A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0+cu124. Affected by this issue is the function torch.mkldnn_max_pool2d. The manipulation leads to denial of service
Research is free — Hunters explains how the bug works, the root-cause code pattern, how the fix addresses it, and how to test whether a target is affected, in chat. Investigate & write exploit is a paid run — the engine reads the advisory and fix commits, then builds and validates a working proof-of-concept exploit with reproduction steps.
Details
A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0+cu124. Affected by this issue is the function torch.mkldnn_max_pool2d. The manipulation leads to denial of service. An attack has to be approached locally. The exploit has been disclosed to the public and may be used. The real existence of this vulnerability is still doubted at the moment. The security policy of the project warns to use unknown models which might establish malicious effects.
The fix
References
- WEBhttps://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models
- ADVISORYhttps://vuldb.com/?id.302006
- ADVISORYhttps://vuldb.com/?submit.521279
- REPORThttps://github.com/pytorch/pytorch/issues/149274
- REPORThttps://github.com/pytorch/pytorch/issues/149274#issue-2923122269
- REPORThttps://vuldb.com/?ctiid.302006
- ADVISORYhttps://github.com/advisories/GHSA-3749-ghw9-m3mg