Vulnerability-Lookup

PYSEC-2026-2288

Vulnerability from pysec - Published: 2026-04-07 06:16 - Updated: 2026-07-13 05:52

Details

A vulnerability in the HuggingFace Transformers library, specifically in the Trainer class, allows for arbitrary code execution. The _load_rng_state() method in src/transformers/trainer.py at line 3059 calls torch.load() without the weights_only=True parameter. This issue affects all versions of the library supporting torch>=2.2 when used with PyTorch versions below 2.6, as the safe_globals() context manager provides no protection in these versions. An attacker can exploit this vulnerability by supplying a malicious checkpoint file, such as rng_state.pth, which can execute arbitrary code when loaded. The issue is resolved in version v5.0.0rc3.

Severity

7.8 (High)


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

Impacted products

Name	purl
transformers	pkg:pypi/transformers

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "ecosystem_specific": {},
      "package": {
        "ecosystem": "PyPI",
        "name": "transformers",
        "purl": "pkg:pypi/transformers"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "5.0.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.1",
        "2.0.0",
        "2.1.0",
        "2.1.1",
        "2.10.0",
        "2.11.0",
        "2.2.0",
        "2.2.1",
        "2.2.2",
        "2.3.0",
        "2.4.0",
        "2.4.1",
        "2.5.0",
        "2.5.1",
        "2.6.0",
        "2.7.0",
        "2.8.0",
        "2.9.0",
        "2.9.1",
        "3.0.0",
        "3.0.1",
        "3.0.2",
        "3.1.0",
        "3.2.0",
        "3.3.0",
        "3.3.1",
        "3.4.0",
        "3.5.0",
        "3.5.1",
        "4.0.0",
        "4.0.0rc1",
        "4.0.1",
        "4.1.0",
        "4.1.1",
        "4.10.0",
        "4.10.1",
        "4.10.2",
        "4.10.3",
        "4.11.0",
        "4.11.1",
        "4.11.2",
        "4.11.3",
        "4.12.0",
        "4.12.1",
        "4.12.2",
        "4.12.3",
        "4.12.4",
        "4.12.5",
        "4.13.0",
        "4.14.0",
        "4.14.1",
        "4.15.0",
        "4.16.0",
        "4.16.1",
        "4.16.2",
        "4.17.0",
        "4.18.0",
        "4.19.0",
        "4.19.1",
        "4.19.2",
        "4.19.3",
        "4.19.4",
        "4.2.0",
        "4.2.1",
        "4.2.2",
        "4.20.0",
        "4.20.1",
        "4.21.0",
        "4.21.1",
        "4.21.2",
        "4.21.3",
        "4.22.0",
        "4.22.1",
        "4.22.2",
        "4.23.0",
        "4.23.1",
        "4.24.0",
        "4.25.0",
        "4.25.1",
        "4.26.0",
        "4.26.1",
        "4.27.0",
        "4.27.1",
        "4.27.2",
        "4.27.3",
        "4.27.4",
        "4.28.0",
        "4.28.1",
        "4.29.0",
        "4.29.1",
        "4.29.2",
        "4.3.0",
        "4.3.0rc1",
        "4.3.1",
        "4.3.2",
        "4.3.3",
        "4.30.0",
        "4.30.1",
        "4.30.2",
        "4.31.0",
        "4.32.0",
        "4.32.1",
        "4.33.0",
        "4.33.1",
        "4.33.2",
        "4.33.3",
        "4.34.0",
        "4.34.1",
        "4.35.0",
        "4.35.1",
        "4.35.2",
        "4.36.0",
        "4.36.1",
        "4.36.2",
        "4.37.0",
        "4.37.1",
        "4.37.2",
        "4.38.0",
        "4.38.1",
        "4.38.2",
        "4.39.0",
        "4.39.1",
        "4.39.2",
        "4.39.3",
        "4.4.0",
        "4.4.1",
        "4.4.2",
        "4.40.0",
        "4.40.1",
        "4.40.2",
        "4.41.0",
        "4.41.1",
        "4.41.2",
        "4.42.0",
        "4.42.1",
        "4.42.2",
        "4.42.3",
        "4.42.4",
        "4.43.0",
        "4.43.1",
        "4.43.2",
        "4.43.3",
        "4.43.4",
        "4.44.0",
        "4.44.1",
        "4.44.2",
        "4.45.0",
        "4.45.1",
        "4.45.2",
        "4.46.0",
        "4.46.1",
        "4.46.2",
        "4.46.3",
        "4.47.0",
        "4.47.1",
        "4.48.0",
        "4.48.1",
        "4.48.2",
        "4.48.3",
        "4.49.0",
        "4.5.0",
        "4.5.1",
        "4.50.0",
        "4.50.1",
        "4.50.2",
        "4.50.3",
        "4.51.0",
        "4.51.1",
        "4.51.2",
        "4.51.3",
        "4.52.0",
        "4.52.1",
        "4.52.2",
        "4.52.3",
        "4.52.4",
        "4.53.0",
        "4.53.1",
        "4.53.2",
        "4.53.3",
        "4.54.0",
        "4.54.1",
        "4.55.0",
        "4.55.1",
        "4.55.2",
        "4.55.3",
        "4.55.4",
        "4.56.0",
        "4.56.1",
        "4.56.2",
        "4.57.0",
        "4.57.1",
        "4.57.2",
        "4.57.3",
        "4.57.4",
        "4.57.5",
        "4.57.6",
        "4.6.0",
        "4.6.1",
        "4.7.0",
        "4.8.0",
        "4.8.1",
        "4.8.2",
        "4.9.0",
        "4.9.1",
        "4.9.2",
        "5.0.0rc0",
        "5.0.0rc1",
        "5.0.0rc2",
        "5.0.0rc3"
      ]
    }
  ],
  "aliases": [
    "CVE-2026-1839",
    "GHSA-69w3-r845-3855"
  ],
  "details": "A vulnerability in the HuggingFace Transformers library, specifically in the `Trainer` class, allows for arbitrary code execution. The `_load_rng_state()` method in `src/transformers/trainer.py` at line 3059 calls `torch.load()` without the `weights_only=True` parameter. This issue affects all versions of the library supporting `torch\u003e=2.2` when used with PyTorch versions below 2.6, as the `safe_globals()` context manager provides no protection in these versions. An attacker can exploit this vulnerability by supplying a malicious checkpoint file, such as `rng_state.pth`, which can execute arbitrary code when loaded. The issue is resolved in version v5.0.0rc3.",
  "id": "PYSEC-2026-2288",
  "modified": "2026-07-13T05:52:14.613148Z",
  "published": "2026-04-07T06:16:41.490Z",
  "references": [
    {
      "type": "FIX",
      "url": "https://github.com/huggingface/transformers/commit/03c8082ba4594c9b8d6fe190ca9bed0e5f8ca396"
    },
    {
      "type": "EVIDENCE",
      "url": "https://huntr.com/bounties/3c77bb97-e493-493d-9a88-c57f5c536485"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-69w3-r845-3855"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

CVE-2026-1839 (GCVE-0-2026-1839)

Vulnerability from cvelistv5 – Published: 2026-04-07 05:22 – Updated: 2026-04-07 13:27

Title

Arbitrary Code Execution via Unsafe torch.load() in Trainer Checkpoint Loading in huggingface/transformers

Summary

A vulnerability in the HuggingFace Transformers library, specifically in the `Trainer` class, allows for arbitrary code execution. The `_load_rng_state()` method in `src/transformers/trainer.py` at line 3059 calls `torch.load()` without the `weights_only=True` parameter. This issue affects all versions of the library supporting `torch>=2.2` when used with PyTorch versions below 2.6, as the `safe_globals()` context manager provides no protection in these versions. An attacker can exploit this vulnerability by supplying a malicious checkpoint file, such as `rng_state.pth`, which can execute arbitrary code when loaded. The issue is resolved in version v5.0.0rc3.

Severity

6.5 (Medium)


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

SSVC

Exploitation: poc Automatable: no Technical Impact: total

CISA Coordinator (v2.0.3)

CWE

CWE-502 - Deserialization of Untrusted Data

Assigner

@huntr_ai

References

2 references

URL	Tags
https://huntr.com/bounties/3c77bb97-e493-493d-9a8…
https://github.com/huggingface/transformers/commi…

Impacted products

1 product

Vendor	Product	Version
huggingface	huggingface/transformers	Affected: unspecified , < v5.0.0rc3 (custom)

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2026-1839",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "total"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2026-04-07T13:27:38.099805Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2026-04-07T13:27:41.789Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "references": [
          {
            "tags": [
              "exploit"
            ],
            "url": "https://huntr.com/bounties/3c77bb97-e493-493d-9a88-c57f5c536485"
          }
        ],
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "huggingface/transformers",
          "vendor": "huggingface",
          "versions": [
            {
              "lessThan": "v5.0.0rc3",
              "status": "affected",
              "version": "unspecified",
              "versionType": "custom"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "A vulnerability in the HuggingFace Transformers library, specifically in the `Trainer` class, allows for arbitrary code execution. The `_load_rng_state()` method in `src/transformers/trainer.py` at line 3059 calls `torch.load()` without the `weights_only=True` parameter. This issue affects all versions of the library supporting `torch\u003e=2.2` when used with PyTorch versions below 2.6, as the `safe_globals()` context manager provides no protection in these versions. An attacker can exploit this vulnerability by supplying a malicious checkpoint file, such as `rng_state.pth`, which can execute arbitrary code when loaded. The issue is resolved in version v5.0.0rc3."
        }
      ],
      "metrics": [
        {
          "cvssV3_0": {
            "attackComplexity": "HIGH",
            "attackVector": "LOCAL",
            "availabilityImpact": "HIGH",
            "baseScore": 6.5,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "LOW",
            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
            "userInteraction": "REQUIRED",
            "vectorString": "CVSS:3.0/AV:L/AC:H/PR:N/UI:R/S:U/C:H/I:L/A:H",
            "version": "3.0"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-502",
              "description": "CWE-502 Deserialization of Untrusted Data",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2026-04-07T05:22:00.959Z",
        "orgId": "c09c270a-b464-47c1-9133-acb35b22c19a",
        "shortName": "@huntr_ai"
      },
      "references": [
        {
          "url": "https://huntr.com/bounties/3c77bb97-e493-493d-9a88-c57f5c536485"
        },
        {
          "url": "https://github.com/huggingface/transformers/commit/03c8082ba4594c9b8d6fe190ca9bed0e5f8ca396"
        }
      ],
      "source": {
        "advisory": "3c77bb97-e493-493d-9a88-c57f5c536485",
        "discovery": "EXTERNAL"
      },
      "title": "Arbitrary Code Execution via Unsafe torch.load() in Trainer Checkpoint Loading in huggingface/transformers"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "c09c270a-b464-47c1-9133-acb35b22c19a",
    "assignerShortName": "@huntr_ai",
    "cveId": "CVE-2026-1839",
    "datePublished": "2026-04-07T05:22:00.959Z",
    "dateReserved": "2026-02-03T16:49:27.781Z",
    "dateUpdated": "2026-04-07T13:27:41.789Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.2"
}

GHSA-69W3-R845-3855

Vulnerability from github – Published: 2026-04-07 06:30 – Updated: 2026-04-08 00:17

Summary

HuggingFace Transformers allows for arbitrary code execution in the `Trainer` class

Details

Severity

6.5 (Medium)


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

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "transformers"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "5.0.0rc3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-1839"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-04-08T00:17:56Z",
    "nvd_published_at": "2026-04-07T06:16:41Z",
    "severity": "MODERATE"
  },
  "details": "A vulnerability in the HuggingFace Transformers library, specifically in the `Trainer` class, allows for arbitrary code execution. The `_load_rng_state()` method in `src/transformers/trainer.py` at line 3059 calls `torch.load()` without the `weights_only=True` parameter. This issue affects all versions of the library supporting `torch\u003e=2.2` when used with PyTorch versions below 2.6, as the `safe_globals()` context manager provides no protection in these versions. An attacker can exploit this vulnerability by supplying a malicious checkpoint file, such as `rng_state.pth`, which can execute arbitrary code when loaded. The issue is resolved in version v5.0.0rc3.",
  "id": "GHSA-69w3-r845-3855",
  "modified": "2026-04-08T00:17:56Z",
  "published": "2026-04-07T06:30:28Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-1839"
    },
    {
      "type": "WEB",
      "url": "https://github.com/huggingface/transformers/commit/03c8082ba4594c9b8d6fe190ca9bed0e5f8ca396"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/huggingface/transformers"
    },
    {
      "type": "WEB",
      "url": "https://github.com/huggingface/transformers/releases/tag/v5.0.0rc3"
    },
    {
      "type": "WEB",
      "url": "https://huntr.com/bounties/3c77bb97-e493-493d-9a88-c57f5c536485"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:L/AC:H/PR:N/UI:R/S:U/C:H/I:L/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "HuggingFace Transformers allows for arbitrary code execution in the `Trainer` class"
}

Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Detection rules are retrieved from Rulezet.

Action not permitted

PYSEC-2026-2288

CVE-2026-1839 (GCVE-0-2026-1839)

GHSA-69W3-R845-3855

Tags

Sightings

Nomenclature