CVE-2026-13544 Feehi CVE debrief

Who should care

System administrators and security teams managing Feehi CMS installations should be aware of this vulnerability. Given the low severity and the fact that the exploit is publicly available, defenders should assess their exposure and apply patches or mitigations as necessary. CVE-2026-13544's low CVSS score indicates limited impact, but it still requires attention to ensure the security of affected systems.

Technical summary

The vulnerability CVE-2026-13544 affects Feehi CMS up to version 2.1.1. It is caused by improper access controls in the /api/users endpoint of the API. The CVSS:4.0 vector is AV:N/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X, resulting in a CVSS score of 2.1, indicating low severity. The weakness can be classified under CWE-266 and CWE-284.

Defensive priority

Given the low severity of CVE-2026-13544 and the availability of the exploit, defenders should prioritize patching or mitigating this vulnerability based on their system's exposure and risk assessment. Although the CVSS score is low, proactive defense measures are essential to prevent potential attacks.

Recommended defensive actions

• Assess the current version of Feehi CMS in use and determine if it is vulnerable.
• Apply patches or updates provided by the vendor as soon as they are available.
• Implement additional security controls to mitigate the impact of this vulnerability, such as restricting access to the /api/users endpoint.
• Monitor systems for suspicious activity related to this vulnerability.
• Consider compensating controls if patches cannot be applied immediately.

Evidence notes

The CVE-2026-13544 entry was created based on information from various sources, including Vuldb and NVD. The vulnerability details indicate that the exploit has been published, but the project maintainers have not yet responded to the issue report. The CVSS score and vector provide a quantitative assessment of the vulnerability's severity.

Sources and references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.