CVE-2025-2099: Transformers Denial of Service Vulnerability

MODERATE
Advisory Identifier: GHSA-qq3j-4f4f-9583
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CVSS 5.3
CWE-1333
Published
Advisory Summary

CVE-2025-2099 is a MODERATE (CVSS 5.3) denial of service vulnerability (CWE-1333: Inefficient Regular Expression Complexity) affecting Transformers libraries in the PyPI ecosystem. The issue involves hugging face transformers regular expression denial of service. Remediation is available by upgrading affected packages to version 4.50.0.

CVE-2025-2099 at a Glance

CVE Identifier CVE-2025-2099
GHSA Identifier GHSA-qq3j-4f4f-9583
Severity MODERATE
CVSS v3.1 Base Score 5.3
CWE Classification CWE-1333: Inefficient Regular Expression Complexity
Affected Product Transformers
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 5.3

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L).

Attack Vector Network (AV:N)
Attack Complexity Low (AC:L)
Privileges Required None (PR:N)
User Interaction None (UI:N)
Scope Unchanged (S:U)
Confidentiality None (C:N)
Integrity None (I:N)
Availability Low (A:L)

How to Fix CVE-2025-2099

To remediate this vulnerability, upgrade all affected Transformers dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

transformers fixed: 4.50.0 
pip install transformers>=4.50.0
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release: 

pip show transformers

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2025-2099, inspect your installed packages using pip:

pip show transformers

Analyze the terminal output to locate any version of Transformers in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 4.50.0), your application is affected.

Note: The pip show transformers command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-1333: Inefficient Regular Expression Complexity, where the product uses a regular expression with a worst-case computational complexity that is inefficient and possibly exponential. In Transformers, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

A Regular Expression Denial of Service (ReDoS) exists in the `preprocess_string()` function of the `transformers.testing_utils` module. In versions **before 4.50.0**, the regex used to process code blocks in docstrings contains nested quantifiers that can trigger catastrophic backtracking when given inputs with many newline characters. An attacker who can supply such input to `preprocess_string()` (or code paths that call it) can force excessive CPU usage and degrade availability. **Fix:** released in **4.50.0**, which rewrites the regex to avoid the inefficient pattern. ([GitHub][1]) * **Affected:** `< 4.50.0` * **Patched:** `4.50.0`

CVE-2025-2099 Affected Transformers Versions

1 component(s)
Fixed Versions:
4.50.0
Product / Package Ecosystem Affected Versions Fixed Version
transformers
pypi/transformers
PyPI
< 4.50.0
4.50.0

References

NVD — CVE-2025-2099 NVD
https://nvd.nist.gov/vuln/detail/CVE-2025-2099
Transformers Source Repository REPOSITORY
https://github.com/huggingface/transformers/pull/36648
Security Fix Commit FIX COMMIT
https://github.com/huggingface/transformers/commit/8cb522b4190bd556ce51be04942720650b1a3e57
Transformers Source Repository REPOSITORY
https://github.com/huggingface/transformers
Transformers Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/transformers/PYSEC-2025-40.yaml
huntr.com/bounties/97b780f3-f... WEB
https://huntr.com/bounties/97b780f3-ffca-424f-ad5d-0e1c57a5bde4

Frequently Asked Questions

What is CVE-2025-2099?
CVE-2025-2099 is a security vulnerability in Transformers involving Hugging Face Transformers Regular Expression Denial of Service under CWE-1333: Inefficient Regular Expression Complexity.
Which Transformers versions are affected?
Affected versions include releases prior to 4.50.0 across affected packages: transformers.
What version fixes CVE-2025-2099?
Upgrading to 4.50.0 (or the latest patched release for your respective branch) resolves the vulnerability.
Is transformers affected?
Yes, transformers is affected in releases prior to 4.50.0. Upgrade your dependency to 4.50.0 or later.
What is the CVSS score of CVE-2025-2099?
CVE-2025-2099 has a CVSS v3.1 base score of 5.3 (MODERATE) with vector string CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L.
What CWE is associated with CVE-2025-2099?
CVE-2025-2099 is classified under CWE-1333: Inefficient Regular Expression Complexity (The product uses a regular expression with a worst-case computational complexity that is inefficient and possibly exponential.).
How can I check PyPI dependencies for CVE-2025-2099?
Run the dependency tree command: 'pip show transformers'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
View Raw JSON 
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-qq3j-4f4f-9583",
  "modified" : "2025-09-25T21:06:38Z",
  "published" : "2025-05-19T12:30:33Z",
  "aliases" : [ "CVE-2025-2099" ],
  "summary" : "Hugging Face Transformers Regular Expression Denial of Service",
  "details" : "A Regular Expression Denial of Service (ReDoS) exists in the `preprocess_string()` function of the `transformers.testing_utils` module. In versions **before 4.50.0**, the regex used to process code blocks in docstrings contains nested quantifiers that can trigger catastrophic backtracking when given inputs with many newline characters. An attacker who can supply such input to `preprocess_string()` (or code paths that call it) can force excessive CPU usage and degrade availability.\n\n**Fix:** released in **4.50.0**, which rewrites the regex to avoid the inefficient pattern. ([GitHub][1])\n\n*   **Affected:** `< 4.50.0`\n*   **Patched:** `4.50.0`",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "transformers"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "4.50.0"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2025-2099"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/huggingface/transformers/pull/36648"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/huggingface/transformers/commit/8cb522b4190bd556ce51be04942720650b1a3e57"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/huggingface/transformers"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/transformers/PYSEC-2025-40.yaml"
  }, {
    "type" : "WEB",
    "url" : "https://huntr.com/bounties/97b780f3-ffca-424f-ad5d-0e1c57a5bde4"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-1333" ],
    "severity" : "MODERATE",
    "github_reviewed" : true,
    "github_reviewed_at" : "2025-05-19T21:53:36Z",
    "nvd_published_at" : "2025-05-19T12:15:19Z"
  }
}