rusackas commented on code in PR #44406:
URL: https://github.com/apache/superset/pull/44406#discussion_r4216846589
##########
superset/common/query_context_processor.py:
##########
@@ -449,34 +481,189 @@ 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 ANNOTATION_SOURCE_TYPES_WITH_CHART_REFERENCE
):
continue
layer_value = layer.get("value")
+ source_scope[str(layer_value)] =
self._annotation_source_scope(layer)
Review Comment:
Good catch @sadpandajoe, the scope is now recorded per layer rather than per
chart ID, so two layers on the same chart with different overrides each keep
their own entry in the key. Added a test for exactly that pair.
##########
superset/common/query_context_processor.py:
##########
@@ -449,34 +481,189 @@ 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 ANNOTATION_SOURCE_TYPES_WITH_CHART_REFERENCE
):
continue
layer_value = layer.get("value")
+ source_scope[str(layer_value)] =
self._annotation_source_scope(layer)
+ if source_scope:
+ context["source_scope"] = source_scope
+
+ return context
+
+ def _annotation_source_scope(self, layer: dict[str, 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. When the chart has a
+ saved query context, this runs the *same* authorization path
+ :meth:`get_viz_annotation_data` executes
+ (``QueryContext.raise_for_access``) rather than the coarser
+ :meth:`SecurityManager.can_access_datasource` — a requester whose
+ access comes from a dashboard/viewer-promiscuous-mode bypass (which
+ depends on the chart's own saved ``form_data``, e.g. its
+ ``slice_id``/``dashboardId``) would otherwise still fail that coarser,
+ context-free check and collapse onto the same denied scope as a
+ genuinely unauthorized requester, letting the latter read the
+ former's cached payload. ``data_key`` is the annotation chart's own
+ query cache key(s) — derived from the same, override-applied query
+ objects actually executed (see :meth:`_apply_annotation_overrides`),
+ so it captures the datasource version, RLS clauses, and any per-user
+ Jinja/virtual-dataset RLS material exactly as the live fetch would,
+ including material an override only introduces at a finer grain.
+ Reusing this logic avoids re-deriving it and automatically inherits
+ any future correctness fixes made there.
+ """
+ layer_value = layer.get("value")
+ datasource = None
+ try:
chart = (
ChartDAO.find_by_id(layer_value) if layer_value is not None
else None
)
- annotation_datasource = chart.datasource if chart else None
- source_rls[str(layer.get("value"))] = (
- security_manager.get_rls_cache_key(annotation_datasource)
- if annotation_datasource
- else None
+ # resolved_datasource, not datasource: the latter is pinned to
+ # table-backed datasources and resolves to None for a
+ # semantic-view-backed chart, which would otherwise collapse
+ # every requester onto the same {access: None, data_key: None}
+ # scope below regardless of their actual access.
+ datasource = chart.resolved_datasource if chart else None
+ if chart is None or datasource is None:
+ return {"access": None, "data_key": None}
Review Comment:
Agreed @sadpandajoe, an unresolved scope is now a no-cache signal rather
than a placeholder key: the payload gets fetched live and never written. The
cleared-datasource case also goes through the saved query context's own
`raise_for_access` now, same as the live fetch, so allowed and denied viewers
no longer land on the same key.
##########
superset/common/query_context_processor.py:
##########
@@ -449,34 +481,189 @@ 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 ANNOTATION_SOURCE_TYPES_WITH_CHART_REFERENCE
):
continue
layer_value = layer.get("value")
+ source_scope[str(layer_value)] =
self._annotation_source_scope(layer)
+ if source_scope:
+ context["source_scope"] = source_scope
+
+ return context
+
+ def _annotation_source_scope(self, layer: dict[str, 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. When the chart has a
+ saved query context, this runs the *same* authorization path
+ :meth:`get_viz_annotation_data` executes
+ (``QueryContext.raise_for_access``) rather than the coarser
+ :meth:`SecurityManager.can_access_datasource` — a requester whose
+ access comes from a dashboard/viewer-promiscuous-mode bypass (which
+ depends on the chart's own saved ``form_data``, e.g. its
+ ``slice_id``/``dashboardId``) would otherwise still fail that coarser,
+ context-free check and collapse onto the same denied scope as a
+ genuinely unauthorized requester, letting the latter read the
+ former's cached payload. ``data_key`` is the annotation chart's own
+ query cache key(s) — derived from the same, override-applied query
+ objects actually executed (see :meth:`_apply_annotation_overrides`),
+ so it captures the datasource version, RLS clauses, and any per-user
+ Jinja/virtual-dataset RLS material exactly as the live fetch would,
+ including material an override only introduces at a finer grain.
+ Reusing this logic avoids re-deriving it and automatically inherits
+ any future correctness fixes made there.
+ """
+ layer_value = layer.get("value")
+ datasource = None
+ try:
chart = (
ChartDAO.find_by_id(layer_value) if layer_value is not None
else None
)
- annotation_datasource = chart.datasource if chart else None
- source_rls[str(layer.get("value"))] = (
- security_manager.get_rls_cache_key(annotation_datasource)
- if annotation_datasource
- else None
+ # resolved_datasource, not datasource: the latter is pinned to
+ # table-backed datasources and resolves to None for a
+ # semantic-view-backed chart, which would otherwise collapse
+ # every requester onto the same {access: None, data_key: None}
+ # scope below regardless of their actual access.
+ datasource = chart.resolved_datasource if chart else None
+ if chart is None or datasource is None:
+ return {"access": None, "data_key": None}
+
+ annotation_query_context = chart.get_query_context()
+ if annotation_query_context is not None:
+ self._apply_annotation_overrides(annotation_query_context,
layer)
+ try:
+ annotation_query_context.raise_for_access()
+ access: Any = True
+ except SupersetSecurityException:
+ access = False
+ data_key: Any = [
Review Comment:
Good call @sadpandajoe. The override now sets `time_range` on the query
objects too, so `cache_key` keys on the logical range and drops the resolved
bounds, same as a saved range would. Added an assertion for it in the overrides
test.
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