Command InjectionWeakness · CWE-77

CVE-2025-50461

MEDIUM · 6.5 CVSS v3.1 Published 2025-08-19
Mitigation only
No fix yet — a mitigation exists. There is no fixed release. A documented workaround reduces exposure in the meantime.
See remediation →
74/100
Remediation priority · Elevated
Remotely reachable No privileges Zero-click

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 · unedited
A deserialization vulnerability exists in Volcengine's verl 3.0.0, specifically in the scripts/model_merger.py script when using the "fsdp" backend. The script calls torch.load() with weights_only=False on user-supplied .pt files, allowing attackers to execute arbitrary code if a maliciously crafted model file is loaded. An attacker can exploit this by convincing a victim to download and place a malicious model file in a local directory with a specific filename pattern. This vulnerability may lead to arbitrary code execution with the privileges of the user running the script.

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 confidence

In Volcengine verl 3.0.0, the scripts/model_merger.py script uses torch.load() with weights_only=False when loading .pt model files in the 'fsdp' backend. This unsafe deserialization allows arbitrary code execution if a victim downloads and places a specially crafted malicious model file with a specific filename pattern in a local directory.

MitigationChange torch.load() calls to use weights_only=True, or implement cryptographic signature validation of model files before loading to prevent deserialization of untrusted pickled data.

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
None

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:N

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 checks

Work through these to decide whether this CVE applies to you.

  1. Identify if Volcengine verl is installed
    Run 'pip show volcengine-verl' or check for the verl package in your Python environment
    Affected if volcengine-verl version 3.0.0 is installed
  2. Locate the model_merger.py script
    Find scripts/model_merger.py in the verl installation directory, typically in the volcengine-verl package path
    Affected if The script exists in the installed package
  3. Verify unsafe torch.load() usage
    Open model_merger.py and search for torch.load() calls, check if weights_only parameter is set to False or not set
    Affected if torch.load() is called with weights_only=False or without specifying weights_only when using the fsdp backend
  4. Check for fsdp backend configuration
    In model_merger.py, locate the code path that handles the 'fsdp' backend and confirms it calls the unsafe torch.load()
    Affected if The fsdp backend code path loads .pt files using the unsafe torch.load()
  5. Inspect for untrusted .pt model files
    Search local directories for .pt model files, particularly any with unusual origin or that match patterns the script expects (check the filename patterns in model_merger.py)
    Affected if Untrusted or externally sourced .pt model files exist in directories accessible to the script

You are affected if you run Volcengine verl 3.0.0, use the fsdp backend in model_merger.py to load .pt files, and have untrusted or malicious model files present in your environment.

Generated from the published advisory. Verify against your own configuration.

Check your environment

Paste your version and any relevant configuration and it will be compared against the affected criteria above. Do not include secrets or credentials.

AI-assisted, checked against the advisory. Informational, not a guarantee.

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 data
Mitigation available No clean upgrade yet — mitigate in the meantime
Mitigation

Change torch.load() calls to use weights_only=True, or implement cryptographic signature validation of model files before loading to prevent deserialization of untrusted pickled data.

Have this fixed Scoped from the published advisory
  • Consultation2.0 h
  • Implementation1.0 h
  • Testing4.0 h
  • Review / QA2.0 h
9.0 hours of engineering $1,540
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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 sources

Practitioner notes

Contributed

Peer-ranked notes from engineers who’ve handled CVE-2025-50461 in production — separate from our analysis above.

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What this is

A place for practitioners to share what actually worked: a mitigation you’ve tested, a configuration change, a version- or environment-specific caveat, or a link to a verified patch. The most useful notes rise to the top as peers upvote them, so the signal stays high.

What belongs here
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  • Version or environment caveats, and links to real fixes
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