CVE-2024-36743 in Oneflow
Summary
by MITRE • 06/06/2024
An issue in OneFlow-Inc. Oneflow v0.9.1 allows attackers to cause a Denial of Service (DoS) when an empty array is processed with oneflow.dot.
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Analysis
by VulDB Data Team • 06/07/2024
The vulnerability identified as CVE-2024-36743 affects OneFlow-Inc. Oneflow version 0.9.1 and represents a denial of service condition that occurs when the oneflow.dot function processes empty arrays. This issue demonstrates a fundamental flaw in input validation and error handling within the deep learning framework's tensor operations. The vulnerability stems from the absence of proper boundary checks when executing dot product calculations on empty array inputs, which can lead to system instability and service disruption.
From a technical perspective, the flaw manifests when the oneflow.dot operation receives empty arrays as input parameters, causing the underlying computational graph to fail during execution. This failure typically results in memory access violations, null pointer dereferences, or other runtime exceptions that terminate the application process. The vulnerability aligns with CWE-476 which addresses null pointer dereference conditions, and potentially CWE-129 which covers improper validation of array indices. The issue represents a classic example of insufficient input sanitization where the system fails to properly handle edge cases in its mathematical operations.
The operational impact of this vulnerability extends beyond simple service interruption as it can be exploited by malicious actors to disrupt machine learning workflows and training processes. In production environments where OneFlow is used for automated model training or inference, an attacker could repeatedly submit empty array inputs to the dot operation, causing repeated service outages and potentially leading to resource exhaustion. This makes the vulnerability particularly dangerous in cloud-based machine learning platforms or containerized environments where multiple users share computational resources.
Mitigation strategies should focus on implementing comprehensive input validation at the API level before executing dot product operations. The recommended approach includes adding explicit checks for empty array conditions and returning appropriate error codes or exceptions rather than allowing the system to crash. Security measures should also incorporate proper error handling mechanisms that prevent cascading failures and implement rate limiting to prevent abuse of the vulnerable function. Organizations should consider updating to patched versions of OneFlow as soon as available, while also implementing monitoring systems to detect unusual patterns of empty array submissions that could indicate exploitation attempts. The vulnerability highlights the importance of robust error handling in mathematical computing libraries and demonstrates how seemingly benign operations can become security risks when proper input validation is omitted. This issue aligns with ATT&CK technique T1499.004 which covers network denial of service attacks and emphasizes the need for resilient system design in artificial intelligence frameworks.