CVE-2025-62608
Unknown Unknown - Not Provided
BaseFortify

Publication date: 2025-11-21

Last updated on: 2025-12-02

Assigner: GitHub, Inc.

Description
MLX is an array framework for machine learning on Apple silicon. Prior to version 0.29.4, there is a heap buffer overflow in mlx::core::load() when parsing malicious NumPy .npy files. Attacker-controlled file causes 13-byte out-of-bounds read, leading to crash or information disclosure. This issue has been patched in version 0.29.4.
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Meta Information
Published
2025-11-21
Last Modified
2025-12-02
Generated
2026-05-07
AI Q&A
2025-11-21
EPSS Evaluated
2026-05-05
NVD
EUVD
Affected Vendors & Products
Showing 1 associated CPE
Vendor Product Version / Range
ml-explore mlx to 0.29.4 (exc)
Helpful Resources
Exploitability
CWE
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KEV
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CWE ID Description
CWE-122 A heap overflow condition is a buffer overflow, where the buffer that can be overwritten is allocated in the heap portion of memory, generally meaning that the buffer was allocated using a routine such as malloc().
Attack-Flow Graph
AI Powered Q&A
Can you explain this vulnerability to me?

This vulnerability is a heap buffer overflow in the MLX array framework for machine learning on Apple silicon. It occurs in the mlx::core::load() function when parsing malicious NumPy .npy files. The attacker can craft a file that causes a 13-byte out-of-bounds read, which can lead to a crash or information disclosure.


How can this vulnerability impact me? :

The vulnerability can cause the application using MLX to crash or potentially disclose sensitive information due to the out-of-bounds read caused by a maliciously crafted NumPy file. This could lead to denial of service or leakage of information.


What immediate steps should I take to mitigate this vulnerability?

Update the MLX array framework to version 0.29.4 or later, as this version contains the patch that fixes the heap buffer overflow vulnerability caused by parsing malicious NumPy .npy files.


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0/70
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