CVE-2023-0057
Improper UI layer restriction in pyload (before 0.5.0b3.dev33) allows unauthorized access
- CVSS 6.1
- CWE-1021 Improper Restriction of Rendered UI Layers or Frames
- Input Validation and Sanitization
- Remote
Improper Restriction of Rendered UI Layers or Frames in GitHub repository pyload/pyload prior to 0.5.0b3.dev33.
- CVSS base score
- 6.1
- Published
- 2023-01-05
- OWASP
- A01 Broken Access Control
- Orthogonal defect classification
- Checking
- Code defect classification
- Missing Check
- Category
- Input Validation and Sanitization
- Subcategory
- Insecure Direct Object References (IDOR)
- Accessibility scope
- Remote
- Impact
- Unauthorized Access
- Fixed by upgrading
- Yes
Solution
Update pyload to version 0.5.0b3.dev33 or higher.
Vulnerable code sample
def calculate(expression):
"""Calculate expression - VULNERABLE to code injection"""
# VULNERABILITY: eval() executes arbitrary Python code
return eval(expression)
# Example exploitation:
# calculate("__import__('os').system('whoami')")Patched code sample
import ast
import operator
def calculate_secure(expression):
"""Securely calculate mathematical expression"""
try:
# Parse expression into AST
tree = ast.parse(expression, mode='eval')
return eval_ast_node(tree.body)
except:
return None
def eval_ast_node(node):
"""Safely evaluate AST node"""
if isinstance(node, ast.Constant):
return node.value
elif isinstance(node, ast.BinOp):
left = eval_ast_node(node.left)
right = eval_ast_node(node.right)
ops = {ast.Add: operator.add, ast.Sub: operator.sub}
return ops[type(node.op)](left, right)
else:
raise ValueError("Unsupported operation")Cite this entry
@misc{vaitp:cve20230057,
title = {{Improper UI layer restriction in pyload (before 0.5.0b3.dev33) allows unauthorized access}},
author = {Bogaerts, Fr\'ed\'eric and Ivaki, Naghmeh and Fonseca, Jos\'e},
year = {2023},
note = {VAITP Python Vulnerability Dataset, entry CVE-2023-0057},
howpublished = {\url{https://netpack.pt/vaitp/vulnerability/CVE-2023-0057/}}
}
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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