CVE-2025-12084 (GCVE-0-2025-12084)
Vulnerability from cvelistv5 – Published: 2025-12-03 18:55 – Updated: 2026-03-03 14:41
VLAI
EPSS
VEX
Title
Quadratic complexity in node ID cache clearing
Summary
When building nested elements using xml.dom.minidom methods such as appendChild() that have a dependency on _clear_id_cache() the algorithm is quadratic. Availability can be impacted when building excessively nested documents.
Severity
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-12-03 19:13 UTC
CWE
- CWE-407 - Inefficient Algorithmic Complexity
Assigner
References
14 references
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Python Software Foundation | CPython |
Affected:
0 , < 3.10.20
(python)
Affected: 3.11.0 , < 3.11.15 (python) Affected: 3.12.0 , < 3.12.13 (python) Affected: 3.13.0 , < 3.13.11 (python) Affected: 3.14.0 , < 3.14.2 (python) Affected: 3.15.0a1 , < 3.15.0a3 (python) |
guessed |
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"value": "When building nested elements using xml.dom.minidom methods such as appendChild() that have a dependency on _clear_id_cache() the algorithm is quadratic. Availability can be impacted when building excessively nested documents."
}
],
"metrics": [
{
"cvssV4_0": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "PRESENT",
"attackVector": "NETWORK",
"baseScore": 6.3,
"baseSeverity": "MEDIUM",
"exploitMaturity": "NOT_DEFINED",
"privilegesRequired": "NONE",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "NONE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
"version": "4.0",
"vulnAvailabilityImpact": "LOW",
"vulnConfidentialityImpact": "NONE",
"vulnIntegrityImpact": "NONE",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"format": "CVSS",
"scenarios": [
{
"lang": "en",
"value": "GENERAL"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2026-03-03T14:41:38.821Z",
"orgId": "28c92f92-d60d-412d-b760-e73465c3df22",
"shortName": "PSF"
},
"references": [
{
"tags": [
"patch"
],
"url": "https://github.com/python/cpython/pull/142146"
},
{
"tags": [
"issue-tracking"
],
"url": "https://github.com/python/cpython/issues/142145"
},
{
"tags": [
"patch"
],
"url": "https://github.com/python/cpython/commit/08d8e18ad81cd45bc4a27d6da478b51ea49486e4"
},
{
"tags": [
"patch"
],
"url": "https://github.com/python/cpython/commit/027f21e417b26eed4505ac2db101a4352b7c51a0"
},
{
"tags": [
"patch"
],
"url": "https://github.com/python/cpython/commit/ddcd2acd85d891a53e281c773b3093f9db953964"
},
{
"tags": [
"patch"
],
"url": "https://github.com/python/cpython/commit/27648a1818749ef44c420afe6173af6868715437"
},
{
"tags": [
"patch"
],
"url": "https://github.com/python/cpython/commit/8d2d7bb2e754f8649a68ce4116271a4932f76907"
},
{
"tags": [
"patch"
],
"url": "https://github.com/python/cpython/commit/9c9dda6625a2a90d2a06c657eee021d6be19842d"
},
{
"tags": [
"patch"
],
"url": "https://github.com/python/cpython/commit/a696ba8b4d42fd632afc9bc88ad830a2e4cceed8"
},
{
"tags": [
"patch"
],
"url": "https://github.com/python/cpython/commit/41f468786762348960486c166833a218a0a436af"
},
{
"tags": [
"patch"
],
"url": "https://github.com/python/cpython/commit/57937a8e5e293f0dcba5115f7b7a11b1e0c9a273"
},
{
"tags": [
"patch"
],
"url": "https://github.com/python/cpython/commit/e91c11449cad34bac3ea55ee09ca557691d92b53"
},
{
"tags": [
"patch"
],
"url": "https://github.com/python/cpython/commit/a46c10ec9d4050ab67b8a932e0859a2ea60c3cb8"
},
{
"tags": [
"patch"
],
"url": "https://github.com/python/cpython/commit/c97e87593063d84a2bd9fe7068b30eb44de23dc0"
}
],
"source": {
"discovery": "UNKNOWN"
},
"title": "Quadratic complexity in node ID cache clearing",
"x_generator": {
"engine": "Vulnogram 0.5.0"
}
}
},
"cveMetadata": {
"assignerOrgId": "28c92f92-d60d-412d-b760-e73465c3df22",
"assignerShortName": "PSF",
"cveId": "CVE-2025-12084",
"datePublished": "2025-12-03T18:55:32.222Z",
"dateReserved": "2025-10-22T16:06:55.078Z",
"dateUpdated": "2026-03-03T14:41:38.821Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2"
}
}
}
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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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