diff --git a/flexmeasures/api/v3_0/sensors.py b/flexmeasures/api/v3_0/sensors.py
index 62a427321..c5d2e31b1 100644
--- a/flexmeasures/api/v3_0/sensors.py
+++ b/flexmeasures/api/v3_0/sensors.py
@@ -1632,6 +1632,18 @@ def trigger_forecast(self, id: int, **params):
         # Put the sensor to save in the parameters
         parameters["sensor"] = params["sensor_to_save"].id
 
+        # Check read permissions for regressor sensors specified in the config.
+        # The schema has already validated that these sensor IDs exist.
+        config = parameters.get("config", {})
+        regressor_ids = set(
+            config.get("future-regressors", [])
+            + config.get("past-regressors", [])
+            + config.get("regressors", [])
+        )
+        for regressor_id in regressor_ids:
+            regressor = db.session.get(Sensor, regressor_id)
+            check_access(regressor, "read")
+
         # Set forecaster model
         model = parameters.pop("model", "TrainPredictPipeline")
 
diff --git a/flexmeasures/api/v3_0/tests/test_forecasting_api.py b/flexmeasures/api/v3_0/tests/test_forecasting_api.py
index df7e3fef8..fddc8288c 100644
--- a/flexmeasures/api/v3_0/tests/test_forecasting_api.py
+++ b/flexmeasures/api/v3_0/tests/test_forecasting_api.py
@@ -1,3 +1,5 @@
+from datetime import timedelta
+
 from flask import current_app
 import isodate
 import pytest
@@ -8,6 +10,9 @@
 from flexmeasures.api.tests.utils import get_auth_token
 from flexmeasures.data.services.forecasting import handle_forecasting_exception
 from flexmeasures.data.models.forecasting.pipelines import TrainPredictPipeline
+from flexmeasures.data import db
+from flexmeasures.data.models.generic_assets import GenericAsset, GenericAssetType
+from flexmeasures.data.models.time_series import Sensor
 
 
 @pytest.mark.parametrize("requesting_user", ["test_admin_user@seita.nl"], indirect=True)
@@ -126,3 +131,78 @@ def test_trigger_and_fetch_forecasts(
 
         # API should return exactly these most-recent beliefs
         assert api_forecasts == expected_values
+
+
+@pytest.mark.parametrize(
+    "regressor_field",
+    ["future-regressors", "past-regressors", "regressors"],
+)
+@pytest.mark.parametrize(
+    "requesting_user", ["test_supplier_user_4@seita.nl"], indirect=True
+)
+def test_trigger_forecast_with_unreadable_regressor_returns_403(
+    app,
+    setup_roles_users_fresh_db,
+    setup_accounts_fresh_db,
+    requesting_user,
+    regressor_field,
+):
+    """Triggering a forecast that uses a regressor the requesting user cannot read must return 403."""
+
+    supplier_account = setup_accounts_fresh_db["Supplier"]
+    prosumer_account = setup_accounts_fresh_db["Prosumer"]
+
+    asset_type = GenericAssetType(name="test-asset-type-regressor-perm")
+    db.session.add(asset_type)
+
+    # Target sensor: owned by Supplier account – requesting user has create-children here
+    supplier_asset = GenericAsset(
+        name=f"supplier-target-asset-{regressor_field}",
+        generic_asset_type=asset_type,
+        owner=supplier_account,
+    )
+    db.session.add(supplier_asset)
+    target_sensor = Sensor(
+        name=f"supplier-target-sensor-{regressor_field}",
+        unit="kW",
+        event_resolution=timedelta(hours=1),
+        generic_asset=supplier_asset,
+    )
+    db.session.add(target_sensor)
+
+    # Regressor sensor: owned by Prosumer account – requesting user has no read access here
+    prosumer_asset = GenericAsset(
+        name=f"prosumer-private-regressor-asset-{regressor_field}",
+        generic_asset_type=asset_type,
+        owner=prosumer_account,
+    )
+    db.session.add(prosumer_asset)
+    private_regressor = Sensor(
+        name=f"prosumer-private-regressor-sensor-{regressor_field}",
+        unit="kW",
+        event_resolution=timedelta(hours=1),
+        generic_asset=prosumer_asset,
+    )
+    db.session.add(private_regressor)
+    db.session.commit()
+
+    client = app.test_client()
+    token = get_auth_token(client, "test_supplier_user_4@seita.nl", "testtest")
+
+    payload = {
+        "start": "2025-01-05T00:00:00+00:00",
+        "end": "2025-01-05T02:00:00+00:00",
+        "max-forecast-horizon": "PT1H",
+        "forecast-frequency": "PT1H",
+        "config": {
+            "train-start": "2025-01-01T00:00:00+00:00",
+            "retrain-frequency": "PT1H",
+            regressor_field: [private_regressor.id],
+        },
+    }
+
+    trigger_url = url_for("SensorAPI:trigger_forecast", id=target_sensor.id)
+    trigger_res = client.post(
+        trigger_url, json=payload, headers={"Authorization": token}
+    )
+    assert trigger_res.status_code == 403