CVE-2003-0973
Denial of service in mod_python (3.0.x < 3.0.4, 2.7.x < 2.7.9)
- CVSS 5.0
- CWE-400: Uncontrolled Resource Consumption
- Resource Management
- Remote
Unknown vulnerability in mod_python 3.0.x before 3.0.4, and 2.7.x before 2.7.9, allows remote attackers to cause a denial of service (httpd crash) via a certain query string.
- CVSS base score
- 5.0
- Published
- 2003-12-15
- OWASP
- A03 Injection
- 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 to mod_python version 3.0.4 or 2.7.9 or higher
Vulnerable code sample
from mod_python import apache
def handler(req):
query_string = req.args
if query_string:
req.write("Query string received: {}".format(query_string))
else:
req.write("No query string provided.")
return apache.OKPatched code sample
from mod_python import apache
def handler(req):
try:
query_string = req.args
if not query_string:
raise ValueError("Empty query string")
max_length = 1024
if len(query_string) > max_length:
raise ValueError("Query string too long")
req.write("Query string processed successfully.")
except Exception as e:
req.log_error("Error processing request: {}".format(e))
req.status = apache.HTTP_BAD_REQUEST
req.write("Bad Request: {}".format(e))
return apache.OKCite this entry
@misc{vaitp:cve20030973,
title = {{Denial of service in mod_python (3.0.x < 3.0.4, 2.7.x < 2.7.9)}},
author = {Bogaerts, Fr\'ed\'eric and Ivaki, Naghmeh and Fonseca, Jos\'e},
year = {2003},
note = {VAITP Python Vulnerability Dataset, entry CVE-2003-0973},
howpublished = {\url{https://netpack.pt/vaitp/vulnerability/CVE-2003-0973/}}
}
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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