CVE-2025-0207

Jan. 10, 2025, 9:27 p.m.

7.3
High

Description

A vulnerability, which was classified as critical, has been found in code-projects Online Shoe Store 1.0. Affected by this issue is some unknown functionality of the file /function/login.php. The manipulation of the argument password leads to sql injection. The attack may be launched remotely. The exploit has been disclosed to the public and may be used.

Product(s) Impacted

Vendor Product Versions
Code-projects
  • Online Shoe Store
  • 1.0

Weaknesses

CWE-74
Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection')
The product constructs all or part of a command, data structure, or record using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify how it is parsed or interpreted when it is sent to a downstream component.
CWE-89
Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')
The product constructs all or part of an SQL command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended SQL command when it is sent to a downstream component.

*CPE(s)

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a code-projects online_shoe_store 1.0 / / / / / / /

CVSS Score

7.3 / 10

CVSS Data

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Privileges Required: NONE
  • Scope: UNCHANGED
  • Confidentiality Impact: LOW
  • Integrity Impact: LOW
  • Availability Impact: LOW
  • View Vector String

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

Date

  • Published: Jan. 4, 2025, 1:15 p.m.
  • Last Modified: Jan. 10, 2025, 9:27 p.m.

Status : Analyzed

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

More info

Source

cna@vuldb.com

*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.