CVE-2025-64459

Nov. 6, 2025, 7:45 p.m.

9.1
Critical

Description

An issue was discovered in 5.1 before 5.1.14, 4.2 before 4.2.26, and 5.2 before 5.2.8. The methods `QuerySet.filter()`, `QuerySet.exclude()`, and `QuerySet.get()`, and the class `Q()`, are subject to SQL injection when using a suitably crafted dictionary, with dictionary expansion, as the `_connector` argument. Earlier, unsupported Django series (such as 5.0.x, 4.1.x, and 3.2.x) were not evaluated and may also be affected. Django would like to thank cyberstan for reporting this issue.

Product(s) Impacted

Vendor Product Versions
Djangoproject
  • Django
  • <5.1.14, <4.2.26, <5.2.8

Weaknesses

Common security weaknesses mapped to this vulnerability.

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)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a djangoproject django <5.1.14 / / / / / / /
a djangoproject django <4.2.26 / / / / / / /
a djangoproject django <5.2.8 / / / / / / /

CVSS Score

9.1 / 10

CVSS Data - 3.1

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

    View Vector String

Timeline

Published: Nov. 5, 2025, 3:15 p.m.
Last Modified: Nov. 6, 2025, 7:45 p.m.

Status : Awaiting Analysis

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

More info

Source

6a34fbeb-21d4-45e7-8e0a-62b95bc12c92

*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.