彙總 numpy 相關全部產品的 CVE 與安全漏洞情報，包括 CVSS、EPSS、公開時間與漏洞情報資料。
歷史漏洞主要涉及 緩衝區溢位與路徑處理缺陷 等問題，部分漏洞可能導致 異常行為，並影響 軟體部署與生產負載 相關場景。
相關漏洞資料主要來源於公開漏洞披露與安全公告，可用於評估歷史漏洞暴露面與修補優先順序。
| CVE | 摘要 | 來源 | 最高 CVSS | EPSS % | 公開時間 | 更新時間 |
|---|---|---|---|---|---|---|
| CVE-2021-41496 | 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) | [email protected] | 5.5 | 0.37% | 2021-12-17 | 2024-11-21 |
| CVE-2021-41495 | 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 | [email protected] | 5.3 | 1.15% | 2021-12-17 | 2024-11-21 |
| CVE-2021-34141 | 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." | [email protected] | 5.3 | 1.56% | 2021-12-17 | 2024-11-21 |
| CVE-2021-33430 | 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 | [email protected] | 5.3 | 1.07% | 2021-12-17 | 2024-11-21 |
| CVE-2019-6446 | 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 behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. | [email protected] | 9.8 | 17.08% | 2019-01-16 | 2025-07-21 |
| CVE-2014-1859 | (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. | [email protected] | 5.5 | 0.48% | 2018-01-08 | 2024-11-21 |
| CVE-2014-1858 | __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. | [email protected] | 5.5 | 0.46% | 2018-01-08 | 2024-11-21 |
| CVE-2017-12852 | 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. | [email protected] | 7.5 | 2.68% | 2017-08-15 | 2026-05-13 |