PYSEC-2021-359
Vulnerability from pysec - Published: 2021-09-08 18:15 - Updated: 2021-10-11 01:16
VLAI
Details
Flask-AppBuilder is an application development framework, built on top of Flask. In affected versions if using Flask-AppBuilder OAuth, an attacker can share a carefully crafted URL with a trusted domain for an application built with Flask-AppBuilder, this URL can redirect a user to a malicious site. This is an open redirect vulnerability. To resolve this issue upgrade to Flask-AppBuilder 3.2.2 or above. If upgrading is infeasible users may filter HTTP traffic containing ?next={next-site} where the next-site domain is different from the application you are protecting as a workaround.
Impacted products
| Name | purl | flask-appbuilder | pkg:pypi/flask-appbuilder |
|---|
Aliases
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "flask-appbuilder",
"purl": "pkg:pypi/flask-appbuilder"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "6af28521589599b1dbafd6313256229ee9a4fa74"
}
],
"repo": "https://github.com/dpgaspar/Flask-AppBuilder",
"type": "GIT"
},
{
"events": [
{
"introduced": "0"
},
{
"fixed": "3.3.2"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"0.1.10",
"0.1.11",
"0.1.12",
"0.1.13",
"0.1.14",
"0.1.15",
"0.1.16",
"0.1.17",
"0.1.18",
"0.1.19",
"0.1.20",
"0.1.21",
"0.1.22",
"0.1.23",
"0.1.24",
"0.1.25",
"0.1.26",
"0.1.27",
"0.1.28",
"0.1.29",
"0.1.3",
"0.1.33",
"0.1.34",
"0.1.35",
"0.1.36",
"0.1.37",
"0.1.38",
"0.1.4",
"0.1.43",
"0.1.44",
"0.1.45",
"0.1.46",
"0.1.47",
"0.1.5",
"0.1.6",
"0.1.7",
"0.1.8",
"0.1.9",
"0.10.0",
"0.10.1",
"0.10.2",
"0.10.3",
"0.10.4",
"0.10.5",
"0.10.6",
"0.10.7",
"0.2.0",
"0.2.1",
"0.2.2",
"0.3.0",
"0.3.1",
"0.3.10",
"0.3.11",
"0.3.12",
"0.3.13",
"0.3.14",
"0.3.15",
"0.3.16",
"0.3.17",
"0.3.2",
"0.3.3",
"0.3.4",
"0.3.5",
"0.3.6",
"0.3.7",
"0.3.8",
"0.3.9",
"0.4.0",
"0.4.1",
"0.4.2",
"0.4.3",
"0.5.0",
"0.5.1",
"0.5.2",
"0.5.3",
"0.5.4",
"0.5.5",
"0.5.6",
"0.6.1",
"0.6.10",
"0.6.11",
"0.6.12",
"0.6.13",
"0.6.14",
"0.6.2",
"0.6.3",
"0.6.4",
"0.6.5",
"0.6.6",
"0.6.7",
"0.6.8",
"0.6.9",
"0.7.0",
"0.7.1",
"0.7.2",
"0.7.3",
"0.7.4",
"0.7.5",
"0.7.6",
"0.7.7",
"0.7.8",
"0.8.0",
"0.8.1",
"0.8.2",
"0.8.3",
"0.8.4",
"0.8.5",
"0.9.0",
"0.9.1",
"0.9.2",
"0.9.3",
"1.0.0",
"1.0.1",
"1.1.0",
"1.1.1",
"1.1.2",
"1.1.3",
"1.10.0",
"1.11.0",
"1.11.1",
"1.12.0",
"1.12.1",
"1.12.2",
"1.12.3",
"1.12.4",
"1.12.5",
"1.13.0",
"1.13.1",
"1.2.0",
"1.2.1",
"1.3.0",
"1.3.1",
"1.3.2",
"1.3.3",
"1.3.4",
"1.3.5",
"1.3.6",
"1.3.7",
"1.4.0",
"1.4.1",
"1.4.2",
"1.4.3",
"1.4.4",
"1.4.5",
"1.4.6",
"1.4.7",
"1.5.0",
"1.6.0",
"1.6.1",
"1.6.2",
"1.6.3",
"1.7.0",
"1.7.1",
"1.8.0",
"1.8.1",
"1.9.0",
"1.9.1",
"1.9.2",
"1.9.3",
"1.9.4",
"1.9.5",
"1.9.6",
"2.0.0",
"2.1.0",
"2.1.1",
"2.1.10",
"2.1.11",
"2.1.12",
"2.1.13",
"2.1.2",
"2.1.3",
"2.1.4",
"2.1.5",
"2.1.6",
"2.1.7",
"2.1.8",
"2.1.9",
"2.2.0",
"2.2.0rc1",
"2.2.0rc2",
"2.2.1",
"2.2.1rc1",
"2.2.1rc2",
"2.2.1rc3",
"2.2.2",
"2.2.2rc1",
"2.2.2rc2",
"2.2.2rc3",
"2.2.3",
"2.2.3rc1",
"2.2.3rc2",
"2.2.3rc3",
"2.2.3rc4",
"2.2.3rc5",
"2.2.3rc6",
"2.2.4",
"2.2.4rc1",
"2.3.0",
"2.3.0rc1",
"2.3.0rc2",
"2.3.0rc3",
"2.3.0rc4",
"2.3.1",
"2.3.1rc1",
"2.3.2",
"2.3.2rc1",
"2.3.3",
"2.3.3rc1",
"2.3.3rc2",
"2.3.3rc3",
"2.3.4",
"2.3.4rc1",
"3.0.0",
"3.0.0rc1",
"3.0.0rc2",
"3.0.0rc3",
"3.0.0rc4",
"3.0.1",
"3.0.1rc1",
"3.1.0",
"3.1.0rc1",
"3.1.0rc2",
"3.1.0rc3",
"3.1.1",
"3.1.1rc1",
"3.1.1rc2",
"3.1.1rc3",
"3.2.0",
"3.2.0rc1",
"3.2.0rc2",
"3.2.1",
"3.2.1rc1",
"3.2.2",
"3.2.2rc1",
"3.2.3",
"3.2.3rc1",
"3.2.3rc2",
"3.3.0",
"3.3.0rc1",
"3.3.1",
"3.3.1rc1",
"3.3.2rc1"
]
}
],
"aliases": [
"CVE-2021-32805",
"GHSA-624f-cqvr-3qw4"
],
"details": "Flask-AppBuilder is an application development framework, built on top of Flask. In affected versions if using Flask-AppBuilder OAuth, an attacker can share a carefully crafted URL with a trusted domain for an application built with Flask-AppBuilder, this URL can redirect a user to a malicious site. This is an open redirect vulnerability. To resolve this issue upgrade to Flask-AppBuilder 3.2.2 or above. If upgrading is infeasible users may filter HTTP traffic containing `?next={next-site}` where the `next-site` domain is different from the application you are protecting as a workaround.",
"id": "PYSEC-2021-359",
"modified": "2021-10-11T01:16:40.573932Z",
"published": "2021-09-08T18:15:00Z",
"references": [
{
"type": "ADVISORY",
"url": "https://github.com/dpgaspar/Flask-AppBuilder/security/advisories/GHSA-624f-cqvr-3qw4"
},
{
"type": "FIX",
"url": "https://github.com/dpgaspar/Flask-AppBuilder/commit/6af28521589599b1dbafd6313256229ee9a4fa74"
}
]
}
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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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