Fix tool output sharing when inputs come from public sources (#21802)

When a user's history is configured with private default permissions,
running a tool on a dataset imported from a public library would fail
with "Job attempted to create sharable output datasets in a storage
location with sharing disabled". This happened because output permissions
were derived solely from input datasets — public inputs produced outputs
with no DATASET_ACCESS restrictions, which conflicted with the private
object store.

The fix ensures that the history's default DATASET_ACCESS restrictions
are applied to tool outputs when the derived permissions from inputs lack
them. This respects the user's privacy intent (expressed via history
defaults) regardless of input origin.

lib/galaxy/tools/actions/__init__.py

@@ -512,11 +512,19 @@ class DefaultToolAction(ToolAction):
 
         if not completed_job:
             # Determine output dataset permission/roles list
+            default_history_permissions = app.security_agent.history_get_default_permissions(history)
             if all_permissions:
                 output_permissions = app.security_agent.guess_derived_permissions(all_permissions)
+                # Ensure history default access restrictions are applied even when
+                # inputs are less restrictive (e.g. public library datasets). The
+                # history defaults reflect the user's intent for output privacy.
+                # See https://github.com/galaxyproject/galaxy/issues/21802
+                access_action = app.security_agent.get_action("access")
+                if access_action in default_history_permissions and access_action not in output_permissions:
+                    output_permissions[access_action] = default_history_permissions[access_action]
             else:
                 # No valid inputs, we will use history defaults
-                output_permissions = app.security_agent.history_get_default_permissions(history)
+                output_permissions = default_history_permissions
 
         # Add the dbkey to the incoming parameters
         incoming["dbkey"] = input_dbkey

test/integration/objectstore/test_private_handling_library_imports.py

@@ -95,13 +95,11 @@ class TestToolOutputFromLibraryImportWithPrivateObjectStore(BaseObjectStoreInteg
             ), f"Library import should retain default store, got {copied_storage['object_store_id']}"
 
             # Make the imported dataset public — simulating a dataset from a public
-            # data library where datasets are accessible to all users. This is the
-            # crux of the bug: the input's access permissions (public) propagate to
-            # tool outputs, which then conflict with the private object store.
+            # data library where datasets are accessible to all users.
             response = self.dataset_populator.make_dataset_public_raw(history_id, copied_hda["id"])
             api_asserts.assert_status_code_is_ok(response)
 
-            # Run a tool on the library-imported dataset — this is the scenario from the bug
+            # Run a tool on the library-imported dataset
             run_response = self.dataset_populator.run_tool(
                 "cat1",
                 inputs={"input1": {"src": "hda", "id": copied_hda["id"]}},
@@ -110,9 +108,6 @@ class TestToolOutputFromLibraryImportWithPrivateObjectStore(BaseObjectStoreInteg
             self.dataset_populator.wait_for_history(history_id)
             job = run_response["jobs"][0]
             job_details = self.dataset_populator.get_job_details(job["id"], full=True).json()
-            # This is the core assertion — the job should succeed, not fail with
-            # "Job attempted to create sharable output datasets in a storage location
-            #  with sharing disabled"
             assert job_details["state"] == "ok", (
                 f"Tool run on library-imported dataset failed with state '{job_details['state']}'. "
                 f"Expected outputs to respect history's private store preference regardless of input origin."