CVE-2023-39660
Remote code execution via crafted prompt function request.
- CVSS 9.8
- CWE-94
- Input Validation and Sanitization
- Remote
An issue in Gaberiele Venturi pandasai v.0.8.0 and before allows a remote attacker to execute arbitrary code via a crafted request to the prompt function.
- CWE
- CWE-94
- CVSS base score
- 9.8
- Published
- 2023-08-21
- OWASP
- A01 Broken Access Control
- Orthogonal defect classification
- Function
- Code defect classification
- Incorrect Functionality
- Category
- Input Validation and Sanitization
- Subcategory
- Command Injection
- Accessibility scope
- Remote
- Impact
- Arbitrary Code Execution
- Affected component
- pandasai
- Fixed by upgrading
- Yes
Solution
Upgrade to Gaberiele Venturi pandasai v.0.8.1 or later.
Vulnerable code sample
def prompt():
"""Vulnerable function that demonstrates the security issue."""
user_input = input("Enter your command: ")
exec(user_input)
def main():
"""Vulnerable function that demonstrates the security issue."""
prompt()
if __name__ == "__main__":
main()Patched code sample
def prompt():
"""Secure function that fixes the vulnerability."""
blacklist = ["import", "os", "sys", "eval", "exec", "open", "__", "subprocess", "input", "globals", "locals"]
user_input = input("Enter your command: ")
if any(word in user_input for word in blacklist):
print("Unsafe command detected.")
return
try:
exec(user_input)
except Exception as e:
print(f"Error executing command: {e}")
def main():
"""Secure function that fixes the vulnerability."""
prompt()
if __name__ == "__main__":
main()Payload
__import__('os').system('whoami')
Cite this entry
@misc{vaitp:cve202339660,
title = {{Remote code execution via crafted prompt function request.}},
author = {Bogaerts, Fr\'ed\'eric and Ivaki, Naghmeh and Fonseca, Jos\'e},
year = {2023},
note = {VAITP Python Vulnerability Dataset, entry CVE-2023-39660},
howpublished = {\url{https://netpack.pt/vaitp/vulnerability/CVE-2023-39660/}}
}
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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