381 lines
14 KiB
Python
381 lines
14 KiB
Python
"""Connected-components identity clusterer (v1).
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Builds a similarity graph over observations (per-IP attacker rows),
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runs union-find over edges that pass a confidence threshold, and writes
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one ``attacker_identities`` row per component.
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**v1 signal coverage (this commit):**
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* High-weight tier: JA3 / HASSH / payload-hash / C2-endpoint exact
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match (alone enough to cluster). The production tick currently sees
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JA3 + HASSH only — payload + C2 require log mining and join in
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later commits. The fixture tests exercise the full high-weight set
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through the in-memory path.
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Subsequent commits add medium / low / very-low tier edges, phase-
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handoff edges, and revocable merges. Edges MUST stay time-agnostic
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— fixture 7 forbids recency-decay clustering.
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**v1 behavior:**
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The clusterer assigns identities to NULL observations, merges existing
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identities when a single predicted component spans them, and revokes
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prior merges when the predicted component splits a merged-out identity
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away from its winner. Observations stay FK'd to their original identity
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row throughout — merges are soft pointers via
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``attacker_identities.merged_into_uuid``, never observation re-points.
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That keeps the audit trail intact and lets cached subscribers resolve
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merged-out UUIDs through the chain.
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"""
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from __future__ import annotations
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import json
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import uuid as _uuid
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from datetime import datetime, timezone
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from typing import Any, Iterable, Optional
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from decnet.clustering.base import Clusterer, ClusterResult
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from decnet.clustering.impl.similarity import (
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EDGE_THRESHOLD,
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Observation,
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combined_edge_weight,
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)
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from decnet.logging import get_logger
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from decnet.profiler.identity_rollup import extract_fp_summaries
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from decnet.web.db.repository import BaseRepository
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log = get_logger("clustering.connected_components")
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def cluster_observations(
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observations: Iterable[Observation],
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) -> dict[str, str]:
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"""Run connected-components over the high-weight similarity graph.
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Pure: no DB, no clock, no I/O. Both the fixture-validation tests
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and the production ``tick`` consume this. The mapping is a
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deterministic function of the input set + edge function.
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Singletons get a stable per-observation cluster id so callers can
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distinguish "isolated observation" from "merged into nothing."
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Returns ``{observation_id: cluster_id}``. Cluster ids are opaque
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strings — callers must not rely on their format.
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"""
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obs_list = list(observations)
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parent: dict[str, str] = {o.observation_id: o.observation_id for o in obs_list}
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def find(x: str) -> str:
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while parent[x] != x:
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parent[x] = parent[parent[x]]
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x = parent[x]
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return x
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def union(x: str, y: str) -> None:
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rx, ry = find(x), find(y)
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if rx != ry:
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parent[rx] = ry
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for i, a in enumerate(obs_list):
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for b in obs_list[i + 1:]:
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if combined_edge_weight(a, b) >= EDGE_THRESHOLD:
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union(a.observation_id, b.observation_id)
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# Roots: each unique find(o) is a component representative. Use
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# them as the cluster id so two runs over the same input produce
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# the same labels (handy for assertions).
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return {o.observation_id: f"cc-{find(o.observation_id)}" for o in obs_list}
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def from_attacker_row(row: dict[str, Any]) -> Observation:
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"""Project an ``Attacker`` row dict into an :class:`Observation`.
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Pulls JA3 / HASSH out of the ``Attacker.fingerprints`` JSON list
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(one entry per fingerprint event the prober collected). Multiple
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JA3s on a single observation are flattened to a single value —
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the most-recent — because :class:`Observation` is a single-row
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projection; an observation that exhibits two distinct JA3s across
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its lifetime is a wire-level oddity that the clusterer treats by
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keeping the latest. The identity row itself can store the full
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list across observations.
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Payload + C2 + commands are left empty — log mining lands in
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later commits. The function shape doesn't change when they do.
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"""
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raw = row.get("fingerprints") or "[]"
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try:
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entries = json.loads(raw) if isinstance(raw, str) else list(raw)
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except (TypeError, ValueError):
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entries = []
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ja3: Optional[str] = None
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hassh: Optional[str] = None
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for entry in entries:
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if not isinstance(entry, dict):
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continue
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kind = entry.get("kind")
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h = entry.get("hash") or entry.get("value")
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if not h:
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continue
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if kind == "ja3":
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ja3 = h
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elif kind == "hassh":
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hassh = h
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return Observation(
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observation_id=row["uuid"],
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ja3=ja3,
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hassh=hassh,
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asn=row.get("asn"),
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)
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class ConnectedComponentsClusterer(Clusterer):
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"""Connected-components clusterer over the similarity graph.
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See module docstring for v1 signal coverage and behavior notes.
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"""
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name = "connected_components"
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async def tick(self, repo: BaseRepository) -> ClusterResult:
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try:
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rows = await repo.list_attackers_for_clustering()
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except Exception: # noqa: BLE001
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log.exception("clusterer: failed to read attackers")
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return ClusterResult()
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if not rows:
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return ClusterResult()
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# Build the merge chain so a row's "effective" identity follows
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# merged_into_uuid up to the canonical winner. Pre-computing it
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# lets us reason about post-merge identity membership in one
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# place. ``identity_chain[u]`` is the canonical winner for
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# identity ``u`` (or ``u`` itself if not merged out).
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try:
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all_identities = await repo.list_all_identities()
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except Exception: # noqa: BLE001
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log.exception("clusterer: failed to read identities")
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return ClusterResult()
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identity_chain = _build_merge_chain(all_identities)
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# Project + cluster.
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observations: list[Observation] = []
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row_by_id: dict[str, dict[str, Any]] = {}
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for r in rows:
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obs = from_attacker_row(r)
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observations.append(obs)
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row_by_id[obs.observation_id] = r
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labels = cluster_observations(observations)
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# Group observations by predicted cluster.
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components: dict[str, list[str]] = {}
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for obs_id, cluster_id in labels.items():
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components.setdefault(cluster_id, []).append(obs_id)
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result = ClusterResult()
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now = datetime.now(timezone.utc)
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# Pass 1 — per-component reconciliation: form, link, merge.
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for member_ids in components.values():
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literal_ids = {
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row_by_id[m]["identity_id"] for m in member_ids
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if row_by_id[m].get("identity_id")
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}
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effective_ids = {identity_chain.get(i, i) for i in literal_ids}
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unassigned = [
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m for m in member_ids
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if not row_by_id[m].get("identity_id")
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]
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if not effective_ids:
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# Fresh component — mint a new identity.
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identity_uuid = str(_uuid.uuid4())
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try:
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await repo.create_attacker_identity({
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"uuid": identity_uuid,
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"schema_version": 1,
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"first_seen_at": now,
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"last_seen_at": now,
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"created_at": now,
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"updated_at": now,
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"observation_count": len(member_ids),
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})
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except Exception: # noqa: BLE001
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log.exception(
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"clusterer: failed to create identity for component %s",
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member_ids,
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)
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continue
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linked: list[str] = []
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for obs_id in member_ids:
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if await _link(repo, obs_id, identity_uuid):
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linked.append(obs_id)
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if linked:
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result.identities_formed.append({
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"identity_uuid": identity_uuid,
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"observation_uuids": linked,
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})
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await _roll_up_fingerprints(
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repo, identity_uuid, [row_by_id[m] for m in member_ids],
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)
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continue
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# Deterministic winner so two clusterer runs produce the
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# same merge direction. Sorting by uuid string is stable
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# and doesn't depend on row insertion order.
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winner_uuid = min(effective_ids)
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losers = effective_ids - {winner_uuid}
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for loser_uuid in losers:
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try:
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await repo.update_identity_merged_into(loser_uuid, winner_uuid)
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except Exception: # noqa: BLE001
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log.exception(
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"clusterer: failed to merge %s -> %s",
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loser_uuid, winner_uuid,
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)
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continue
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identity_chain[loser_uuid] = winner_uuid
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result.identities_merged.append({
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"winner_uuid": winner_uuid,
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"loser_uuid": loser_uuid,
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})
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# Link any unassigned observations in the component to the
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# winner so a subsequent tick sees a single-identity
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# component and skips this branch entirely.
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for obs_id in unassigned:
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if await _link(repo, obs_id, winner_uuid):
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result.observations_linked.append({
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"identity_uuid": winner_uuid,
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"observation_uuid": obs_id,
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})
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# Re-roll the winner's fingerprint summary across every
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# observation now in this component (including the loser
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# side — the merge unifies their evidence even though the
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# loser's identity row stays FK'd via merged_into_uuid).
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await _roll_up_fingerprints(
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repo, winner_uuid, [row_by_id[m] for m in member_ids],
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)
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# Pass 2 — revocable-merge undo. For each currently-merged-out
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# identity, check whether its observations still cluster with
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# the winner's. If not, the merge is contradicted by new
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# evidence — clear merged_into_uuid and emit identity.unmerged.
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# Observations FK'd to the resurrected loser stay where they
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# were; the chain just stops following.
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observations_by_literal_identity: dict[str, list[str]] = {}
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for obs_id, r in row_by_id.items():
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iid = r.get("identity_id")
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if iid:
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observations_by_literal_identity.setdefault(iid, []).append(obs_id)
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for identity_row in all_identities:
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if not identity_row.get("merged_into_uuid"):
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continue
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loser_uuid = identity_row["uuid"]
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winner_uuid = identity_chain.get(loser_uuid, loser_uuid)
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if winner_uuid == loser_uuid:
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continue # broken chain — paranoia
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loser_obs = observations_by_literal_identity.get(loser_uuid, [])
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winner_obs = observations_by_literal_identity.get(winner_uuid, [])
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if not loser_obs or not winner_obs:
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# No observations either side — can't disprove the merge.
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continue
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loser_clusters = {labels[o] for o in loser_obs}
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winner_clusters = {labels[o] for o in winner_obs}
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if loser_clusters & winner_clusters:
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continue # still co-clustered with winner — merge stands
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try:
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await repo.update_identity_merged_into(loser_uuid, None)
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except Exception: # noqa: BLE001
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log.exception(
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"clusterer: failed to unmerge %s from %s",
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loser_uuid, winner_uuid,
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)
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continue
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identity_chain[loser_uuid] = loser_uuid
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result.identities_unmerged.append({
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"resurrected_uuid": loser_uuid,
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"former_winner_uuid": winner_uuid,
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})
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return result
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def _build_merge_chain(
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identities: list[dict[str, Any]],
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) -> dict[str, str]:
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"""Build a uuid → canonical-winner map from a list of identity rows.
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Follows ``merged_into_uuid`` to a fixed point per identity, with a
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hop cap to defend against accidental cycles. The returned dict
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contains an entry for every identity uuid (mapping to itself if
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not merged out).
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"""
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_MAX_HOPS = 8
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by_uuid: dict[str, dict[str, Any]] = {i["uuid"]: i for i in identities}
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chain: dict[str, str] = {}
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for uuid_ in by_uuid:
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cur = uuid_
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for _ in range(_MAX_HOPS):
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row = by_uuid.get(cur)
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if row is None:
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break
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nxt = row.get("merged_into_uuid")
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if not nxt or nxt == cur:
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break
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cur = nxt
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chain[uuid_] = cur
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return chain
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async def _link(
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repo: BaseRepository, observation_uuid: str, identity_uuid: str,
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) -> bool:
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"""Set ``attackers.identity_id`` and return ``True`` on success.
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Wraps the repo call so the tick body stays linear and exception
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handling is consistent across the form / link / merge branches.
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"""
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try:
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await repo.set_attacker_identity_id(observation_uuid, identity_uuid)
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return True
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except Exception: # noqa: BLE001
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log.exception(
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"clusterer: failed to link obs=%s -> identity=%s",
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observation_uuid, identity_uuid,
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)
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return False
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async def _roll_up_fingerprints(
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repo: BaseRepository,
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identity_uuid: str,
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member_rows: list[dict[str, Any]],
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) -> None:
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"""Project member observations' fingerprint blobs onto the identity's
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summary columns. Best-effort: a write failure is logged but never
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breaks the clusterer tick — the columns just stay stale until the
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next pass."""
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summaries = extract_fp_summaries(member_rows)
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fp_kwargs = {k: v for k, v in summaries.items() if k in {"ja3_hashes", "hassh_hashes", "tls_cert_sha256"}}
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try:
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await repo.update_identity_fingerprints(identity_uuid, **fp_kwargs)
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except Exception: # noqa: BLE001
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log.exception(
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"clusterer: failed to roll up fingerprints for identity=%s",
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identity_uuid,
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)
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__all__ = [
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"ConnectedComponentsClusterer",
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"cluster_observations",
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"from_attacker_row",
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]
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