CWE-459: Incomplete Cleanup

What is Incomplete Cleanup?

• Overview: Incomplete Cleanup occurs when a software application fails to properly remove temporary or auxiliary resources after usage, which can lead to resource leaks and potential security vulnerabilities.

• Exploitation Methods:

• Attackers can exploit this vulnerability by accessing residual data left in temporary files or memory, leading to unauthorized information disclosure.
• Common attack patterns include analyzing leftover artifacts that may contain sensitive information or leveraging resource exhaustion to degrade application performance.

• Security Impact:

• Direct consequences include unauthorized access to sensitive data and potential information leakage.
• Potential cascading effects include system instability, performance degradation, and increased attack surface for other vulnerabilities.
• Business impact may involve data breaches, compliance violations, and loss of customer trust.

• Prevention Guidelines:

• Specific code-level fixes involve ensuring that all temporary resources are explicitly deleted or released after use, such as closing file handles and clearing memory buffers.
• Security best practices include implementing regular resource cleanup routines and using secure functions for handling temporary data.
• Recommended tools and frameworks include static code analysis tools to identify incomplete cleanup patterns and memory management libraries that automatically manage resource deallocation.

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Technical Details

Likelihood of Exploit: Not specified

Affected Languages: Not Language-Specific

Affected Technologies: Not specified

Vulnerable Code Example

import os
import tempfile

def process_data(data):
    # Create a temporary file to process data
    temp_file = tempfile.NamedTemporaryFile(delete=False)  # Temporary file is not set to delete automatically
    try:
        temp_file.write(data.encode('utf-8'))
        temp_file.seek(0)
        # Process data from temp file
        # ... some processing logic ...
    finally:
        temp_file.close()
    # Temporary file is not deleted, leading to incomplete cleanup
    # This can leave behind files with sensitive data

Explanation:

• Vulnerability: The temporary file is created with delete=False, and no explicit deletion is performed after its use. This results in leftover files on the disk.
• Impact: Accumulation of temporary files can lead to disk space issues and potential security risks if the files contain sensitive data and are accessed by unauthorized users.

How to fix Incomplete Cleanup?

To properly fix this vulnerability:

• Use the delete=True parameter of NamedTemporaryFile, which ensures the file is automatically deleted when closed.
• Alternatively, explicitly delete the temporary file using os.remove() within a finally block to ensure cleanup even if an exception occurs during processing.
• Ensure that cleanup operations (like file deletion) are robust and handle exceptions gracefully.

Fixed Code Example

import os
import tempfile

def process_data(data):
    # Create a temporary file to process data
    with tempfile.NamedTemporaryFile(delete=True) as temp_file:  # Temporary file will be deleted automatically
        temp_file.write(data.encode('utf-8'))
        temp_file.seek(0)
        # Process data from temp file
        # ... some processing logic ...
    # Temporary file is automatically deleted when closed

Explanation:

• Fix: Utilizing with statement with NamedTemporaryFile(delete=True) ensures that the temporary file is automatically deleted upon exiting the block.
• Improvement: This approach simplifies error handling, as the with statement ensures that the file is closed and cleaned up properly, even if an error occurs during processing.
• Best Practices: Always prefer automatic resource management techniques like context managers in Python to ensure proper resource cleanup. This reduces the risk of human error and improves code reliability.