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Potential sensitive information disclosed in error reports

Low severity GitHub Reviewed Published Apr 1, 2021 in ubernostrum/django-registration • Updated Sep 16, 2024

Package

pip django-registration (pip)

Affected versions

< 3.1.2

Patched versions

3.1.2

Description

django-registration is a user-registration application for Django.

Impact

The django-registration package provides tools for implementing user-account registration flows in the Django web framework. In django-registration prior to 3.1.2, the base user-account registration view did not properly apply filters to sensitive data, with the result that sensitive data could be included in error reports rather than removed automatically by Django.

Triggering this requires the following conditions:

  • A site is using django-registration < 3.1.2
  • The site has detailed error reports (such as Django's emailed error reports to site staff/developers) enabled
  • A server-side error (HTTP 5xx) occurs during an attempt by a user to register an account

Under these conditions, recipients of the detailed error report will see all submitted data from the account-registration attempt, which may include the user's proposed credentials (such as a password).

Patches

As of version 3.1.2, django-registration properly applies Django's sensitive_post_parameters() decorator to the base user-registration view, which will cause all data from the HTTP request body to be filtered from detailed error reports in the event of a server-side crash during user account registration.

Note that as applied, this filters all HTTP request data from error reports. To selectively allow some fields but not others, see Django's own documentation (in references) and the notes below for how to apply sensitive_post_parameters() manually to a particular codebase's RegistrationView subclass(es).

Workarounds

Users who cannot upgrade quickly can apply the django.views.decorators.debug.sensitive_post_parameters() decorator to their own registration views. The decorator should be applied on the dispatch() method of the appropriate RegistrationView class, using Django's method_decorator() helper. For example:

from django.utils.decorators import method_decorator
from django.views.decorators.debug import sensitive_post_parameters

from django_registration.views import RegistrationView

class MyRegistrationView(RegistrationView):
    """
    A RegistrationView subclass manually protected against sensitive information disclosure
    in error reports.

    """
    @method_decorator(sensitive_post_parameters())
    def dispatch(self, *args, **kwargs):
        return super().dispatch(*args, **kwargs)

References

References

Reviewed Apr 1, 2021
Published by the National Vulnerability Database Apr 1, 2021
Published to the GitHub Advisory Database Apr 6, 2021
Last updated Sep 16, 2024

Severity

Low

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements Present
Privileges Required High
User interaction Passive
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability None
Subsequent System Impact Metrics
Confidentiality Low
Integrity Low
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:P/PR:H/UI:P/VC:N/VI:N/VA:N/SC:L/SI:L/SA:N

EPSS score

0.054%
(24th percentile)

CVE ID

CVE-2021-21416

GHSA ID

GHSA-58c7-px5v-82hh

Credits

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