CVE-2026-2106

Feb. 7, 2026, 6:15 p.m.

5.3
Medium

Description

A vulnerability has been found in yeqifu warehouse up to aaf29962ba407d22d991781de28796ee7b4670e4. The impacted element is the function addNotice/updateNotice/deleteNotice/batchDeleteNotice of the file dataset\repos\warehouse\src\main\java\com\yeqifu\sys\controller\NoticeController.java of the component Notice Management. The manipulation leads to improper authorization. The attack can be initiated remotely. The exploit has been disclosed to the public and may be used. Continious delivery with rolling releases is used by this product. Therefore, no version details of affected nor updated releases are available. The project was informed of the problem early through an issue report but has not responded yet.

Product(s) Impacted

Vendor Product Versions
Yeqifu
  • Warehouse
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-266
Incorrect Privilege Assignment
A product incorrectly assigns a privilege to a particular actor, creating an unintended sphere of control for that 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 yeqifu warehouse / / / / / / / /

CVSS Score

5.3 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: LOW
  • User Interaction: NONE
  • Scope:
  • Confidentiality Impact: LOW
  • Integrity Impact: LOW
  • Availability Impact: LOW
  • Exploit Maturity: PROOF_OF_CONCEPT
  • CVSS:4.0/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

    View Vector String

Timeline

Published: Feb. 7, 2026, 6:15 p.m.
Last Modified: Feb. 7, 2026, 6:15 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.