fix(ai): bind model scope to immutable geometry

.env.example

@@ -118,6 +118,11 @@ YOLO_MODEL_DISPLAY_NAME=Configured YOLO detector
 YOLO_MODEL_VERSION=
 YOLO_MODEL_CLASSES=building
 YOLO_ENFORCE_VALIDATION_SCOPE=false
+# Required when scope enforcement is enabled. The manifest is bound to exact
+# model bytes and contains the allowed EPSG:4326 validation geometry.
+YOLO_VALIDATION_SCOPE_MANIFEST_PATH=
+YOLO_VALIDATION_SCOPE_MANIFEST_SHA256=
+# Deprecated display metadata; never used as an inference authorization gate.
 YOLO_VALIDATED_AREA_NAMES=Mol,Kempen
 YOLO_CONFIG_DIR=./storage/ultralytics
 YOLO_DEVICE=cpu

backend/app/core/config.py

@@ -359,6 +359,17 @@ class Settings(BaseSettings):
     yolo_model_version: str | None = Field(default=None, validation_alias="YOLO_MODEL_VERSION")
     yolo_model_classes: str = Field(default="building", validation_alias="YOLO_MODEL_CLASSES")
     yolo_enforce_validation_scope: bool = Field(default=False, validation_alias="YOLO_ENFORCE_VALIDATION_SCOPE")
+    yolo_validation_scope_manifest_path: str | None = Field(
+        default=None,
+        validation_alias="YOLO_VALIDATION_SCOPE_MANIFEST_PATH",
+    )
+    yolo_validation_scope_manifest_sha256: str | None = Field(
+        default=None,
+        validation_alias="YOLO_VALIDATION_SCOPE_MANIFEST_SHA256",
+    )
+    # Deprecated compatibility field. Mutable Area names are never an
+    # inference authorization boundary; deployments must use the immutable
+    # checksum-bound scope manifest above.
     yolo_validated_area_names: str = Field(default="Mol,Kempen", validation_alias="YOLO_VALIDATED_AREA_NAMES")
     yolo_device: str = Field(default="cpu", validation_alias="YOLO_DEVICE")
     yolo_require_cuda: bool = Field(default=False, validation_alias="YOLO_REQUIRE_CUDA")

backend/app/services/detection_service.py

@@ -22,6 +22,7 @@ from app.services.detection_qa_service import DetectionQaService
 from app.services.dataset_consumption_gate_service import DatasetConsumptionGate
 from app.services.model_asset_catalog_service import ModelAssetCatalogService
 from app.services.model_registry_service import ModelRegistryService
+from app.services.model_validation_scope_service import ModelValidationScopeService
 from app.services.qa_service import QaService
 from app.services.quality_service import QualityService
 from app.services.runtime_model_provenance_service import RuntimeModelProvenance, RuntimeModelProvenanceService
@@ -235,16 +236,30 @@ class DetectionService:
 
     @staticmethod
     def _validate_model_area_scope(db, dataset: Dataset, settings: Settings) -> None:
-        allowed_names = [value.strip().casefold() for value in settings.yolo_validated_area_names.split(",") if value.strip()]
         area = db.get(Area, dataset.area_id) if dataset.area_id else None
-        area_name = area.name.strip() if area is not None else ""
+        if area is None or area.geometry is None:
-        if not area_name or not any(token in area_name.casefold() for token in allowed_names):
             raise AppError(
                 code="DETECTION_VALIDATION_SCOPE_UNAVAILABLE",
-                message="Configured YOLO inference is not validated for this Dataset area.",
+                message="Configured YOLO inference requires a persisted Dataset area geometry.",
-                details={"dataset_id": str(dataset.id), "dataset_area": area_name or None, "validated_area_names": allowed_names},
+                details={"dataset_id": str(dataset.id)},
                 status_code=422,
             )
+        try:
+            area_geometry = to_shape(area.geometry)
+        except Exception as exc:
+            raise AppError(
+                code="DETECTION_VALIDATION_SCOPE_UNAVAILABLE",
+                message="The persisted Dataset area geometry cannot be validated for model inference.",
+                details={"dataset_id": str(dataset.id), "error_type": type(exc).__name__},
+                status_code=422,
+            ) from exc
+        ModelValidationScopeService.assert_area_covered(
+            area_geometry=area_geometry,
+            manifest_path=settings.yolo_validation_scope_manifest_path,
+            expected_manifest_sha256=settings.yolo_validation_scope_manifest_sha256,
+            model_id=settings.yolo_model_id,
+            model_path=settings.yolo_model_path,
+        )
     @staticmethod
     def _fail_run_after_exception(db, analysis_run: AnalysisRun, job: Job, exc: Exception, fallback_code: str) -> None:
         try:

backend/app/services/model_validation_scope_service.py

@@ -0,0 +1,142 @@
+"""Checksum-bound geographic validation scope for production model inference."""
+
+from __future__ import annotations
+
+from hashlib import sha256
+import json
+from pathlib import Path
+import re
+from typing import Any
+
+from shapely.geometry import shape
+from shapely.geometry.base import BaseGeometry
+
+from app.core.errors import AppError
+
+
+_SHA256 = re.compile(r"^[0-9a-f]{64}$")
+
+
+class ModelValidationScopeService:
+    """Load an immutable, model-bound AOI and prove that an input is covered."""
+
+    SCHEMA_VERSION = "geointel.model-validation-scope/v1"
+
+    @classmethod
+    def assert_area_covered(
+        cls,
+        *,
+        area_geometry: BaseGeometry,
+        manifest_path: str | None,
+        expected_manifest_sha256: str | None,
+        model_id: str,
+        model_path: str | None,
+    ) -> dict[str, str]:
+        path = Path(manifest_path).expanduser() if manifest_path else None
+        expected_checksum = (expected_manifest_sha256 or "").strip().lower()
+        if path is None or not expected_checksum:
+            cls._raise(
+                "DETECTION_VALIDATION_SCOPE_NOT_CONFIGURED",
+                "Configured YOLO inference requires a checksum-bound geographic validation-scope manifest.",
+            )
+        if not _SHA256.fullmatch(expected_checksum):
+            cls._raise(
+                "DETECTION_VALIDATION_SCOPE_INVALID",
+                "The configured validation-scope checksum must be a lowercase SHA-256 digest.",
+                manifest_path=str(path),
+            )
+        try:
+            raw_manifest = path.read_bytes()
+            payload = json.loads(raw_manifest.decode("utf-8"))
+        except (OSError, UnicodeDecodeError, json.JSONDecodeError) as exc:
+            cls._raise(
+                "DETECTION_VALIDATION_SCOPE_INVALID",
+                "The configured validation-scope manifest is missing or unreadable.",
+                manifest_path=str(path),
+                error_type=type(exc).__name__,
+            )
+        observed_manifest_sha256 = sha256(raw_manifest).hexdigest()
+        if observed_manifest_sha256 != expected_checksum:
+            cls._raise(
+                "DETECTION_VALIDATION_SCOPE_CHECKSUM_MISMATCH",
+                "The validation-scope manifest does not match its configured checksum.",
+                manifest_path=str(path),
+                expected=expected_checksum,
+                observed=observed_manifest_sha256,
+            )
+        if not isinstance(payload, dict) or payload.get("schema_version") != cls.SCHEMA_VERSION:
+            cls._raise(
+                "DETECTION_VALIDATION_SCOPE_INVALID",
+                "The validation-scope manifest has an unsupported schema.",
+                manifest_path=str(path),
+            )
+        if payload.get("model_id") != model_id:
+            cls._raise(
+                "DETECTION_VALIDATION_SCOPE_MODEL_MISMATCH",
+                "The validation scope is not bound to the selected model identity.",
+                expected_model_id=model_id,
+                observed_model_id=payload.get("model_id"),
+            )
+        configured_model_path = Path(model_path).expanduser() if model_path else None
+        if configured_model_path is None or not configured_model_path.is_file():
+            cls._raise(
+                "DETECTION_VALIDATION_SCOPE_MODEL_UNAVAILABLE",
+                "The model bytes bound by the validation scope are unavailable.",
+            )
+        declared_model_sha256 = str(payload.get("model_sha256") or "").strip().lower()
+        observed_model_sha256 = cls._file_sha256(configured_model_path)
+        if not _SHA256.fullmatch(declared_model_sha256) or declared_model_sha256 != observed_model_sha256:
+            cls._raise(
+                "DETECTION_VALIDATION_SCOPE_MODEL_MISMATCH",
+                "The validation scope is not bound to the exact selected model bytes.",
+                expected=declared_model_sha256 or None,
+                observed=observed_model_sha256,
+            )
+        if payload.get("crs") != "EPSG:4326":
+            cls._raise(
+                "DETECTION_VALIDATION_SCOPE_INVALID",
+                "The validation-scope geometry must explicitly use EPSG:4326.",
+                observed_crs=payload.get("crs"),
+            )
+        try:
+            scope_geometry = shape(payload.get("geometry"))
+        except Exception as exc:
+            cls._raise(
+                "DETECTION_VALIDATION_SCOPE_INVALID",
+                "The validation-scope geometry is not valid GeoJSON.",
+                error_type=type(exc).__name__,
+            )
+        if (
+            scope_geometry.is_empty
+            or not scope_geometry.is_valid
+            or scope_geometry.geom_type not in {"Polygon", "MultiPolygon"}
+        ):
+            cls._raise(
+                "DETECTION_VALIDATION_SCOPE_INVALID",
+                "The validation scope must be a non-empty valid Polygon or MultiPolygon.",
+                geometry_type=scope_geometry.geom_type,
+            )
+        if area_geometry.is_empty or not area_geometry.is_valid or not scope_geometry.covers(area_geometry):
+            cls._raise(
+                "DETECTION_VALIDATION_SCOPE_UNAVAILABLE",
+                "Configured YOLO inference is not validated for the complete Dataset area.",
+                scope_key=payload.get("scope_key"),
+            )
+        return {
+            "scope_key": str(payload.get("scope_key") or "unspecified"),
+            "manifest_path": str(path.resolve()),
+            "manifest_sha256": observed_manifest_sha256,
+            "model_sha256": observed_model_sha256,
+        }
+
+    @staticmethod
+    def _file_sha256(path: Path) -> str:
+        digest = sha256()
+        with path.open("rb") as handle:
+            for chunk in iter(lambda: handle.read(1024 * 1024), b""):
+                digest.update(chunk)
+        return digest.hexdigest()
+
+    @staticmethod
+    def _raise(code: str, message: str, **details: Any) -> None:
+        raise AppError(code=code, message=message, details=details, status_code=422)

backend/tests/test_sprint122_model_asset_activation_guardrails.py

@@ -25,9 +25,9 @@ def test_detection_lab_explains_explicit_model_asset_and_threshold_selection() -
 
     assert "Lokaal modelbestand" in lab
     assert "GeoIntel kiest automatisch het actieve lokale model" in lab
-    assert "Gevalideerde YOLO-profielen" in lab
+    assert "Historische YOLO-controleprofielen" in lab
     assert "DETECTION_OPERATOR_PROFILES" in lab
-    assert "kandidaat, extra controle vereist" in lab
+    assert "historisch, geen releasebewijs" in lab
     assert "will_download_models" in lab
 
 

backend/tests/test_sprint155_detection_operator_profiles.py

@@ -4,7 +4,7 @@ from pathlib import Path
 ROOT = Path(__file__).resolve().parents[2]
 
 
-def test_detection_operator_profiles_define_explicit_yolo_candidates_and_promoted_profile() -> None:
+def test_detection_operator_profiles_define_explicit_historical_yolo_controls_without_promotion_claim() -> None:
     profiles = ROOT / "frontend" / "src" / "components" / "detection" / "detectionProfiles.ts"
     source = profiles.read_text(encoding="utf-8")
 
@@ -17,16 +17,17 @@ def test_detection_operator_profiles_define_explicit_yolo_candidates_and_promote
     assert "conservative-review" in source
     assert "confidenceThreshold: 0.15" in source
     assert "confidenceThreshold: 0.35" in source
-    assert "defaultApproved: true" in source
+    assert "defaultApproved" not in source
-    assert "promotionRecommendation: 'promote_candidate'" in source
+    assert "promotionRecommendation" not in source
+    assert "independentTestProven: false" in source
     assert "positiveSampleCount: 7" in source
     assert "precision: 0.6140895327792112" in source
     assert "recall: 0.6062221049337548" in source
     assert "f1: 0.6068607646002744" in source
     assert "f1: 0.5432865390636915" in source
     assert "maxBackgroundDetections: 0" in source
-    assert "lege-achtergrondtest is geslaagd" in source
+    assert "Slechts drie pure-achtergrondbeelden" in source
-    assert "Postel blijft met 47,5% F1" in source
+    assert "ruimtelijke onafhankelijkheid niet bewezen" in source
     assert "controlekandidaat en niet als grondwaarheid" in source
 
 
@@ -39,11 +40,11 @@ def test_detection_lab_surfaces_profiles_as_deliberate_operator_actions() -> Non
     )
 
     assert "DETECTION_OPERATOR_PROFILES" in lab
-    assert "Gevalideerde YOLO-profielen" in lab
+    assert "Historische YOLO-controleprofielen" in lab
     assert "profile.displayName" in lab
     assert "profile.confidenceThreshold" in lab
-    assert "kandidaat, extra controle vereist" in lab
+    assert "historisch, geen releasebewijs" in lab
-    assert "standaardprofiel" in lab
+    assert "historische F1" in lab
     assert "Profiel gebruiken" in lab
     assert "onApplyOperatorProfile(profile)" in lab
     assert "Recommended starting threshold: 0.25" not in lab

backend/tests/test_sprint193_end_user_workbench.py

@@ -72,7 +72,7 @@ def test_visible_ai_and_quality_labels_are_end_user_facing() -> None:
     providers = read("frontend/src/components/providers/ProviderPanel.tsx")
 
     assert "Aanbevolen controleprofiel kleine gebouwen" in profiles
-    assert "Postel blijft met 47,5% F1" in profiles
+    assert "Slechts drie pure-achtergrondbeelden" in profiles
     assert "controlekandidaat en niet als grondwaarheid" in profiles
     assert "qualityStatusLabel" in quality
     assert "nog niet uitgevoerd" in quality

backend/tests/test_sprint8b_yolo_foundation.py

@@ -8,6 +8,8 @@ from types import SimpleNamespace
 from uuid import uuid4
 
 import pytest
+from geoalchemy2.shape import from_shape
+from shapely.geometry import box, mapping
 
 from app.core.config import Settings
 from app.core.errors import AppError
@@ -15,6 +17,7 @@ from app.models import AnalysisRun, Area, Dataset, Detection, Job, Project, Sour
 from app.services.detection_georeferencing import pixel_bbox_to_epsg4326_polygon
 from app.services.detection_service import DetectionService
 from app.services.model_registry_service import ModelRegistryService
+from app.services.model_validation_scope_service import ModelValidationScopeService
 from app.services.runtime_model_provenance_service import RuntimeModelProvenanceService
 from app.services.yolo_adapter import YoloDetectionAdapter
 
@@ -207,6 +210,28 @@ def _settings(tmp_path: Path, **overrides) -> Settings:
     return Settings(**values)
 
 
+def _scope_settings(tmp_path: Path, scope_geometry=None, **overrides) -> Settings:
+    model_path = tmp_path / "model.pt"
+    model_path.write_bytes(b"scope-bound-model")
+    payload = {
+        "schema_version": ModelValidationScopeService.SCHEMA_VERSION,
+        "model_id": "yolo-configured",
+        "model_sha256": sha256(model_path.read_bytes()).hexdigest(),
+        "scope_key": "mol-kempen-test",
+        "crs": "EPSG:4326",
+        "geometry": mapping(scope_geometry or box(4.0, 50.8, 5.5, 52.0)),
+    }
+    manifest_path = tmp_path / "model-validation-scope.json"
+    manifest_path.write_text(json.dumps(payload, sort_keys=True), encoding="utf-8")
+    values = {
+        "yolo_model_path": str(model_path),
+        "yolo_validation_scope_manifest_path": str(manifest_path),
+        "yolo_validation_scope_manifest_sha256": sha256(manifest_path.read_bytes()).hexdigest(),
+    }
+    values.update(overrides)
+    return _settings(tmp_path, **values)
+
+
 def _write_model_sidecar(
     model_path: Path,
     settings: Settings,
@@ -399,21 +424,49 @@ def test_yolo_runtime_rejects_cpu_device_when_cuda_is_required(tmp_path: Path, m
 
 def test_yolo_validation_scope_requires_persisted_validated_area(tmp_path: Path) -> None:
     dataset = Dataset(id=uuid4(), project_id=uuid4(), name="image.tif", dataset_type="raster", source="test", area_id=uuid4())
-    wrong_area = Area(id=dataset.area_id, project_id=dataset.project_id, name="Brussels", geometry="MULTIPOLYGON EMPTY")
+    wrong_area = Area(
+        id=dataset.area_id,
+        project_id=dataset.project_id,
+        name="Mol validation bypass",
+        geometry=from_shape(box(-74.1, 40.6, -73.8, 40.9), srid=4326),
+    )
     db = FakeSession(objects={(Area, dataset.area_id): wrong_area})
 
     with pytest.raises(AppError) as exc_info:
-        DetectionService._validate_model_area_scope(db, dataset, _settings(tmp_path, yolo_validated_area_names="Mol,Kempen"))
+        DetectionService._validate_model_area_scope(db, dataset, _scope_settings(tmp_path))
 
     assert exc_info.value.code == "DETECTION_VALIDATION_SCOPE_UNAVAILABLE"
 
 
 def test_yolo_validation_scope_accepts_bound_mol_area(tmp_path: Path) -> None:
     dataset = Dataset(id=uuid4(), project_id=uuid4(), name="image.tif", dataset_type="raster", source="test", area_id=uuid4())
-    area = Area(id=dataset.area_id, project_id=dataset.project_id, name="Gemeente Mol", geometry="MULTIPOLYGON EMPTY")
+    area = Area(
+        id=dataset.area_id,
+        project_id=dataset.project_id,
+        name="Een wijzigbare weergavenaam",
+        geometry=from_shape(box(5.0, 51.1, 5.2, 51.3), srid=4326),
+    )
     db = FakeSession(objects={(Area, dataset.area_id): area})
 
-    DetectionService._validate_model_area_scope(db, dataset, _settings(tmp_path, yolo_validated_area_names="Mol,Kempen"))
+    DetectionService._validate_model_area_scope(db, dataset, _scope_settings(tmp_path))
+
+
+def test_yolo_validation_scope_rejects_tampered_manifest(tmp_path: Path) -> None:
+    dataset = Dataset(id=uuid4(), project_id=uuid4(), name="image.tif", dataset_type="raster", source="test", area_id=uuid4())
+    area = Area(
+        id=dataset.area_id,
+        project_id=dataset.project_id,
+        name="Gemeente Mol",
+        geometry=from_shape(box(5.0, 51.1, 5.2, 51.3), srid=4326),
+    )
+    settings = _scope_settings(tmp_path)
+    Path(settings.yolo_validation_scope_manifest_path).write_text("{}", encoding="utf-8")
+    db = FakeSession(objects={(Area, dataset.area_id): area})
+
+    with pytest.raises(AppError) as exc_info:
+        DetectionService._validate_model_area_scope(db, dataset, settings)
+
+    assert exc_info.value.code == "DETECTION_VALIDATION_SCOPE_CHECKSUM_MISMATCH"
 
 
 def test_yolo_run_requires_tile_manifest_path(tmp_path: Path) -> None:

deploy/unraid/Dockerfile.all-in-one

@@ -113,6 +113,7 @@ COPY scripts/provision_buildings_addresses_register.py /app/scripts/provision_bu
 COPY scripts/provision_regional_timeseries.py /app/scripts/provision_regional_timeseries.py
 COPY scripts/geographic_scopes.py /app/scripts/geographic_scopes.py
 COPY scripts/provision_geographic_scope.py /app/scripts/provision_geographic_scope.py
+COPY scripts/build_model_validation_scope_manifest.py /app/scripts/build_model_validation_scope_manifest.py
 COPY scripts/provision_belgium_north_sea_scope.py /app/scripts/provision_belgium_north_sea_scope.py
 COPY scripts/provision_release_golden_areas.py /app/scripts/provision_release_golden_areas.py
 COPY scripts/provision_regional_grb_buildings.py /app/scripts/provision_regional_grb_buildings.py

deploy/unraid/geointel-unraid-template.xml

@@ -137,8 +137,10 @@
   <Config Name="YOLO Device" Target="YOLO_DEVICE" Default="cuda:0" Mode="" Description="Required NVIDIA CUDA inference device." Type="Variable" Display="advanced" Required="true" Mask="false">cuda:0</Config>
   <Config Name="Require CUDA" Target="YOLO_REQUIRE_CUDA" Default="true" Mode="" Description="Fail closed instead of silently falling back to CPU when NVIDIA CUDA is unavailable." Type="Variable" Display="advanced" Required="true" Mask="false">true</Config>
   <Config Name="YOLO Classes" Target="YOLO_MODEL_CLASSES" Default="building" Mode="" Description="Comma-separated classes proven for the active model; the current promoted model is building-only." Type="Variable" Display="advanced" Required="true" Mask="false">building</Config>
-  <Config Name="Enforce YOLO Scope" Target="YOLO_ENFORCE_VALIDATION_SCOPE" Default="true" Mode="" Description="Reject inference outside persisted validated Areas." Type="Variable" Display="advanced" Required="true" Mask="false">true</Config>
+  <Config Name="Enforce YOLO Scope" Target="YOLO_ENFORCE_VALIDATION_SCOPE" Default="true" Mode="" Description="Reject inference outside the checksum-bound model validation geometry." Type="Variable" Display="advanced" Required="true" Mask="false">true</Config>
-  <Config Name="Validated YOLO Areas" Target="YOLO_VALIDATED_AREA_NAMES" Default="Mol,Kempen" Mode="" Description="Persisted Area name tokens with promotion evidence for the active model." Type="Variable" Display="advanced" Required="true" Mask="false">Mol,Kempen</Config>
+  <Config Name="YOLO Scope Manifest" Target="YOLO_VALIDATION_SCOPE_MANIFEST_PATH" Default="/app/storage/operator-data/model-validation-scopes/active-building-model.json" Mode="" Description="Immutable model-bound EPSG:4326 validation-scope manifest." Type="Variable" Display="advanced" Required="true" Mask="false">/app/storage/operator-data/model-validation-scopes/active-building-model.json</Config>
+  <Config Name="YOLO Scope Manifest SHA256" Target="YOLO_VALIDATION_SCOPE_MANIFEST_SHA256" Default="" Mode="" Description="Exact lowercase SHA-256 of the validation-scope manifest." Type="Variable" Display="advanced" Required="true" Mask="false"></Config>
+  <Config Name="Validated YOLO Areas (Display Only)" Target="YOLO_VALIDATED_AREA_NAMES" Default="Mol,Kempen" Mode="" Description="Deprecated display metadata; never authorizes inference." Type="Variable" Display="advanced" Required="false" Mask="false">Mol,Kempen</Config>
   <Config Name="YOLO Image Size" Target="YOLO_IMAGE_SIZE" Default="640" Mode="" Description="Inference image size in pixels." Type="Variable" Display="advanced" Required="true" Mask="false">640</Config>
   <Config Name="YOLO Maximum Tiles" Target="YOLO_MAX_TILES" Default="100" Mode="" Description="Hard tile limit per detection run." Type="Variable" Display="advanced" Required="true" Mask="false">100</Config>
   <Config Name="YOLO Maximum Detections" Target="YOLO_MAX_DETECTIONS" Default="1000" Mode="" Description="Hard persisted detection limit per run." Type="Variable" Display="advanced" Required="true" Mask="false">1000</Config>

deploy/unraid/geointel.env.example

@@ -166,6 +166,9 @@ YOLO_DEVICE=cuda:0
 YOLO_REQUIRE_CUDA=true
 YOLO_MODEL_CLASSES=building
 YOLO_ENFORCE_VALIDATION_SCOPE=true
+YOLO_VALIDATION_SCOPE_MANIFEST_PATH=/app/storage/operator-data/model-validation-scopes/active-building-model.json
+YOLO_VALIDATION_SCOPE_MANIFEST_SHA256=
+# Deprecated display metadata; never used as an inference authorization gate.
 YOLO_VALIDATED_AREA_NAMES=Mol,Kempen
 YOLO_IMAGE_SIZE=640
 YOLO_MAX_TILES=100

deploy/unraid/run-dockerman-container.sh

@@ -136,6 +136,8 @@ YOLO_MODEL_DISPLAY_NAME="${YOLO_MODEL_DISPLAY_NAME:-Configured YOLO detector}"
 YOLO_MODEL_VERSION="${YOLO_MODEL_VERSION:-}"
 YOLO_MODEL_CLASSES="${YOLO_MODEL_CLASSES:-building}"
 YOLO_ENFORCE_VALIDATION_SCOPE="${YOLO_ENFORCE_VALIDATION_SCOPE:-true}"
+YOLO_VALIDATION_SCOPE_MANIFEST_PATH="${YOLO_VALIDATION_SCOPE_MANIFEST_PATH:-}"
+YOLO_VALIDATION_SCOPE_MANIFEST_SHA256="${YOLO_VALIDATION_SCOPE_MANIFEST_SHA256:-}"
 YOLO_VALIDATED_AREA_NAMES="${YOLO_VALIDATED_AREA_NAMES:-Mol,Kempen}"
 YOLO_CONFIG_DIR="${YOLO_CONFIG_DIR:-/app/storage/ultralytics}"
 YOLO_DEVICE="${YOLO_DEVICE:-cuda:0}"
@@ -413,6 +415,8 @@ docker run -d \
   -e YOLO_MODEL_VERSION="$YOLO_MODEL_VERSION" \
   -e YOLO_MODEL_CLASSES="$YOLO_MODEL_CLASSES" \
   -e YOLO_ENFORCE_VALIDATION_SCOPE="$YOLO_ENFORCE_VALIDATION_SCOPE" \
+  -e YOLO_VALIDATION_SCOPE_MANIFEST_PATH="$YOLO_VALIDATION_SCOPE_MANIFEST_PATH" \
+  -e YOLO_VALIDATION_SCOPE_MANIFEST_SHA256="$YOLO_VALIDATION_SCOPE_MANIFEST_SHA256" \
   -e YOLO_VALIDATED_AREA_NAMES="$YOLO_VALIDATED_AREA_NAMES" \
   -e YOLO_CONFIG_DIR="$YOLO_CONFIG_DIR" \
   -e YOLO_DEVICE="$YOLO_DEVICE" \

docs/AI_PIPELINES.md

@@ -121,8 +121,13 @@ Environment variables:
 - `YOLO_REQUIRE_CUDA` (set to `true` on the production server; inference then
   fails closed when CUDA is unavailable or `YOLO_DEVICE` selects CPU)
 - `YOLO_MODEL_CLASSES` (the active promoted detector is `building` only)
-- `YOLO_ENFORCE_VALIDATION_SCOPE` and `YOLO_VALIDATED_AREA_NAMES` (production
+- `YOLO_ENFORCE_VALIDATION_SCOPE` (keep `true` in production)
-  rejects inference when the raster is not bound to a persisted validated Area)
+- `YOLO_VALIDATION_SCOPE_MANIFEST_PATH` and
+  `YOLO_VALIDATION_SCOPE_MANIFEST_SHA256` (production accepts inference only
+  when the exact active model bytes match the manifest and the complete
+  persisted Dataset AOI is covered by its valid EPSG:4326 geometry)
+- `YOLO_VALIDATED_AREA_NAMES` is deprecated display metadata and never grants
+  inference access
 - `YOLO_IMAGE_SIZE`
 - `YOLO_MAX_TILES`
 - `YOLO_MAX_DETECTIONS`
@@ -136,6 +141,25 @@ the upstream default would cap recall before QA/QC begins. Operators may lower
 the value for small rasters or raise it for dense urban tiles after reviewing
 runtime and false-positive behavior.
 
+Create a new immutable scope artifact whenever either the model bytes or the
+governed validation boundary changes:
+
+```bash
+python /app/scripts/build_model_validation_scope_manifest.py \
+  --model /app/models/active-building.pt \
+  --model-id yolo-configured \
+  --scope-geojson /app/storage/operator-data/geographic-scopes/kempen-transport-region/kempen_transport_region_boundary_YYYY-MM-DD.geojson \
+  --scope-key kempen-transport-region \
+  --authority "Digitaal Vlaanderen VRBG/Refgem" \
+  --snapshot-date YYYY-MM-DD \
+  --output /app/storage/operator-data/model-validation-scopes/active-building-model.json
+```
+
+The command refuses to overwrite an existing manifest and prints the checksum
+for `YOLO_VALIDATION_SCOPE_MANIFEST_SHA256`. Area names are intentionally not
+part of this decision: they are mutable presentation text, not accuracy or
+authorization evidence.
+
 After YOLO boxes are georeferenced, configured-YOLO runs apply a GeoIntel
 cross-tile duplicate suppression pass before persistence. Candidates are grouped
 by canonical class and sorted by confidence; lower-confidence same-class

docs/CODEX_EXECUTION_LOG.md

@@ -12444,3 +12444,31 @@ Open:
   `not_evaluable` without governed evidence. Phase 4 remains **in progress**,
   Phase 5 remains **not ready**, and promotion/training feedback from protected
   data is not authorized.
+
+## 2026-08-09 - Model accuracy boundary and truthful evidence labels
+
+### Changed
+
+- Replaced the configured-YOLO Area-name substring gate with a fail-closed,
+  checksum-bound validation-scope manifest. The exact model SHA-256 must match
+  and the immutable EPSG:4326 scope geometry must cover the complete persisted
+  Dataset AOI. Renaming an Area can no longer widen model applicability.
+- Added an operator tool that builds the model-bound manifest from exact model
+  bytes and governed scope GeoJSON without overwriting prior evidence.
+- Corrected the detection UI: legacy Mol/Kempen profile scores are now labelled
+  historical calibration context, spatial independence is explicitly unproven,
+  and no profile is marked approved or promotion-ready.
+
+### Verified
+
+- Targeted backend/UI contract selection: 34 passed.
+- `git diff --check`: passed before the documentation update; final check is
+  part of the handoff verification.
+
+### Remaining limitations
+
+- The current active model is still not nationally validated. A new governed
+  corpus, independent spatial split, representative human review and immutable
+  product benchmark remain required before any production-accuracy claim.
+- Every deployed model asset needs its own generated scope manifest and exact
+  configured manifest checksum before enforced inference is available.

docs/TODO.md

@@ -1115,8 +1115,10 @@ This file now starts with the current implementation status. Older preparation/b
   112 Ruff findings and add real frontend lint.
 - [ ] P2-02: fix CRS ingest, metre buffering and Area geometry/CRS updates;
   auditably quarantine or repair the four legacy Geel detections.
-- [ ] P2-03: isolate coverage by source/theme/layer/zone, make official source
+- [ ] P2-03: isolate coverage by source/theme/layer/zone and make official
-  identity server-attested and replace mutable-name legal/model scope checks.
+  source identity server-attested. The mutable-name YOLO scope bypass is fixed
+  with a model/checksum-bound geometry manifest; equivalent legal-scope checks
+  still require the same review.
 - [ ] P2-04: make derived persistence transactional, require complete
   RunManifest hashes and expose every fallback/persistence failure.
 - [ ] P2-05: remove every protected-test feedback path, introduce a test vault

frontend/src/components/detection/DetectionLab.tsx

@@ -21,11 +21,8 @@ const DETECTION_PAGE_SIZE_OPTIONS = [25, 50, 100] as const
 const DEFAULT_DETECTION_PAGE_SIZE = 50
 
 function detectionQualityInterpretation(f1: number | null | undefined): string {
-  if (typeof f1 !== 'number' || !Number.isFinite(f1)) return 'Nog geen gevalideerde kwaliteitsmeting.'
+  if (typeof f1 !== 'number' || !Number.isFinite(f1)) return 'Nog geen onafhankelijke kwaliteitsmeting beschikbaar.'
-  if (f1 >= 0.85) return 'Sterk resultaat; steekproefcontrole blijft vereist.'
+  return `Historische F1 ${f1.toFixed(3)} is alleen kalibratiecontext. Een actuele, ruimtelijk onafhankelijke QA-run bepaalt of dit resultaat lokaal bruikbaar is.`
-  if (f1 >= 0.70) return 'Bruikbaar met gerichte handmatige controle.'
-  if (f1 >= 0.50) return 'Verkennend resultaat; beoordeel fouten voor operationeel gebruik.'
-  return 'Onvoldoende betrouwbaar voor operationeel gebruik.'
 }
 
 function detectionStatusLabel(status: string): string {
@@ -311,8 +308,8 @@ export function DetectionLab({
           <p>{yoloRuntimeReady ? `${yoloPreflight?.runtime.cuda_available ? 'GPU' : 'CPU'} · lokaal model gevonden` : 'Controleer de modelconfiguratie onder beheer.'}</p>
         </div>
         <div className="ai-user-summary-card">
-          <span>Validatiescope</span>
+          <span>Bewijsstatus</span>
-          <strong>{selectedOperatorProfile ? `F1 ${selectedOperatorProfile.f1.toFixed(3)}` : 'Nog niet gekoppeld'}</strong>
+          <strong>{selectedOperatorProfile ? `Historische F1 ${selectedOperatorProfile.f1.toFixed(3)}` : 'Nog niet gekoppeld'}</strong>
           <p>{selectedOperatorProfile ? selectedOperatorProfile.validationScope : 'Kies een modelprofiel met gedocumenteerd evaluatiebewijs.'}</p>
         </div>
         <div className={rasterDatasets.length > 0 ? 'ai-user-summary-card ai-user-summary-card-ready' : 'ai-user-summary-card'}>

frontend/src/components/detection/DetectionModelManagement.tsx

@@ -141,7 +141,7 @@ export function DetectionModelManagement({
                 {selectedModelAsset ? 'model gekozen' : 'geen model gekozen'}
               </span>
             </div>
-            <div className="operator-profile-grid" aria-label="Gevalideerde YOLO-profielen">
+            <div className="operator-profile-grid" aria-label="Historische YOLO-controleprofielen">
               {DETECTION_OPERATOR_PROFILES.map((profile) => {
                 const profileAsset = modelAssets.find((asset) => asset.model_asset_id === profile.modelAssetId)
                 const profileSelected =
@@ -154,18 +154,18 @@ export function DetectionModelManagement({
                   >
                     <div className="operator-profile-card-header">
                       <strong>{profile.displayName}</strong>
-                      <span className={profile.defaultApproved ? 'status-badge status-badge-ready' : 'status-badge'}>
+                      <span className="status-badge">
-                        {profile.defaultApproved ? 'standaardprofiel' : 'kandidaat, extra controle vereist'}
+                        {profile.independentTestProven ? 'onafhankelijk getoetst' : 'historisch, geen releasebewijs'}
                       </span>
                     </div>
                     <p>{profile.description}</p>
                     <div className="operator-profile-metrics">
                       <span>drempel {profile.confidenceThreshold.toFixed(2)}</span>
-                      <span>precisie {profile.precision.toFixed(3)}</span>
+                      <span>historische precisie {profile.precision.toFixed(3)}</span>
-                      <span>herkenningsgraad {profile.recall.toFixed(3)}</span>
+                      <span>historische herkenningsgraad {profile.recall.toFixed(3)}</span>
-                      <span>F1 {profile.f1.toFixed(3)}</span>
+                      <span>historische F1 {profile.f1.toFixed(3)}</span>
-                      <span>testgebieden {profile.positiveSampleCount}</span>
+                      <span>positieve controles {profile.positiveSampleCount}</span>
-                      <span>max. achtergrondfouten {profile.maxBackgroundDetections}</span>
+                      <span>gemeten achtergrondfouten {profile.maxBackgroundDetections}</span>
                     </div>
                     <p className="field-guidance">{profile.limitationMessage}</p>
                     <button

frontend/src/components/detection/detectionProfiles.ts

@@ -3,8 +3,7 @@ export interface DetectionOperatorProfile {
   displayName: string
   modelAssetId: string
   confidenceThreshold: number
-  defaultApproved: boolean
+  independentTestProven: boolean
-  promotionRecommendation: 'none' | 'promote_candidate'
   precision: number
   recall: number
   f1: number
@@ -21,51 +20,48 @@ export const DETECTION_OPERATOR_PROFILES: DetectionOperatorProfile[] = [
     displayName: 'Aanbevolen controleprofiel kleine gebouwen',
     modelAssetId: 'geointel-building-yolov8s-smallbld-minpx3-img640-ft30-pt',
     confidenceThreshold: 0.15,
-    defaultApproved: true,
+    independentTestProven: false,
-    promotionRecommendation: 'promote_candidate',
     precision: 0.6140895327792112,
     recall: 0.6062221049337548,
     f1: 0.6068607646002744,
     positiveSampleCount: 7,
     maxBackgroundDetections: 0,
-    validationScope: '7 onafhankelijke testgebieden in Mol en de Kempen',
+    validationScope: 'historische operatorcontrole in Mol en de Kempen; ruimtelijke onafhankelijkheid niet bewezen',
     description:
-      'Aanbevolen profiel met een evenwicht tussen gevonden en gemiste kleine gebouwen, opnieuw gemeten over zeven onafhankelijke testgebieden in Mol en de Kempen.',
+      'Historisch controleprofiel met een evenwicht tussen gevonden en gemiste kleine gebouwen. Gebruik dit als startpunt voor lokale QA, niet als vrijgavebewijs.',
     limitationMessage:
-      'De drie lege-achtergrondtests zijn geslaagd. Postel blijft met 47,5% F1 het moeilijkste testgebied; behandel elke detectie als een controlekandidaat en niet als grondwaarheid.',
+      'Slechts drie pure-achtergrondbeelden en geen onafhankelijke hold-out ondersteunen deze historische meting. Postel bleef het moeilijkste gebied; behandel elke detectie als controlekandidaat en niet als grondwaarheid.',
   },
   {
     id: 'expanded-balanced-review',
     displayName: 'Voorgaand gebalanceerd controleprofiel',
     modelAssetId: 'geointel-building-yolov8s-aoi1024expandedminpx4vis035e50-pt',
     confidenceThreshold: 0.15,
-    defaultApproved: true,
+    independentTestProven: false,
-    promotionRecommendation: 'promote_candidate',
     precision: 0.6470590036169351,
     recall: 0.4699913836847832,
     f1: 0.5432865390636915,
     positiveSampleCount: 7,
     maxBackgroundDetections: 0,
-    validationScope: '7 onafhankelijke testgebieden in Mol en de Kempen',
+    validationScope: 'historische operatorcontrole in Mol en de Kempen; ruimtelijke onafhankelijkheid niet bewezen',
-    description: 'Voorgaand profiel voor controles waarbij minder foutieve vondsten belangrijker zijn dan maximale dekking.',
+    description: 'Historisch profiel voor lokale controles waarbij minder foutieve vondsten belangrijker zijn dan maximale dekking.',
     limitationMessage:
-      'De lege-achtergrondtest is geslaagd. Dit profiel vindt minder onterechte objecten, maar mist meer kleine gebouwen dan het aanbevolen profiel.',
+      'Dit profiel vond historisch minder onterechte objecten, maar miste meer kleine gebouwen. De meting is geen onafhankelijke productbenchmark.',
   },
   {
     id: 'conservative-review',
     displayName: 'Conservatief controleprofiel',
     modelAssetId: 'geointel-building-yolov8s-aoi1024bg512r3e50-pt',
     confidenceThreshold: 0.35,
-    defaultApproved: true,
+    independentTestProven: false,
-    promotionRecommendation: 'promote_candidate',
     precision: 0.840006,
     recall: 0.202135,
     f1: 0.32086574003576274,
     positiveSampleCount: 7,
     maxBackgroundDetections: 0,
-    validationScope: '7 onafhankelijke testgebieden in Mol en de Kempen',
+    validationScope: 'historische operatorcontrole in Mol en de Kempen; ruimtelijke onafhankelijkheid niet bewezen',
-    description: 'Profiel met hoge precisie voor controles waarbij zo weinig mogelijk foutieve vondsten zwaarder wegen dan volledige dekking.',
+    description: 'Historisch profiel voor lokale controles waarbij zo weinig mogelijk foutieve vondsten zwaarder wegen dan volledige dekking.',
     limitationMessage:
-      'Goedgekeurd na de lege-achtergrondtest. Resultaten in dun bebouwde context blijven altijd controlebewijs en geen automatische waarheid.',
+      'De historische precisie gaat samen met zeer lage herkenningsgraad. Resultaten blijven controlebewijs en geen automatische waarheid of releasebewijs.',
   },
 ]

scripts/build_model_validation_scope_manifest.py

@@ -0,0 +1,89 @@
+"""Build an immutable geographic validation scope bound to exact model bytes."""
+
+from __future__ import annotations
+
+import argparse
+from hashlib import sha256
+import json
+from pathlib import Path
+from typing import Any
+
+from shapely.geometry import mapping, shape
+from shapely.ops import unary_union
+
+
+SCHEMA_VERSION = "geointel.model-validation-scope/v1"
+
+
+def file_sha256(path: Path) -> str:
+    digest = sha256()
+    with path.open("rb") as handle:
+        for chunk in iter(lambda: handle.read(1024 * 1024), b""):
+            digest.update(chunk)
+    return digest.hexdigest()
+
+
+def read_scope_geometry(path: Path):
+    payload = json.loads(path.read_text(encoding="utf-8"))
+    payload_type = payload.get("type") if isinstance(payload, dict) else None
+    if payload_type == "FeatureCollection":
+        geometries = [shape(feature.get("geometry")) for feature in payload.get("features", [])]
+        geometry = unary_union([item for item in geometries if not item.is_empty])
+    elif payload_type == "Feature":
+        geometry = shape(payload.get("geometry"))
+    else:
+        geometry = shape(payload)
+    if geometry.is_empty or not geometry.is_valid or geometry.geom_type not in {"Polygon", "MultiPolygon"}:
+        raise ValueError("Scope input must resolve to one non-empty valid Polygon or MultiPolygon")
+    return geometry
+
+
+def build_manifest(args: argparse.Namespace) -> dict[str, Any]:
+    model_path = args.model.expanduser().resolve()
+    scope_path = args.scope_geojson.expanduser().resolve()
+    if not model_path.is_file():
+        raise FileNotFoundError(f"Model file not found: {model_path}")
+    if not scope_path.is_file():
+        raise FileNotFoundError(f"Scope GeoJSON not found: {scope_path}")
+    return {
+        "schema_version": SCHEMA_VERSION,
+        "model_id": args.model_id,
+        "model_sha256": file_sha256(model_path),
+        "scope_key": args.scope_key,
+        "crs": "EPSG:4326",
+        "geometry": mapping(read_scope_geometry(scope_path)),
+        "source": {
+            "scope_geojson_path": str(scope_path),
+            "scope_geojson_sha256": file_sha256(scope_path),
+            "authority": args.authority,
+            "snapshot_date": args.snapshot_date,
+        },
+    }
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--model", type=Path, required=True)
+    parser.add_argument("--model-id", required=True)
+    parser.add_argument("--scope-geojson", type=Path, required=True)
+    parser.add_argument("--scope-key", required=True)
+    parser.add_argument("--authority", required=True)
+    parser.add_argument("--snapshot-date", required=True)
+    parser.add_argument("--output", type=Path, required=True)
+    return parser.parse_args()
+
+
+def main() -> int:
+    args = parse_args()
+    output = args.output.expanduser().resolve()
+    if output.exists():
+        raise FileExistsError(f"Refusing to overwrite immutable scope manifest: {output}")
+    output.parent.mkdir(parents=True, exist_ok=True)
+    encoded = (json.dumps(build_manifest(args), ensure_ascii=False, indent=2, sort_keys=True) + "\n").encode("utf-8")
+    output.write_bytes(encoded)
+    print(json.dumps({"manifest_path": str(output), "manifest_sha256": sha256(encoded).hexdigest()}, sort_keys=True))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())