CVE-2026-87936

mediumpriority · track · 0EPSS 0.003 · 20 %ileDEUS
grimoire priorityP3 · Track
Exploitable?
—
no known exploitation
Likely / severe?
0.27% (20th) EPSS
CVSS 6.5 · medium
Is it mine?
29 products
Check your exposure
Who says so?
2 sources
cert_bund · osv

EPSS · scored 2026-10-28

Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection') vulnerability in Drupal amazee.ai Private AI Provider allows SQL Injection. This issue affects amazee.ai Private AI Provider versions: from 0.0.0 to 1.3.7, from 1.4.0 to 1.4.3.

01

cvss

Technical severity, 0–10. One row per scoring source.

6.5
010

base score 0–10 · higher = more severe · hover a vector to decode

v3.16.5mediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:L/A:Nsecondaryexploitability 2.2 · impact 4.2
v3.16mediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:L/A:N/E:Usecondary · CVSS-BT (t0sche)
02

ssvc

A stakeholder decision — act, attend, or track — from exploitation and impact.

Trackcoordinatorcisa_ssvcUS
03

weaknesses

The CWE weakness classes this flaw belongs to.

04

affected products (29)

Products and version ranges known to be affected.

05

advisories (2)

Vendor and ecosystem advisories describing this.

  • WID-SEC-W-2026-3284Drupal Erweiterungen: Mehrere SchwachstellenDeutsch2026-09-09csaf · cert_bundDE

    Ein Angreifer kann mehrere Schwachstellen in Drupal ausnutzen, um Datenbankinhalte zu manipulieren oder auszulesen, Zugriffsbeschränkungen und Authentifizierungsmechanismen zu umgehen, vertrauliche Informationen offenzulegen, Cross Site Scripting Angriffe auszuführen, Benutzer auf manipulierte Webseiten umzuleiten, SAML-Authentifizierungen zu beeinflussen oder wiederzuverwenden, interne Ressourcen über SSRF anzusprechen sowie unberechtigt Dateien auf den Server hochzuladen.

  • DRUPAL-CONTRIB-2026-1342026-09-09vendor · osvUS

    **Update 2026-09-11:** Increased risk score to reflect publicly documented methods for developing exploits. This module integrates amazee.ai's AI services into Drupal, including a Postgres/pgvector vector database backend for use with Search API AI Search. The module doesn't sufficiently sanitize filter values before using them to build SQL queries in its Postgres/pgvector backend, allowing SQL injection. This vulnerability is mitigated by the fact that a site must be using the module's Postgres/pgvector vector database backend for a Search API AI Search index, and must expose one of that index's non-string fields as a filter (for example, through a View) that is reachable by the attacker.

06

sources

Which sources assert this record, and when.

published 2026-10-22modified 2026-10-22
07

references (1) nvd

External citations — patches, advisories, analysis.

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