FKIE_CVE-2025-8869
Vulnerability from fkie_nvd - Published: 2025-09-24 15:15 - Updated: 2026-09-26 00:10
Severity
Summary
When extracting a tar archive pip may not check symbolic links point into the extraction directory if the tarfile module doesn't implement PEP 706.
Note that upgrading pip to a "fixed" version for this vulnerability doesn't fix all known vulnerabilities that are remediated by using a Python version that implements PEP 706.
Note that this is a vulnerability in pip's fallback implementation of tar extraction for Python versions that don't implement PEP 706
and therefore are not secure to all vulnerabilities in the Python 'tarfile' module. If you're using a Python version that implements PEP 706
then pip doesn't use the "vulnerable" fallback code.
Mitigations include upgrading to a version of pip that includes the fix, upgrading to a Python version that implements PEP 706 (Python >=3.9.17, >=3.10.12, >=3.11.4, or >=3.12),
applying the linked patch, or inspecting source distributions (sdists) before installation as is already a best-practice.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"collectionURL": "https://pypi.org/project/pip",
"defaultStatus": "unaffected",
"packageName": "pip",
"product": "pip",
"repo": "https://github.com/pypa/pip",
"vendor": "Python Packaging Authority",
"versions": [
{
"lessThan": "25.3",
"status": "affected",
"version": "0",
"versionType": "python"
}
]
}
],
"source": "cna@python.org"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "When extracting a tar archive pip may not check symbolic links point into the extraction directory if the tarfile module doesn\u0027t implement PEP 706.\nNote that upgrading pip to a \"fixed\" version for this vulnerability doesn\u0027t fix all known vulnerabilities that are remediated by using a Python version that implements PEP 706.\n\nNote that this is a vulnerability in pip\u0027s fallback implementation of tar extraction for Python versions that don\u0027t implement PEP 706\nand therefore are not secure to all vulnerabilities in the Python \u0027tarfile\u0027 module. If you\u0027re using a Python version that implements PEP 706\nthen pip doesn\u0027t use the \"vulnerable\" fallback code.\n\nMitigations include upgrading to a version of pip that includes the fix, upgrading to a Python version that implements PEP 706 (Python \u003e=3.9.17, \u003e=3.10.12, \u003e=3.11.4, or \u003e=3.12),\napplying the linked patch, or inspecting source distributions (sdists) before installation as is already a best-practice."
},
{
"lang": "es",
"value": "Al extraer un archivo tar, pip podr\u00eda no verificar que los enlaces simb\u00f3licos apunten al directorio de extracci\u00f3n si el m\u00f3dulo tarfile no implementa PEP 706.\nTenga en cuenta que actualizar pip a una versi\u00f3n \u201ccorregida\u201d para esta vulnerabilidad no corrige todas las vulnerabilidades conocidas que se remedian usando una versi\u00f3n de Python que implementa PEP 706.\n\nTenga en cuenta que esta es una vulnerabilidad en la implementaci\u00f3n de reserva de pip para la extracci\u00f3n de tar para versiones de Python que no implementan PEP 706 y, por lo tanto, no son seguras frente a todas las vulnerabilidades en el m\u00f3dulo \u0027tarfile\u0027 de Python. Si est\u00e1 utilizando una versi\u00f3n de Python que implementa PEP 706, entonces pip no utiliza el c\u00f3digo de reserva \u201cvulnerable\u201d.\n\nLas mitigaciones incluyen actualizar a una versi\u00f3n de pip que incluya la correcci\u00f3n, actualizar a una versi\u00f3n de Python que implemente PEP 706 (Python \u003e=3.9.17, \u003e=3.10.12, \u003e=3.11.4, o \u003e=3.12), aplicar el parche vinculado, o inspeccionar las distribuciones de origen (sdists) antes de la instalaci\u00f3n, como ya es una buena pr\u00e1ctica."
}
],
"id": "CVE-2025-8869",
"lastModified": "2026-09-26T00:10:00.127",
"metrics": {
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "PRESENT",
"attackVector": "NETWORK",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 5.9,
"baseSeverity": "MEDIUM",
"confidentialityRequirement": "NOT_DEFINED",
"exploitMaturity": "NOT_DEFINED",
"integrityRequirement": "NOT_DEFINED",
"modifiedAttackComplexity": "NOT_DEFINED",
"modifiedAttackRequirements": "NOT_DEFINED",
"modifiedAttackVector": "NOT_DEFINED",
"modifiedPrivilegesRequired": "NOT_DEFINED",
"modifiedSubAvailabilityImpact": "NOT_DEFINED",
"modifiedSubConfidentialityImpact": "NOT_DEFINED",
"modifiedSubIntegrityImpact": "NOT_DEFINED",
"modifiedUserInteraction": "NOT_DEFINED",
"modifiedVulnAvailabilityImpact": "NOT_DEFINED",
"modifiedVulnConfidentialityImpact": "NOT_DEFINED",
"modifiedVulnIntegrityImpact": "NOT_DEFINED",
"privilegesRequired": "NONE",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "ACTIVE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:A/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"version": "4.0",
"vulnAvailabilityImpact": "NONE",
"vulnConfidentialityImpact": "NONE",
"vulnIntegrityImpact": "HIGH",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "cna@python.org",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2025-8869",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-10-16T19:47:29.080800Z",
"version": "2.0.3"
}
}
]
},
"published": "2025-09-24T15:15:41.293",
"references": [
{
"source": "cna@python.org",
"url": "https://github.com/pypa/pip/pull/13550"
},
{
"source": "cna@python.org",
"url": "https://mail.python.org/archives/list/security-announce@python.org/thread/IF5A3GCJY3VH7BVHJKOWOJFKTW7VFQEN/"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"url": "https://lists.debian.org/debian-lts-announce/2025/10/msg00028.html"
}
],
"sourceIdentifier": "cna@python.org",
"vulnStatus": "Deferred"
}
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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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