CVE-2026-31822

March 11, 2026, 7:32 p.m.

5.3
Medium

Description

Sylius is an Open Source eCommerce Framework on Symfony. A cross-site scripting (XSS) vulnerability exists in the shop checkout login form handled by the ApiLoginController Stimulus controller. When a login attempt fails, AuthenticationFailureHandler returns a JSON response whose message field is rendered into the DOM using innerHTML, allowing any HTML or JavaScript in that value to be parsed and executed by the browser. The issue is fixed in versions: 2.0.16, 2.1.12, 2.2.3 and above.

Product(s) Impacted

Vendor Product Versions
Sylius
  • Sylius
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-79
Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
The product does not neutralize or incorrectly neutralizes user-controllable input before it is placed in output that is used as a web page that is served to other users.

*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 sylius sylius / / / / / / / /
a sylius sylius / / / / / / / /
a sylius sylius / / / / / / / /

CVSS Score

5.3 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: NONE
  • User Interaction: PASSIVE
  • Scope:
  • Confidentiality Impact: NONE
  • Integrity Impact: NONE
  • Availability Impact: NONE
  • Exploit Maturity: NOT_DEFINED
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:N/VA:N/SC:L/SI:L/SA:N/E:X/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: March 10, 2026, 10:16 p.m.
Last Modified: March 11, 2026, 7:32 p.m.

Status : Analyzed

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.