FKIE_CVE-2022-24836
Vulnerability from fkie_nvd - Published: 2022-04-11 22:15 - Updated: 2026-06-17 04:32
Severity
7.5 (High) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
7.5 (High) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
7.5 (High) - CVSS:3.1/
Summary
Nokogiri is an open source XML and HTML library for Ruby. Nokogiri `< v1.13.4` contains an inefficient regular expression that is susceptible to excessive backtracking when attempting to detect encoding in HTML documents. Users are advised to upgrade to Nokogiri `>= 1.13.4`. There are no known workarounds for this issue.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| nokogiri | nokogiri | * | |
| fedoraproject | fedora | 34 | |
| fedoraproject | fedora | 35 | |
| fedoraproject | fedora | 36 | |
| debian | debian_linux | 9.0 | |
| debian | debian_linux | 10.0 | |
| apple | macos | * |
{
"affected": [
{
"affectedData": [
{
"product": "nokogiri",
"vendor": "sparklemotion",
"versions": [
{
"status": "affected",
"version": "\u003c 1.13.4"
}
]
}
],
"source": "security-advisories@github.com"
}
],
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"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Nokogiri is an open source XML and HTML library for Ruby. Nokogiri `\u003c v1.13.4` contains an inefficient regular expression that is susceptible to excessive backtracking when attempting to detect encoding in HTML documents. Users are advised to upgrade to Nokogiri `\u003e= 1.13.4`. There are no known workarounds for this issue."
},
{
"lang": "es",
"value": "Nokogiri es una biblioteca XML y HTML de c\u00f3digo abierto para Ruby. Nokogiri versiones anteriores a v1.13.4 contiene una expresi\u00f3n regular ineficiente que es susceptible de un retroceso excesivo cuando intenta detectar la codificaci\u00f3n en documentos HTML. Se recomienda a usuarios actualizar a Nokogiri versiones posteriores a 1.13.4 incluy\u00e9ndola. No se presentan medidas de mitigaci\u00f3n conocidas para este problema"
}
],
"id": "CVE-2022-24836",
"lastModified": "2026-06-17T04:32:37.603",
"metrics": {
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"baseSeverity": "MEDIUM",
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"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 5.0,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:L/Au:N/C:N/I:N/A:P",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 2.9,
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"source": "nvd@nist.gov",
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"scope": "UNCHANGED",
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"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
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"published": "2022-04-11T22:15:07.347",
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"tags": [
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},
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},
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}
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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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