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| purl | pkg:pypi/torch@2.6.0 |
| Vulnerability | Summary | Fixed by |
|---|---|---|
|
VCID-3cvu-c3jj-yyhx
Aliases: CVE-2025-55560 PYSEC-2025-209 |
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. |
Affected by 3 other vulnerabilities. |
|
VCID-8u6v-jzkr-nkb4
Aliases: CVE-2025-46152 PYSEC-2025-201 |
In PyTorch before 2.7.0, bitwise_right_shift produces incorrect output for certain out-of-bounds values of the "other" argument. |
Affected by 7 other vulnerabilities. |
|
VCID-dm2h-xssw-xqhb
Aliases: CVE-2025-55554 PYSEC-2025-206 |
pytorch v2.8.0 was discovered to contain an integer overflow in the component torch.nan_to_num-.long(). |
Affected by 0 other vulnerabilities. |
|
VCID-fzd6-jxxp-h7c8
Aliases: CVE-2025-46153 PYSEC-2025-202 |
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, and nn.Dropout3d for fallback_random=True. |
Affected by 7 other vulnerabilities. |
|
VCID-jqpq-n5zb-2ydh
Aliases: CVE-2025-55552 PYSEC-2025-204 |
pytorch v2.8.0 was discovered to display unexpected behavior when the components torch.rot90 and torch.randn_like are used together. |
Affected by 0 other vulnerabilities. |
|
VCID-rr2u-g78b-yfev
Aliases: CVE-2025-55551 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. |
Affected by 0 other vulnerabilities. |
|
VCID-tw2j-udhp-nydv
Aliases: CVE-2025-55553 PYSEC-2025-205 |
A syntax error in the component proxy_tensor.py of pytorch v2.7.0 allows attackers to cause a Denial of Service (DoS). |
Affected by 3 other vulnerabilities. |
|
VCID-vy3e-sq4h-eybf
Aliases: CVE-2025-55558 PYSEC-2025-208 |
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). |
Affected by 3 other vulnerabilities. |
|
VCID-w8cd-83qu-uygf
Aliases: CVE-2025-46150 PYSEC-2025-200 |
In PyTorch before 2.7.0, when torch.compile is used, FractionalMaxPool2d has inconsistent results. |
Affected by 7 other vulnerabilities. |
|
VCID-x8ck-txve-s7gy
Aliases: CVE-2025-55557 PYSEC-2025-207 |
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). |
Affected by 3 other vulnerabilities. |
|
VCID-xgau-bn5a-t3cg
Aliases: CVE-2025-46149 PYSEC-2025-199 |
In PyTorch before 2.7.0, when inductor is used, nn.Fold has an assertion error. |
Affected by 7 other vulnerabilities. |
|
VCID-z22a-fyhr-bbg4
Aliases: CVE-2025-46148 PYSEC-2025-198 |
In PyTorch through 2.6.0, when eager is used, nn.PairwiseDistance(p=2) produces incorrect results. |
Affected by 7 other vulnerabilities. |
| Vulnerability | Summary | Aliases |
|---|---|---|
| VCID-7563-j935-rkh5 | PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. In version 2.5.1 and prior, a Remote Command Execution (RCE) vulnerability exists in PyTorch when loading a model using torch.load with weights_only=True. This issue has been patched in version 2.6.0. |
CVE-2025-32434
GHSA-53q9-r3pm-6pq6 PYSEC-2025-41 |