merge: testing → main (reconcile 2-week divergence)
This commit is contained in:
441
decnet/clustering/campaign/impl/similarity.py
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441
decnet/clustering/campaign/impl/similarity.py
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"""Similarity-graph primitives for the campaign clusterer.
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The campaign clusterer reads ``AttackerIdentity`` rows (the layer below)
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and groups them into operations. The graph it builds is **not** the
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identity-level graph: identity-level signals don't translate 1:1, and
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some that get vetoed at identity level (shared infra) are the *primary
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positive signal* at campaign level.
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Mirror of ``decnet.clustering.impl.similarity`` for the
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identity layer; see that module for the four-tier identity taxonomy.
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**Time-agnostic.** Same F7 invariant as the identity layer — edges
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MUST depend only on *pairwise relative* offsets, never on absolute
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clocks. Shift two identities' session windows by the same Δ and the
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edge weights MUST be identical. The temporal-overlap edge below uses
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this invariant explicitly.
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**Edge families** (from ``development/CAMPAIGN_CLUSTERING.md``):
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* **Phase-handoff** — A ends in ``COMMAND_AND_CONTROL`` / ``PERSISTENCE``
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on decky D, B begins ``DISCOVERY`` / ``LATERAL_MOVEMENT`` on D
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within window W. Load-bearing for fixture F5 (multi_operator) — the
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signal the identity-side fingerprint-disagreement veto deliberately
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doesn't try to be.
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* **Shared-infra** — Jaccard over aggregated payload-hashes /
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C2-endpoints / decky-set across the identities' member observations.
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Vetoed at identity level (``ed32358``); primary positive signal here.
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* **Temporal overlap** — sessions inside a bounded *relative* window.
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Campaigns are operations and operations have bounded duration;
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overlap of distinct identities on shared infra is the canonical
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co-op pattern.
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* **Cohort** — ASN-cohort + tooling-cohort weak signals. Defeated alone
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(per F2); useful as supporting weight only.
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The functions are pure (no DB, no I/O); the worker maps identities into
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:class:`IdentityFeatures` once per tick and feeds these into the graph
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builder in a sibling module.
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"""
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from __future__ import annotations
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from dataclasses import dataclass, field
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from typing import Mapping, Optional
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# ─── Identity-level projection ──────────────────────────────────────────────
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@dataclass(frozen=True)
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class IdentityFeatures:
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"""Minimal projection of an :class:`AttackerIdentity` row.
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Built once per identity by the worker (or per fixture identity in
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tests via :func:`from_synthetic_identity`). Keeping the projection
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tight isolates the campaign-graph code from schema drift on the
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identity layer.
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"""
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identity_uuid: str
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"""Stable ID — production: ``AttackerIdentity.uuid``."""
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asn_cohort: frozenset[int] = field(default_factory=frozenset)
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"""All ASNs observed across the identity's member observations.
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A single rotating actor (F2) appears in many ASNs; the *set*
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overlap is the cohort signal."""
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tooling_cohort: frozenset[str] = field(default_factory=frozenset)
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"""Tooling labels (e.g. ``"hydra"``, ``"hping"``) inferred from
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fingerprints / commands. Empty until tooling-attribution lands."""
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payload_hashes: frozenset[str] = field(default_factory=frozenset)
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"""Aggregated payload hashes across member observations."""
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c2_endpoints: frozenset[str] = field(default_factory=frozenset)
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"""Aggregated C2 endpoints across member observations."""
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decky_set: frozenset[str] = field(default_factory=frozenset)
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"""Aggregated decky IDs the identity touched."""
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commands_by_phase_on_decky: Mapping[
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tuple[str, str], tuple[str, ...]
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] = field(default_factory=dict)
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"""``(decky_id, UKCPhase.value)`` → ordered command sequence
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observed on that decky in that phase. Required for the
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phase-handoff edge — same decky is the join key. Empty when
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``commands_by_phase`` is unavailable on the production-row
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adapter (deferred per TODO.md until log-mining lands)."""
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session_windows: tuple[tuple[float, float], ...] = ()
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"""Per-session ``(start_ts, end_ts)`` tuples in seconds since
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epoch. Used ONLY for pairwise relative deltas — never compared
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to an absolute clock. F7 (slow_burn) invariance check verifies
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that adding Δ to every entry on both sides yields the same edge
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weight."""
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last_phase_per_decky: Mapping[str, str] = field(default_factory=dict)
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"""``decky_id`` → last UKC phase observed on that decky. The
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"from" side of a phase handoff."""
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first_phase_per_decky: Mapping[str, str] = field(default_factory=dict)
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"""``decky_id`` → first UKC phase observed on that decky. The
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"to" side of a phase handoff."""
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last_seen_per_decky: Mapping[str, float] = field(default_factory=dict)
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"""``decky_id`` → last activity timestamp on that decky. Pairs
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with :attr:`first_seen_per_decky` to compute pairwise handoff
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gap relative to the two identities (no absolute clock)."""
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first_seen_per_decky: Mapping[str, float] = field(default_factory=dict)
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"""``decky_id`` → first activity timestamp on that decky."""
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# ─── Phase-handoff edge ─────────────────────────────────────────────────────
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#: Phases that mark a *handoff-out* — operator A is finished setting
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#: up a foothold and the next operator can step in. Drawn from the
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#: STAGE_IN tail (PERSISTENCE / COMMAND_AND_CONTROL) per the UKC
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#: vocabulary; expanding this set is a tunable knob.
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HANDOFF_OUT_PHASES: frozenset[str] = frozenset({
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"command_and_control",
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"persistence",
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})
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#: Phases that mark a *handoff-in* — operator B picks up a prepared
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#: foothold and starts operating through the network. STAGE_THROUGH
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#: head (DISCOVERY / LATERAL_MOVEMENT).
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HANDOFF_IN_PHASES: frozenset[str] = frozenset({
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"discovery",
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"lateral_movement",
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})
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#: Default handoff-window in seconds. The "B starts within W of A's
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#: end" guard. Bounded relative to the pair — fixture F7 invariant
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#: still holds because shifting both timestamps preserves the gap.
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DEFAULT_HANDOFF_WINDOW_S: float = 24 * 3600.0 # 24h
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def phase_handoff_weight(
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a: IdentityFeatures,
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b: IdentityFeatures,
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window_s: float = DEFAULT_HANDOFF_WINDOW_S,
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) -> float:
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"""Phase-handoff edge — the load-bearing F5 signal.
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Returns ``1.0`` if there exists a decky D such that EITHER:
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* A's last phase on D is in :data:`HANDOFF_OUT_PHASES`, B's first
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phase on D is in :data:`HANDOFF_IN_PHASES`, and B's first
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activity on D is within ``window_s`` AFTER A's last activity
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on D, OR
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* the symmetric case with A and B swapped.
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Returns ``0.0`` when no shared decky has a matching out→in pair
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within window. Window comparison is on the *gap* (a single
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subtraction) — pairwise-relative, so F7 invariance holds.
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"""
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return max(
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_directed_handoff(a, b, window_s),
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_directed_handoff(b, a, window_s),
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)
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def _directed_handoff(
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out: IdentityFeatures, in_: IdentityFeatures, window_s: float,
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) -> float:
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shared = set(out.last_phase_per_decky) & set(in_.first_phase_per_decky)
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for decky in shared:
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out_phase = out.last_phase_per_decky.get(decky)
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in_phase = in_.first_phase_per_decky.get(decky)
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if out_phase not in HANDOFF_OUT_PHASES:
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continue
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if in_phase not in HANDOFF_IN_PHASES:
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continue
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out_t = out.last_seen_per_decky.get(decky)
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in_t = in_.first_seen_per_decky.get(decky)
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if out_t is None or in_t is None:
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continue
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gap = in_t - out_t
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if 0.0 <= gap <= window_s:
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return 1.0
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return 0.0
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# ─── Shared-infra edge ──────────────────────────────────────────────────────
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def shared_infra_weight(a: IdentityFeatures, b: IdentityFeatures) -> float:
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"""Jaccard over payload-hashes ∪ C2-endpoints.
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Excludes ``decky_set`` deliberately: decky overlap is a *fleet
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scarcity* artifact (a small fleet means many distinct campaigns
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hit the same deckies) and would fuse F1's two unrelated campaigns
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on shared targeting. Payload hashes and C2 endpoints are
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operational artifacts; distinct campaigns rarely share them.
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At identity level this gets vetoed by the fingerprint-disagreement
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rule (``ed32358``); at campaign level it's the *primary* positive
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signal — distinct identities sharing payload + C2 is the canonical
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co-op pattern (F5 multi_operator).
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The decky-overlap signal lives in :func:`cohort_weight` instead
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where its weak-tier multiplier prevents F1-style false merges.
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Returns Jaccard across the union of the two set families,
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``0.0`` when both sides are empty.
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"""
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a_set = a.payload_hashes | a.c2_endpoints
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b_set = b.payload_hashes | b.c2_endpoints
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if not a_set and not b_set:
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return 0.0
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union = a_set | b_set
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if not union:
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return 0.0
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return len(a_set & b_set) / len(union)
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# ─── Temporal-overlap edge ──────────────────────────────────────────────────
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def temporal_overlap_weight(
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a: IdentityFeatures, b: IdentityFeatures,
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) -> float:
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"""Pairwise-relative temporal overlap fraction.
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Returns the fraction of A's total session time that overlaps any
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B session, capped at ``1.0``. Pairwise-relative: the value is
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invariant under a uniform Δ-shift of every timestamp on both
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sides (F7 fixture's invariant). Returns ``0.0`` when either side
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has no session windows.
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Two non-cooperating actors with bounded operations rarely overlap
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by chance; co-op campaigns overlap heavily. Defeated alone (one
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overlapping minute means little) — combined with shared-infra
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or handoff it pulls a pair over threshold.
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"""
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if not a.session_windows or not b.session_windows:
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return 0.0
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a_total = sum(end - start for start, end in a.session_windows)
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if a_total <= 0:
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return 0.0
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overlap = 0.0
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for a_start, a_end in a.session_windows:
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for b_start, b_end in b.session_windows:
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lo = max(a_start, b_start)
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hi = min(a_end, b_end)
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if hi > lo:
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overlap += hi - lo
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return min(1.0, overlap / a_total)
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# ─── Cohort edges ───────────────────────────────────────────────────────────
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def cohort_weight(a: IdentityFeatures, b: IdentityFeatures) -> float:
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"""ASN-cohort + tooling-cohort + decky-overlap weak signal.
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Jaccard over the union of ASN cohort, tooling cohort, and decky
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set. F2's failure mode (one identity rotating across many ASNs)
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doesn't apply at *campaign* level — but multiple identities
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cooperating out of the same hosting cohort is plausible co-op
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evidence. Decky overlap lives here (not in :func:`shared_infra`)
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because decky scarcity in a small honeypot fleet would otherwise
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fuse unrelated campaigns hitting the same SSH targets (F1
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shared_wordlist).
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Weak by design: the combined-weight tier multiplier keeps this
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from crossing threshold alone.
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"""
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a_set: frozenset = frozenset(
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{("asn", str(x)) for x in a.asn_cohort}
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| {("tool", x) for x in a.tooling_cohort}
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| {("decky", x) for x in a.decky_set}
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)
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b_set: frozenset = frozenset(
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{("asn", str(x)) for x in b.asn_cohort}
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| {("tool", x) for x in b.tooling_cohort}
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| {("decky", x) for x in b.decky_set}
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)
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if not a_set and not b_set:
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return 0.0
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union = a_set | b_set
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if not union:
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return 0.0
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return len(a_set & b_set) / len(union)
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# ─── Combined campaign-level weight ─────────────────────────────────────────
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#: Tier multipliers for the campaign graph. Tuned so:
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#:
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#: * Phase-handoff alone (max 1.0) crosses threshold — a clean
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#: F5-style handoff is sufficient evidence on its own.
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#: * Shared-infra alone (max 1.0) crosses threshold — payload+C2
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#: overlap is the canonical co-op signal (F5 multi_operator's
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#: intended pass condition; decky overlap was deliberately moved
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#: to :func:`cohort_weight` to avoid F1's false merge on shared
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#: targeting).
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#: * Temporal overlap alone (max 1.0) yields 0.4 — supporting weight.
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#: * Cohort alone (max 1.0) yields 0.1 — defeats F1's shared-decky
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#: failure mode and F2's rotating-ASN one.
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#:
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#: F1 shared_wordlist: payload+C2 = ∅ on both sides → shared_infra =
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#: 0; ASN+decky overlap fires cohort but at 0.1 stays well below
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#: threshold. F2 vpn_hopping is folded by the identity layer first,
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#: so the campaign clusterer sees one identity → one campaign.
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CAMPAIGN_TIER_WEIGHTS: dict[str, float] = {
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"phase_handoff": 1.0,
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"shared_infra": 1.0,
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"temporal_overlap": 0.4,
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"cohort": 0.1,
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}
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#: Threshold a combined campaign-edge weight must meet to survive
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#: into the similarity graph.
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CAMPAIGN_EDGE_THRESHOLD: float = 1.0
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def combined_campaign_weight(
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a: IdentityFeatures,
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b: IdentityFeatures,
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*,
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handoff_window_s: float = DEFAULT_HANDOFF_WINDOW_S,
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) -> float:
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"""Sum of all four tier scores, weighted by
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:data:`CAMPAIGN_TIER_WEIGHTS`.
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The campaign-clusterer worker compares this against
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:data:`CAMPAIGN_EDGE_THRESHOLD` to decide whether to draw an
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edge. Pure / time-agnostic — F7 invariant preserved.
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"""
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return (
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CAMPAIGN_TIER_WEIGHTS["phase_handoff"]
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* phase_handoff_weight(a, b, handoff_window_s)
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+ CAMPAIGN_TIER_WEIGHTS["shared_infra"] * shared_infra_weight(a, b)
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+ CAMPAIGN_TIER_WEIGHTS["temporal_overlap"]
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* temporal_overlap_weight(a, b)
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+ CAMPAIGN_TIER_WEIGHTS["cohort"] * cohort_weight(a, b)
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)
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# ─── Adapter for synthetic-fixture tests ────────────────────────────────────
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def from_synthetic_identity(att, identity_uuid: Optional[str] = None) -> IdentityFeatures: # type: ignore[no-untyped-def]
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"""Build an :class:`IdentityFeatures` from a ``SyntheticAttacker``.
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Treats one ``SyntheticAttacker`` as one identity — adequate for
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fixture validation where the campaign-clusterer reads identities
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not raw observations. The worker's production-row adapter
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(commit 3) builds the same shape from real ``AttackerIdentity``
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rows + their member observations.
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Lives here so test code doesn't import the factory shape into the
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production module — the adapter is a documented integration point.
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"""
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payload_hashes: set[str] = set()
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c2_endpoints: set[str] = set()
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decky_set: set[str] = set()
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asn_cohort: set[int] = set()
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if att.asn is not None:
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asn_cohort.add(att.asn)
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commands_by_phase_on_decky: dict[tuple[str, str], list[str]] = {}
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last_phase_per_decky: dict[str, str] = {}
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first_phase_per_decky: dict[str, str] = {}
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last_seen_per_decky: dict[str, float] = {}
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first_seen_per_decky: dict[str, float] = {}
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session_windows: list[tuple[float, float]] = []
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# SyntheticSession order is the campaign DSL's emission order, which
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# is monotonically time-ordered by construction. We rely on that to
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# extract first/last phase per decky.
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for s in att.sessions:
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if s.payload_hash:
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payload_hashes.add(s.payload_hash)
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if s.c2_callback:
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c2_endpoints.add(s.c2_callback)
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decky = getattr(s, "decky", None) or getattr(s, "decky_id", None)
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if decky:
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decky_set.add(decky)
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# SyntheticSession exposes ``started_at`` (datetime) +
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# ``duration_s``; the production-row adapter (commit 3) gets
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# ``start_ts``/``end_ts`` directly. Support both.
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started_at = getattr(s, "started_at", None)
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duration_s = getattr(s, "duration_s", None)
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if started_at is not None:
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ts_start = started_at.timestamp()
|
||||
ts_end = ts_start + (float(duration_s) if duration_s else 0.0)
|
||||
else:
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||||
ts_start = getattr(s, "start_ts", None)
|
||||
ts_end = getattr(s, "end_ts", None)
|
||||
if ts_start is not None and ts_end is not None:
|
||||
session_windows.append((float(ts_start), float(ts_end)))
|
||||
phase_value = s.phase.value if hasattr(s, "phase") else None
|
||||
if decky and phase_value:
|
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key = (decky, phase_value)
|
||||
if s.commands:
|
||||
commands_by_phase_on_decky.setdefault(key, []).extend(s.commands)
|
||||
if decky not in first_phase_per_decky:
|
||||
first_phase_per_decky[decky] = phase_value
|
||||
if ts_start is not None:
|
||||
first_seen_per_decky[decky] = float(ts_start)
|
||||
last_phase_per_decky[decky] = phase_value
|
||||
if ts_end is not None:
|
||||
last_seen_per_decky[decky] = float(ts_end)
|
||||
elif ts_start is not None:
|
||||
last_seen_per_decky[decky] = float(ts_start)
|
||||
|
||||
return IdentityFeatures(
|
||||
identity_uuid=identity_uuid or att.attacker_id,
|
||||
asn_cohort=frozenset(asn_cohort),
|
||||
tooling_cohort=frozenset(),
|
||||
payload_hashes=frozenset(payload_hashes),
|
||||
c2_endpoints=frozenset(c2_endpoints),
|
||||
decky_set=frozenset(decky_set),
|
||||
commands_by_phase_on_decky={
|
||||
k: tuple(v) for k, v in commands_by_phase_on_decky.items()
|
||||
},
|
||||
session_windows=tuple(session_windows),
|
||||
last_phase_per_decky=dict(last_phase_per_decky),
|
||||
first_phase_per_decky=dict(first_phase_per_decky),
|
||||
last_seen_per_decky=dict(last_seen_per_decky),
|
||||
first_seen_per_decky=dict(first_seen_per_decky),
|
||||
)
|
||||
|
||||
|
||||
__all__ = [
|
||||
"IdentityFeatures",
|
||||
"phase_handoff_weight",
|
||||
"shared_infra_weight",
|
||||
"temporal_overlap_weight",
|
||||
"cohort_weight",
|
||||
"combined_campaign_weight",
|
||||
"from_synthetic_identity",
|
||||
"HANDOFF_OUT_PHASES",
|
||||
"HANDOFF_IN_PHASES",
|
||||
"DEFAULT_HANDOFF_WINDOW_S",
|
||||
"CAMPAIGN_TIER_WEIGHTS",
|
||||
"CAMPAIGN_EDGE_THRESHOLD",
|
||||
]
|
||||
Reference in New Issue
Block a user