PytorchApplication · Linuxfoundation
CVE-2025-2999
Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.
NVD · uneditedA 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.
Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.
dbcve analysis · moderate confidenceA memory corruption vulnerability exists in PyTorch 2.6.0's `torch.nn.utils.rnn.unpack_sequence` function. This RNN utility, used for unpacking packed sequences returned by `pack_padded_sequence`, contains a memory handling flaw that could be exploited locally to potentially achieve arbitrary code execution or cause denial of service.
Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.
Affected products & versions What the vendor confirmedThe version ranges the vendor confirmed as vulnerable. If your version sits inside a range here, treat yourself as exposed until you have upgraded.
NVD · CPE data
PytorchApplication
= 2.6.0CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.
From the vector- Attack vector
- Local
- Complexity
- Low
- Privileges
- Low
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- Low
- Integrity
- Low
- Availability
- Low
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L
Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.
dbcve checksWork through these to decide whether this CVE applies to you.
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Identify installed PyTorch versionRun 'python -c "import torch; print(torch.__version__)"' to get the installed versionAffected if Version is exactly 2.6.0
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Check if torch.nn.utils.rnn module is importedSearch codebase or run 'python -c "from torch.nn.utils.rnn import unpack_sequence"' to verify the module is accessibleAffected if The module is importable and unpack_sequence function is available in the environment
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Locate usage of unpack_sequence in codeSearch project files for 'unpack_sequence' calls, particularly with packed sequences from 'pack_padded_sequence'Affected if Code calls unpack_sequence on packed sequences, especially with untrusted or externally-sourced sequence data
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Inspect input validation on sequence dataReview code paths where packed sequence data (batch sizes, sequences) are passed to unpack_sequence - check if lengths and data are validated before the callAffected if unpack_sequence is called without validating sequence lengths or data integrity beforehand
Environment is affected if PyTorch 2.6.0 is installed AND unpack_sequence is used with packed sequences, particularly without input validation on the sequence data.
Generated from the published advisory. Verify against your own configuration.
Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.
From vendor dataUpgrade to the patched version of PyTorch when available. Until then, avoid using `unpack_sequence` with untrusted packed sequence data, and ensure proper input validation is performed on sequence lengths and data before passing to RNN utilities.
Fix this in Pytorch
Scoped from the published advisory
- Consultation4.0 h
- Implementation8.0 h
- Testing6.0 h
- Review / QA3.0 h
An estimate, not a bill — we confirm scope with you before any work starts. Need it this week? Rush from $5,888.
Scan for this in your stack
Free · runs locallyCheck whether your project pulls in CVE-2025-2999 — or any other known-vulnerable package — straight from your lock files. Free and open source; it runs locally and uploads nothing.
References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.
Primary sourcesPractitioner notes
ContributedPeer-ranked notes from engineers who’ve handled CVE-2025-2999 in production — separate from our analysis above.
The advisory tells you what broke. It rarely tells you what actually worked. If you’ve dealt with this one, that detail is what the next engineer is searching for.
- The version that genuinely resolved it — not the one the vendor claimed
- A config change or rule that shut the vector down
- A gotcha in the upgrade path that cost you an afternoon
No notes yet
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- Version or environment caveats, and links to real fixes
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