CVE-2026-34572

April 2, 2026, 2:16 p.m.

8.8
High

Description

CI4MS is a CodeIgniter 4-based CMS skeleton that delivers a production-ready, modular architecture with RBAC authorization and theme support. Prior to version 0.31.0.0, the application fails to immediately revoke active user sessions when an account is deactivated. Due to a logic flaw in the backend design, account state changes are enforced only during authentication (login), not for already-established sessions. The system implicitly assumes that authenticated users remain trusted for the lifetime of their session. There is no session expiration or account expiration mechanism in place, causing deactivated accounts to retain indefinite access until the user manually logs out. This behavior breaks the intended access control policy and results in persistent unauthorized access, representing a critical security flaw. This issue has been patched in version 0.31.0.0.

Product(s) Impacted

Vendor Product Versions
Codeigniter
  • Codeigniter
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-284
Improper Access Control
The product does not restrict or incorrectly restricts access to a resource from an unauthorized actor.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a codeigniter codeigniter / <0.31.0.0>* / / / / /

CVSS Score

8.8 / 10

CVSS Data - 3.1

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Privileges Required: LOW
  • Scope: UNCHANGED
  • Confidentiality Impact: HIGH
  • Integrity Impact: HIGH
  • Availability Impact: HIGH
  • CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

    View Vector String

Timeline

Published: April 1, 2026, 10:16 p.m.
Last Modified: April 2, 2026, 2:16 p.m.

Status : Received

CVE has been recently published to the CVE List and has been received by the NVD.

More info

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.