Intel

AIKIDO-2026-775417

numpy is vulnerable to Untrusted Pointer Dereference

Untrusted Pointer Dereference Pre-CVE
Found by Aikido Intel before public disclosure or CVE publication.
Published Yesterday

59

Medium Risk

This Affects:

PYTHONnumpy
1.0.0 - 2.5.2
Fixed in 2.5.3
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TL;DR

numpy.rec.fromstring and numpy.rec.fromfile build a recarray directly over a caller-supplied byte buffer or file according to a caller-supplied dtype, without checking whether that dtype contains object references. When the dtype includes reference fields, the raw buffer bytes land in memory that NumPy later treats as PyObject* pointers, so arbitrary bytes from an untrusted string or file get dereferenced and reference-counted as if they were real Python objects. Reading or garbage-collecting the resulting array can crash the process or corrupt memory. The fix rejects dtypes whose hasobject flag is set before constructing the array.

Who does this affect?

You are affected if you are using a version that falls within the vulnerable range and you call numpy.rec.fromstring or numpy.rec.fromfile with a dtype containing object/reference fields on data you do not fully control.

Background info

numpy is vulnerable to Untrusted Pointer Dereference in versions 1.0.0 - 2.5.2.

How to fix this

Upgrade the numpy library to the patch version.

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