Vulnerability from bitnami_vulndb
Published
2026-08-17 05:47
Modified
2026-08-17 06:10
Summary
Quadratic Behavior in xml.etree.ElementPath Index Predicates
Details
Element.findall() and fully-consumed Element.iterfind() exhibit O(n^2) time complexity when using XPath index predicates (e.g. [1], [last()], [last()-N]) on XML documents with many same-tag siblings. Element.find() is only affected when the first match is near the end of the sibling list, such as with [last()] or [last()-N]; .//item[1] short-circuits after the first match.
{
"affected": [
{
"package": {
"ecosystem": "Bitnami",
"name": "libpython",
"purl": "pkg:bitnami/libpython"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "3.13.15"
},
{
"introduced": "3.14.0"
},
{
"fixed": "3.14.7"
}
],
"type": "SEMVER"
}
],
"severity": [
{
"score": "CVSS:4.0/AV:N/AC:H/AT:P/PR:H/UI:P/VC:N/VI:N/VA:L/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",
"type": "CVSS_V4"
}
]
}
],
"aliases": [
"CVE-2026-6879"
],
"database_specific": {
"cpes": [
"cpe:2.3:a:python:python:*:*:*:*:*:*:*:*"
],
"severity": "Low"
},
"details": "`Element.findall()` and fully-consumed `Element.iterfind()` exhibit `O(n^2)` time complexity when using XPath index predicates (e.g. `[1]`, `[last()]`, `[last()-N]`) on XML documents with many same-tag siblings. `Element.find()` is only affected when the first match is near the end\u00a0 of the sibling list, such as with `[last()]` or `[last()-N]`;\u00a0 `.//item[1]` short-circuits after the first match.",
"id": "BIT-libpython-2026-6879",
"modified": "2026-08-17T06:10:32.268Z",
"published": "2026-08-17T05:47:19.661Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/python/cpython/commit/02c08e6b747ac43d0d866a4ffa916bedf3423f81"
},
{
"type": "WEB",
"url": "https://github.com/python/cpython/commit/037965c00a427cba5c05447efadc67c51a492e85"
},
{
"type": "WEB",
"url": "https://github.com/python/cpython/commit/0583f24ae678993e3f7939f51ad5bcae5ad9dc70"
},
{
"type": "WEB",
"url": "https://github.com/python/cpython/commit/2ffab083782968a4d732738f4f1dff6bbd69d2b0"
},
{
"type": "WEB",
"url": "https://github.com/python/cpython/commit/390337b8ba1658833fdef379e1739c9f9533a8db"
},
{
"type": "WEB",
"url": "https://github.com/python/cpython/commit/96510a3758f4a075f43223afdee3b6ee1a7a7f02"
},
{
"type": "WEB",
"url": "https://github.com/python/cpython/commit/cb409342a19f25656f62e679f8bac265fe1442c3"
},
{
"type": "WEB",
"url": "https://github.com/python/cpython/issues/152674"
},
{
"type": "WEB",
"url": "https://github.com/python/cpython/pull/152676"
},
{
"type": "WEB",
"url": "https://mail.python.org/archives/list/security-announce@python.org/thread/7YMZ6DDZVR26TJJBVO3RDNBAVGHNYAKR/"
},
{
"type": "WEB",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-6879"
}
],
"schema_version": "1.6.2",
"summary": "Quadratic Behavior in xml.etree.ElementPath Index Predicates"
}
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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.
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.
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