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Medium

Regular Expression Denial of Service (ReDoS) in huggingface/transformers

Type: advisorySources: OSV

A Regular Expression Denial of Service (ReDoS) vulnerability exists in the Hugging Face Transformers library, specifically in the `convert_tf_weight_name_to_pt_weight_name()` function. This function, responsible for converting TensorFlow weight names to PyTorch format, uses a regex pattern `/[^/]*___([^/]*)/` that can be exploited to cause excessive CPU consumption through crafted input strings due to catastrophic backtracking. The vulnerability affects versions up to 4.51.3 and is fixed in version 4.53.0. This issue can lead to service disruption, resource exhaustion, and potential API service vulnerabilities, impacting model conversion processes between TensorFlow and PyTorch formats.

Products
Not specified
Affected versions
Not specified
Fixed versions
Not specified
CVEs
CVE-2025-5197
Confirmed fixed CVEs
Not specified
Updated in this feed
4 Nov 2026, 15:31 UTC · Revision 1

Source evidence

Regular Expression Denial of Service (ReDoS) in huggingface/transformers

core-osv · Original source

Published 6 Aug 2025, 11:53 UTC

A Regular Expression Denial of Service (ReDoS) vulnerability exists in the Hugging Face Transformers library, specifically in the `convert_tf_weight_name_to_pt_weight_name()` function. This function, responsible for converting TensorFlow weight names to PyTorch format, uses a regex pattern `/[^/]*___([^/]*)/` that can be exploited to cause excessive CPU consumption through crafted input strings due to catastrophic backtracking. The vulnerability affects versions up to 4.51.3 and is fixed in version 4.53.0. This issue can lead to service disruption, resource exhaustion, and potential API service vulnerabilities, impacting model conversion processes between TensorFlow and PyTorch formats.

osv:CVE-2025-5197
Complete source record
{
  "id": "f56a96aed639105b8c9b293155c863511e8841a82d32993ddcd0537cae4219d9",
  "url": "https://osv.dev/vulnerability/CVE-2025-5197",
  "method": "structured",
  "payload": {
    "kind": "advisory",
    "title": "Regular Expression Denial of Service (ReDoS) in huggingface/transformers",
    "summary": "A Regular Expression Denial of Service (ReDoS) vulnerability exists in the Hugging Face Transformers library, specifically in the `convert_tf_weight_name_to_pt_weight_name()` function. This function, responsible for converting TensorFlow weight names to PyTorch format, uses a regex pattern `/[^/]*___([^/]*)/` that can be exploited to cause excessive CPU consumption through crafted input strings due to catastrophic backtracking. The vulnerability affects versions up to 4.51.3 and is fixed in version 4.53.0. This issue can lead to service disruption, resource exhaustion, and potential API service vulnerabilities, impacting model conversion processes between TensorFlow and PyTorch formats.",
    "evidence": "osv:CVE-2025-5197",
    "products": [],
    "severity": "medium",
    "structured": {
      "id": "CVE-2025-5197",
      "aliases": [
        "CVE-2025-5197",
        "GHSA-9356-575x-2w9m",
        "PYSEC-2026-1983"
      ],
      "metrics": [
        {
          "type": "CVSS_V3",
          "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L"
        }
      ],
      "affected": [
        {
          "ranges": [
            {
              "repo": "https://github.com/huggingface/transformers",
              "type": "GIT",
              "events": [
                {
                  "introduced": "0"
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                {
                  "fixed": "67ddc82fbc7e52c6f42a395b4a6d278c55b77a39"
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                {
                  "fixed": "944b56000be5e9b61af8301aa340838770ad8a0b"
                }
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              "database_specific": {
                "extracted_events": [
                  {
                    "cpe": "cpe:2.3:a:huggingface:transformers:*:*:*:*:*:*:*:*",
                    "range": [
                      {
                        "introduced": "0"
                      },
                      {
                        "fixed": "4.53.0"
                      }
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                    "source": "CPE_RANGE"
                  },
                  {
                    "range": [
                      {
                        "fixed": "944b56000be5e9b61af8301aa340838770ad8a0b"
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                    "source": "REFERENCES_COMMIT"
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          "versions": [
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            "v4.49.0-Mistral-3",
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            "v3.1.0",
            "v3.0.2",
            "v3.0.1",
            "3.0.1",
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            "v0.2.0",
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          ],
          "database_specific": {
            "source": "https://storage.googleapis.com/cve-osv-conversion/osv-output/CVE-2025-5197.json"
          }
        }
      ],
      "modified": "2026-10-28T02:30:36.906294794Z",
      "provider": "osv",
      "references": [
        "https://huntr.com/bounties/3f8b3fd0-166b-46e7-b60f-60dd9d2678bf",
        "https://github.com/CVEProject/cvelistV5/tree/main/cves/2025/5xxx/CVE-2025-5197.json",
        "https://nvd.nist.gov/vuln/detail/CVE-2025-5197",
        "https://github.com/huggingface/transformers/commit/944b56000be5e9b61af8301aa340838770ad8a0b"
      ],
      "provider_metadata": {
        "cwe_ids": [
          "CWE-1333"
        ],
        "cna_assigner": "@huntr_ai",
        "osv_generated_from": "https://github.com/CVEProject/cvelistV5/tree/main/cves/2025/5xxx/CVE-2025-5197.json"
      }
    },
    "related_cves": [
      {
        "value": "CVE-2025-5197",
        "evidence": "/id"
      }
    ],
    "security_relevant": true,
    "severity_evidence": "/severity/0/score"
  },
  "source_id": "core-osv",
  "document_id": 504153,
  "published_at": "2025-08-06T11:53:37.232+00:00"
}