FKIE_CVE-2025-66440
Vulnerability from fkie_nvd - Published: 2025-12-15 18:15 - Updated: 2026-06-17 09:56
Severity
8.8 (High) - CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
9.8 (Critical) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
9.8 (Critical) - CVSS:3.1/
Summary
An issue was discovered in Frappe ERPNext through 15.89.0. Function get_outstanding_reference_documents() at erpnext/accounts/doctype/payment_entry/payment_entry.py is vulnerable to SQL Injection. It allows an attacker to extract arbitrary data from the database by injecting SQL payloads via the to_posting_date parameter, which is directly interpolated into the query without proper sanitization or parameter binding.
References
| URL | Tags | ||
|---|---|---|---|
| cve@mitre.org | https://github.com/frappe/frappe/security | Product | |
| cve@mitre.org | https://iamanc.github.io/post/erpnext-sqli | Exploit, Third Party Advisory |
{
"affected": [
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"affectedData": [
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"vendor": "n/a",
"versions": [
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"status": "affected",
"version": "n/a"
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"source": "cve@mitre.org"
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"configurations": [
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"matchCriteriaId": "DAA2FB4F-48C5-4BA5-A15F-175B8A752866",
"versionEndIncluding": "15.89.0",
"vulnerable": true
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"cveTags": [],
"descriptions": [
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"value": "An issue was discovered in Frappe ERPNext through 15.89.0. Function get_outstanding_reference_documents() at erpnext/accounts/doctype/payment_entry/payment_entry.py is vulnerable to SQL Injection. It allows an attacker to extract arbitrary data from the database by injecting SQL payloads via the to_posting_date parameter, which is directly interpolated into the query without proper sanitization or parameter binding."
}
],
"id": "CVE-2025-66440",
"lastModified": "2026-06-17T09:56:50.903",
"metrics": {
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"cvssData": {
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"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.8,
"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:H",
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"source": "nvd@nist.gov",
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"role": "CISA Coordinator",
"timestamp": "2025-12-16T15:22:52.332798Z",
"version": "2.0.3"
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"published": "2025-12-15T18:15:48.663",
"references": [
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"tags": [
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"url": "https://github.com/frappe/frappe/security"
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"url": "https://iamanc.github.io/post/erpnext-sqli"
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"sourceIdentifier": "cve@mitre.org",
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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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