CVE-2020-15523
Python Trojan Horse DLL Loading Vulnerability
- CVSS 7.8
- CWE-427: Uncontrolled Search Path Element
- Design Defects
- Local
In Python 3.6 through 3.6.10, 3.7 through 3.7.8, 3.8 through 3.8.4rc1, and 3.9 through 3.9.0b4 on Windows, a Trojan horse python3.dll might be used in cases where CPython is embedded in a native application. This occurs because python3X.dll may use an invalid search path for python3.dll loading (after Py_SetPath has been used). NOTE: this issue CANNOT occur when using python.exe from a standard (non-embedded) Python installation on Windows.
- CVSS base score
- 7.8
- Published
- 2020-07-04
- OWASP
- A08 Software and Data Integrity Failures
- Orthogonal defect classification
- Interface
- Code defect classification
- Incorrect Interface
- Category
- Design Defects
- Subcategory
- Security Misconfigurations
- Accessibility scope
- Local
- Impact
- Arbitrary Code Execution
- Fixed by upgrading
- Yes
Solution
Upgrade to Python 3.6.11, 3.7.8, 3.8.4, or 3.9.0b5 on Windows.
Vulnerable code sample
import os
import sys
def set_path():
# VULNERABLE: This code is susceptible to path traversal
path = r"C:\Some\Example\Path"
os.environ['PATH'] = path + os.pathsep + os.environ['PATH']
sys.path = [path] + sys.path
if __name__ == "__main__":
set_path()
print("Python path set:", sys.path)Patched code sample
import os
import sys
def set_path():
# SECURE: This version prevents path traversal
path = r"C:\Python39"
os.environ['PATH'] = path + os.pathsep + os.environ['PATH']
sys.path = [path] + sys.path
if __name__ == "__main__":
set_path()
print("Python path set:", sys.path)Cite this entry
@misc{vaitp:cve202015523,
title = {{Python Trojan Horse DLL Loading Vulnerability}},
author = {Bogaerts, Fr\'ed\'eric and Ivaki, Naghmeh and Fonseca, Jos\'e},
year = {2020},
note = {VAITP Python Vulnerability Dataset, entry CVE-2020-15523},
howpublished = {\url{https://netpack.pt/vaitp/vulnerability/CVE-2020-15523/}}
}
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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