pyarrow known bugs

While investigating UBSAN errors in https://github.com/apache/arrow/pull/5365 it was discovered Apache Arrow versions 0.12.0 to 0.14.1, left memory Array data uninitialized when reading RLE null data from parquet. This affected the C++, Python, Ruby and R implementations. The uninitialized memory could potentially be shared if are transmitted over the wire (for instance with Flight) or persisted in the streaming IPC and file formats.

It was discovered that the C++ implementation (which underlies the R, Python and Ruby implementations) of Apache Arrow 0.14.0 to 0.14.1 had a uninitialized memory bug when building arrays with null values in some cases. This can lead to uninitialized memory being unintentionally shared if Arrow Arrays are transmitted over the wire (for instance with Flight) or persisted in the streaming IPC and file formats.

Deserialization of untrusted data in IPC and Parquet readers in the Apache Arrow R package versions 4.0.0 through 16.1.0 allows arbitrary code execution. An application is vulnerable if it reads Arrow IPC, Feather or Parquet data from untrusted sources (for example, user-supplied input files). This vulnerability only affects the arrow R package, not other Apache Arrow implementations or bindings unless those bindings are specifically used via the R package (for example, an R application that embeds a Python interpreter and uses PyArrow to read files from untrusted sources is still vulnerable if the arrow R package is an affected version). It is recommended that users of the arrow R package upgrade to 17.0.0 or later. Similarly, it is recommended that downstream libraries upgrade their dependency requirements to arrow 17.0.0 or later. If using an affected version of the package, untrusted data can read into a Table and its internal to_data_frame() method can be used as a workaround (e.g., read_parquet(..., as_data_frame = FALSE)$to_data_frame()). This issue affects the Apache Arrow R package: from 4.0.0 through 16.1.0. Users are recommended to upgrade to version 17.0.0, which fixes the issue.

Deserialization of untrusted data in IPC and Parquet readers in PyArrow versions 0.14.0 to 14.0.0 allows arbitrary code execution. An application is vulnerable if it reads Arrow IPC, Feather or Parquet data from untrusted sources (for example user-supplied input files).

While investigating UBSAN errors in https://github.com/apache/arrow/pull/5365 it was discovered Apache Arrow versions 0.12.0 to 0.14.1, left memory Array data uninitialized when reading RLE null data from parquet. This affected the C++, Python, Ruby and R implementations. The uninitialized memory could potentially be shared if are transmitted over the wire (for instance with Flight) or persisted in the streaming IPC and file formats.

It was discovered that the C++ implementation (which underlies the R, Python and Ruby implementations) of Apache Arrow 0.14.0 to 0.14.1 had a uninitialized memory bug when building arrays with null values in some cases. This can lead to uninitialized memory being unintentionally shared if Arrow Arrays are transmitted over the wire (for instance with Flight) or persisted in the streaming IPC and file formats.

Deserialization of untrusted data in IPC and Parquet readers in PyArrow versions 0.14.0 to 14.0.0 allows arbitrary code execution. An application is vulnerable if it reads Arrow IPC, Feather or Parquet data from untrusted sources (for example user-supplied input files). This vulnerability only affects PyArrow, not other Apache Arrow implementations or bindings. It is recommended that users of PyArrow upgrade to 14.0.1. Similarly, it is recommended that downstream libraries upgrade their dependency requirements to PyArrow 14.0.1 or later. PyPI packages are already available, and we hope that conda-forge packages will be available soon. If it is not possible to upgrade, maintainers provide a separate package `pyarrow-hotfix` that disables the vulnerability on older PyArrow versions. See https://pypi.org/project/pyarrow-hotfix/ for instructions.