CVE-2026-92820 (GCVE-0-2026-92820)
Vulnerability from cvelistv5 – Published: 2026-10-02 05:30 – Updated: 2026-10-02 05:30
VLAI
EPSS
VEX
Title
Ninja Forms - File Uploads <= 3.3.34 - Unauthenticated Arbitrary File Upload
Summary
The Ninja Forms - File Uploads plugin for WordPress is vulnerable to arbitrary file operations in all versions up to, and including, 3.3.34 via the external (Amazon S3) upload flow. The plugin trusts an attacker-supplied file path from the form submission and stores it as the upload's file_path, which is then used without validation to attach a file to the form's notification email (arbitrary file read), to write fetched content (arbitrary file write, leading to remote code execution when the external store is configured), and in a scheduled deletion (arbitrary file deletion). This makes it possible for unauthenticated attackers to read, write, or delete arbitrary files on the server. Exploitation requires the site to use the plugin's External File Upload (Amazon S3) action; the read variant additionally requires a form Email action configured to attach the uploaded file.
Severity
8.1 (High)
CWE
- CWE-434 - Unrestricted Upload of File with Dangerous Type
Assigner
References
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| SaturdayDrive | Ninja Forms - File Uploads |
Affected:
0 , ≤ 3.3.34
(semver)
|
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}
],
"metrics": [
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"providerMetadata": {
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},
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},
{
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}
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"timeline": [
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"value": "Vendor Notified"
},
{
"lang": "en",
"time": "2026-10-01T16:54:50.000Z",
"value": "Disclosed"
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],
"title": "Ninja Forms - File Uploads \u003c= 3.3.34 - Unauthenticated Arbitrary File Upload"
}
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"dateReserved": "2026-09-16T20:19:51.864Z",
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"state": "PUBLISHED"
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"dataType": "CVE_RECORD",
"dataVersion": "5.2",
"vulnerability-lookup:meta": {
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}
],
"id": "CVE-2026-92820",
"lastModified": "2026-10-02T06:16:43.197",
"metrics": {
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"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
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"scope": "UNCHANGED",
"userInteraction": "NONE",
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"url": "https://ninjaforms.com/extensions/file-uploads/"
},
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"sourceIdentifier": "security@wordfence.com",
"vulnStatus": "Received",
"weaknesses": [
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"value": "CWE-434"
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],
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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.
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- 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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