PyPI package
numpy
pkg:pypi/numpy
Vulnerabilities (8)
| CVE | Sev | CVSS | KEV | Affected versions | Fixed in | Published | Description |
|---|---|---|---|---|---|---|---|
| CVE-2021-41496 | — | < 1.19 | 1.19 | Dec 17, 2021 | Buffer overflow in the array_from_pyobj function of fortranobject.c in NumPy < 1.19, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimens | ||
| CVE-2021-41495 | — | < 1.19 | 1.19 | Dec 17, 2021 | Null Pointer Dereference vulnerability exists in numpy.sort in NumPy < and 1.19 in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. NOTE: While correct that validation is mi | ||
| CVE-2021-34141 | — | < 1.22 | 1.22 | Dec 17, 2021 | An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless." | ||
| CVE-2021-33430 | — | >= 1.9.0, < 1.21 | 1.21 | Dec 17, 2021 | A Buffer Overflow vulnerability exists in NumPy 1.9.x in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a v | ||
| CVE-2019-6446 | — | <= 1.16.0 | — | Jan 16, 2019 | An issue was discovered in NumPy before 1.16.3. 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. NOTE: third parties dispute this issue because it is a behavio | ||
| CVE-2014-1859 | — | < 1.8.1 | 1.8.1 | Jan 8, 2018 | (1) core/tests/test_memmap.py, (2) core/tests/test_multiarray.py, (3) f2py/f2py2e.py, and (4) lib/tests/test_io.py in NumPy before 1.8.1 allow local users to write to arbitrary files via a symlink attack on a temporary file. | ||
| CVE-2014-1858 | — | < 1.8.1 | 1.8.1 | Jan 8, 2018 | __init__.py in f2py in NumPy before 1.8.1 allows local users to write to arbitrary files via a symlink attack on a temporary file. | ||
| CVE-2017-12852 | Hig | 7.5 | < 1.13.3 | 1.13.3 | Aug 15, 2017 | The numpy.pad function in Numpy 1.13.1 and older versions is missing input validation. An empty list or ndarray will stick into an infinite loop, which can allow attackers to cause a DoS attack. |
- CVE-2021-41496Dec 17, 2021affected < 1.19fixed 1.19
Buffer overflow in the array_from_pyobj function of fortranobject.c in NumPy < 1.19, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimens
- CVE-2021-41495Dec 17, 2021affected < 1.19fixed 1.19
Null Pointer Dereference vulnerability exists in numpy.sort in NumPy < and 1.19 in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. NOTE: While correct that validation is mi
- CVE-2021-34141Dec 17, 2021affected < 1.22fixed 1.22
An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless."
- CVE-2021-33430Dec 17, 2021affected >= 1.9.0, < 1.21fixed 1.21
A Buffer Overflow vulnerability exists in NumPy 1.9.x in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a v
- CVE-2019-6446Jan 16, 2019affected <= 1.16.0
An issue was discovered in NumPy before 1.16.3. 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. NOTE: third parties dispute this issue because it is a behavio
- CVE-2014-1859Jan 8, 2018affected < 1.8.1fixed 1.8.1
(1) core/tests/test_memmap.py, (2) core/tests/test_multiarray.py, (3) f2py/f2py2e.py, and (4) lib/tests/test_io.py in NumPy before 1.8.1 allow local users to write to arbitrary files via a symlink attack on a temporary file.
- CVE-2014-1858Jan 8, 2018affected < 1.8.1fixed 1.8.1
__init__.py in f2py in NumPy before 1.8.1 allows local users to write to arbitrary files via a symlink attack on a temporary file.
- affected < 1.13.3fixed 1.13.3
The numpy.pad function in Numpy 1.13.1 and older versions is missing input validation. An empty list or ndarray will stick into an infinite loop, which can allow attackers to cause a DoS attack.