brew-certsync-cve-2022-29361
Vulnerability from osv_homebrew
Published
2026-08-13 16:39
Modified
2026-08-13 16:39
Summary
Details
** DISPUTED ** Improper parsing of HTTP requests in Pallets Werkzeug v2.1.0 and below allows attackers to perform HTTP Request Smuggling using a crafted HTTP request with multiple requests included inside the body. NOTE: the vendor's position is that this behavior can only occur in unsupported configurations involving development mode and an HTTP server from outside the Werkzeug project.
References
{
"affected": [
{
"ecosystem_specific": {
"fix": "bump",
"range_state": "fixed",
"resource": "werkzeug",
"resource_purl": "pkg:pypi/werkzeug@3.1.8",
"upstream_fixed_in": "2.1.1"
},
"package": {
"ecosystem": "Homebrew",
"name": "certsync",
"purl": "pkg:brew/certsync"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.1.6_11"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "registry",
"upstream_evidence": [
{
"ecosystem": "PyPI",
"key": "pkg:pypi/werkzeug@3.1.8",
"name": "werkzeug",
"resource": "werkzeug",
"strategy": "registry",
"subject_version": "3.1.8"
}
]
},
"details": "** DISPUTED ** Improper parsing of HTTP requests in Pallets Werkzeug v2.1.0 and below allows attackers to perform HTTP Request Smuggling using a crafted HTTP request with multiple requests included inside the body. NOTE: the vendor\u0027s position is that this behavior can only occur in unsupported configurations involving development mode and an HTTP server from outside the Werkzeug project.",
"id": "BREW-certsync-CVE-2022-29361",
"modified": "2026-08-13T16:39:03Z",
"published": "2026-08-13T16:39:03Z",
"references": [
{
"type": "FIX",
"url": "https://github.com/pallets/werkzeug/commit/9a3a981d70d2e9ec3344b5192f86fcaf3210cd85"
},
{
"type": "REPORT",
"url": "https://github.com/pallets/werkzeug/issues/2420"
}
],
"schema_version": "1.7.3",
"upstream": [
"PYSEC-2022-203",
"CVE-2022-29361"
]
}
Loading…
Loading…
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.
Loading…
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.
Loading…
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.
Loading…