CVE-2026-40486

April 17, 2026, 11:16 p.m.

4.3
Medium

Description

Kimai is an open-source time tracking application. In versions 2.52.0 and below, the User Preferences API endpoint (PATCH /api/users/{id}/preferences) applies submitted preference values without checking the isEnabled() flag on preference objects. Although the hourly_rate and internal_rate fields are correctly marked as disabled for users lacking the hourly-rate role permission, the API ignores this restriction and saves the values directly. Any authenticated user can modify their own billing rates through this endpoint, resulting in unauthorized financial tampering affecting invoices and timesheet calculations. This issue has been fixed in version 2.53.0.

Product(s) Impacted

Vendor Product Versions
Kimai
  • Kimai
  • 2.52.0, <2.53.0

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-915
Improperly Controlled Modification of Dynamically-Determined Object Attributes
The product receives input from an upstream component that specifies multiple attributes, properties, or fields that are to be initialized or updated in an object, but it does not properly control which attributes can be modified.

*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 kimai kimai 2.52.0 / / / / / / /
a kimai kimai <2.53.0 / / / / / / /

CVSS Score

4.3 / 10

CVSS Data - 3.1

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Privileges Required: LOW
  • Scope: UNCHANGED
  • Confidentiality Impact: NONE
  • Integrity Impact: LOW
  • Availability Impact: NONE
  • CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:N

    View Vector String

Timeline

Published: April 17, 2026, 11:16 p.m.
Last Modified: April 17, 2026, 11:16 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.