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Archiwum podatności 71 757
Simple Colorbox <= 1.6.1 - Authenticated (Contributor+) Stored Cross-Site Scripting
WP Recipe Maker < 10.1.0 - Unauthenticated Arbitrary Shortcode Execution
Yext <= 1.1.3 - Missing Authorization
Lenix scss compiler <= 1.2 - Authenticated (Administrator+) Stored Cross-Site Scripting
HivePress Claim Listings <= 1.1.3 - Missing Authorization
Liferay Portal and DXP vulnerable to a memory leak
TweetThis Shortcode <= 1.8.0 - Authenticated (Contributor+) Stored Cross-Site Scripting
Markdown Shortcode <= 0.2.1 - Authenticated (Contributor+) Stored Cross-Site Scripting
Zephyr Project Manager <= 3.3.202 - Authenticated (Admin+) Stored Cross-Site Scripting
Snow Monkey <= 29.1.5 - Unauthenticated Blind Server-Side Request Forgery
An issue in pytorch v2.7.0 can lead to a Denial of Service (DoS) when a PyTorch model consists of torch.Tensor.to_sparse() and torch.Tensor.to_dense() and is compiled by Inductor.
A buffer overflow occurs in pytorch v2.7.0 when a PyTorch model consists of torch.nn.Conv2d, torch.nn.functional.hardshrink, and torch.Tensor.view-torch.mv() and is compiled by Inductor, leading to a
A Name Error occurs in pytorch v2.7.0 when a PyTorch model consists of torch.cummin and is compiled by Inductor, leading to a Denial of Service (DoS).
pytorch v2.8.0 was discovered to contain an integer overflow in the component torch.nan_to_num-.long().
A syntax error in the component proxy_tensor.py of pytorch v2.7.0 allows attackers to cause a Denial of Service (DoS).
pytorch v2.8.0 was discovered to display unexpected behavior when the components torch.rot90 and torch.randn_like are used together.
Featured Image from URL (FIFU) <= 5.2.7 - Missing Authorization to Password Protected Post Disclosure
cors-anywhere vulnerable to server-side request forgery
apidoc-core is vulnerable to prototype pollution
dref is vulnerable to prototype pollution
An issue in the component torch.linalg.lu of pytorch v2.8.0 allows attackers to cause a Denial of Service (DoS) when performing a slice operation.
PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d,
In PyTorch before 2.7.0, bitwise_right_shift produces incorrect output for certain out-of-bounds values of the "other" argument.
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Po podłączeniu integracji DockRay i włączeniu raportowania oprogramowania DockRay porównuje zgłoszone wersje komponentów ze znanymi podatnościami i powiadamia o potwierdzonych dopasowaniach. Zakres zależy od obsługiwanej technologii i dostępnych biuletynów.