(CVE-2024-47561)
Vulnerability from cleanstart – Published: 2026-08-13 12:10 – Updated: 2026-09-18 11:59 – Source website
Withdrawn 2026-09-18
VLAI
Summary
Security fixes in spark-sc213-jdk17-py312 3.4.4-r1
Details
Package spark-sc213-jdk17-py312 version 3.4.4-r1 fixes 26 vulnerabilities: CVE-2024-47561, ghsa-rhrv-645h-fjfh, CVE-2023-39410, ghsa-r7pg-v2c8-mfg3, CVE-2024-7254...
References
| URL | Type | |
|---|---|---|
{
"affected": [
{
"package": {
"ecosystem": "CleanStart",
"name": "spark-sc213-jdk17-py312"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "3.4.4-r1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"3.4.4-r1"
]
}
],
"credits": [],
"database_specific": {},
"details": "Package spark-sc213-jdk17-py312 version 3.4.4-r1 fixes 26 vulnerabilities: CVE-2024-47561, ghsa-rhrv-645h-fjfh, CVE-2023-39410, ghsa-r7pg-v2c8-mfg3, CVE-2024-7254...",
"id": "CLEANSTART-2026-OI56852",
"modified": "2026-09-18T11:59:01.768079Z",
"published": "2026-08-13T12:10:09Z",
"references": [
{
"type": "WEB",
"url": "https://spark.apache.org"
}
],
"related": [],
"schema_version": "1.7.3",
"summary": "Security fixes in spark-sc213-jdk17-py312 3.4.4-r1",
"upstream": [
"CVE-2024-47561",
"ghsa-rhrv-645h-fjfh",
"CVE-2023-39410",
"ghsa-r7pg-v2c8-mfg3",
"CVE-2024-7254",
"ghsa-wrvw-hg22-4m67",
"CVE-2021-22569",
"ghsa-h4h5-3hr4-j3g2",
"CVE-2022-3171",
"CVE-2021-22570",
"CVE-2022-3509",
"CVE-2022-3510",
"ghsa-735f-pc8j-v9w8",
"CVE-2024-47554",
"ghsa-78wr-2p64-hpwj",
"CVE-2026-54512",
"CVE-2026-54513",
"CVE-2026-54514",
"CVE-2026-54515",
"ghsa-j3rv-43j4-c7qm",
"ghsa-hgj6-7826-r7m5",
"ghsa-rmj7-2vxq-3g9f",
"CVE-2025-12183",
"ghsa-vqf4-7m7x-wgfc",
"CVE-2025-52999",
"ghsa-h46c-h94j-95f3"
],
"withdrawn": "2026-09-18T11:59:01.768079Z"
}
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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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