# CVE-2025-2998: PyTorch memory corruption in pad_packed_sequence

Source: https://junglewise.ai/threats/cve-2025-2998-pytorch-memory-corruption-in-pad-packed-sequence  
Publisher: Junglewise Threat Intelligence, https://junglewise.ai/threats  
Published: 2025-03-31. Updated: 2026-06-09  
License: CC BY 4.0 with a link back

CVE-2025-2998 · Severity: medium · CVSS 5.3 · Published 2025-03-31

PyTorch, a popular machine learning library, is vulnerable to a memory corruption issue when processing specific data sequences. An attacker with local access to a system running PyTorch could provide specially crafted empty data structures to trigger a crash or potentially execute unauthorized code. This could lead to service interruptions or a compromise of the system's integrity and data.

Technologies: [torch (PyPI)](https://junglewise.ai/threats/technologies/torch). Vendors: [PyPI](https://junglewise.ai/threats/vendors/pypi).

## Quick answers

**Is CVE-2025-2998 exploited in the wild?** No. Junglewise Threat Intelligence has no report of CVE-2025-2998 being exploited in the wild.

**How severe is CVE-2025-2998?** Medium severity, with a CVSS score of 5.3, published 31 March 2025.

**Which products and versions are affected?** torch (PyPI) <= 2.6.0, ECOSYSTEM:introduced=0,last_affected=2.6.0, ECOSYSTEM:introduced=0,last_affected=2.6.0-NA.

**Is there a fix for CVE-2025-2998?** No fixed version is recorded yet. Check the vendor's advisory in the references below. If you run it, Junglewise drafts a mitigation that fits your setup and applies it once you approve, with senior security engineers behind it.

**How is CVE-2025-2998 attacked?** It is attacked with local access, in a software library.

**Am I affected by CVE-2025-2998?** Check whether you run torch (PyPI) at an affected version. Junglewise does that check for you around the clock: connect your code, cloud and domains, and it matches new vulnerabilities like this one against what you actually run and tells you when one reaches you.

## Technical details

A memory corruption vulnerability (CWE-119) exists in PyTorch versions up to and including 2.6.0 within the torch.nn.utils.rnn.pad_packed_sequence and torch.nn.utils.rnn.unpack_sequence functions. The root cause is improper handling of empty tensors and batch sizes within PackedSequence objects, which leads to a segmentation fault. An attacker with local access and low privileges can exploit this by passing malformed input to these functions. While primarily resulting in a crash (Denial of Service), memory corruption bugs of this class can sometimes be leveraged for arbitrary code execution. A fix has been committed to the PyTorch repository.

## Affected products

- PyTorch PyTorch <= 2.6.0

## Identifiers

- CVE-2025-2998
- GHSA-f4hp-rmr7-r7v8
- PYSEC-2025-192

## Timeline

- 2025-03-20: disclosed: Issue reported on GitHub
- 2025-03-31: advisory: NVD and GitHub Advisory published

## References

- [https://github.com/pytorch/pytorch/issues/149622](https://github.com/pytorch/pytorch/issues/149622)
- [https://github.com/pytorch/pytorch/issues/149622](https://github.com/pytorch/pytorch/issues/149622)
- [https://vuldb.com/?ctiid.302047](https://vuldb.com/?ctiid.302047)
- [https://vuldb.com/?id.302047](https://vuldb.com/?id.302047)
- [https://vuldb.com/?submit.524151](https://vuldb.com/?submit.524151)

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