GHSA-XGPW-MM25-3WHC
Vulnerability from github – Published: 2026-10-02 09:31 – Updated: 2026-10-02 09:31The Dc Woocommerce Multi Vendor plugin for WordPress is vulnerable to SQL Injection via the 'order_by' parameter of the /multivendorx/v1/compliance/report-abuse REST endpoint in versions up to and including 5.0.18. This is due to insufficient escaping on the user supplied parameter and lack of sufficient preparation on the existing SQL query — the value is concatenated directly into an ORDER BY clause where esc_sql() (which only neutralizes characters needed to break out of quoted string literals) provides no protection. This makes it possible for authenticated attackers, with vendor-level access and above (users granted the 'edit_stores' capability), to append additional SQL queries into already existing queries that can be used to extract sensitive information from the database.
{
"affected": [],
"aliases": [
"CVE-2026-12951"
],
"database_specific": {
"cwe_ids": [
"CWE-89"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-10-02T08:17:01Z",
"severity": "MODERATE"
},
"details": "The Dc Woocommerce Multi Vendor plugin for WordPress is vulnerable to SQL Injection via the \u0027order_by\u0027 parameter of the /multivendorx/v1/compliance/report-abuse REST endpoint in versions up to and including 5.0.18. This is due to insufficient escaping on the user supplied parameter and lack of sufficient preparation on the existing SQL query \u2014 the value is concatenated directly into an ORDER BY clause where esc_sql() (which only neutralizes characters needed to break out of quoted string literals) provides no protection. This makes it possible for authenticated attackers, with vendor-level access and above (users granted the \u0027edit_stores\u0027 capability), to append additional SQL queries into already existing queries that can be used to extract sensitive information from the database.",
"id": "GHSA-xgpw-mm25-3whc",
"modified": "2026-10-02T09:31:19Z",
"published": "2026-10-02T09:31:19Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-12951"
},
{
"type": "WEB",
"url": "https://plugins.trac.wordpress.org/browser/dc-woocommerce-multi-vendor/tags/5.0.8/modules/MarketplaceCompliance/Rest.php#L119"
},
{
"type": "WEB",
"url": "https://plugins.trac.wordpress.org/browser/dc-woocommerce-multi-vendor/tags/5.0.8/modules/MarketplaceCompliance/Util.php#L98"
},
{
"type": "WEB",
"url": "https://plugins.trac.wordpress.org/changeset?reponame=\u0026old=3721134%40dc-woocommerce-multi-vendor\u0026new=3721134%40dc-woocommerce-multi-vendor"
},
{
"type": "WEB",
"url": "https://www.wordfence.com/threat-intel/vulnerabilities/id/6131f5d7-cc67-493f-81d0-12b822d27a0e?source=cve"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N",
"type": "CVSS_V3"
}
]
}
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.
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.
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.