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CVE-2025-2999 torch

Fix: pytorch/pytorch@4945180

CVE-2025-2999 is a Buffer Overflow vulnerability in torch. A fix is available for torch — see the affected versions and patch details below.

PyTorch torch.nn.utils.rnn.unpack_sequence memory corruption

Also known asBIT-pytorch-2025-2999GHSA-vgrw-7cvw-pwgxPYSEC-2025-193
Published
Mar 31, 2025
Updated
Aug 12, 2026
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed
Exploitation data as of Sep 22, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

  • CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.

Exploitation and automatability from CISA’s SSVC triage for CVE-2025-2999.

EPSS Exploitation Probability

via FIRST.org ↗
0.2%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs10th percentile — riskier than 10% of all scored CVEsHighest risk

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

Real-World Exposure

1 pkg affected
🐍torch

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

A vulnerability was found in PyTorch 2.6.0. It has been rated as critical. Affected by this issue is the function torch.nn.utils.rnn.unpack_sequence. The manipulation leads to memory corruption. Attacking locally is a requirement. The exploit has been disclosed to the public and may be used.

A patch is available through commit 4945180.

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItorchall versions2.9.1pip install --upgrade 'torch==2.9.1'

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for torch, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update torch to 2.9.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2025-2999 is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like CVE-2025-2999 can be triaged on real exposure rather than presence alone.

Tailored to CVE-2025-2999. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

A vulnerability was found in PyTorch 2.6.0. It has been rated as critical. Affected by this issue is the function torch.nn.utils.rnn.unpack_sequence. The manipulation leads to memory corruption. Attacking locally is a requirement. The exploit has been disclosed to the public and may be used. A patch is available through commit [4945180](https://github.com/pytorch/pytorch/commit/494518046816d29099b7d056a74ffa5c244fdcdd).
O3 Security · Impact-Aware SCA

Is CVE-2025-2999 in your dependencies?

O3 Security finds CVE-2025-2999 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.

CVE-2025-2999: torch | O3 Security