FKIE_CVE-2025-58375
Vulnerability from fkie_nvd - Published: 2025-09-06 00:15 - Updated: 2026-08-07 19:17
Severity
Summary
Frappe is a full-stack web application framework. Versions 14.96.9 and below, and 15.0.0 through 15.71.0 have an insecure endpoint parameter that is vulnerable to error-based SQL Injection through lack of validation. Sensitive information such as versioning can be retrieved. This issue is fixed in versions 14.96.10 and 15.72.0.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"product": "frappe",
"vendor": "frappe",
"versions": [
{
"status": "affected",
"version": "\u003c 14.96.10"
},
{
"status": "affected",
"version": "\u003e= 15.0.0, \u003c 15.72.0"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Frappe is a full-stack web application framework. Versions 14.96.9 and below, and 15.0.0 through 15.71.0 have an insecure endpoint parameter that is vulnerable to error-based SQL Injection through lack of validation. Sensitive information such as versioning can be retrieved. This issue is fixed in versions 14.96.10 and 15.72.0."
}
],
"id": "CVE-2025-58375",
"lastModified": "2026-08-07T19:17:33.410",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 8.1,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 5.2,
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
},
"published": "2025-09-06T00:15:35.047",
"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/frappe/frappe/commit/2dab009c8b15e29aa14bcd421eee8c6b2dc0fce6"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/frappe/frappe/commit/ec70383ef0196d7b64fcf51b230483dac095a68b"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/frappe/frappe/security/advisories/GHSA-mggw-6xqj-rphj"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Received",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-89"
}
],
"source": "security-advisories@github.com",
"type": "Primary"
}
]
}
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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.
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.
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