Security Vulnerabilities
- CVEs Published In September 2025
An issue was discovered TensorFlow v2.18.0. A Denial of Service (DoS) occurs when padding is set to 'valid' in tf.keras.layers.Conv2D.
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.
Flag Forge is a Capture The Flag (CTF) platform. In versions from 2.2.0 to before 2.3.1, the FlagForge web application improperly handles session invalidation. Authenticated users can continue to access protected endpoints, such as /api/profile, even after logging out. CSRF tokens are also still valid post-logout, which can allow unauthorized actions. This issue has been patched in version 2.3.1.
Dell Cloud Disaster Recovery, version(s) prior to 19.20, contain(s) an Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection') vulnerability. A high privileged attacker with local access could potentially exploit this vulnerability to execute arbitrary commands with root privileges.
pytorch v2.8.0 was discovered to display unexpected behavior when the components torch.rot90 and torch.randn_like are used together.
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 contain an integer overflow in the component torch.nan_to_num-.long().
TensorFlow v2.18.0 was discovered to output random results when compiling Embedding, leading to unexpected behavior in the application.
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).
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 Denial of Service (DoS).