Ray: Remote Code Execution via Parquet Arrow Extension Type Deserialization
Ray Data registers custom Arrow extension types (`ray.data.arrow_tensor`, `ray.data.arrow_tensor_v2`, `ray.data.arrow_variable_shaped_tensor`) globally in PyArrow. When PyArrow reads a Parquet file containing one of these extension types, it calls `__arrow_ext_deserialize__` on the field's metadata bytes. Ray's implementation passes these bytes directly to `cloudpickle.loads()`, achieving arbitrary code execution during schema parsing, before any row data is read.
In May 2024, Ray fixed a related vulnerability in `PyExtensionType`-based extension types (issue #41314
https://github.com/ray-project/ray/issues/41314, PR #45084
https://github.com/ray-project/ray/pull/45084) In July 2025, PR #54831
https://github.com/ray-project/ray/pull/54831 introduced `cloudpickle.loads()` into the replacement extension types' deserialization path, reintroducing the same class of vulnerability.
## Impact
- **Affected versions**: Ray 2.49.0 through 2.54.0 (latest release as of March 2026). The vulnerable `_deserialize_with_fallback` function with `cloudpickle.loads()` was introduced in commit `f6d21db1a4` (PR #54831
https://github.com/ray-project/ray/pull/54831, July 2025), first released in Ray 2.49.0.
- **Affected configurations**: Any process that uses Ray Data and reads Parquet files. The extension types are registered globally in PyArrow, so all Parquet reads in the process are affected, including `ray.data.read_parquet()`, `pyarrow.parquet.read_table()`, `pandas.read_parquet()`, etc.
- **Attacker prerequisites**: The attacker must place a crafted Parquet file where a Ray Data pipeline reads it. No authentication or cluster access is required. The Parquet file must contain a column with a `ray.data.arrow_tensor` (or v2, or variable-shaped) extension type name, which makes this a targeted attack against Ray Data users.