FKIE_CVE-2025-62608
Vulnerability from fkie_nvd - Published: 2025-11-21 19:16 - Updated: 2026-10-08 10:10
Severity
Summary
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.
References
| URL | Tags | ||
|---|---|---|---|
| security-advisories@github.com | https://github.com/ml-explore/mlx/pull/1 | Issue Tracking, Patch | |
| security-advisories@github.com | https://github.com/ml-explore/mlx/pull/2 | Issue Tracking, Patch | |
| security-advisories@github.com | https://github.com/ml-explore/mlx/security/advisories/GHSA-w6vg-jg77-2qg6 | Exploit, Vendor Advisory |
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| ml-explore | mlx | * |
{
"affected": [
{
"affectedData": [
{
"product": "mlx",
"vendor": "ml-explore",
"versions": [
{
"status": "affected",
"version": "\u003c 0.29.4"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"configurations": [
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"matchCriteriaId": "C62C2D2D-92D7-4480-BDB9-56CECD1626E7",
"versionEndExcluding": "0.29.4",
"vulnerable": true
}
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],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "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."
},
{
"lang": "es",
"value": "MLX es un framework de arrays para aprendizaje autom\u00e1tico en silicio de Apple. Antes de la versi\u00f3n 0.29.4, existe un desbordamiento de b\u00fafer de mont\u00f3n en mlx::core::load() al analizar archivos NumPy .npy maliciosos. Un archivo controlado por el atacante causa una lectura fuera de l\u00edmites de 13 bytes, lo que lleva a un fallo o revelaci\u00f3n de informaci\u00f3n. Este problema ha sido parcheado en la versi\u00f3n 0.29.4."
}
],
"id": "CVE-2025-62608",
"lastModified": "2026-10-08T10:10:00.227",
"metrics": {
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"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
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"modifiedAttackVector": "NOT_DEFINED",
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"modifiedSubAvailabilityImpact": "NOT_DEFINED",
"modifiedSubConfidentialityImpact": "NOT_DEFINED",
"modifiedSubIntegrityImpact": "NOT_DEFINED",
"modifiedUserInteraction": "NOT_DEFINED",
"modifiedVulnAvailabilityImpact": "NOT_DEFINED",
"modifiedVulnConfidentialityImpact": "NOT_DEFINED",
"modifiedVulnIntegrityImpact": "NOT_DEFINED",
"privilegesRequired": "NONE",
"providerUrgency": "NOT_DEFINED",
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"subConfidentialityImpact": "NONE",
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"valueDensity": "NOT_DEFINED",
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"role": "CISA Coordinator",
"timestamp": "2025-11-21T19:09:52.499633Z",
"version": "2.0.3"
}
}
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"published": "2025-11-21T19:16:02.267",
"references": [
{
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"type": "Secondary"
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}
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
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The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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