Numpy
By the Year
In 2024 there have been 0 vulnerabilities in Numpy . Numpy did not have any published security vulnerabilities last year.
| Year | Vulnerabilities | Average Score |
|---|---|---|
| 2024 | 0 | 0.00 |
| 2023 | 0 | 0.00 |
| 2022 | 0 | 0.00 |
| 2021 | 4 | 5.35 |
| 2020 | 0 | 0.00 |
| 2019 | 1 | 9.80 |
| 2018 | 0 | 0.00 |
It may take a day or so for new Numpy vulnerabilities to show up in the stats or in the list of recent security vulnerabilties. Additionally vulnerabilities may be tagged under a different product or component name.
Recent Numpy Security Vulnerabilities
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
CVE-2021-41495
5.3 - Medium
- December 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 missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place
NULL Pointer Dereference
Buffer overflow in the array_from_pyobj function of fortranobject.c in NumPy < 1.19, which
CVE-2021-41496
5.5 - Medium
- December 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 dimensions can only be created by an already privileged user (or internally)
Classic Buffer Overflow
An incomplete string comparison in the numpy.core component in NumPy before 1.22.0
CVE-2021-34141
5.3 - Medium
- December 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."
Incorrect Comparison
A Buffer Overflow vulnerability exists in NumPy 1.9.x in the PyArray_New
CVE-2021-33430
5.3 - Medium
- December 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 vulneraility; In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user
Classic Buffer Overflow
An issue was discovered in NumPy 1.16.0 and earlier
CVE-2019-6446
9.8 - Critical
- January 16, 2019
An issue was discovered in NumPy 1.16.0 and earlier. 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 behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources
Marshaling, Unmarshaling
