FKIE_CVE-2025-3262
Vulnerability from fkie_nvd - Published: 2025-07-07 10:15 - Updated: 2026-06-17 09:19
Severity
Summary
A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the huggingface/transformers repository, specifically in version 4.49.0. The vulnerability is due to inefficient regular expression complexity in the `SETTING_RE` variable within the `transformers/commands/chat.py` file. The regex contains repetition groups and non-optimized quantifiers, leading to exponential backtracking when processing 'almost matching' payloads. This can degrade application performance and potentially result in a denial-of-service (DoS) when handling specially crafted input strings. The issue is fixed in version 4.51.0.
References
| URL | Tags | ||
|---|---|---|---|
| security@huntr.dev | https://github.com/huggingface/transformers/commit/0720e206c6ba28887e4d60ef60a6a089f6c1cc76 | Patch | |
| security@huntr.dev | https://huntr.com/bounties/ecf5ccc4-39e7-4fb3-b547-14a41d31a184 | Exploit, Third Party Advisory | |
| 134c704f-9b21-4f2e-91b3-4a467353bcc0 | https://huntr.com/bounties/ecf5ccc4-39e7-4fb3-b547-14a41d31a184 | Exploit, Third Party Advisory |
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| huggingface | transformers | * |
{
"affected": [
{
"affectedData": [
{
"product": "huggingface/transformers",
"vendor": "huggingface",
"versions": [
{
"lessThan": "4.51.0",
"status": "affected",
"version": "unspecified",
"versionType": "custom"
}
]
}
],
"source": "security@huntr.dev"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:huggingface:transformers:*:*:*:*:*:*:*:*",
"matchCriteriaId": "EE8F40B9-E52D-4DD7-9E09-EADE25B7788C",
"versionEndExcluding": "4.51.0",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the huggingface/transformers repository, specifically in version 4.49.0. The vulnerability is due to inefficient regular expression complexity in the `SETTING_RE` variable within the `transformers/commands/chat.py` file. The regex contains repetition groups and non-optimized quantifiers, leading to exponential backtracking when processing \u0027almost matching\u0027 payloads. This can degrade application performance and potentially result in a denial-of-service (DoS) when handling specially crafted input strings. The issue is fixed in version 4.51.0."
},
{
"lang": "es",
"value": "Se descubri\u00f3 una vulnerabilidad de denegaci\u00f3n de servicio por expresi\u00f3n regular (ReDoS) en el repositorio huggingface/transformers, concretamente en la versi\u00f3n 4.49.0. La vulnerabilidad se debe a la complejidad ineficiente de la expresi\u00f3n regular en la variable `SETTING_RE` del archivo `transformers/commands/chat.py`. La expresi\u00f3n regular contiene grupos de repetici\u00f3n y cuantificadores no optimizados, lo que provoca un retroceso exponencial al procesar payloads casi coincidentes. Esto puede reducir el rendimiento de la aplicaci\u00f3n y potencialmente provocar una denegaci\u00f3n de servicio (DoS) al procesar cadenas de entrada especialmente manipuladas. El problema se ha corregido en la versi\u00f3n 4.51.0."
}
],
"id": "CVE-2025-3262",
"lastModified": "2026-06-17T09:19:32.770",
"metrics": {
"cvssMetricV30": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "LOW",
"baseScore": 5.3,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
"version": "3.0"
},
"exploitabilityScore": 3.9,
"impactScore": 1.4,
"source": "security@huntr.dev",
"type": "Secondary"
}
],
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 3.6,
"source": "nvd@nist.gov",
"type": "Primary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2025-3262",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "yes"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-07-07T15:19:35.031775Z",
"version": "2.0.3"
}
}
]
},
"published": "2025-07-07T10:15:27.200",
"references": [
{
"source": "security@huntr.dev",
"tags": [
"Patch"
],
"url": "https://github.com/huggingface/transformers/commit/0720e206c6ba28887e4d60ef60a6a089f6c1cc76"
},
{
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{
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}
],
"sourceIdentifier": "security@huntr.dev",
"vulnStatus": "Analyzed",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-1333"
}
],
"source": "security@huntr.dev",
"type": "Secondary"
}
]
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
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.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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