GSD-2021-29448
Vulnerability from gsd - Updated: 2023-12-13 01:23Details
Pi-hole is a Linux network-level advertisement and Internet tracker blocking application. The Stored XSS exists in the Pi-hole Admin portal, which can be exploited by the malicious actor with the network access to DNS server. See the referenced GitHub security advisory for patch details.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2021-29448",
"description": "Pi-hole is a Linux network-level advertisement and Internet tracker blocking application. The Stored XSS exists in the Pi-hole Admin portal, which can be exploited by the malicious actor with the network access to DNS server. See the referenced GitHub security advisory for patch details.",
"id": "GSD-2021-29448"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
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],
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"id": "GSD-2021-29448",
"modified": "2023-12-13T01:23:36.663432Z",
"schema_version": "1.4.0"
}
},
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"STATE": "PUBLIC",
"TITLE": "Stored DOM XSS in Pi-hole Admin Web Interface"
},
"affects": {
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{
"product": {
"product_data": [
{
"product_name": "AdminLTE",
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}
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},
"impact": {
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"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.6,
"baseSeverity": "HIGH",
"confidentialityImpact": "LOW",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:L/I:L/A:H",
"version": "3.1"
}
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"value": "{\"CWE-79\":\"Improper Neutralization of Input During Web Page Generation (\u0027Cross-site Scripting\u0027)\"}"
}
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}
]
},
"source": {
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"discovery": "UNKNOWN"
}
},
"nvd.nist.gov": {
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"nodes": [
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"cpe_name": [],
"vulnerable": true
},
{
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{
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"impact": {
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"cvssV2": {
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"accessVector": "NETWORK",
"authentication": "NONE",
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"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:M/Au:N/C:N/I:P/A:P",
"version": "2.0"
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"impactScore": 4.9,
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"severity": "MEDIUM",
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"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:H",
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"exploitabilityScore": 2.8,
"impactScore": 5.3
}
},
"lastModifiedDate": "2021-05-14T20:07Z",
"publishedDate": "2021-04-15T16:15Z"
}
}
}
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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.
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- 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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