Fixing Security Bugs

[isabellaaas]

Hi, I found a few security bugs in your code, hope this helps you)

Command Injection

The product constructs all or part of an OS command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended OS command when it is sent to a downstream component.This could allow attackers to execute unexpected, dangerous commands directly on the operating system.

lines of code where the bug was found:

20       GANFactory.factories[gan_id] = \                                                 
21       eval(gan_id + '.Factory()')
22       return GANFactory.factories[gan_id].create(net_d, criterion)

Оne of the possible solutions:

# Assuming gan_id is a known identifier, not influenced by external input
GANFactory.factories[gan_id] = GANFactory.get_factory(gan_id)
return GANFactory.factories[gan_id].create(net_d, criterion)

I replaced eval() with a safer method, assuming get_factory() is a predefined method that returns the appropriate factory based on gan_id. This avoids the security risk associated with eval()."

Use of weak SHA1 hash for security.

It uses a broken or insecure cryptographic algorithm or protocol. Insecure cryptography can be used to disclose confidential information, modify data in unexpected ways, spoof other users' or devices' identities, or otherwise affect.

The use of a non-standard or deliberately insecure algorithm is dangerous because a determined adversary can break the algorithm and compromise any data that has been protected.

lines of code where the bug was found:

34          names = ''.join(map(os.path.basename, (path_a, path_b)))
35          return sha1(f'{names}_{salt}'.encode()).hexdigest()"   

Оne of the possible solutions:
import os
import hashlib

def generate_hash(path_a, path_b, salt):
    # Ensure paths are encoded before concatenation
    names = ''.join(map(lambda p: os.path.basename(p).encode(), (path_a, path_b)))
    
    # Use hashlib to generate the hash
    return hashlib.sha1(f'{names}_{salt}'.encode()).hexdigest()

The use of the assert statement without proper handling of exceptional conditions.
The product does not properly anticipate or handle exceptional conditions that rarely occur during normal operation of the product.The issue arises when exceptional conditions, which are not expected to occur during normal operation, do happen. Since assert statements are omitted in optimized code, the product lacks proper anticipation and handling of these exceptional conditions.

lines of code where the bug was found:
62 assert len(files_a) == len(files_b)

Оne of the possible solutions:
"To address the issue and enhance code robustness, replace the assert statement with explicit exception handling. This will allow for proper anticipation and handling of exceptional conditions. For example:

if len(files_a) != len(files_b):
    raise ValueError(""Number of files in files_a does not match files_b"")

Use of unsafe yaml load
Input validation is a frequently-used technique for checking potentially dangerous inputs in order to ensure that the inputs are safe for processing within the code, or when communicating with other components. When software does not validate input properly, an attacker is able to craft the input in a form that is not expected by the rest of the application. This will lead to parts of the system receiving unintended input, which may result in altered control flow, arbitrary control of a resource, or arbitrary code execution.

lines of code where the bug was found:

18  with open('config/config.yaml',encoding='utf-8') as cfg:
19   config = yaml.load(cfg, Loader=yaml.FullLoader)
20   model = get_generator(model_name or config['model'])"

Оne of the possible solutions:
"To address this, you can replace yaml.load with the safer alternative yaml.safe_load:

import yaml
# ...
with open('config/config.yaml', encoding='utf-8') as cfg:
    config = yaml.safe_load(cfg)
model = get_generator(model_name or config['model'])

By making this change, we mitigate the risk of code execution through malicious YAML input and enhance the overall security of the code. We have always to use safe_load when dealing with untrusted YAML data to prevent security vulnerabilities."

Assumption of Parameters
The assertion assumes that num_classes should always be equal to settings['num_classes'] without comprehensive validation. If this assumption is not met during runtime, the assertion will fail, potentially leading to unexpected behavior, errors, or even security issues.

lines of code where the bug was found:

360     def initialize_pretrained_model(model, num_classes, settings):
361     assert num_classes == settings['num_classes'], \
362    'num_classes should be {}, but is {}'.format(
363     settings['num_classes'], num_classes)
364    model.load_state_dict(model_zoo.load_url(settings['url']))

Оne of the possible solutions:
"We need to Implement explicit input validation to ensure that num_classes matches the expected value in settings['num_classes']. If a mismatch occurs, raise a clear and informative exception instead of relying solely on an assert statement.

Revised Code:

def initialize_pretrained_model(model, num_classes, settings):
    expected_num_classes = settings.get('num_classes')
    
    if num_classes != expected_num_classes:
        raise ValueError(f""Expected num_classes: {expected_num_classes}, but received: {num_classes}"")
    
    model.load_state_dict(model_zoo.load_url(settings['url']))

This revised code incorporates explicit input validation using a ValueError exception, providing clearer information about the mismatch and improving overall code robustness."

I hope this helps you! Good luck!