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new d0a63ebd72 [GH-2152] fix: prevent information disclosure through
exception messages in STAC client (#2153)
d0a63ebd72 is described below
commit d0a63ebd72323220f3afdb732270edfd287f9c4f
Author: Feng Zhang <[email protected]>
AuthorDate: Thu Jul 24 17:36:00 2025 -0700
[GH-2152] fix: prevent information disclosure through exception messages in
STAC client (#2153)
---
python/sedona/spark/stac/collection_client.py | 14 +++++++-------
1 file changed, 7 insertions(+), 7 deletions(-)
diff --git a/python/sedona/spark/stac/collection_client.py
b/python/sedona/spark/stac/collection_client.py
index bc020cfdf8..f4f168f1a6 100644
--- a/python/sedona/spark/stac/collection_client.py
+++ b/python/sedona/spark/stac/collection_client.py
@@ -257,9 +257,9 @@ class CollectionClient:
# Return an iterator of the items
return iter(items)
except Exception as e:
- # Log the error and raise a RuntimeError
- logging.error(f"Error getting items: {e}")
- raise RuntimeError("Failed to get items") from e
+ # Log error type without exposing sensitive details
+ logging.error(f"Error getting items: {type(e).__name__}")
+ raise RuntimeError("Failed to get items") from None
def get_dataframe(
self,
@@ -303,8 +303,8 @@ class CollectionClient:
return df
except Exception as e:
- logging.error(f"Error getting filtered dataframe: {e}")
- raise RuntimeError("Failed to get filtered dataframe") from e
+ logging.error(f"Error getting filtered dataframe:
{type(e).__name__}")
+ raise RuntimeError("Failed to get filtered dataframe") from None
def save_to_geoparquet(
self,
@@ -344,8 +344,8 @@ class CollectionClient:
df_geoparquet.write.format("geoparquet").save(output_path)
logging.info(f"DataFrame successfully saved to {output_path}")
except Exception as e:
- logging.error(f"Error saving DataFrame to GeoParquet: {e}")
- raise RuntimeError("Failed to save DataFrame to GeoParquet") from e
+ logging.error(f"Error saving DataFrame to GeoParquet:
{type(e).__name__}")
+ raise RuntimeError("Failed to save DataFrame to GeoParquet") from
None
@staticmethod
def _convert_assets_schema(df: DataFrame) -> DataFrame:
