CVE-2022-41840 (GCVE-0-2022-41840)
Vulnerability from cvelistv5 – Published: 2022-11-18 18:27 – Updated: 2026-04-28 16:07Title
WordPress Welcart eCommerce plugin <= 2.7.7 - Unauth. Directory Traversal vulnerability
Summary
Unauth. Directory Traversal vulnerability in Welcart eCommerce plugin <= 2.7.7 on WordPress.
Severity
7.5 (High)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-02-20 19:15 UTC
CWE
- CWE-22 - Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
Assigner
References
1 reference
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| Collne Inc. | Welcart e-Commerce (WordPress plugin) |
Affected:
<= 2.7.7 , ≤ 2.7.7
(custom)
|
Date Public
2022-10-20 00:00
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: fdc452ff-8808-40bc-ac4c-331403a8e33a
Exploited: Yes
Timestamps
First Seen: 2025-06-06
Asserted: 2025-06-06
Scope
Notes: WordPress Welcart eCommerce plugin <= 2.7.7 - Unauth. Directory Traversal vulnerability | Affected: Collne / Welcart e-Commerce (WordPress plugin) | CVSS: 7.5 (HIGH) | EPSS: 0.05521 | Used in malware: unknown | Not yet in CISA KEV: True
Evidence
Type: Public Report
Signal: Successful Exploitation
Confidence: 70%
Source: previdian
Details
| Feed | Previdian (previdian.com) |
|---|---|
| Title | WordPress Welcart eCommerce plugin <= 2.7.7 - Unauth. Directory Traversal vulnerability |
| Cve Id | CVE-2022-41840 |
| Vendor | Collne |
| Ghsa Id | None |
| Product | Welcart e-Commerce (WordPress plugin) |
| Added Date | 2025-06-06T00:00:00.000Z |
| Cvss Score | 7.5 |
| Epss Score | 0.05521 |
| Previous Ids | |
| Cvss Severity | HIGH |
| Virtual Patch | False |
| Cvss Estimated | False |
| Epss Percentile | 0.92557 |
| Used In Malware | unknown |
| Vulnerability Id | CVE-2022-41840 |
| Ahead Of Cisa Kev | None |
| Not Yet In Cisa Kev | True |
References
Created: 2026-10-02 09:09 CEST
| Updated: 2026-10-02 09:09 CEST
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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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