CVE Vulnerabilities

CVE-2024-41991

Improper Validation of Specified Quantity in Input

Published: Aug 07, 2024 | Modified: Aug 07, 2024
CVSS 3.x
7.5
HIGH
Source:
NVD
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
CVSS 2.x
RedHat/V2
RedHat/V3
7.5 MODERATE
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Ubuntu
MEDIUM

An issue was discovered in Django 5.0 before 5.0.8 and 4.2 before 4.2.15. The urlize and urlizetrunc template filters, and the AdminURLFieldWidget widget, are subject to a potential denial-of-service attack via certain inputs with a very large number of Unicode characters.

Weakness

The product receives input that is expected to specify a quantity (such as size or length), but it does not validate or incorrectly validates that the quantity has the required properties.

Affected Software

Name Vendor Start Version End Version
Django Djangoproject 4.2 (including) 4.2.15 (excluding)
Django Djangoproject 5.0 (including) 5.0.8 (excluding)
Red Hat Ansible Automation Platform 2.4 for RHEL 8 RedHat automation-controller-0:4.5.10-1.el8ap *
Red Hat Ansible Automation Platform 2.4 for RHEL 8 RedHat python3x-django-0:4.2.15-1.el8ap *
Red Hat Ansible Automation Platform 2.4 for RHEL 9 RedHat automation-controller-0:4.5.10-1.el9ap *
Red Hat Ansible Automation Platform 2.4 for RHEL 9 RedHat python-django-0:4.2.15-1.el9ap *
Red Hat Satellite 6.15 for RHEL 8 RedHat python-django-0:4.2.15-1.el8pc *
Red Hat Satellite 6.15 for RHEL 8 RedHat python-django-0:4.2.15-1.el8pc *
Python-django Ubuntu devel *
Python-django Ubuntu esm-infra/bionic *
Python-django Ubuntu focal *
Python-django Ubuntu jammy *
Python-django Ubuntu noble *
Python-django Ubuntu oracular *
Python-django Ubuntu upstream *

Extended Description

Specified quantities include size, length, frequency, price, rate, number of operations, time, and others. Code may rely on specified quantities to allocate resources, perform calculations, control iteration, etc. When the quantity is not properly validated, then attackers can specify malicious quantities to cause excessive resource allocation, trigger unexpected failures, enable buffer overflows, etc.

Potential Mitigations

  • Assume all input is malicious. Use an “accept known good” input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.
  • When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, “boat” may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as “red” or “blue.”
  • Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code’s environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.

References