CVE-2005-1632
Arbitrary code execution in Cheetah 0.9.15 and 0.9.16 via /tmp/ directory modules
- CVSS 7.2
- CWE-426: Untrusted Search Path
- Configuration Issues
- Local
Cheetah 0.9.15 and 0.9.16 searches the /tmp directory for modules before using the paths in the PYTHONPATH variable, which allows local users to execute arbitrary code via a malicious module in /tmp/.
- CVSS base score
- 7.2
- Published
- 2005-05-17
- OWASP
- A05 Security Misconfiguration
- Orthogonal defect classification
- Build/Package/Merge
- Code defect classification
- Packaging Issues
- Category
- Configuration Issues
- Subcategory
- Dynamic Link Library (DLL) Loading Issues
- Accessibility scope
- Local
- Impact
- Arbitrary Code Execution
- Fixed by upgrading
- Yes
Solution
Update to Cheetah version 2.5.6 or higher
Vulnerable code sample
import sys
import os
def modified_import(module_name):
tmp_path = '/tmp'
if os.path.isdir(tmp_path):
sys.path.insert(0, tmp_path)
module = __import__(module_name)
return module
if __name__ == "__main__":
module_name = "example_module"
modified_import(module_name)Patched code sample
import sys
import os
def modified_import(module_name):
python_path = os.environ.get('PYTHONPATH', '').split(os.pathsep)
filtered_paths = [path for path in python_path if os.path.isabs(path) and path != '/tmp']
for path in filtered_paths:
sys.path.insert(0, path)
try:
module = __import__(module_name)
return module
finally:
sys.path.pop(0)
if __name__ == "__main__":
module_name = "example_module"
modified_import(module_name)Cite this entry
@misc{vaitp:cve20051632,
title = {{Arbitrary code execution in Cheetah 0.9.15 and 0.9.16 via /tmp/ directory modules}},
author = {Bogaerts, Fr\'ed\'eric and Ivaki, Naghmeh and Fonseca, Jos\'e},
year = {2005},
note = {VAITP Python Vulnerability Dataset, entry CVE-2005-1632},
howpublished = {\url{https://netpack.pt/vaitp/vulnerability/CVE-2005-1632/}}
}
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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