Vulnerability-Lookup

GHSA-Q6X7-QQGQ-H832

Vulnerability from github – Published: 2025-11-05 06:30 – Updated: 2025-11-05 06:30

Details

The AI Engine plugin for WordPress is vulnerable to Sensitive Information Exposure in all versions up to, and including, 3.1.3 via the /mcp/v1/ REST API endpoint that exposes the 'Bearer Token' value when 'No-Auth URL' is enabled. This makes it possible for unauthenticated attackers to extract the bearer token, which can be used to gain access to a valid session and perform many actions like creating a new administrator account, leading to privilege escalation.

Severity

9.8 (Critical)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

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JSON

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{
  "affected": [],
  "aliases": [
    "CVE-2025-11749"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-200"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-11-05T06:15:33Z",
    "severity": "CRITICAL"
  },
  "details": "The AI Engine plugin for WordPress is vulnerable to Sensitive Information Exposure in all versions up to, and including, 3.1.3 via the /mcp/v1/ REST API endpoint that exposes the \u0027Bearer Token\u0027 value when \u0027No-Auth URL\u0027 is enabled. This makes it possible for unauthenticated attackers to extract the bearer token, which can be used to gain access to a valid session and perform many actions like creating a new administrator account, leading to privilege escalation.",
  "id": "GHSA-q6x7-qqgq-h832",
  "modified": "2025-11-05T06:30:25Z",
  "published": "2025-11-05T06:30:25Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-11749"
    },
    {
      "type": "WEB",
      "url": "https://plugins.trac.wordpress.org/browser/ai-engine/trunk/labs/mcp.php#L226"
    },
    {
      "type": "WEB",
      "url": "https://plugins.trac.wordpress.org/changeset/3380753/ai-engine#file10"
    },
    {
      "type": "WEB",
      "url": "https://www.wordfence.com/threat-intel/vulnerabilities/id/06eaf624-aedf-453d-8457-d03a572fac0d?source=cve"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

CVE-2025-11749 (GCVE-0-2025-11749)

Vulnerability from cvelistv5 – Published: 2025-11-05 05:31 – Updated: 2026-04-08 16:33

Title

AI Engine <= 3.1.3 - Unauthenticated Sensitive Information Exposure to Privilege Escalation

Summary

Severity

9.8 (Critical)


                        
                          CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

SSVC

Exploitation: none Automatable: yes Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-11-05 14:18 UTC

CWE

CWE-200 - Exposure of Sensitive Information to an Unauthorized Actor

Assigner

Wordfence mitre root

References

3 references

URL	Tags
https://www.wordfence.com/threat-intel/vulnerabil…
https://plugins.trac.wordpress.org/browser/ai-eng…
https://plugins.trac.wordpress.org/changeset/3380…

Impacted products

1 product

Vendor	Product	Version
tigroumeow	AI Engine – The Chatbot, AI Framework & MCP for WordPress	Affected: 0 , ≤ 3.1.3 (semver)

Credits

Emiliano Versini

Show details on NVD website

JSON

To clipboard

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                "timestamp": "2025-11-05T14:18:09.578670Z",
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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.

Detection rules are retrieved from Rulezet.

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.

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.