GSD-2023-27025
Vulnerability from gsd - Updated: 2023-12-13 01:20Details
An arbitrary file download vulnerability in the background management module of RuoYi v4.7.6 and below allows attackers to download arbitrary files in the server.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2023-27025",
"id": "GSD-2023-27025"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
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"details": "An arbitrary file download vulnerability in the background management module of RuoYi v4.7.6 and below allows attackers to download arbitrary files in the server.",
"id": "GSD-2023-27025",
"modified": "2023-12-13T01:20:55.488124Z",
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"gitlab.com": {
"advisories": [
{
"affected_range": "(,4.7.6)",
"affected_versions": "All versions before 4.7.6",
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"cwe_ids": [
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"CWE-494",
"CWE-937"
],
"date": "2023-04-07",
"description": "An arbitrary file download vulnerability in the background management module of RuoYi v4.7.6 and below allows attackers to download arbitrary files in the server.",
"fixed_versions": [
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],
"identifier": "CVE-2023-27025",
"identifiers": [
"GHSA-h4c9-rr5m-32fm",
"CVE-2023-27025"
],
"not_impacted": "All versions starting from 4.7.6",
"package_slug": "maven/com.ruoyi/ruoyi",
"pubdate": "2023-04-02",
"solution": "Upgrade to version 4.7.6 or above.",
"title": "Download of Code Without Integrity Check",
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"tags": [
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"impact": {
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
"version": "3.1"
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"exploitabilityScore": 3.9,
"impactScore": 3.6
}
},
"lastModifiedDate": "2023-04-07T02:16Z",
"publishedDate": "2023-04-02T01:15Z"
}
}
}
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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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