CVE-2024-10713 in hyperlpr
Summary
by MITRE • 03/20/2025
A vulnerability in szad670401/hyperlpr v3.0 allows for a Denial of Service (DoS) attack. The server fails to handle excessive characters appended to the end of multipart boundaries, regardless of the character used. This flaw can be exploited by sending malformed multipart requests with arbitrary characters at the end of the boundary, leading to excessive resource consumption and a complete denial of service for all users. The vulnerability is unauthenticated, meaning no user login or interaction is required for an attacker to exploit this issue.
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Analysis
by VulDB Data Team • 10/15/2025
The vulnerability identified as CVE-2024-10713 affects the szad670401/hyperlpr v3.0 software, which is a license plate recognition system that processes multipart form data for image uploads. This particular flaw represents a classic denial of service condition that can be exploited through improper handling of multipart boundary parsing. The affected system fails to properly validate or limit the length of characters that can be appended to multipart boundaries, creating a scenario where malicious actors can craft specially formatted requests that cause the server to consume excessive computational resources. This issue resides within the HTTP request processing layer of the application, specifically in how it interprets and processes boundary delimiters used in multipart/form-data content types.
The technical implementation of this vulnerability stems from inadequate input validation and boundary parsing logic within the multipart request handling mechanism. When a multipart request is received, the system attempts to parse boundary markers to separate different parts of the form data. However, the current implementation does not enforce reasonable limits on boundary length or character validation, allowing attackers to append arbitrary sequences of characters to boundary definitions. This flaw can be categorized under CWE-129 Input Validation and CWE-400 Uncontrolled Resource Consumption, as the system fails to properly validate input boundaries and subsequently consumes excessive resources during parsing operations. The vulnerability operates at the application layer and can be classified under ATT&CK technique T1499.004 for Network Denial of Service and T1595.001 for Obfuscated Files or Information.
The operational impact of this vulnerability is significant as it allows for complete service disruption without requiring any authentication or prior access to the system. An attacker can simply craft a malformed multipart request containing excessive characters appended to boundary definitions and send it to the target server. The server processes this malformed data by attempting to parse and validate the boundary, leading to resource exhaustion through memory allocation, CPU consumption, or both. This resource consumption can occur rapidly and can affect all users of the service simultaneously, making it particularly dangerous in production environments. The unauthenticated nature of the exploit means that any external party can initiate the denial of service attack, potentially causing widespread disruption to legitimate users of the license plate recognition system.
Mitigation strategies for this vulnerability should focus on implementing proper boundary validation and resource limiting mechanisms within the multipart request processing. Organizations should enforce strict limits on boundary character lengths and reject requests containing excessively long boundary definitions. The system should implement input sanitization that validates boundary markers against predefined character sets and maximum length constraints. Additionally, rate limiting and request size limitations should be implemented to prevent resource exhaustion attacks. The fix should involve updating the multipart parsing logic to properly handle boundary definitions and reject malformed requests before they can consume system resources. Security teams should also consider implementing monitoring and alerting for unusual patterns in multipart request processing that could indicate exploitation attempts. Regular security updates and input validation improvements are essential to prevent similar vulnerabilities in future versions of the software.