), and
|
|
scores against the expected bounds. This is the simplest of the six
|
|
fixtures and is deliberately the first one wired up — its ground truth
|
|
is all singletons, so an identity clusterer trivially passes, which
|
|
proves the DSL → factory → metrics pipeline works before any real
|
|
algorithm is built.
|
|
|
|
Once the connected-components clusterer (CAMPAIGN_CLUSTERING.md §4)
|
|
lands, the same fixture must continue to pass.
|
|
"""
|
|
from __future__ import annotations
|
|
|
|
from pathlib import Path
|
|
|
|
import pytest
|
|
|
|
from tests.clustering.fixture_harness import (
|
|
assert_fixture_bounds,
|
|
identity_clusterer,
|
|
)
|
|
from tests.clustering.metrics import score
|
|
from tests.factories.campaign_factory import generate, load_yaml
|
|
|
|
FIXTURE_DIR = Path(__file__).parent.parent / "fixtures" / "campaigns"
|
|
|
|
|
|
def test_lone_wolf_pipeline_passes_bounds() -> None:
|
|
spec = load_yaml(FIXTURE_DIR / "lone_wolf.yaml")
|
|
corpus = generate(spec, seed=0)
|
|
assert_fixture_bounds(corpus, identity_clusterer, FIXTURE_DIR / "lone_wolf.expected.yaml")
|
|
|
|
|
|
def test_lone_wolf_corpus_shape() -> None:
|
|
"""Sanity: 1 wolf + 8 noise scanners = 9 attackers, 9 sessions."""
|
|
spec = load_yaml(FIXTURE_DIR / "lone_wolf.yaml")
|
|
corpus = generate(spec, seed=0)
|
|
assert len(corpus.attackers) == 9
|
|
assert len(corpus.sessions) == 9
|
|
truth_campaigns = {a.truth_campaign_id for a in corpus.attackers}
|
|
assert len(truth_campaigns) == 9
|
|
|
|
|
|
def test_identity_clusterer_fails_on_a_real_campaign() -> None:
|
|
"""
|
|
Sanity for the harness, NOT a test of the clusterer: a real
|
|
multi-actor campaign should make the placeholder identity clusterer
|
|
fail completeness, since each truth-campaign gets fragmented into
|
|
one-member clusters. If this didn't fail, our metrics would be
|
|
blind to false splits — and that's the entire point of fixtures 4
|
|
and 5 in the design doc.
|
|
"""
|
|
spec = {
|
|
"campaign": {
|
|
"id": "c-real",
|
|
"actors": [
|
|
{"id": "a-1", "asn": 14061},
|
|
{"id": "a-2", "asn": 14061},
|
|
],
|
|
"phases": [
|
|
{"name": "delivery", "actor": "a-1"},
|
|
{"name": "discovery", "actor": "a-2"},
|
|
],
|
|
"duration_days": 1,
|
|
}
|
|
}
|
|
corpus = generate(spec, seed=0)
|
|
pred = identity_clusterer(corpus)
|
|
metrics = score(corpus.truth_labels(), pred)
|
|
assert metrics["completeness"] < 1.0
|
|
assert metrics["homogeneity"] == pytest.approx(1.0)
|