feat: interactive network map, IOC highlighting, AUP hunt selector, type filters

- NetworkMap: hunt-scoped force-directed graph with click-to-inspect popover
- NetworkMap: zoom/pan (wheel, drag, buttons), viewport transform
- NetworkMap: clickable IP/Host/Domain/URL legend chips to filter node types
- NetworkMap: brighter colors, 20% smaller nodes
- DatasetViewer: IOC columns highlighted with colored headers + cell tinting
- AUPScanner: hunt dropdown replacing dataset checkboxes, auto-select all
- Rename 'Social Media (Personal)' theme to 'Social Media' with DB migration
- Fix /api/hunts timeout: Dataset.rows lazy='noload' (was selectin cascade)
- Add OS column mapping to normalizer
- Full backend services, DB models, alembic migrations, new routes
- New components: Dashboard, HuntManager, FileUpload, NetworkMap, etc.
- Docker Compose deployment with nginx reverse proxy

backend/app/db/repositories/datasets.py

@@ -0,0 +1,127 @@
+"""Dataset repository — CRUD operations for datasets and their rows."""
+
+import logging
+from typing import Sequence
+
+from sqlalchemy import select, func, delete
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.db.models import Dataset, DatasetRow
+
+logger = logging.getLogger(__name__)
+
+
+class DatasetRepository:
+    """Typed CRUD for Dataset and DatasetRow models."""
+
+    def __init__(self, session: AsyncSession):
+        self.session = session
+
+    # ── Dataset CRUD ──────────────────────────────────────────────────
+
+    async def create_dataset(self, **kwargs) -> Dataset:
+        ds = Dataset(**kwargs)
+        self.session.add(ds)
+        await self.session.flush()
+        return ds
+
+    async def get_dataset(self, dataset_id: str) -> Dataset | None:
+        result = await self.session.execute(
+            select(Dataset).where(Dataset.id == dataset_id)
+        )
+        return result.scalar_one_or_none()
+
+    async def list_datasets(
+        self,
+        hunt_id: str | None = None,
+        limit: int = 100,
+        offset: int = 0,
+    ) -> Sequence[Dataset]:
+        stmt = select(Dataset).order_by(Dataset.created_at.desc())
+        if hunt_id:
+            stmt = stmt.where(Dataset.hunt_id == hunt_id)
+        stmt = stmt.limit(limit).offset(offset)
+        result = await self.session.execute(stmt)
+        return result.scalars().all()
+
+    async def count_datasets(self, hunt_id: str | None = None) -> int:
+        stmt = select(func.count(Dataset.id))
+        if hunt_id:
+            stmt = stmt.where(Dataset.hunt_id == hunt_id)
+        result = await self.session.execute(stmt)
+        return result.scalar_one()
+
+    async def delete_dataset(self, dataset_id: str) -> bool:
+        ds = await self.get_dataset(dataset_id)
+        if not ds:
+            return False
+        await self.session.delete(ds)
+        await self.session.flush()
+        return True
+
+    # ── Row CRUD ──────────────────────────────────────────────────────
+
+    async def bulk_insert_rows(
+        self,
+        dataset_id: str,
+        rows: list[dict],
+        normalized_rows: list[dict] | None = None,
+        batch_size: int = 500,
+    ) -> int:
+        """Insert rows in batches. Returns count inserted."""
+        count = 0
+        for i in range(0, len(rows), batch_size):
+            batch = rows[i : i + batch_size]
+            norm_batch = normalized_rows[i : i + batch_size] if normalized_rows else [None] * len(batch)
+            objects = [
+                DatasetRow(
+                    dataset_id=dataset_id,
+                    row_index=i + j,
+                    data=row,
+                    normalized_data=norm,
+                )
+                for j, (row, norm) in enumerate(zip(batch, norm_batch))
+            ]
+            self.session.add_all(objects)
+            await self.session.flush()
+            count += len(objects)
+        return count
+
+    async def get_rows(
+        self,
+        dataset_id: str,
+        limit: int = 1000,
+        offset: int = 0,
+    ) -> Sequence[DatasetRow]:
+        stmt = (
+            select(DatasetRow)
+            .where(DatasetRow.dataset_id == dataset_id)
+            .order_by(DatasetRow.row_index)
+            .limit(limit)
+            .offset(offset)
+        )
+        result = await self.session.execute(stmt)
+        return result.scalars().all()
+
+    async def count_rows(self, dataset_id: str) -> int:
+        stmt = select(func.count(DatasetRow.id)).where(
+            DatasetRow.dataset_id == dataset_id
+        )
+        result = await self.session.execute(stmt)
+        return result.scalar_one()
+
+    async def get_row_by_index(
+        self, dataset_id: str, row_index: int
+    ) -> DatasetRow | None:
+        stmt = select(DatasetRow).where(
+            DatasetRow.dataset_id == dataset_id,
+            DatasetRow.row_index == row_index,
+        )
+        result = await self.session.execute(stmt)
+        return result.scalar_one_or_none()
+
+    async def delete_rows(self, dataset_id: str) -> int:
+        result = await self.session.execute(
+            delete(DatasetRow).where(DatasetRow.dataset_id == dataset_id)
+        )
+        return result.rowcount  # type: ignore[return-value]