rusackas commented on code in PR #44406:
URL: https://github.com/apache/superset/pull/44406#discussion_r4045402367


##########
superset/common/query_context_processor.py:
##########
@@ -445,31 +464,144 @@ def query_cache_key(self, query_obj: QueryObject, 
**kwargs: Any) -> str | None:
         )
         return cache_key
 
-    def _annotation_cache_context(self, query_obj: QueryObject) -> dict[str, 
Any]:
+    def annotation_cache_key(self, query_obj: QueryObject) -> str | None:
+        """
+        Cache key for this query's annotation-layer payload, or ``None`` when
+        the query has no annotation layers.
+
+        Annotation payloads are fetched under the requesting user's access
+        scope, which is a stricter security requirement than the dataframe
+        itself has. Keying them separately from :meth:`query_cache_key` keeps
+        that scoping from forcing every distinct viewer of an annotated chart
+        onto their own full copy of the (potentially much larger) shared
+        dataframe: users with the same access scope share this key too.
         """
-        Cache-key material binding cached annotation data to its security
-        context.
+        if not query_obj or not query_obj.annotation_layers:
+            return None
+        return self.query_cache_key(
+            query_obj, 
annotation_context=self._annotation_cache_context(query_obj)
+        )
 
-        Annotation payloads are fetched per requesting user and stored on the
-        same cache entry as the dataframe, so the key also binds the requesting
-        user and, for chart-backed layers, the RLS clauses of the referenced
-        chart's datasource.
+    def _annotation_cache_context(self, query_obj: QueryObject) -> dict[str, 
Any]:
+        """
+        Cache-key material binding annotation data to its security *scope* so
+        users with the same access share a cache entry and users with a
+        different scope — or no access — never read each other's data.
+
+        * NATIVE layers: the ``can_read`` permission on ``Annotation``, the
+          only user-dependent dimension of these global records.
+        * Chart-backed (``line``/``table``) layers: see
+          :meth:`_annotation_source_scope`.
         """
-        source_rls: dict[str, list[str] | None] = {}
+        context: dict[str, Any] = {}
+
+        if any(
+            layer.get("sourceType") == "NATIVE" for layer in 
query_obj.annotation_layers
+        ):
+            context["annotation_read"] = security_manager.can_access(
+                "can_read", "Annotation"
+            )
+
+        source_scope: dict[str, Any] = {}
         for layer in query_obj.annotation_layers:
             if layer.get("sourceType") not in ("line", "table"):
                 continue
             layer_value = layer.get("value")
-            chart = (
-                ChartDAO.find_by_id(layer_value) if layer_value is not None 
else None
+            source_scope[str(layer_value)] = 
self._annotation_source_scope(layer_value)
+        if source_scope:
+            context["source_scope"] = source_scope
+
+        return context
+
+    def _annotation_source_scope(self, layer_value: Any) -> dict[str, Any]:
+        """
+        Access and data-identity cache-key material for one chart-backed
+        annotation layer.
+
+        ``access`` keeps a user denied the referenced chart's datasource from
+        reading an authorized user's cached payload. ``data_key`` is the
+        annotation chart's own query cache key(s), which already capture the
+        datasource version, RLS clauses, and any per-user Jinja/virtual-dataset
+        RLS material — reusing it here avoids re-deriving that logic and
+        automatically inherits any future correctness fixes made there.
+        """
+        chart = ChartDAO.find_by_id(layer_value) if layer_value is not None 
else None
+        datasource = chart.datasource if chart else None
+        if chart is None or datasource is None:
+            return {"access": None, "data_key": None}
+
+        try:
+            access = security_manager.can_access_datasource(datasource)
+            # Fall back to the RLS-clause identity when the chart has no saved
+            # query context to key on.
+            annotation_query_context = chart.get_query_context()
+            data_key: Any = (
+                [
+                    annotation_query_context.query_cache_key(query_object)
+                    for query_object in annotation_query_context.queries
+                ]
+                if annotation_query_context is not None
+                else security_manager.get_rls_cache_key(datasource)
+            )
+        except SupersetException:

Review Comment:
   Good catch, widened it to a bare except. Also found the fallback re-calls 
get_rls_cache_key, so if that's what failed in the first place it'd re-raise 
right out of the except block too. Wrapped that as well.



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