CWE-434

What is CWE-434 (Unrestricted Upload of File with Dangerous Type)?

AI-generated file upload handlers often lack file type validation, size limits, and proper storage configuration, enabling arbitrary file upload attacks.

Vulnerability Insights

In the context of vulnerabilities in ai-generated code, this vulnerability poses significant risk because compiled binaries and complex AI logic cannot be easily patched without vendor cooperation. Organizations relying on third-party software must use structural analysis tools to detect these flaws.

Impact on Systems

• Remote Code Execution (RCE): Uploading and executing a web shell
• Malware Distribution: Hosting malicious payloads for other users to download
• Defacement: Overwriting critical application files

Real-World Attack Scenario

An attacker targets an avatar upload feature. Instead of an image, they upload a .php script containing a web shell. The server places the file in a publicly accessible uploads/ directory without altering its extension. The attacker then navigates to domain.com/uploads/webshell.php, forcing the server to execute their malicious script, leading to full server compromise.

Code Examples

Vulnerable Implementation

// VULNERABLE: Moves the uploaded file based purely on the supplied filename
$target_path = "uploads/" . basename($_FILES['uploadedfile']['name']);
move_uploaded_file($_FILES['uploadedfile']['tmp_name'], $target_path);

Secure Alternative

// SECURE: Validates extension, renames file, stores outside web root
$ext = pathinfo($_FILES['uploadedfile']['name'], PATHINFO_EXTENSION);
if (in_array($ext, ['jpg', 'png'])) {
    $new_name = uniqid() . "." . $ext;
    move_uploaded_file($_FILES['uploadedfile']['tmp_name'], "/safe/outside/webdir/" . $new_name);
}

Remediation

Ensure robust input validation, boundary checking, and adherence to secure architecture frameworks when designing AI-Generated Code solutions. Use automated code scanning or binary analysis to detect flaws early in the SDLC.