Vulnerability database
Every flaw the U.S. government’s cybersecurity agency (CISA) has confirmed attackers are using, plus the new WordPress plugin and theme bugs published each day, sorted by what they mean for a small business. We refresh it twice a day. If you see something your website or office runs, tell us.
16 results
Sep 26, 2026MONAI before 1.6.0 contains an unsafe deserialization vulnerability in the NumpyReader class that unconditionally uses numpy.load with allow_pickle=True when loCVE-2026-100845 · Other software · Project-MONAI · reported by VulnCheckHigh 8.5
MONAI before 1.6.0 contains an unsafe deserialization vulnerability in the NumpyReader class that unconditionally uses numpy.load with allow_pickle=True when loading .npy and .npz files. Attackers can craft malicious .npy files with pickle payloads that execute arbitrary code when loaded through MONAI's standard data pipeline.
- Product
- MONAI
- What to do
- Apply the vendor’s update. The NVD record links to the advisory.
Full record and what to do →NVD recordgithub.comvulncheck.com
Jul 3, 2026Picklescan before 0.0.33 fails to detect the numpy.f2py.crackfortran.getlincoef gadget in pickle __reduce__ methods, allowing arbitrary code execution.CVE-2025-71372 · Other software · Picklescan · reported by VulnCheckHigh 7.6
Picklescan before 0.0.33 fails to detect the numpy.f2py.crackfortran.getlincoef gadget in pickle __reduce__ methods, allowing arbitrary code execution. Attackers can craft malicious pickle files that execute arbitrary Python code when loaded, bypassing Picklescan's safety checks and enabling supply-chain poisoning of shared model files.
- Product
- Picklescan
- What to do
- Apply the vendor’s update. The NVD record links to the advisory.
Full record and what to do →NVD recordgithub.comvulncheck.com
Jul 3, 2026picklescan before 0.0.33 fails to detect unsafe deserialization when numpy.f2py.crackfortran functions call eval on arbitrary strings.CVE-2025-71362 · Other software · picklescan · reported by VulnCheckHigh 7.6
picklescan before 0.0.33 fails to detect unsafe deserialization when numpy.f2py.crackfortran functions call eval on arbitrary strings. Attackers can embed malicious code in pickle files that executes when loaded from untrusted sources.
- Product
- picklescan
- What to do
- Apply the vendor’s update. The NVD record links to the advisory.
Full record and what to do →NVD recordgithub.comvulncheck.com
Jul 3, 2026picklescan before 0.0.33 fails to detect malicious pickle files using numpy.f2py.crackfortran.param_eval function in reduce methods, allowing attackers to bypasCVE-2025-71347 · Other software · picklescan · reported by VulnCheckHigh 7.6
picklescan before 0.0.33 fails to detect malicious pickle files using numpy.f2py.crackfortran.param_eval function in reduce methods, allowing attackers to bypass security checks. Remote attackers can embed undetected code in pickle files that executes during deserialization, enabling arbitrary code execution in applications loading untrusted pickle data.
- Product
- picklescan
- What to do
- Apply the vendor’s update. The NVD record links to the advisory.
Full record and what to do →NVD recordgithub.comvulncheck.com
Jun 30, 2026Picklescan before 0.0.25 fails to detect unsafe global functions in the Numpy library, allowing attackers to bypass static analysis and execute arbitrary code dCVE-2025-71355 · Other software · Picklescan · reported by VulnCheckHigh 7.6
Picklescan before 0.0.25 fails to detect unsafe global functions in the Numpy library, allowing attackers to bypass static analysis and execute arbitrary code during deserialization. Attackers can craft malicious pickle files using numpy.testing._private.utils.runstring within the reduce method to import dangerous libraries like os and execute arbitrary OS commands when the pickle file is loaded.
- Product
- Picklescan
- What to do
- Apply the vendor’s update. The NVD record links to the advisory.
Full record and what to do →NVD recordgithub.comvulncheck.com
Jun 23, 2026picklescan before 0.0.33 fails to detect malicious pickle files that invoke numpy.f2py.crackfortran.myeval function through the reduce method.CVE-2025-71365 · Other software · picklescan · reported by VulnCheckHigh 7.6
picklescan before 0.0.33 fails to detect malicious pickle files that invoke numpy.f2py.crackfortran.myeval function through the reduce method. Attackers can craft malicious pickle files embedding arbitrary code that evades picklescan detection and executes remote code when loaded.
- Product
- picklescan
- What to do
- Apply the vendor’s update. The NVD record links to the advisory.
Full record and what to do →NVD recordgithub.comvulncheck.com
Jun 22, 2026Picklescan before 0.0.33 fails to detect the numpy.f2py.crackfortran._eval_length gadget in pickle __reduce__ methods, allowing arbitrary code execution.CVE-2025-71339 · Other software · Picklescan · reported by VulnCheckHigh 7.6
Picklescan before 0.0.33 fails to detect the numpy.f2py.crackfortran._eval_length gadget in pickle __reduce__ methods, allowing arbitrary code execution. Attackers can craft malicious pickle files that execute arbitrary Python code when loaded by victims who trust Picklescan's safety validation.
- Product
- Picklescan
- What to do
- Apply the vendor’s update. The NVD record links to the advisory.
Full record and what to do →NVD recordgithub.comvulncheck.com
May 17, 2024joblib v1.4.2 was discovered to contain a deserialization vulnerability via the component joblib.numpy_pickle::NumpyArrayWrapper().read_array().CVE-2024-34997 · Other software · joblib_project · reported by MITREHigh 7.5
joblib v1.4.2 was discovered to contain a deserialization vulnerability via the component joblib.numpy_pickle::NumpyArrayWrapper().read_array(). NOTE: this is disputed by the supplier because NumpyArrayWrapper is only used during caching of trusted content.
- Product
- joblib
- What to do
- Apply the vendor’s update. The NVD record links to the advisory.
Dec 17, 2021Buffer 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 CVE-2021-41496 · Other software · Numpy · reported by MITREMedium 5.5
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)
- Product
- Numpy
- What to do
- Apply the vendor’s update. The NVD record links to the advisory.
Dec 17, 2021Null Pointer Dereference vulnerability exists in numpy.sort in NumPy < and 1.19 in the PyArray_DescrNew function due to missing return-value validation, whichCVE-2021-41495 · Other software · Numpy · reported by MITREMedium 5.3
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
- Product
- Numpy
- What to do
- Apply the vendor’s update. The NVD record links to the advisory.
Dec 17, 2021An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specifCVE-2021-34141 · Other software · Numpy · reported by MITREMedium 5.3
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."
- Product
- Numpy
- What to do
- Apply the vendor’s update. The NVD record links to the advisory.
Dec 17, 2021A 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) fCVE-2021-33430 · Other software · Numpy · reported by MITREMedium 5.3
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
- Product
- Numpy
- What to do
- Apply the vendor’s update. The NVD record links to the advisory.
Jan 16, 2019An issue was discovered in NumPy before 1.16.3.CVE-2019-6446 · Other software · Numpy · reported by MITRECritical 9.8
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.
- Product
- Numpy
- What to do
- Apply the vendor’s update. The NVD record links to the advisory.
Full record and what to do →NVD recordlists.opensuse.orglists.opensuse.org
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 wrCVE-2014-1859 · Other software · Numpy · reported by MITREMedium 5.5
(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.
- Product
- Numpy
- What to do
- Apply the vendor’s update. The NVD record links to the advisory.
Full record and what to do →NVD recordlists.fedoraproject.orglists.fedoraproject.org
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-2014-1858 · Other software · Numpy · reported by MITREMedium 5.5
__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.
- Product
- Numpy
- What to do
- Apply the vendor’s update. The NVD record links to the advisory.
Full record and what to do →NVD recordlists.fedoraproject.orglists.fedoraproject.org
Aug 15, 2017The numpy.pad function in Numpy 1.13.1 and older versions is missing input validation.CVE-2017-12852 · Other software · Numpy · reported by MITREHigh 7.5
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.
- Product
- Numpy
- What to do
- Apply the vendor’s update. The NVD record links to the advisory.
Where this comes from: the exploited list is CISA’s Known Exploited Vulnerabilities catalog. Everything else is the whole National Vulnerability Database, where each record is published by the team that found the bug (Wordfence, Patchstack, WPScan, the vendors themselves and others); we show who. Exploit odds are FIRST’s EPSS, updated daily. Titles and categories are ours, so check the linked record before acting on a detail. For a write-up of the big ones, see our advisories. Every vendor, and every WordPress plugin and theme with a recorded flaw, also has its own page. All of it is free to reuse as JSON, CSV or RSS.
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