diff --git a/gnat/analysis/attribution/builder.py b/gnat/analysis/attribution/builder.py
new file mode 100644
index 0000000..febad19
--- /dev/null
+++ b/gnat/analysis/attribution/builder.py
@@ -0,0 +1,148 @@
+# SPDX-License-Identifier: Apache-2.0
+# Copyright 2026 Bill Halpin
+"""
+gnat.analysis.attribution.builder
+=====================================
+
+Campaign builder — promotes :class:`~gnat.analysis.correlation.cluster_detector.Cluster`
+objects into :class:`CampaignProfile` instances and wires up indicator,
+actor, and investigation linkage.
+
+The builder is the bridge between the automated correlation layer
+(which produces clusters) and the analyst-managed campaign layer
+(which tracks lifecycle, attribution hypotheses, and kill-chain
+progression). It is explicitly *not* automatic: clusters must be
+promoted by an analyst or by a rule-triggered workflow.
+"""
+
+from __future__ import annotations
+
+import logging
+from typing import Any
+
+from gnat.analysis.attribution.models import CampaignProfile, CampaignStatus
+
+logger = logging.getLogger(__name__)
+
+
+class CampaignBuilder:
+    """
+    Converts correlation clusters into campaign profiles.
+
+    Stateless — takes cluster data as dicts (matching
+    :meth:`Cluster.to_dict`) and returns :class:`CampaignProfile`
+    instances ready for persistence via :class:`CampaignService`.
+    """
+
+    @staticmethod
+    def from_cluster(
+        cluster: dict[str, Any],
+        *,
+        created_by: str = "cluster_detector",
+        classification: str = "amber",
+    ) -> CampaignProfile:
+        """
+        Build a :class:`CampaignProfile` from a single cluster dict.
+
+        Uses the cluster's ``suggested_campaign`` as the campaign name
+        (falls back to the cluster label), and ``suggested_actor`` as
+        the initial ``threat_actor_id``. Member IDs become the campaign's
+        ``indicator_ids`` and the cluster ID is linked as a
+        ``cluster_id``.
+
+        Parameters
+        ----------
+        cluster : dict
+            Output of ``Cluster.to_dict()``.
+        created_by : str
+            Principal that triggered the promotion.
+        classification : str
+            TLP classification for the new campaign.
+        """
+        name = (
+            cluster.get("suggested_campaign")
+            or cluster.get("label")
+            or f"Cluster {cluster.get('id', 'unknown')}"
+        )
+
+        actor_id = None
+        actor_label = cluster.get("suggested_actor")
+        if actor_label:
+            actor_id = f"threat-actor--{actor_label}"
+
+        campaign = CampaignProfile(
+            name=name,
+            description=f"Auto-promoted from cluster {cluster.get('id', '')}. "
+            f"Signals: {'; '.join(cluster.get('signals') or [])}",
+            status=CampaignStatus.SUSPECTED,
+            threat_actor_id=actor_id,
+            indicator_ids=list(cluster.get("member_ids") or []),
+            cluster_ids=[cluster.get("id", "")],
+            tags=["auto-promoted", "from-cluster"],
+            classification=classification,
+            created_by=created_by,
+        )
+
+        logger.info(
+            "CampaignBuilder: promoted cluster %s → campaign %s (%s)",
+            cluster.get("id"),
+            campaign.id,
+            name,
+        )
+        return campaign
+
+    @staticmethod
+    def from_clusters(
+        clusters: list[dict[str, Any]],
+        *,
+        created_by: str = "cluster_detector",
+        min_confidence: int = 0,
+    ) -> list[CampaignProfile]:
+        """
+        Batch-promote multiple clusters, optionally filtering by
+        minimum STIX confidence.
+
+        Parameters
+        ----------
+        clusters : list of dict
+            Each dict is the output of ``Cluster.to_dict()``.
+        min_confidence : int
+            Skip clusters whose ``confidence.stix_confidence`` is below
+            this threshold. Default 0 (promote all).
+        """
+        campaigns: list[CampaignProfile] = []
+        for cluster in clusters:
+            conf = cluster.get("confidence") or {}
+            stix_conf = conf.get("stix_confidence", 0) if isinstance(conf, dict) else 0
+            if stix_conf < min_confidence:
+                logger.debug(
+                    "CampaignBuilder: skipping cluster %s (confidence %d < %d)",
+                    cluster.get("id"),
+                    stix_conf,
+                    min_confidence,
+                )
+                continue
+            campaigns.append(
+                CampaignBuilder.from_cluster(cluster, created_by=created_by)
+            )
+        return campaigns
+
+    @staticmethod
+    def merge_into_existing(
+        campaign: CampaignProfile,
+        cluster: dict[str, Any],
+    ) -> CampaignProfile:
+        """
+        Merge a cluster's indicators into an existing campaign.
+
+        Adds the cluster's ``member_ids`` to the campaign's
+        ``indicator_ids`` (deduplicated) and links the cluster ID.
+        Does NOT change campaign status or attribution.
+        """
+        for mid in cluster.get("member_ids") or []:
+            if mid not in campaign.indicator_ids:
+                campaign.indicator_ids.append(mid)
+        cluster_id = cluster.get("id", "")
+        if cluster_id and cluster_id not in campaign.cluster_ids:
+            campaign.cluster_ids.append(cluster_id)
+        return campaign
diff --git a/tests/unit/analysis/test_campaign_builder.py b/tests/unit/analysis/test_campaign_builder.py
new file mode 100644
index 0000000..0938d01
--- /dev/null
+++ b/tests/unit/analysis/test_campaign_builder.py
@@ -0,0 +1,161 @@
+# SPDX-License-Identifier: Apache-2.0
+# Copyright 2026 Bill Halpin
+"""
+tests/unit/analysis/test_campaign_builder.py
+===============================================
+
+Unit tests for the CampaignBuilder — cluster-to-campaign promotion
+(Phase 4 of the attribution & campaign tracking extension).
+"""
+
+from __future__ import annotations
+
+from gnat.analysis.attribution.builder import CampaignBuilder
+from gnat.analysis.attribution.models import CampaignProfile, CampaignStatus
+
+
+def _make_cluster(
+    cluster_id: str = "cluster-1",
+    label: str = "Subnet overlap cluster",
+    member_ids: list[str] | None = None,
+    signals: list[str] | None = None,
+    suggested_campaign: str | None = None,
+    suggested_actor: str | None = None,
+    stix_confidence: int = 60,
+) -> dict:
+    return {
+        "id": cluster_id,
+        "label": label,
+        "member_ids": member_ids or ["ioc-1", "ioc-2", "ioc-3"],
+        "signals": signals or ["subnet_overlap", "timing_correlation"],
+        "confidence": {
+            "source_reliability": "C",
+            "information_credibility": 3,
+            "stix_confidence": stix_confidence,
+            "band": "MEDIUM",
+            "label": "C3 (MEDIUM)",
+            "rationale": None,
+        },
+        "suggested_actor": suggested_actor,
+        "suggested_campaign": suggested_campaign,
+        "size": 3,
+    }
+
+
+class TestCampaignBuilderFromCluster:
+    def test_basic_promotion(self):
+        cluster = _make_cluster()
+        campaign = CampaignBuilder.from_cluster(cluster)
+        assert isinstance(campaign, CampaignProfile)
+        assert campaign.status == CampaignStatus.SUSPECTED
+        assert campaign.indicator_ids == ["ioc-1", "ioc-2", "ioc-3"]
+        assert "cluster-1" in campaign.cluster_ids
+        assert "auto-promoted" in campaign.tags
+
+    def test_uses_suggested_campaign_as_name(self):
+        cluster = _make_cluster(suggested_campaign="Operation Sunrise")
+        campaign = CampaignBuilder.from_cluster(cluster)
+        assert campaign.name == "Operation Sunrise"
+
+    def test_falls_back_to_label(self):
+        cluster = _make_cluster(label="Infrastructure overlap")
+        campaign = CampaignBuilder.from_cluster(cluster)
+        assert campaign.name == "Infrastructure overlap"
+
+    def test_links_suggested_actor(self):
+        cluster = _make_cluster(suggested_actor="APT28")
+        campaign = CampaignBuilder.from_cluster(cluster)
+        assert campaign.threat_actor_id == "threat-actor--APT28"
+
+    def test_no_actor_when_not_suggested(self):
+        cluster = _make_cluster(suggested_actor=None)
+        campaign = CampaignBuilder.from_cluster(cluster)
+        assert campaign.threat_actor_id is None
+
+    def test_description_includes_signals(self):
+        cluster = _make_cluster(signals=["subnet_overlap", "tag_match"])
+        campaign = CampaignBuilder.from_cluster(cluster)
+        assert "subnet_overlap" in campaign.description
+        assert "tag_match" in campaign.description
+
+    def test_created_by_default(self):
+        cluster = _make_cluster()
+        campaign = CampaignBuilder.from_cluster(cluster)
+        assert campaign.created_by == "cluster_detector"
+
+    def test_created_by_custom(self):
+        cluster = _make_cluster()
+        campaign = CampaignBuilder.from_cluster(
+            cluster, created_by="senior_analyst"
+        )
+        assert campaign.created_by == "senior_analyst"
+
+
+class TestCampaignBuilderFromClusters:
+    def test_batch_promotion(self):
+        clusters = [
+            _make_cluster(cluster_id="c1", label="A"),
+            _make_cluster(cluster_id="c2", label="B"),
+            _make_cluster(cluster_id="c3", label="C"),
+        ]
+        campaigns = CampaignBuilder.from_clusters(clusters)
+        assert len(campaigns) == 3
+        names = {c.name for c in campaigns}
+        assert names == {"A", "B", "C"}
+
+    def test_min_confidence_filter(self):
+        clusters = [
+            _make_cluster(cluster_id="c1", stix_confidence=80),
+            _make_cluster(cluster_id="c2", stix_confidence=30),
+            _make_cluster(cluster_id="c3", stix_confidence=60),
+        ]
+        campaigns = CampaignBuilder.from_clusters(
+            clusters, min_confidence=50
+        )
+        assert len(campaigns) == 2
+
+    def test_min_confidence_zero_includes_all(self):
+        clusters = [
+            _make_cluster(cluster_id="c1", stix_confidence=10),
+            _make_cluster(cluster_id="c2", stix_confidence=0),
+        ]
+        campaigns = CampaignBuilder.from_clusters(clusters, min_confidence=0)
+        assert len(campaigns) == 2
+
+    def test_empty_list(self):
+        assert CampaignBuilder.from_clusters([]) == []
+
+
+class TestCampaignBuilderMerge:
+    def test_merge_adds_indicators(self):
+        campaign = CampaignProfile(
+            name="Existing",
+            indicator_ids=["ioc-a", "ioc-b"],
+            cluster_ids=["old-cluster"],
+        )
+        cluster = _make_cluster(
+            cluster_id="new-cluster",
+            member_ids=["ioc-b", "ioc-c", "ioc-d"],
+        )
+        CampaignBuilder.merge_into_existing(campaign, cluster)
+        assert set(campaign.indicator_ids) == {"ioc-a", "ioc-b", "ioc-c", "ioc-d"}
+        assert "new-cluster" in campaign.cluster_ids
+        assert "old-cluster" in campaign.cluster_ids
+
+    def test_merge_deduplicates(self):
+        campaign = CampaignProfile(
+            name="Existing",
+            indicator_ids=["ioc-1", "ioc-2"],
+        )
+        cluster = _make_cluster(member_ids=["ioc-1", "ioc-2", "ioc-3"])
+        CampaignBuilder.merge_into_existing(campaign, cluster)
+        assert campaign.indicator_ids == ["ioc-1", "ioc-2", "ioc-3"]
+
+    def test_merge_does_not_change_status(self):
+        campaign = CampaignProfile(
+            name="Active Campaign",
+            status=CampaignStatus.ACTIVE,
+        )
+        cluster = _make_cluster()
+        CampaignBuilder.merge_into_existing(campaign, cluster)
+        assert campaign.status == CampaignStatus.ACTIVE