CVE-2024-0304 (GCVE-0-2024-0304)
Vulnerability from cvelistv5 – Published: 2024-01-08 08:00 – Updated: 2025-06-03 14:38
VLAI
EPSS
VEX
Title
Youke365 collect.php server-side request forgery
Summary
A vulnerability has been found in Youke365 up to 1.5.3 and classified as critical. Affected by this vulnerability is an unknown functionality of the file /app/api/controller/collect.php. The manipulation of the argument url leads to server-side request forgery. The attack can be launched remotely. The exploit has been disclosed to the public and may be used. The associated identifier of this vulnerability is VDB-249871.
Severity
6.3 (Medium)
6.3 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-05-08 15:56 UTC
CWE
- CWE-918 - Server-Side Request Forgery
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://vuldb.com/?id.249871 | vdb-entrytechnical-description |
| https://vuldb.com/?ctiid.249871 | signaturepermissions-required |
| https://note.zhaoj.in/share/3jF3Xpl3ttlZ | broken-linkexploit |
Impacted products
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"technical-description"
],
"url": "https://vuldb.com/?id.249871"
},
{
"tags": [
"signature",
"permissions-required"
],
"url": "https://vuldb.com/?ctiid.249871"
},
{
"tags": [
"broken-link",
"exploit"
],
"url": "https://note.zhaoj.in/share/3jF3Xpl3ttlZ"
}
],
"timeline": [
{
"lang": "en",
"time": "2024-01-07T00:00:00.000Z",
"value": "Advisory disclosed"
},
{
"lang": "en",
"time": "2024-01-07T00:00:00.000Z",
"value": "CVE reserved"
},
{
"lang": "en",
"time": "2024-01-07T01:00:00.000Z",
"value": "VulDB entry created"
},
{
"lang": "en",
"time": "2024-01-25T09:33:50.000Z",
"value": "VulDB entry last update"
}
],
"title": "Youke365 collect.php server-side request forgery"
}
},
"cveMetadata": {
"assignerOrgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
"assignerShortName": "VulDB",
"cveId": "CVE-2024-0304",
"datePublished": "2024-01-08T08:00:05.121Z",
"dateReserved": "2024-01-07T20:00:50.705Z",
"dateUpdated": "2025-06-03T14:38:16.923Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
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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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