GSD-2024-0854
Vulnerability from gsd - Updated: 2024-01-25 06:03Details
URL redirection to untrusted site ('Open Redirect') vulnerability in file access component in Synology DiskStation Manager (DSM) before 7.2.1-69057-2 allows remote authenticated users to conduct phishing attacks via unspecified vectors.
Aliases
{
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2024-0854"
],
"details": "URL redirection to untrusted site (\u0027Open Redirect\u0027) vulnerability in file access component in Synology DiskStation Manager (DSM) before 7.2.1-69057-2 allows remote authenticated users to conduct phishing attacks via unspecified vectors.",
"id": "GSD-2024-0854",
"modified": "2024-01-25T06:03:20.750874Z",
"schema_version": "1.4.0"
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"affects": {
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"product_name": "DiskStation Manager (DSM)",
"version": {
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"version_value": "not down converted",
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"credits": [
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"lang": "en",
"value": "Jangwoo Choi, HYEONJUN LEE, SoYeon Kim, TaeWan Ha, DoHwan Kim (https://zrr.kr/SWND)"
}
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"value": "URL redirection to untrusted site (\u0027Open Redirect\u0027) vulnerability in file access component in Synology DiskStation Manager (DSM) before 7.2.1-69057-2 allows remote authenticated users to conduct phishing attacks via unspecified vectors."
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"baseScore": 4.1,
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"confidentialityImpact": "NONE",
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"scope": "CHANGED",
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"name": "https://www.synology.com/en-global/security/advisory/Synology_SA_24_02",
"refsource": "MISC",
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"cve": {
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},
{
"lang": "es",
"value": "La vulnerabilidad de redirecci\u00f3n de URL a un sitio que no es de confianza (\"Open Redirect\") en el componente de acceso a archivos de Synology DiskStation Manager (DSM) anterior a 7.2.1-69057-2 permite a usuarios remotos autenticados realizar ataques de phishing a trav\u00e9s de vectores no especificados."
}
],
"id": "CVE-2024-0854",
"lastModified": "2024-01-30T17:01:37.127",
"metrics": {
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"source": "security@synology.com",
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"published": "2024-01-24T10:15:09.533",
"references": [
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"source": "security@synology.com",
"tags": [
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}
}
}
}
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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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