{
  "affected": [
    {
      "database_specific": {
        "affected_versions": "\u003c1.3.7 || \u003e=1.4.0 \u003c1.4.3"
      },
      "package": {
        "ecosystem": "Packagist:https://packages.drupal.org/8",
        "name": "drupal/ai_provider_amazeeio"
      },
      "ranges": [
        {
          "database_specific": {
            "constraint": "\u003c1.3.7"
          },
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.3.7"
            }
          ],
          "type": "ECOSYSTEM"
        },
        {
          "database_specific": {
            "constraint": "\u003e=1.4.0 \u003c1.4.3"
          },
          "events": [
            {
              "introduced": "1.4.0"
            },
            {
              "fixed": "1.4.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "severity": []
    }
  ],
  "aliases": [
    "CVE-2026-87936"
  ],
  "credits": [
    {
      "contact": [
        "https://www.drupal.org/u/matank001"
      ],
      "name": "Matan Kotick (matank001)"
    }
  ],
  "details": "This module integrates amazee.ai\u0027s AI services into Drupal, including a Postgres/pgvector vector database backend for use with Search API AI Search.\n\nThe module doesn\u0027t sufficiently sanitize filter values before using them to build SQL queries in its Postgres/pgvector backend, allowing SQL injection.\n\nThis vulnerability is mitigated by the fact that a site must be using the module\u0027s Postgres/pgvector vector database backend for a Search API AI Search index, and must expose one of that index\u0027s non-string fields as a filter (for example, through a View) that is reachable by the attacker.",
  "id": "DRUPAL-CONTRIB-2026-134",
  "modified": "2026-09-09T17:14:57.000Z",
  "published": "2026-09-09T17:14:00.000Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://www.drupal.org/sa-contrib-2026-134"
    }
  ],
  "schema_version": "1.7.0"
}