GSD-2016-9910
Vulnerability from gsd - Updated: 2023-12-13 01:21Details
The serializer in html5lib before 0.99999999 might allow remote attackers to conduct cross-site scripting (XSS) attacks by leveraging mishandling of special characters in attribute values, a different vulnerability than CVE-2016-9909.
Aliases
Aliases
{
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"alias": "CVE-2016-9910",
"description": "The serializer in html5lib before 0.99999999 might allow remote attackers to conduct cross-site scripting (XSS) attacks by leveraging mishandling of special characters in attribute values, a different vulnerability than CVE-2016-9909.",
"id": "GSD-2016-9910",
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"https://www.suse.com/security/cve/CVE-2016-9910.html",
"https://advisories.mageia.org/CVE-2016-9910.html",
"https://security.archlinux.org/CVE-2016-9910"
]
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"name": "https://github.com/html5lib/html5lib-python/issues/12",
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"advisories": [
{
"affected_range": "\u003c0.99999999",
"affected_versions": "All versions before 0.99999999",
"cvss_v2": "AV:N/AC:M/Au:N/C:N/I:P/A:N",
"cvss_v3": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N",
"cwe_ids": [
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"CWE-79",
"CWE-79",
"CWE-937"
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"date": "2022-06-02",
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],
"not_impacted": "All versions starting from 0.99999999",
"package_slug": "pypi/html5lib",
"pubdate": "2022-05-17",
"solution": "Upgrade to version 0.99999999 or above.",
"title": "Improper Neutralization of Input During Web Page Generation (\u0027Cross-site Scripting\u0027)",
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"impact": {
"baseMetricV2": {
"cvssV2": {
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"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "NONE",
"baseScore": 4.3,
"confidentialityImpact": "NONE",
"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:M/Au:N/C:N/I:P/A:N",
"version": "2.0"
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"exploitabilityScore": 8.6,
"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": true
},
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"attackVector": "NETWORK",
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"baseScore": 6.1,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "CHANGED",
"userInteraction": "REQUIRED",
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"impactScore": 2.7
}
},
"lastModifiedDate": "2017-02-23T18:56Z",
"publishedDate": "2017-02-22T16:59Z"
}
}
}
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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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