| 0 |
| url |
VCID-1fx4-95p5-6kgv |
| vulnerability_id |
VCID-1fx4-95p5-6kgv |
| summary |
In PyTorch before trunk/89695, torch.jit.annotations.parse_type_line can cause arbitrary code execution because eval is used unsafely. |
| references |
|
| fixed_packages |
| 0 |
| url |
pkg:pypi/torch@1.13.1 |
| purl |
pkg:pypi/torch@1.13.1 |
| is_vulnerable |
true |
| affected_by_vulnerabilities |
| 0 |
| vulnerability |
VCID-3cvu-c3jj-yyhx |
|
| 1 |
| vulnerability |
VCID-57ph-1jp3-rff4 |
|
| 2 |
| vulnerability |
VCID-69gt-qhaf-63gv |
|
| 3 |
| vulnerability |
VCID-7563-j935-rkh5 |
|
| 4 |
| vulnerability |
VCID-avxx-n31w-4fgu |
|
| 5 |
| vulnerability |
VCID-dm2h-xssw-xqhb |
|
| 6 |
| vulnerability |
VCID-jqpq-n5zb-2ydh |
|
| 7 |
| vulnerability |
VCID-pryj-149u-zqe7 |
|
| 8 |
| vulnerability |
VCID-rr2u-g78b-yfev |
|
| 9 |
| vulnerability |
VCID-tw2j-udhp-nydv |
|
| 10 |
| vulnerability |
VCID-vy3e-sq4h-eybf |
|
| 11 |
| vulnerability |
VCID-x8ck-txve-s7gy |
|
| 12 |
| vulnerability |
VCID-z22a-fyhr-bbg4 |
|
|
| resource_url |
http://public2.vulnerablecode.io/packages/pkg:pypi/torch@1.13.1 |
|
|
| aliases |
CVE-2022-45907, PYSEC-2022-43015
|
| risk_score |
null |
| exploitability |
null |
| weighted_severity |
null |
| resource_url |
http://public2.vulnerablecode.io/vulnerabilities/VCID-1fx4-95p5-6kgv |
|
| 1 |
| url |
VCID-3cvu-c3jj-yyhx |
| vulnerability_id |
VCID-3cvu-c3jj-yyhx |
| summary |
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. |
| references |
|
| fixed_packages |
|
| aliases |
CVE-2025-55560, PYSEC-2025-209
|
| risk_score |
null |
| exploitability |
null |
| weighted_severity |
null |
| resource_url |
http://public2.vulnerablecode.io/vulnerabilities/VCID-3cvu-c3jj-yyhx |
|
| 2 |
|
| 3 |
| url |
VCID-69gt-qhaf-63gv |
| vulnerability_id |
VCID-69gt-qhaf-63gv |
| summary |
Pytorch before version v2.2.0 was discovered to contain a use-after-free vulnerability in torch/csrc/jit/mobile/interpreter.cpp. |
| references |
|
| fixed_packages |
| 0 |
| url |
pkg:pypi/torch@2.2.0 |
| purl |
pkg:pypi/torch@2.2.0 |
| is_vulnerable |
true |
| affected_by_vulnerabilities |
| 0 |
| vulnerability |
VCID-3cvu-c3jj-yyhx |
|
| 1 |
| vulnerability |
VCID-7563-j935-rkh5 |
|
| 2 |
| vulnerability |
VCID-dm2h-xssw-xqhb |
|
| 3 |
| vulnerability |
VCID-jqpq-n5zb-2ydh |
|
| 4 |
| vulnerability |
VCID-pryj-149u-zqe7 |
|
| 5 |
| vulnerability |
VCID-rr2u-g78b-yfev |
|
| 6 |
| vulnerability |
VCID-tw2j-udhp-nydv |
|
| 7 |
| vulnerability |
VCID-vy3e-sq4h-eybf |
|
| 8 |
| vulnerability |
VCID-x8ck-txve-s7gy |
|
| 9 |
| vulnerability |
VCID-z22a-fyhr-bbg4 |
|
|
| resource_url |
http://public2.vulnerablecode.io/packages/pkg:pypi/torch@2.2.0 |
|
|
| aliases |
CVE-2024-31583, GHSA-pg7h-5qx3-wjr3, PYSEC-2024-251
|
| risk_score |
null |
| exploitability |
null |
| weighted_severity |
null |
| resource_url |
http://public2.vulnerablecode.io/vulnerabilities/VCID-69gt-qhaf-63gv |
|
| 4 |
| url |
VCID-7563-j935-rkh5 |
| vulnerability_id |
VCID-7563-j935-rkh5 |
| summary |
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. |
| references |
|
| fixed_packages |
| 0 |
| url |
pkg:pypi/torch@2.6.0 |
| purl |
pkg:pypi/torch@2.6.0 |
| is_vulnerable |
true |
| affected_by_vulnerabilities |
| 0 |
| vulnerability |
VCID-3cvu-c3jj-yyhx |
|
| 1 |
| vulnerability |
VCID-8u6v-jzkr-nkb4 |
|
| 2 |
| vulnerability |
VCID-dm2h-xssw-xqhb |
|
| 3 |
| vulnerability |
VCID-fzd6-jxxp-h7c8 |
|
| 4 |
| vulnerability |
VCID-jqpq-n5zb-2ydh |
|
| 5 |
| vulnerability |
VCID-rr2u-g78b-yfev |
|
| 6 |
| vulnerability |
VCID-tw2j-udhp-nydv |
|
| 7 |
| vulnerability |
VCID-vy3e-sq4h-eybf |
|
| 8 |
| vulnerability |
VCID-w8cd-83qu-uygf |
|
| 9 |
| vulnerability |
VCID-x8ck-txve-s7gy |
|
| 10 |
| vulnerability |
VCID-xgau-bn5a-t3cg |
|
| 11 |
| vulnerability |
VCID-z22a-fyhr-bbg4 |
|
|
| resource_url |
http://public2.vulnerablecode.io/packages/pkg:pypi/torch@2.6.0 |
|
|
| aliases |
CVE-2025-32434, GHSA-53q9-r3pm-6pq6, PYSEC-2025-41
|
| risk_score |
null |
| exploitability |
null |
| weighted_severity |
null |
| resource_url |
http://public2.vulnerablecode.io/vulnerabilities/VCID-7563-j935-rkh5 |
|
| 5 |
| url |
VCID-avxx-n31w-4fgu |
| vulnerability_id |
VCID-avxx-n31w-4fgu |
| summary |
PyTorch before v2.2.0 was discovered to contain a heap buffer overflow vulnerability in the component /runtime/vararg_functions.cpp. This vulnerability allows attackers to cause a Denial of Service (DoS) via a crafted input. |
| references |
|
| fixed_packages |
| 0 |
| url |
pkg:pypi/torch@2.2.0 |
| purl |
pkg:pypi/torch@2.2.0 |
| is_vulnerable |
true |
| affected_by_vulnerabilities |
| 0 |
| vulnerability |
VCID-3cvu-c3jj-yyhx |
|
| 1 |
| vulnerability |
VCID-7563-j935-rkh5 |
|
| 2 |
| vulnerability |
VCID-dm2h-xssw-xqhb |
|
| 3 |
| vulnerability |
VCID-jqpq-n5zb-2ydh |
|
| 4 |
| vulnerability |
VCID-pryj-149u-zqe7 |
|
| 5 |
| vulnerability |
VCID-rr2u-g78b-yfev |
|
| 6 |
| vulnerability |
VCID-tw2j-udhp-nydv |
|
| 7 |
| vulnerability |
VCID-vy3e-sq4h-eybf |
|
| 8 |
| vulnerability |
VCID-x8ck-txve-s7gy |
|
| 9 |
| vulnerability |
VCID-z22a-fyhr-bbg4 |
|
|
| resource_url |
http://public2.vulnerablecode.io/packages/pkg:pypi/torch@2.2.0 |
|
|
| aliases |
CVE-2024-31580, GHSA-5pcm-hx3q-hm94, PYSEC-2024-252
|
| risk_score |
null |
| exploitability |
null |
| weighted_severity |
null |
| resource_url |
http://public2.vulnerablecode.io/vulnerabilities/VCID-avxx-n31w-4fgu |
|
| 6 |
|
| 7 |
|
| 8 |
| url |
VCID-pryj-149u-zqe7 |
| vulnerability_id |
VCID-pryj-149u-zqe7 |
| summary |
In PyTorch <=2.4.1, the RemoteModule has Deserialization RCE. NOTE: this is disputed by multiple parties because this is intended behavior in PyTorch distributed computing. |
| references |
|
| fixed_packages |
|
| aliases |
CVE-2024-48063, PYSEC-2024-259
|
| risk_score |
null |
| exploitability |
null |
| weighted_severity |
null |
| resource_url |
http://public2.vulnerablecode.io/vulnerabilities/VCID-pryj-149u-zqe7 |
|
| 9 |
|
| 10 |
|
| 11 |
| url |
VCID-vy3e-sq4h-eybf |
| vulnerability_id |
VCID-vy3e-sq4h-eybf |
| summary |
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). |
| references |
|
| fixed_packages |
|
| aliases |
CVE-2025-55558, PYSEC-2025-208
|
| risk_score |
null |
| exploitability |
null |
| weighted_severity |
null |
| resource_url |
http://public2.vulnerablecode.io/vulnerabilities/VCID-vy3e-sq4h-eybf |
|
| 12 |
|
| 13 |
|