CVE-2026-31250
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 · uneditedCosyVoice thru commit 6e01309e01bc93bbeb83bdd996b1182a81aaf11e (2025-30-21) contains an insecure deserialization vulnerability (CWE-502) in its average_model.py model averaging tool. The script loads PyTorch checkpoint files (epoch_*.pt) for model averaging using torch.load() without enabling the weights_only=True security parameter. This allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing malicious checkpoint files within a directory. When a victim uses the tool to average models from this directory, arbitrary code is executed on the victim's system.
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 · high confidenceCosyVoice's average_model.py uses torch.load() without the weights_only=True parameter when loading PyTorch checkpoint files (epoch_*.pt). This enables pickle deserialization of arbitrary Python objects, allowing remote code execution when a victim processes a directory containing malicious checkpoint files.
Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.
CVSS 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
- Network
- Complexity
- Low
- Privileges
- None
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- Low
- Integrity
- Low
- Availability
- Low
CVSS:3.1/AV:N/AC:L/PR:N/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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Locate the CosyVoice installationFind the average_model.py file in the CosyVoice codebase - typically in a 'cosyvoice' directory or source folder. Search for files named average_model.pyAffected if Cannot locate average_model.py means CosyVoice may not be installed or is in a non-standard location
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Inspect torch.load() calls in average_model.pyOpen average_model.py and search for 'torch.load(' pattern. Check if the weights_only parameter is set to TrueAffected if The code contains torch.load() calls loading epoch_*.pt files without weights_only=True parameter - this indicates the vulnerability is present
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Identify checkpoint file loading patternsSearch for code that loads files matching 'epoch_*.pt' pattern using torch.load(). Look for functions that load model checkpoints for averagingAffected if Checkpoint files (epoch_*.pt) are loaded via unprotected torch.load() calls enabling arbitrary deserialization
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Check if model averaging feature is enabledDetermine if the CosyVoice application uses the average_model.py functionality - check if model averaging is invoked during training or inference workflowsAffected if The model averaging feature processes checkpoint files and is actively used in the environment
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Verify Python and PyTorch versionsCheck installed PyTorch version with 'python -c "import torch; print(torch.__version__)"'. Compare against known affected versions (older PyTorch releases had fewer safeguards)Affected if Running with older PyTorch versions may have additional deserialization risks, though the code vulnerability exists regardless of PyTorch version
You are affected if CosyVoice's average_model.py loads epoch_*.pt checkpoint files using torch.load() without the weights_only=True parameter, and your workflow processes these checkpoint files.
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.
dbcve · scopedAdd weights_only=True to all torch.load() calls in average_model.py. If the model averaging requires loading non-tensor objects, implement a custom unpickler with an allowlist of safe types or restructure the checkpoint format to use safer serialization methods.
- Locate the average_model.py file in the CosyVoice repository
- Open average_model.py and find all instances of torch.load() used to load checkpoint files (epoch_*.pt)
- For each torch.load() call, add the weights_only=True parameter (e.g., change torch.load(path) to torch.load(path, weights_only=True))
- If the model requires loading custom classes/objects, refactor to use a safer approach such as defining a custom weights_only=True compliant loader or using state_dict for model weights instead of full checkpoint objects
- After applying the patch, test the average_model.py script with legitimate checkpoint files to ensure functionality is preserved
- Commit the changes and redeploy
Generated from the published advisory — verify against the referenced sources before acting.
- Consultation2.0 h
- Implementation1.0 h
- Testing2.0 h
- Review / QA1.0 h
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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-2026-31250 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
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- Version or environment caveats, and links to real fixes
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