CVE-2011-4137
Django URLField verify_exists DoS vulnerability
- CVSS 5.0
- CWE-399
- Resource Management
- Remote
The verify_exists functionality in the URLField implementation in Django before 1.2.7 and 1.3.x before 1.3.1 relies on Python libraries that attempt access to an arbitrary URL with no timeout, which allows remote attackers to cause a denial of service (resource consumption) via a URL associated with (1) a slow response, (2) a completed TCP connection with no application data sent, or (3) a large amount of application data, a related issue to CVE-2011-1521.
- CWE
- CWE-399
- CVSS base score
- 5.0
- Published
- 2011-10-19
- OWASP
- A10 Server Side Request Forgery (SSRF)
- Orthogonal defect classification
- Function
- Code defect classification
- Incorrect Functionality
- Category
- Resource Management
- Subcategory
- Resource Exhaustion
- Accessibility scope
- Remote
- Impact
- Denial of Service (DoS)
- Fixed by upgrading
- Yes
Solution
Update Django to version 1.2.7 or 1.3.1 or higher.
Vulnerable code sample
import urllib2
class URLField(models.URLField):
def verify_exists(self, value):
response = urllib2.urlopen(value)
if response.getcode() != 200:
raise ValidationError(f'URL does not exist: {value}')Patched code sample
import requests
from django.core.exceptions import ValidationError
from django.db import models
class URLField(models.URLField):
def verify_exists(self, value):
try:
response = requests.head(value, timeout=5)
if response.status_code != 200:
raise ValidationError(f'URL does not exist: {value}')
except requests.exceptions.RequestException as e:
raise ValidationError(f'Invalid URL: {value} - {str(e)}')Cite this entry
@misc{vaitp:cve20114137,
title = {{Django URLField verify_exists DoS vulnerability}},
author = {Bogaerts, Fr\'ed\'eric and Ivaki, Naghmeh and Fonseca, Jos\'e},
year = {2011},
note = {VAITP Python Vulnerability Dataset, entry CVE-2011-4137},
howpublished = {\url{https://netpack.pt/vaitp/vulnerability/CVE-2011-4137/}}
}
Introducing the "VAITP dataset": a specialized repository of Python vulnerabilities and patches, meticulously compiled for the use of the security research community. As Python's prominence grows, understanding and addressing potential security vulnerabilities become crucial. Crafted by and for the cybersecurity community, this dataset offers a valuable resource for researchers, analysts, and developers to analyze and mitigate the security risks associated with Python. Through the comprehensive exploration of vulnerabilities and corresponding patches, the VAITP dataset fosters a safer and more resilient Python ecosystem, encouraging collaborative advancements in programming security.
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