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PyTorch: Mehrere Schwachstellen
view advisory published 2025-09-25
Ein Angreifer kann mehrere Schwachstellen in PyTorch ausnutzen, um Informationen offenzulegen, einen Denial-of-Service-Zustand zu erzeugen oder andere nicht näher spezifizierte Angriffe durchzuführen.
01
describes (12)
Related CVEs.
| ID | severity | exploitable | ||
|---|---|---|---|---|
| CVE-2025-55560US | high7.5 | — | ||
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. | ||||
| CVE-2025-55558US | — | — | ||
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 Ind… | ||||
| CVE-2025-55557US | high7.5 | — | ||
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). | ||||
| CVE-2025-55554US | — | — | ||
pytorch v2.8.0 was discovered to contain an integer overflow in the component torch.nan_to_num-.long(). | ||||
| CVE-2025-55553US | high7.5 | — | ||
A syntax error in the component proxy_tensor.py of pytorch v2.7.0 allows attackers to cause a Denial of Service (DoS). | ||||
| CVE-2025-55552US | high7.5 | — | ||
pytorch v2.8.0 was discovered to display unexpected behavior when the components torch.rot90 and torch.randn_like are used together. | ||||
| CVE-2025-55551US | high7.5 | — | ||
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. | ||||
| CVE-2025-46153US | — | — | ||
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.Drop… | ||||
| CVE-2025-46152US | — | — | ||
In PyTorch before 2.7.0, bitwise_right_shift produces incorrect output for certain out-of-bounds values of the "other" argument. | ||||
| CVE-2025-46150US | — | — | ||
In PyTorch before 2.7.0, when torch.compile is used, FractionalMaxPool2d has inconsistent results. | ||||
| CVE-2025-46149US | — | — | ||
In PyTorch before 2.7.0, when inductor is used, nn.Fold has an assertion error. | ||||
| CVE-2025-46148US | — | — | ||
In PyTorch through 2.6.0, when eager is used, nn.PairwiseDistance(p=2) produces incorrect results. | ||||
02
references
External citations — patches, advisories, analysis.
- GitHub Security Advisory GHSA-2qm5-pr8v-rjvp vom 2025-09-25external
- GitHub Security Advisory GHSA-765F-85MC-5QMW vom 2025-09-25external
- GitHub Security Advisory GHSA-79PG-RRP8-8WQM vom 2025-09-25external
- GitHub Security Advisory GHSA-8f2w-3w4c-pwj2 vom 2025-09-25external
- GitHub Security Advisory GHSA-f9wh-qr6g-v2h4 vom 2025-09-25external
- GitHub Security Advisory GHSA-fw73-7p7w-p28m vom 2025-09-25external
- GitHub Security Advisory GHSA-h36m-9qjr-pv93 vom 2025-09-25external
- GitHub Security Advisory GHSA-m7x9-2m87-mqhf vom 2025-09-25external
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