3291 matches found
CVE-2025-55552
pytorch v2.8.0 was discovered to display unexpected behavior when the components torch.rot90 and torch.randnlike are used together...
CVE-2025-55554
pytorch v2.8.0 was discovered to contain an integer overflow in the component torch.nantonum-.long...
CVE-2025-55558
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...
UBUNTU-CVE-2025-55553
A syntax error in the component proxytensor.py of pytorch v2.7.0 allows attackers to cause a Denial of Service DoS...
UBUNTU-CVE-2025-55558
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...
UBUNTU-CVE-2025-55554
pytorch v2.8.0 was discovered to contain an integer overflow in the component torch.nantonum-.long...
UBUNTU-CVE-2025-55552
pytorch v2.8.0 was discovered to display unexpected behavior when the components torch.rot90 and torch.randnlike are used together...
UBUNTU-CVE-2025-55560
An issue in pytorch v2.7.0 can lead to a Denial of Service DoS when a PyTorch model consists of torch.Tensor.tosparse and torch.Tensor.todense and is compiled by Inductor...
UBUNTU-CVE-2025-55557
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...
Always-Incorrect Control Flow Implementation
Overview Affected versions of this package are vulnerable to Always-Incorrect Control Flow Implementation when compiling model with torch.rot90 and torch.randnlike functions while backend="aoteagerdecomppartition". An attacker can cause unexpected behavior or potentially manipulate outputs by...
Improper Validation of Syntactic Correctness of Input
Overview Affected versions of this package are vulnerable to Improper Validation of Syntactic Correctness of Input in the torch.Tensor.random function when a model is compiled with Inductor. An attacker can cause the application to crash or become unresponsive by triggering a syntax error...
Improper Handling of Undefined Values
Overview Affected versions of this package are vulnerable to Improper Handling of Undefined Values in the torch.cummin component when compiling a model with Inductor. An attacker can cause the application to crash or become unresponsive by submitting a specially crafted model that triggers a name...
PYSEC-2025-203
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...
DEBIAN-CVE-2025-55551
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...
PYSEC-2025-203
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...
AZL-68100 CVE-2025-55551 affecting package pytorch 2.2.2-17
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...
AZL-68117 CVE-2025-55551 affecting package pytorch 2.0.0-14
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...
DEBIAN-CVE-2025-46153
PyTorch before 3.7.0 has a bernoullip decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallbackrandom=True...
PYSEC-2025-201
In PyTorch before 2.7.0, bitwiserightshift produces incorrect output for certain out-of-bounds values of the "other" argument...
PYSEC-2025-202
PyTorch before 3.7.0 has a bernoullip decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallbackrandom=True...