BREW-BUKU-CVE-2018-16516 (GHSA-894G-6J7Q-2HX6)
Vulnerability from osv_homebrew – Published: 2026-08-13 16:38 – Updated: 2026-09-09 23:44 – Source website
VLAI
Summary
Flask-Admin Cross-site Scripting vulnerability
Details
helpers.py in Flask-Admin 1.5.2 has Reflected XSS via a crafted URL.
Severity
6.1 (Medium)
References
{
"affected": [
{
"ecosystem_specific": {
"fix": "bump",
"range_state": "fixed",
"resource": "flask-admin",
"resource_purl": "pkg:pypi/flask-admin@2.2.0",
"upstream_fixed_in": "1.5.3"
},
"package": {
"ecosystem": "Homebrew",
"name": "buku",
"purl": "pkg:brew/buku"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "5.1_6"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "registry",
"upstream_evidence": [
{
"ecosystem": "PyPI",
"key": "pkg:pypi/flask-admin@2.2.0",
"name": "flask-admin",
"resource": "flask-admin",
"strategy": "registry",
"subject_version": "2.2.0"
}
]
},
"details": "helpers.py in Flask-Admin 1.5.2 has Reflected XSS via a crafted URL.",
"id": "BREW-buku-CVE-2018-16516",
"modified": "2026-09-09T23:44:40Z",
"published": "2026-08-13T16:38:25Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2018-16516"
},
{
"type": "WEB",
"url": "https://github.com/flask-admin/flask-admin/pull/1699"
},
{
"type": "WEB",
"url": "https://github.com/flask-admin/flask-admin/commit/8af10e0b022464fdcb2da3d0ea5bbd2f11c0acd1"
},
{
"type": "ADVISORY",
"url": "https://github.com/advisories/GHSA-894g-6j7q-2hx6"
},
{
"type": "PACKAGE",
"url": "https://github.com/flask-admin/flask-admin"
},
{
"type": "WEB",
"url": "https://github.com/flask-admin/flask-admin/releases/tag/v1.5.3"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/flask-admin/PYSEC-2018-54.yaml"
},
{
"type": "WEB",
"url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/UJIYCWIH3BRLI2QNC53CQXLKVP27X7EH"
},
{
"type": "WEB",
"url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/ZU2VKULURVXEU4YFTLMBQGYMPSXQ4MBN"
}
],
"schema_version": "1.7.3",
"severity": [
{
"score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:N/VA:N/SC:L/SI:L/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Flask-Admin Cross-site Scripting vulnerability",
"upstream": [
"GHSA-894g-6j7q-2hx6",
"CVE-2018-16516",
"PYSEC-2018-54"
]
}
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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.
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- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
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- 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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